VOL: XLVIII, No. 01
Printed by Karunaratne & Sons (Pvt) Ltd.
January 2015
ISSN 1800-1122
VOL: XLVIII,, No. 01
January 2015
ISSN 1800-1122
ENGINEER
CONTENTS
Vol.: XLVIII, No. 01, January 2015
ISSN 1800-1122
JOURNAL OF THE INSTITUTION OF ENGINEERS, SRI LANKA
* 43rd Year of Publication *
EDITORIAL BOARD
From the Editor ...
Eng. (Dr.) S. B. Wijekoon
- President (Chairman)
Eng. R. G. Rubasinghe
- Chairman, L&P Com
Eng. (Prof.) T. M. Pallewatta
- Editor ‘ENGINEER’
Eng. (Dr.) K. E. D. Sumanasiri
- Editor Transactions
Eng. (Dr.) U. P. Nawagamuwa
- Editor ‘SLEN’
Eng. W. J. L. S. Fernando
Eng. (Prof.) (Mrs.) N. Rathnayaka
Eng. (Prof.) K. P. P. Pathirana
Eng. (Dr.) D. A. R. Dolage
Eng. W. Gamage
Eng. (Miss.) Arundathi Wimalasuriya
Eng. (Dr.) K. S. Wanniarachchi
SECTION I
The Institution of Engineers, Sri Lanka
120/15, Wijerama Mawatha,
Colombo - 00700
Sri Lanka.
Telephone: 94-11-2698426, 2685490, 2699210
Fax: 94-11-2699202
E-mail: iesl@slt.lk
E-mail (Publications): ed@sltnet.lk
Website: http://www.iesl.lk
The statements made or opinions expressed in the
“Engineer” do not necessarily reflect the views of the
Council or a Committee of the Institution of
Engineers Sri Lanka, unless expressly stated.
COVER PAGE
VOL: XLVIII,, No. 01
January 2015
ISSN 1800-1122
III
HEC-HMS Model for Runoff Simulation in a
Tropical Catchment with Intra-Basin
Diversions – Case Study of the Deduru Oya
River Basin, Sri Lanka
by:
Eng. D. S. Sampath,
Eng. (Prof.) S. B. Weerakoon and
Prof. Srikantha Herath
III
1
Analysis on Energy Efficiency and
Optimality of LED and Photovoltaic Based
Street Lighting System
by:
Eng. Chandana Kulasooriyage,
Dr. Satish S. Namasivayam and
Dr. Lanka Udawatta
11
Mitigation of Construction Delays
Attributable to the Contractors in the
Construction Industry of Sri Lanka
by:
Eng. (Dr.) D. A. R. Dolage and
Eng. T. Pathmarajah
21
Use of Dynamites, Watergels and Emulsion
Explosives in Sri Lankan Quarrying/Mining
Practice
by:
Eng. P. V. A. Hemalal,
Prof. P. G. R. Dharmarathne and
Eng. P. I. Kumarage
31
An Approach to Seismic Analysis and Design 39
of (Engineered) Buildings in Sri Lanka
by:
Eng. (Dr.) C. S. Lewangamage and
Miss. H. G. S. R. Kularathna
Printed by Karunaratne & Sons (Pvt) Ltd.
Daduru Oya Reservoir Project
The fourth largest river in Sri Lanka, ‘Daduru Oya’ runs
through four districts, fed by a catchment of over 2600
km2, discharges close to a billion cubic meters of water
annually. The multipurpose hydro scheme reservoir
impounding 75 million cubic meters and spread over an
area of 2000 Hectares is contained by a 2.4 km long earthen
dam with an 8 radial gated spill. The reservoir is capable
of discharging at a combined rate of 15.5 m3/s through
twin sluices to left and right bank canals for irrigating over
11,000 Hectares. Further, 1.5 MW of hydro electric power
is also expected to be generated through this project.
Contributed by:
Eng. B. A. S. S. Perera
Director of Irrigation
Kurunegala.
SECTION II
Monitoring of Exhaust Gas Parameters of
51
Stationary Combustion Systems - In View of
Environmental Standards
by:
Eng. K. T. Jayasinghe
Notes:

ENGINEER, established in 1973, is a Quarterly
Journal, published in the months of January,
April, July & October of the year.

All published articles have been refereed in
anonymity by at least two subject specialists.

Section I contains articles based on Engineering
Research while Section II contains articles of
Professional Interest.
Projecting turbidity levels in future river
flow: A mathematical modeling approach
by:
Eng. (Dr.) (Mrs.) T. N.
Wickramaarachchi,
Eng. (Dr.) H. Ishidaira,
Eng. (Dr.) J. Magome and
Eng. (Dr.) T. M. N. Wijayaratna
61
The above Paper was placed First in the „Over 35
years of age‟ Category at the Competition on “Eco
Friendly Water Infrastructure for Sustainable
Development and Management Experiences gained
from Integrated Water Resources Development
and Management in Sri Lanka” 2013/2014
Sponsored by: St. Anthony’s Industries Group
(Pvt) Ltd.
Coastal Investigations for sustainable
development of fisheries infrastructure
by :
81
Eng. A. H. R. Ratnasooriya and
Eng. (Prof.) S. P. Samarawickrama
The above Paper was placed Second in the „Over 35
years of age‟ Category at the Competition on “Eco
Friendly Water Infrastructure for Sustainable
Development and Management Experiences gained
from Integrated Water Resources Development
and Management in Sri Lanka” 2013/2014
Sponsored by: St. Anthony’s Industries Group
(Pvt) Ltd.
II
FROM THE EDITOR…………..
Once again we are in a position to proudly talk about a project
of our own. An Irrigation/hydro Power project in our own country,
designed by our own Engineers, managed by our own Engineering
organizations, constructed by our own workforce and funded by our
own government, indeed places this project on this pedestal.
Being the fourth longest river in Sri Lanka, Daduru Oya,
originating in the western slopes of the wet zone hill country has
passed through some of the dry plains in the north-west of the island
for centuries without bestowing full potential benefits to the
inhabitants. The Daduru Oya reservoir project by the Department of Irrigation is another
historical step in harnessing the beneficial potential from near a billion cubic meters of
water flowing through this river fed by many tributaries at various levels.
Apart from building the potential to irrigate over 11,00 Hectares of rice cultivation
in both Yala and Maha seasons, the proposed reservoir would enable potable water supply
for an area housing over 50,000 families and generate 1.5 MW of electric power. As further
benefits this project is expected to control floods, recharge ground water table and fulfil the
baseline requirements for enhancing the infrastructure of the area.
Our island country may not have many of the natural resources valued by the
present day economists, such as petroleum, coal or metal ores, but has been blessed with a
cartwheel of waterways enriching the peripheries. As our ancestors have done throughout
the recorded history, it is our sacred duty to harness the maximum potential of these for the
benefit of all the inhabitants. The Daduru Oya project will be a contribution of this
generation and especially the Engineers of this generation, to this historical quest.
Eng. (Prof.) T. M. Pallewatta, Int. PEng (SL), C. Eng, FIE(SL), FIAE(SL)
Editor, ‘ENGINEER’, Journal of The Institution of Engineers.
III
III
SECTION I
ENGINEER - Vol. XLVIII, No. 01, pp. [1-9], 2015
ENGINEER - Vol. XLVIII, No. 01, pp. [page range], 2015
© The Institution of Engineers, Sri Lanka
© The Institution of Engineers, Sri Lanka
HEC-HMS Model for Runoff Simulation in a Tropical
Catchment with Intra-Basin Diversions – Case Study
of the Deduru Oya River Basin, Sri Lanka
D. S. Sampath, S. B. Weerakoon and S. Herath
Abstract:
Hydrological modeling is a commonly used tool by water resource planners to
simulate the hydrological response in a basin due to precipitation for the purpose of management of
basin water. With the increasing demand for limited water resources in every basin, careful
management of water resources becomes more important. The Deduru Oya river in Sri Lanka supplies
water to number of new and ancient irrigation systems and the management of water resources in the
Deduru Oya river basin, which has an area of 2620 km2, is important for optimum utilization of water
for these irrigation systems. This paper describes a case study of continuous rainfall-runoff modeling
in part of the Deduru Oya basin with intra-basin diversions and storage irrigation systems using the
Hydrologic Engineering Center – Hydrologic Modeling System (HEC–HMS) version 3.0.1 to estimate
runoff in the Deduru Oya river.
Long term daily rainfall data at several rain gauging stations, evaporation, land use and soil data in
the river basin, daily river runoff at a stream gauging station, intra-basin diversions from the river into
a storage reservoir, irrigation releases from the reservoir and drainage flow returned to the river from
irrigation systems were used to set up the HEC-HMS model. Five-layer soil moisture accounting loss
method, Clark unit hydrograph transformation method, and recession base flow method of the HECHMS model were used. Temporally varying irrigation water uses, storages and losses in the basin
were taken into account in the analysis. The results depict the capability of HEC–HMS to reproduce
stream flows in the basin to a high accuracy with averaged computed Nash Sutcliffe efficiencies of
0.80. The study demonstrates potential HEC–HMS application in flow estimation from tropical
catchments with intra-basin diversions and irrigation storages. The model developed is a tool for
water management in the Deduru Oya river basin.
Keywords:
Deduru Oya basin, HEC-HMS, Hydrological Modeling, Irrigation, Magalla tank
1. Introduction
and the objective of the hydrological prediction
in the basin.
Sustainable management of limited fresh water
sources is a major challenge and is extremely
important for the people living in the world.
Failure to manage the water sources in an
effective manner will adversely affect the
society and the economy of the country.
Management of water resources in a basin
essentially requires understanding of dynamics
of basin water and assessment of basin water
availability for development use.
The HEC–HMS, developed by Hydrologic
Engineering Center of U.S. Army Corps of
Engineers is a hydrological model that supports
both lumped parameter based modeling as well
as distributed parameter based modeling [15].
HEC-HMS is a set of mathematical models to
simulate the precipitation runoff-routing
processes of dendritic watershed system.
Eng. D. S. Sampath, B. Sc. Eng.(Hons)(Peradeniya),
AMIE(Sri Lanka), Lecturer (Probationary), Dept. of Civil
Engineering, University of Jaffna, Ariviyal Nagar,
Kilinochchi, Sri Lanka and M. Phil. candidate, Dept. of
Civil Engineering, University of Peradeniya, Peradeniya,
Sri Lanka.
Eng. (Prof.) S. B. Weerakoon, B.Sc.Eng.(Peradeniya),
M.Eng., D.Eng. (Tokyo), FIE(Sri Lanka), Int. PE SL, C.
Eng, Professor of Civil Engineering, Dept. of Civil
Engineering, University of Peradeniya, Peradeniya, Sri
Lanka.
Prof. Srikantha Herath, B.Sc.Eng.(Peradeniya), M.Eng.
(AIT), D.Eng. (Tokyo), Senior Academic Programme
Director, UNU-IAS, Tokyo, Japan.
Hydrological modeling is a commonly used
tool to estimate the basin’s hydrological
response due to precipitation. Various types of
hydrological models from black box models
which require less basin data to physically
based models which require large amount of
basin data have been developed [2]. The
selection of the model depends on the basin
ENGINEER
1 1
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Figure 1 - Location and Topography of the Basin
HEC-HMS needs three input components such
as the basin model, the meteorological model,
and the control specifications. The basin model
is the representation of real-world objects with
parameters describing their behavior. The basin
model elements are sub basin, reach, junction,
source, sink, reservoir, diversion, river reach,
point of intersection of river reaches, input flow
point to basin system, outlet of the basin
system, reservoir, and diversion for a reach in
the real world, respectively. Each of these
elements needs some parameters to define their
behavior in a hydrologic system. Each element
stores the element downstream to it to facilitate
the flow of water and to create a dendritic
network [1].
step for simulation. Control specifications
include a starting date and time, ending date
and time, and a time interval [15]. The input
time-series and other paired-value data are
stored in HEC’s Data Storage System (DSS).
The output of HEC-HMS includes peak flow
and total volume for each element in the basin
model. These output data are also stored in DSS
[1].
HEC-HMS has been successfully applied to
many basins to assess water resources
including river basins in Sri Lanka [(4), (8)]. In
this paper the HEC HMS Model is applied for a
part of the Deduru Oya river basin (Deduru
Oya river basin above Moragaswewa (79.9900 E,
7.7000 N) hereafter referred as DMW sub basin)
in Sri Lanka which is a special case of practical
importance where there are intra-basin
diversions for irrigation systems. Irrigation
systems release part of irrigated water as
drainage flow to the downstream of them and
these drainage flows enter into the basin
drainage network and contributes to the flow at
the downstream reach of the Deduru Oya river
in the DMW sub basin. HEC-HMS model is
used for rainfall-runoff modeling of DMW sub
basin which contains intra-basin diversions and
storages.
The metrological model is responsible for
preparing the boundary conditions that act on
the watershed during a simulation. The
meteorological model stores the information of
precipitation falling on the watershed and
evapotranspiration. HEC-HMS supports six
different historical and synthetic precipitation
methods as well as one evapotranspiration
method [15].
The time span of a simulation is controlled by
control specifications and control specification
is used to describe the time period and time
ENGINEER
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2
2
1.1
DMW sub basin of Deduru Oya River
basin
DMW sub basin, which is an upper basin of the
Deduru Oya river, has an area of 1950 km2
ranging from 30 m to 1280 m MSL extending
from Moragaswewa to the central hills of Sri
Lanka (Figure 1). DMW sub basin of Deduru
Oya river basin covers 74% of whole Deduru
Oya river basin. DMW sub basin, located
between 7.3200 N and 7.8600 N latitudes, and
79.9900 E and 80.5800 E longitudes, is one of the
major rice production basins in the country.
The Deduru Oya river of DMW sub basin flows
through Matale and Kurunegala districts.
constructed under
reservoir project.
ongoing
Deduru
Rainfall is the only source of water and there
are no transbasin diversions into or out of the
basin at present. The rainfall in the basin has a
significant temporal and spatial variation.
Annual rainfall ranges from 2600 mm in the
upper basin to 1100 mm in the lower basin.
From the annual rainfall about 50% is received
during inter monsoon months (March-April &
October-November),
about
35%
during
Southwest
monsoon
months (May to
September), and remaining 15% during
Northeast monsoon months (December to
February). The Deduru Oya river carries flash
floods during rainy season and very low flow
during dry season. Presently nearly 1000 MCM
of water flows to sea annually from Deduru
Oya river basin without being used in the basin
[13]. There is a strong need to store flood water
carried by Deduru Oya river to use during lean
season, especially for irrigation.
The basin contains a number of small and large
reservoirs (tanks), mostly rain-fed, used for
irrigating paddy cultivation in two seasons per
year. There are several weirs (anicuts) built
across the river along its length to divert water
for irrigation system to cultivate paddy. There
are few reservoirs across tributaries of Deduru
Oya river but the only reservoir intercepting
the Deduru Oya river is the one being
Figure 2 - Study Area
3
ENGINEER
Oya
ENGINEER
3
1.2
Intra-basin diversion to Magalla tank
There is an intra–basin diversion of
considerable volume of the Deduru Oya river
flow to the right bank at its middle reach for
irrigated paddy cultivation. A weir constructed
across the river diverts water to an unlined
canal (Ridi Bendi Ela canal) of 21 km length and
4.25 m3/s capacity to Magalla tank (Figure 2).
The weir diverts almost all of the flow of the
river to the Magalla tank during low river flow
months. The Magalla tank with a capacity of 9
MCM stores water for the irrigation
requirements in downstream areas. The basin
area of Magalla tank is 32 km2. There are 2224
ha of paddy lands cultivated presently under
the Magalla tank irrigation system.
DRB Sub basin
Magalla Sub
basin
Ridi
Bendi Ela
Magalla tank
Irrigation
Systems
DMW-RB
Sub basin
The Magalla tank has three irrigation canals;
Right Bank (RB) canal, Left Bank (LB) canal and
Centre canal to distribute water. Capacities of
the canals and the irrigable areas under each
canal are shown in Table 1. The drainage water
from the paddy fields at Magalla tank irrigation
systems flows into the Deduru Oya river at the
upstream of Moragaswewa (Figure 2).
Moragaswewa
gauging station
Figure 3 - Schematic Diagram
Table 1 - Capacities of Magalla Tank Outlet
Canals and Irrigation Area
Canal
2.
Capacity
from DRB basin outlet through Ridi Bendi Ela
canal is 4.25 m3/s or maximum available at the
DRB basin outlet. The flow in excess of 4.25
m3/s is an inflow to the DMW-RB basin
through Deduru Oya river.
Irrigation
Area
RB Canal
3.40 m3/s
1792 ha
LB Canal
1.13 m3/s
312 ha
Center Canal
0.43 m3/s
120 ha
Magalla tank receives inflow from its own basin
and from the Ridi Bendi Ela canal. Daily
releases from Magalla reservoir for irrigation
systems through the three canals depend on the
irrigation requirements and available storage.
Methodology
Reservoir simulation was carried
estimate the actual daily releases.
For the application of HEC-HMS, the DMW sub
basin which has an area of 1950 km2 was
divided into two sub-basins; DRB sub basin of
an area of 1400 km2 above the irrigation
diversion at Ridi Bendi Ela and rest of the
DMW basin (referred to as DMW-RB sub basin)
of an area of 550 km2 (Figure 2). The schematic
diagram of the HEC-HMS model setup is given
in Figure 3.
to
2.1
Data collection
GIS data were used to identify stream paths,
catchments, natural streams, land use patterns,
geology and soil types in the basin.
Topographic, geological and land use details
were collected from the digital data of the
Survey Department of Sri Lanka. A major
portion of the soil in river basin was identified
as reddish brown earth [(9), (11)].
Daily stream flow at the DRB basin outlet was
estimated by HEC-HMS model application to
the DRB basin. Diversion to Magalla reservoir
ENGINEER
out
Irrigation requirements in the irrigation
systems were estimated by CROPWAT model.
Drainage flow from the irrigation systems was
taken as 40 % of the total release of Magalla
tank through the three canals according to loss
calculation and water balance study.
Ridi Bendi Ela canal was modeled as a
diversion element and Magalla tank was
modeled as a reservoir element. The drainage
flow from the irrigation systems under Magalla
tank is modeled as a reach element.
ENGINEER
Weir
Ela canal
4
4
Daily rainfall was collected from seven stations
in the basin (Figure 4), viz. Kurunegala,
Delwita, Wariyapola, Millawa, Ridi Bendi Ela,
Batalagoda and Nikaweratiya, for the past
twenty years from 1980 to 2000. Monthly
evaporation data for the same years for the
agro meteorological station Mahawa was used
in the study. The rainfall data and the
evaporation data were obtained from the
Rainfall Division of the Department of
Meteorology,
Colombo.
Also
hydro
meteorological data are available at the
Department of Meteorology [10]. The only flow
data available for the Deduru Oya is from 1980
to 1989 at Moragswewa gauging station. Daily
flow data for the latest three year from this data
set was used for model calibration and
validation, viz. 3 months for calibration and 3
years for validation.
For the calculation of CWRs, CROPWAT
needs data on evapotranspiration (ETo),
rainfall, crop data and soil data.
CROPWAT allows the user to either enter
measured ETo values, or to input data on
temperature, humidity, wind speed and
sunshine, which allows CROPWAT to
calculate ETo using the Penman-Monteith
formulae [3].
Rainfall data are used with CROPWAT to
compute effective rainfall data as input for
the CWR and scheduling calculations. Crop
data are needed for the CWR calculations
and soil data to calculate irrigation
schedules. Whereas CROPWAT normally
calculates CWR and schedules for one crop,
it can also calculate a scheme supply, which
is basically the combined CWR of multiple
crops, each with its individual planting
date [3].
Figure 4 - Rain Gauge Stations and Thiesson Polygon Areas
2.2
Crop Water Requirements
CROPWAT 8.0 software developed based on
the Food and Agriculture Organization of the
United Nations (FAO) guidelines is used for
calculation of Crop Water Requirements (CWR)
and irrigation requirements from climatic and
crop data. The program also allows the
development of irrigation schedules for
different management conditions and the
calculation of scheme water supply for varying
crop patterns [(3), (14)].
calculated for 105 day low land paddy crop
type. It was calculated using CROPWAT for
paddy crop on monthly basis. Rainfall data at
Nikaweratiya station in year 1980 to 2000,
Mahailuppallama
reference
crop
evapotranspiration rates and crop factors for
each growth stages were used for the
CROPWAT model to calculate CWR.
Computations of irrigation water requirements
were made using 60% application efficiency
and 75% conveyance efficiency.
5
ENGINEER
ENGINEER
5
it is possible to account for increased storage
during the rising side of a flood wave and
it
is possible
to account
storage
decreased
storage
during for
theincreased
falling side.
The
during
the
rising
side
of
a
flood
wave
and
Muskingum K is essentially the travel time
decreased
falling side.
through thestorage
reach. during
It can bethe
estimated
fromThe
the
Muskingum
K
is
essentially
the
travel
knowledge of the cross section properties time
and
through
the reach. The
It canMuskingum
be estimatedXfrom
the
flow
properties.
is the
knowledge ofbetween
the cross inflow
section properties
and
weighting
and outflow
flow
properties.
The Muskingum X is the
influence
[15].
weighting between inflow and outflow
influence
[15].
The inflow-diversion
function defines the
2.3
Model calibration
HEC-HMS version 3.0.1 was utilized as the
2.3
Model
calibration
rainfall
– runoff
model in Deduru Oya river
HEC-HMS
version
was utilized
as was
the
basin. Calibration for3.0.1
continuous
modeling
rainfall
–
runoff
model
in
Deduru
Oya
river
carried out by using daily rainfall occurred
basin. Calibration
for Dec
continuous
modeling
was
from
Oct 1985 to
1985. Soil
moisture
carried
out
by
using
daily
rainfall
occurred
accounting loss method, Clark unit hydrograph
from Oct 1985 method,
to Dec and
1985. recession
Soil moisture
transformation
base
accounting
loss were
method,
Clark unit
flow
method
utilized
for hydrograph
continuous
transformation
method, and recession base
simulations.
flow method were utilized for continuous
simulations.
The soil moisture accounting loss method uses
amount of flow that is diverted from a given
The
function variable.
defines The
the
inflow.inflow-diversion
Inflow is the independent
amount
of
flow
that
is
diverted
from
a
given
range of inflows specified in the function
inflow.
the complete
independent
variable.
The
should Inflow
cover isthe
range
of total
range offrom
inflows
specified
in the
inflows
upstream
elements.
Thefunction
inflowshould cover
the complete
range ofin total
diversion
function
must be defined
the
inflows data
frommanager
upstream
elements.
inflowpaired
before
it canThe
be used
in
diversion
function
must
be
defined
in
the
the diversion elements [15].
paired data manager before it can be used in
the
diversionObjective
elements [15].
Normalized
Function (𝑁𝑁𝑂𝑂𝐹𝐹), Nash
five layers to represent the dynamics of water
The
soil moisture
accounting
lossLayers
method
uses
movement
above and
in the soil.
include
five
layers
to
represent
the
dynamics
of
water
canopy interception, surface depression
movement
above
and groundwater,
in the soil. Layers
storage,
soil,
upper
andinclude
lower
canopy interception,
surface
depression
groundwater.
The soil layer
is subdivided
into
storage, storage
soil, upper
groundwater,
and lower
tension
and gravity
storage [(15),
(16)].
groundwater.
The accounting
soil layer isloss
subdivided
into
The
soil moisture
method was
tension
storage
and
gravity
storage
[(15),
(16)].
utilized for continuous simulations in all sub
The soil moisture accounting loss method was
basins.
utilized for continuous simulations in all sub
basins. unit hydrograph was selected as a
Clark
Sutcliffe efficiency (𝑅𝑅 ʹ ), Percentage bias (𝛿𝛿𝑏𝑏 )
Normalized Objective𝑁𝑁𝑆𝑆Function (𝑁𝑁𝑂𝑂𝐹𝐹), Nash
and Root Mean Square
ʹ Error (𝑅𝑅𝑀𝑀𝑆𝑆𝐸𝐸) values
(𝑅𝑅
), measures
Percentage
Sutcliffe
efficiency
𝑏𝑏 )
𝑁𝑁𝑆𝑆
were used as quantitative
forbias
the (𝛿𝛿
skill
andsimulations.
Root Mean Past
Square
Errorhave
(𝑅𝑅𝑀𝑀𝑆𝑆𝐸𝐸)
values
of
studies
shown
that
were
used
as
quantitative
measures
for
the
these parameters were successfully usedskill
to
of
simulations.
analyze
goodnessPast
of fitstudies
[(5), (6),have
(12)].shown that
these parameters were successfully used to
analyze goodness of fit [(5), (6), (12)].
transform method. Time of concentration and
Clark unit
hydrograph
selected to
as be
a
storage
coefficient
are thewas
parameters
transform method.
Time ofunit
concentration
and
defined
in
Clark
hydrograph
storage coefficient
the parameters
to be
transformation.
Thearetime
of concentration
defined the inmaximum
Clark travel
unittime hydrograph
defines
in the sub
transformation.
The
time
of
concentration
basin. It is used in the development of the
defines thehydrograph.
maximum travel
time in
the sub
translation
The storage
coefficient
basin.
It
is
used
in
the
development
of the
is used in the linear reservoir that accounts
for
translation
hydrograph.
The
storage
coefficient
storage affects [(15), (16)].
is used in the linear reservoir that accounts for
storage
affects base
[(15),flow
(16)].method is designed to
The
recession
ͳ
𝑁𝑁𝑂𝑂𝐹𝐹 ൌ 𝑂𝑂
ͳ
𝑁𝑁𝑂𝑂𝐹𝐹 ൌ 𝑂𝑂
𝑖𝑖ൌͳ
𝑛𝑛
ሺ𝑆𝑆𝑖𝑖 − 𝑂𝑂𝑖𝑖 ሻʹ
𝑖𝑖ൌͳ
ʹ
𝑅𝑅𝑁𝑁𝑆𝑆
ൌ ͳ − 𝑛𝑛
ʹ
𝑖𝑖ൌͳ ሺ𝑂𝑂𝑖𝑖 − 𝑂𝑂 ሻ ʹ
𝑛𝑛
𝑖𝑖ൌͳ ሺ𝑆𝑆𝑖𝑖 − 𝑂𝑂𝑖𝑖 ሻ
ʹ
𝑅𝑅𝑁𝑁𝑆𝑆 ൌ ͳ − 𝑛𝑛
ʹ
𝑛𝑛
𝑖𝑖ൌͳ ሺ𝑂𝑂𝑖𝑖 − 𝑂𝑂 ሻ
𝑖𝑖ൌͳ ሺ𝑆𝑆𝑖𝑖 − 𝑂𝑂𝑖𝑖 ሻ
𝛿𝛿𝑏𝑏 ൌ ∗ ͳͲͲΨ
𝑛𝑛
𝑂𝑂
𝑛𝑛 𝑖𝑖−ͳ 𝑖𝑖
𝑖𝑖ൌͳ ሺ𝑆𝑆𝑖𝑖 − 𝑂𝑂𝑖𝑖 ሻ
𝛿𝛿𝑏𝑏 ൌ ∗ ͳͲͲΨ
𝑛𝑛
𝑖𝑖−ͳ 𝑂𝑂𝑖𝑖
𝑛𝑛
approximate the typical behavior observed in
The recessionwhen
base flow
method isflow
designed
to
watersheds
the channel
recedes
approximate the
typical
behavior
in
exponentially
after
an event.
The observed
initial base
watersheds
when
the
channel
flow
recedes
flow at the beginning of a simulation must be
exponentially
after
an event.
initial base
specified.
Two
methods
areThe
available
for
flow
at
the
beginning
of
a
simulation
must be
specifying the initial condition: initial discharge
specified.
Two methods
are[15].
available
for
and
initial discharge
per area
Here initial
specifying
the
initial
condition:
initial
discharge
discharge was selected as one parameter. The
and
discharge
per area
[15]. Here
initial
otherinitial
parameter,
recession
constant,
describes
discharge
was
selected
as
one
parameter.
The
the rate at which base flow recedes between
other parameter,
constant,
storm
events. It isrecession
defined as
the ratiodescribes
of base
the rate
at current
which base
recedes
between
flow
at the
time,flow
to the
base flow
one
storm
events.
It
is
defined
as
the
ratio
of
base
day earlier. There are two different methods for
flow at the current
base
flow
one
determining
how to time,
reset to
thethe
base
flow
during
day
earlier.
There
are
two
different
methods
for
a storm event: ratio to peak and threshold flow
determining
how
to
reset
the
base
flow
during
[15]. Ratio to peak was selected as a parameter
a storm
event:
ratio
to peak
and threshold flow
in
this study
after
several
trials.
[15].
Ratio
to
peak
was
selected
a parameter
The Muskingum routing methodasuses
a simple
in
this
study
after
several
trials.
conservation of mass approach to route flow
The Muskingum
routing
uses
a simple
through
the stream
reach.method
However,
it does
not
conservation
approach
assume
that of
themass
water
surface tois route
level.flow
By
through
the
stream
reach.
However,
it
does
not
assuming a linear, but non-level, water surface
assume that the water surface is level. By
assuming a linear, but non-level, water surface
ENGINEER
ENGINEER
ENGINEER
𝑛𝑛
ͳ
ሺ𝑂𝑂𝑖𝑖 − 𝑆𝑆𝑖𝑖 ሻʹ
𝑛𝑛 𝑛𝑛
ͳ 𝑖𝑖ൌͳ
ሺ𝑂𝑂𝑖𝑖 − 𝑆𝑆𝑖𝑖 ሻʹ
𝑛𝑛
[1]
[1]
[2]
[2]
[3]
[3]
ͳ
ሺ𝑂𝑂𝑖𝑖 − 𝑆𝑆𝑖𝑖 ሻʹ
𝑇𝑇 𝑛𝑛
[4]
ͳ 𝑖𝑖ൌͳ
𝑅𝑅𝑀𝑀𝑆𝑆𝐸𝐸 ൌ ሺ𝑂𝑂𝑖𝑖 − 𝑆𝑆𝑖𝑖 ሻʹ
𝑇𝑇
[4]
Where,𝑂𝑂𝑖𝑖 𝑆𝑆𝑖𝑖 𝑛𝑛𝑂𝑂 𝑖𝑖ൌͳ
are observed discharge,
simulated discharge, number of the observed or
Where,
𝑂𝑂𝑖𝑖 𝑆𝑆𝑖𝑖 𝑛𝑛𝑂𝑂
are observed
simulated
data points
and meandischarge,
of the
simulated
discharge,
number
of the observed or
observed discharge respectively.
simulated data points and mean of the
observed
dischargeand
respectively.
All calibration
validation graphical
𝑅𝑅𝑀𝑀𝑆𝑆𝐸𝐸 ൌ representations were numerically analyzed by
All
calibration
and
validation
graphical
the goodness
of fit
according
to Normalized
representations
were numerically
analyzed by
Objective Function
(𝑁𝑁𝑂𝑂𝐹𝐹), Nash–Sutcliffe
the goodness ʹof fit according to Normalized
efficiency (𝑅𝑅𝑁𝑁𝑆𝑆 ), percentage bias (𝛿𝛿𝑏𝑏 ) and
Objective Function (𝑁𝑁𝑂𝑂𝐹𝐹), Nash–Sutcliffe
Root Mean Square
Error (𝑅𝑅𝑀𝑀𝑆𝑆𝐸𝐸) values.
ʹ
efficiency (𝑅𝑅𝑁𝑁𝑆𝑆
), percentage bias (𝛿𝛿𝑏𝑏 ) and
Root Mean Square Error (𝑅𝑅𝑀𝑀𝑆𝑆𝐸𝐸) values.
6 6
6
there is a good agreement between the
observed and simulated flows. Table 2 shows
the goodness of fitting between simulated and
observed flow for validation periods, and the
parameters fall within acceptable ranges. The
observed and simulated discharge hydrographs
are shown in Figure 6 and Figure 7 respectively.
If the simulated values exactly match with the
ʹ
, 𝛿𝛿𝑏𝑏 and𝑅𝑅𝑀𝑀𝑆𝑆𝐸𝐸 would be
observed,𝑁𝑁𝑂𝑂𝐹𝐹, 𝑅𝑅𝑁𝑁𝑆𝑆
equals to zero, one, zero percent and zero
respectively.
3.
Results and Discussions
3.1
Calibration
For the calibration period, which is from Oct –
Dec 1985, simulated daily discharge values
were compared with observed daily discharge
values. Figure 5 shows the graphical
distribution of simulated discharge against
ʹ
, 𝛿𝛿𝑏𝑏
observed discharge. The values of 𝑂𝑂𝐹𝐹 ,𝑅𝑅𝑁𝑁𝑆𝑆
Table 2 - Goodness of Fit for Stream Flow
Simulation
Event
and 𝑅𝑅𝑀𝑀𝑆𝑆𝐸𝐸 are equal to 0.30, 0.96, 4.88% and
Oct 1984 to
Sept 1985
3.2
Validation
The time series data from Oct 1984 to 30 Sept
1985 (1 year) and Oct 1987 to Sept 1989 (2 years)
were used for validation of continuous
simulation. Validation results indicate that
Oct 1987 to
Sept 1989
22 respectively.
𝑵𝑵𝑶𝑶𝑭𝑭
𝑹𝑹𝟐𝟐𝑵𝑵𝑺𝑺
𝜹𝜹𝒃𝒃
1.00
0.76
18%
1.00
0.7
𝑹𝑹𝑴𝑴𝑺𝑺𝑬𝑬
25
17%
34
600
Observed discharge
500
Simulated discharge
Dicharge / (m3/s)
400
300
200
100
0
5-Oct-85
15-Oct-85
25-Oct-85
4-Nov-85
14-Nov-85
24-Nov-85
4-Dec-85
14-Dec-85
24-Dec-85
Time
Figure 5 - Observed and Simulated Discharges at Moragaswewa for Oct - Dec 1985
400
350
Observed discharge
300
Discharge / (m3/s)
Simulated discharge
250
200
150
100
50
0
3-Oct-84
22-Nov-84
11-Jan-85
2-Mar-85
21-Apr-85
10-Jun-85
30-Jul-85
18-Sep-85 Time
Figure 6 - Observed and Simulated Discharges at Moragaswewa for Oct 1984 - Sept 1985
7
ENGINEER
ENGINEER
7
450
400
Observed discharge
350
Simulated discharge
Discharge / (m3/s)
300
250
200
150
100
50
0
3-Oct-87
11-Jan-88
20-Apr-88
29-Jul-88
6-Nov-88
14-Feb-89
25-May-89
2-Sep-89 Time
Figure 7 - Observed and Simulated Discharges at Moragaswewa for Oct 1987- Sept 1989
4. Conclusions
References
Paper presented a case study of runoff
modeling of part of Deduru Oya river basin
with intra- basin diversion and storages by
using the HEC–HMS model. The study used
the computed skill metrics of simulated stream
flow against observation as a criterion to
calibrate model parameters. Simulation skills,
ʹ
,𝛿𝛿𝑏𝑏 and 𝑅𝑅𝑀𝑀𝑆𝑆𝐸𝐸
as described by 𝑁𝑁𝑂𝑂𝐹𝐹 ,𝑅𝑅𝑁𝑁𝑆𝑆
agree reasonably well against observed
discharges.
1.
2.
3.
4.
The results show that the calibrated model is
capable of capturing the seasonal characteristics
of stream flow satisfactorily. By using long term
forecast daily rainfall, the model with the
calibrated parameters can be used for estimating
stream flow at the basin outlet. The study
demonstrates potential HEC–HMS application in
flow estimation from tropical catchments with
intra-basin diversions and irrigation storages.
The model developed is a useful tool for water
management in the Deduru Oya river basin.
5.
6.
Acknowledgements
The authors would like to convey their sincere
gratitude to UN-CECAR program of United
Nations University, Tokyo, Japan, for the
financial support for this research. The
hydrological and meteorological data for the
study were obtained from the Department of
Irrigation and Department of Meteorology.
ENGINEER
ENGINEER
7.
8.
8
8
Agrawal, A., “A Data Model with Pre and
Post Processor for HEC–HMS”, Report of
Graduate Studies, Texas A & M Univ. College
Station, 2005.
Chong–yu Xu, Text book of Hydrological
model, Uppsala university department of
earth science and hydrology, 2002.
Cropwat Reference Manual, 2009.
DE Silva, M. M. G. T., Weerakoon, S. B.,
Herath S., Modeling of Event and
Continuous Flow Hydrographs with HECHMS; A Case Study in the Kelani River
basin Sri Lanka, J. of Hydrologic Engineering,
ASCE, Vol. 19 No 04, 800-806, 2014.
Deva, K., Borah, M., ASCE; Jeffrey, G.,
Arnold; Maitreyee Bera; Edward, C., Krug;
and Xin-Zhong Liang, 2007, Storm Event
and Continuous Hydrologic Modeling for
Comprehensive and Efficient Watershed
Simulations,
Journal
of
Hydrologic
Engineering, Vol. 12, No. 6, November 1, 606616.
Moriasi, D. N., Arnold, J. G., Van Liew, M.
W., Bingner, R. L., Harmel, R. D., Veith, T.
L., 2007, Model Evaluation Guidelines for
Systematic Quantification of Accuracy in
Watershed Simulations, American Society of
Agricultural and Biological Engineers, ISSN
0001−2351, Vol. 50(3): 885−900.
Ehret, U., and Zehe, E., Series Distance – An
Intuitive Metric to Quantify Hydrograph
Similarity in Terms of Occurrence,
Amplitude and Timing of Hydrological
Events ,J. of Hydrology and Earth System
Sciences , Vol. 15., 877-896, 2011.
Halwatura, D., Najim, M. M. M.,
“Application of the HEC-HMS Model for
Runoff Simulation in a Tropical Catchment,
J. of Environmental modeling and software, 46,
155-162, 2013.
10. Long-term Hydro Meteorological Data in Sri
Lanka, Data Book of Hydrological Cycle in
Humid Tropical Ecosystem, Part I, Ed. K.
Nakagawa, H., Edagawa, V., Nandakumar &
Aoki, M., Special Research Projection 1995,
University of Tsukaba.
11. Mapa, R. B., Dissanayake, A. R., Nayakakorale
H. B., Soil of the Intermediate Zone of Sri Lanka:
Morphology characterization and classification,
2005.
12. Nash, J. E. and Sutcliffe, J. V., “River Flows
Forecasting Through Conceptual Models. Part 1
a Discussion of Principles”, J. Hydrology, Vol. 27
(3), pp. 282-290, 1970.
13. Pre-feasibility Study Report of Deduru Oya and
Mee Oya river basins Development Project,
Planning Branch, Irrigation Department,
Colombo, Sri Lanka, 2000.
14. Richard, G. A., Luis, S. P., Dirk, R., Martin, S.,
Crop
Evapotranspiration-Guidelines
for
Computing
Crop
Water
Requirements,
Publication No. 56 of the Irrigation and
Drainage Series of FAO, FAO, Rome, Italy, 1998.
15. Scharffenberg, W. A. and Fleming, M. J.,
“Hydrologic Modeling System HEC–HMS
User's Manual”, US Army Corps of Engineers,
Institute for Water Resources, Hydrologic
Engineering Centre , 2006
16. US army corps of Engineers, Hydrological
Engineering Center, HEC-HMS Technical
Reference Manual., March 2000.
9
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9
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Vol.XLVIII,
XLVIII,No.
No.01,
01,pp.
pp.[11-20],
[page range],
ENGINEER -- Vol.
2015 2015
© The
The Institution
SriSri
Lanka
©
InstitutionofofEngineers,
Engineers,
Lanka
Analysis on Energy Efficiency and Optimality of LED
and Photovoltaic Based Street Lighting System
Chandana S. Kulasooriyage, Satish S. Namasivayam and Lanka Udawatta
Abstract:
This study evaluates the optimality and energy efficiency of Light Emitting Diode
(LED) and Photovoltaic based street lighting systems as a part of energy conservation. This evaluation
is based on the detailed review carried out through a country wide street lamp survey.
Since LEDs are becoming increasingly competitive due to their rapidly increasing efficiencies and
decreasing cost, this research assessed the LED fixtures which have the capability of achieving 50% to
70% energy saving potential compared to the existing established technologies based street lamps
available in the country. As a case study, illumination levels were examined at two neighbouring
traffic junctions in the Capital City, from Bambalapitiya junction to Kollupitiya junction. Two kinds of
measurements were taken and average luminance levels were analysed for all measured points in the
traffic lanes. It was found that same lighting performance could be achieved by replacing 250W HPS
(High Pressure Sodium) by 150W HPS and further it was verified the same results while having 62%
energy saving by replacing 250WHPS lamps with 111W LED through a simulation with Lighting
RealityTM software. This change would easily meet the minimum recommended level of 7.5 Lux and
average luminance of 0.5 cd/m2 as per British Standards.
Even though solar powered street lighting systems need high capital outlay, it will be one of the most
appropriate energy solutions for a country like Sri Lanka. Incentive program development by the
government may further encourage LED street lamp and solar powered system development
adoptions. This study also recommends that any such incentive program should include performance
standards that consider warranty, efficacy and other important criteria as the next steps.
Keywords:
Street lighting, Luminance metrics, Light Emitting Diode, Solar panels, Energy
efficiency.
____________________________________________________________________________________
1.
Introduction
equipment,
control
and
management
practices have a direct impact on the level of
greenhouse gas emissions from street
lighting. Reductions in greenhouse gas
emissions are directly related to reductions in
energy consumption; hence the potential
savings are of the same order and vice versa.
Street lighting is an essential public service
that provides a safer environment at night
time to motorists as well as pedestrians.
Proper use of street lighting as an operative
tool provides economic and social benefits to
the public. The electrical energy consumption
of street lighting constitutes an important
part of total energy consumption. Saving
energy in street lamps is therefore important
for total energy savings.
2.
Annual Electricity consumption
in Sri Lanka
Ceylon Electricity Board (CEB) issues a
Statistical Digest in each year and it indicates
the energy statistics in the particular year.
Reductions in energy consumption through
the installation of modern lighting
Eng. Chandana S. Kulasooriyage, M.Sc. Eng.
(Moratuwa), MIE(Sri Lanka), MIIE(Sri Lanka),
GCGI(UK), C.Eng.,
I. Eng., Electrical Engineer, Ceylon Electricity Board.
Dr. Satish S. Namasivayam, B.Sc.(Hons)(Colombo),
M.Phil.(Colombo) , FilLic ( Uppsala) Ph.D. (Uppsala) ,
M.B.A ( Colombo), Department of Electrical Engineering,
University of Moratuwa.
Dr. Lanka Udawatta, B.Sc. Eng. (Moratuwa), M.Sc.
(Saito), PhD. (Saito), Faculty of Mechatronics Engineering,
Higher Colleges of Technology, UAE.
Figure 1 - Annual Electricity
Consumption in Year 2011
1
11
ENGINEER
ENGINEER
This
Thisis isthetheofficial
officialpublication
publicationto toexpose
exposethethe
energy
data
to
the
public.
Statistical
energy data to the public. Statisticaldata
data
published
publishedbybyCEB
CEBforforannual
annualelectricity
electricity
consumption
in in
SriSri
Lanka
- 2011
is is
shown
in in
consumption
Lanka
- 2011
shown
Figure
1.
Figure 1.
Even
Eventhough
thoughthethepercentage
percentagevalue
valueof ofstreet
street
lighting
energy
consumption
is
1.1%,
its
energy
lighting energy consumption is 1.1%, its energy
wastage
wastageis isfairly
fairlyaccountable
accountablesince
sincefrequent
frequent
complaints
have
been
made
by
the
public
and
complaints have been made by the
public
and
state
media
that
the
street
lamps
state media that the street lamps areare
continuously
continuouslyburning
burningin indaytime
daytimeat atvarious
various
places
in
the
country.
Even
though
control
and
places in the country. Even though
control
and
operational
work
of
the
street
lamps
are
done
byby
operational work of the street lamps are done
local
localauthorities,
authorities,electricity
electricitybills
billsforforenergy
energy
consumption
has
been
levied
consumption has been leviedbybyCEB
CEBin in
accordance
with
prepre
- prepared
estimates
since
accordance
with
- prepared
estimates
since
thethe
energy
meters
have
not
fitted
in
each
and
energy meters have not fitted in each
and
every
street
lamp.
While
there
is no
mechanism
every
street
lamp.
While
there
is no
mechanism
to to
update
that
estimates
and
new
installations
is is
update
that
estimates
and
new
installations
being
done
frequently,
a
large
amount
of
being done frequently, a large amount of
revenue
supposed
to to
be be
gained
byby
CEB
is is
notnot
revenue
supposed
gained
CEB
received
annually.
But,
even
updated
data
base
received annually. But, even updated data base
forfor
thethe
street
lamps
and
its its
accessories
areare
also
street
lamps
and
accessories
also
notnot
available
in
controlling
authorities
or
power
available in controlling authorities or power
utilities
in in
SriSri
Lanka.
Therefore,
it was
anan
utmost
utilities
Lanka.
Therefore,
it was
utmost
requirement
to
conduct
a
street
lamp
census
requirement to conduct a street lamp census
island
wide.
island
wide.
3. 3. The
Street
Lamp
Census
The
Street
Lamp
Census
A street
lamp
census
hashas
been
carried
outout
byby
thethe
A street
lamp
census
been
carried
CEB
in
all
over
the
country,
in
between
late
CEB in all over the country, in between late
February
2010
and
mid
May
2010.
A monitoring
February
2010
and
mid
May
2010.
A monitoring
team
from
each
province
was
formed
with
anan
team from each province was formed
with
Officer
in
Charge
of
each
team
to
carry
out
the
Officer in Charge of each team to carry out the
census
accurately
census
accurately
ByBy
thethe
results
of of
thethe
census
it was
found
that
a a
results
census
it was
found
that
majority
of
street
lamps
used
in
the
country
are
majority of street lamps used in the country are
mercury
mercuryvapour
vapourlamps
lampsand
andits itspercentage
percentageis is
34.2%.
Even
though
these
lamps
are
considered
34.2%. Even though these lamps are
considered
to tobe behaving
a
long
lifetime
by
having a long lifetime byreputed
reputed
manufacturers,
most
of of
thethe
local
authorities
useuse
manufacturers,
most
local
authorities
very
cheap
products
and
as
a
result,
lamp
very cheap products and as a result, lamp
. .
replacements
replacementsarearecounted
countedfrequently
frequentlyin intheir
their
nd highest percentage
maintenance
records.
The
2
nd
maintenance records. The 2 highest percentage
goes
to to
CFL.
Since
they
also
give
a low
intensity,
goes
CFL.
Since
they
also
give
a low
intensity,
these
lamps
are
suitable
for
by-roads.
Being
their
these lamps are suitable for by-roads. Being
their
lifelife
span
is
between
8000
–
10000
hours,
they
span is between 8000 – 10000 hours,
they
also
should
be be
replaced
frequently
[2].[2].
Hence,
also
should
replaced
frequently
Hence,
their
maintenance
cost
tends
to to
be be
higher.
The
their
maintenance
cost
tends
higher.
The
rd
percentage
goes
to
fluorescent
lamps.
3 3highest
rd highest
percentage goes to fluorescent lamps.
This
type
of of
lamps
with
low
wattages,
which
areare
This
type
lamps
with
low
wattages,
which
also
fitted
along
by-roads,
need
to
be
replaced
also fitted along by-roads, need to be replaced
frequently
because
it it
hashas
lower
lifelife
span,
and
frequently
because
lower
span,
and
further,
the
ballast
consumes
a
considerable
further, the ballast consumes a considerable
amount
of of
power.
Although
thethe
percentage
of of
amount
power.
Although
percentage
incandescent
lamps
is
8.5%,
the
number
incandescent lamps is 8.5%, the numberof of
lamps
is is
33,024,
so so
that
thethe
power
loss
is is
thethe
lamps
33,024,
that
power
loss
highest.
The
percentage
of
sodium
vapour
highest. The percentage of sodium vapour
lamps
lampsis is4.3%
4.3%and
andthese
thesearearehaving
havinghigher
higher
efficiency
and
longer
life
span.
efficiency and longer life span.
According
to to
thethe
street
lamp
survey,
some
of of
thethe
According
street
lamp
survey,
some
roads
and
streets
are
not
properly
lit
by
street
roads and streets are not properly lit by street
lamps
butbut
in in
some
streets,
specially
in in
Colombo
lamps
some
streets,
specially
Colombo
city,
it
has
been
found
that
some
roads
areare
over
city, it has been found that some roads
over
lit.lit. Hence
an
illumination
measurement
Hence an illumination measurement
program
hashas
been
implemented
byby
thethe
CEB
to to
program
been
implemented
CEB
understand
the
Lux
level
appearing
on
some
understand the Lux level appearing on some
major
roads.
major
roads.
4. 4.
Case
Study
Case
Study
Improvement
of of
thethe
Galle
road
from
Kollupitiya
Improvement
Galle
road
from
Kollupitiya
junction
to
Bambalapitiya
junction
as
a model
junction to Bambalapitiya junction as
a model
road
is
the
latest
project
of
the
Colombo
road is the latest project of the Colombo
Municipal
Council
(CMC)
which
was
launched
Municipal
Council
(CMC)
which
was
launched
in in
year
2010
to
create
a
sound
road
network
in in
year 2010 to create a sound road network
thethe
city.
An
arrangement
of
the
street
lamps
was
city. An arrangement of the street lamps was
done
donein ina adiagonally
diagonallyopposing
opposingconfiguration
configuration
erected
on
either
side
of
the
road
to to
make
it ait a
erected on either side of the
road
make
new
design
and
new
installation
and
250W
HPS
new design and new installation and 250W HPS
lamp
fixtures
were
also
fitted.
AsAs
a case
study,
lamp
fixtures
were
also
fitted.
a case
study,
illumination
levels
were
examined
by
the
CEB,
illumination levels were examined by the
CEB,
in in
collaboration
with
thethe
CMC,
to to
introduce
thethe
collaboration
with
CMC,
introduce
optimum
street
lighting
system.
optimum
street
lighting
system.
Table
1 -1Street
lamp
census
in in
May
2010
Table
- Street
lamp
census
May
2010
No.
of of
Lamps
No.
Lamps
CEB
CEB
CEB
CEB
CEB
CEB
CEB
CEB
Regon1
Region
2
Region
3
Region
4 4
Regon1
Region 2
Region 3
Region
Incandescent
4928
19787
4369
3940
Incandescent
4928
19787
4369
3940
Fluorescent
18476
38541
9883
17925
Fluorescent
18476
38541
9883
17925
Mercury
Vapour
50383
7520
15500
Mercury
Vapour 50641
50641
50383
7520
15500
Sodium
Vapour
9750
3752
1277
1856
Sodium Vapour
9750
3752
1277
1856
CFL
23091
23005
30083
44388
CFL
23091
23005
30083
44388
Other
430430
729729
7 7
66 66
Other
Total
107325
145197
53139
83675
Total
107325
145197
53139
83675
Type
of of
Lamp
Type
Lamp
ENGINEER
ENGINEER
ENGINEER
2 12
2
Total
Total
%%
33024
8.58.5
33024
84825
21.8
84825
21.8
133044
133044 34.2
34.2
16635
4.3
16635
4.3
120567
120567 31.0
31.0
1241
0.30.3
1241
389336
100.0
389336
100.0
A A convenient
convenient location
location to to measure
measure thethe
illumination
of of
lamps
onon
thethe
Galle
road
was
illumination
lamps
Galle
road
was
light
intensity
selected.
selected.After
After
measuring
measuring
thethe
light
intensity
of of
existing
HPS
lamps,
4 Nos.
adjacent
existing
250250
WW
HPS
lamps,
4 Nos.
of of
adjacent
were
replaced
bulbs
bulbs
with
with
opposite
opposite
direction
direction
were
replaced
byby
new
150W
HPS
lamps
illumination
new
150W
HPS
lamps
to to
getget
thethe
illumination
comparable
with
values
previous
ones.
comparable
with
thethe
values
of of
previous
ones.
78 78
measurement
points
were
laid
a lane
measurement
points
were
laid
outout
onon
a lane
markingcenters
centersto toform
formas asa agrid
gridin inthethe
marking
monitoring
monitoring
area.
area.
Spacing
Spacing
of of
thethe
grid
grid
points
points
of of
monitored
lamp
fixtures
along
road
was
monitored
lamp
fixtures
along
thethe
road
was
5m5m
between
two
onon
alternative
alternative
sides.
sides.
The
The
distance
distance
between
two
adjacentgrid
gridpoints
pointswas
was3.53.5m.m.The
TheLamp
Lamp
adjacent
Fixture
mounting
height
goes
above
Fixture
mounting
height
goes
upup
to to
12 12
mm
above
roadsurface.
surface.Illumination
Illuminationmeasurements
measurements
thetheroad
were
were
taken
taken
at at
a height
a height
of of
6 inches
6 inches
above
above
ground,
ground,
light
from
at at
around
around
7.00pm
7.00pm
when
when
natural
natural
light
from
thethe
moonwas
wasat ata aminimum.
minimum.Two
Twokinds
kindsof of
moon
measurements
were
taken
this
case
study.
measurements
were
taken
in in
this
case
study.
One
measurement
was
taken
switching
ON
One
measurement
was
taken
byby
switching
ON
lamps
that
spacing
between
lamps
was
allall
lamps
so so
that
thethe
spacing
between
lamps
was
30m
and
other
switching
OFF
alternate
lamps
30m
and
other
byby
switching
OFF
alternate
lamps
area
which
spacing
was
57m.
in in
thethe
testtest
area
in in
which
thethe
spacing
was
57m.
Luminance
metrics
were
calculated
identically
Luminance
metrics
were
calculated
identically
both
fixture
spacing
(30m
and
57m),
and
forfor
both
fixture
spacing
(30m
and
57m),
and
over
entire
area.
Average
illumination
over
thethe
entire
testtest
area.
Average
illumination
levels
were
calculated
based
measured
levels
were
calculated
based
onon
allall
measured
points
traffic
lanes
ordinary
calculation
points
in in
thethe
traffic
lanes
byby
ordinary
calculation
method
method
[4].[4].
Theuniformity
uniformityof ofthethelight
lightprovided
providedbybythethe
The
lamp
fixtures
was
measured
three
metrics:
lamp
fixtures
was
measured
byby
three
metrics:
Coefficientof ofVariation
Variation(CV),
(CV),also
alsoknown
knownas as
Coefficient
measureof ofthethedisparity
disparitybetween
betweenthetheactual
actual
measure
values
measured
points
and
average
values
of of
allall
measured
points
and
thethe
average
of of
those
values,
Average-to-Minimum
Uniformity
those
values,
Average-to-Minimum
Uniformity
ratio
ratio (AMU),
(AMU), and
and Maximum-to-Minimum
Maximum-to-Minimum
Uniformity
Uniformityratio
ratio(MMU).
(MMU). A Alower
lowerCVCVis is
indicative
indicative
of of
a more
a more
uniform
uniform
distribution
distribution
and
and
AMU
AMU
provides
provides
anan
indication
indication
of of
how
how
low
low
thethe
minimum
minimum
measured
measured
level
level
is is
compared
compared
to to
thethe
average
average
of of
allall
measured
measured
values.
values.
Thisindicates
indicatesthat
thatconsidering
consideringallallmeasured
measured
This
points
250W
and
150W
HPS
lamps
with
30m
points
of of
250W
and
150W
HPS
lamps
with
30m
spacing,
both
have
somewhat
equal
values
spacing,
both
have
somewhat
equal
values
forfor
AMU
and
MMU
and
that
tended
provide
AMU
and
MMU
and
that
tended
to to
provide
a a
more
uniform
lighting
distribution
both
cases
more
uniform
lighting
distribution
in in
both
cases
shownin inthethesummary
summaryof ofillumination
illumination
as asshown
measurement
table
2. Additionally,
both
cases
measurement
in in
table
2. Additionally,
both
cases
provide
better
uniformity
illuminated
areas
provide
better
uniformity
in in
illuminated
areas
and
57m
spacing
case,
it gets
worse
than
and
in in
thethe
57m
spacing
case,
it gets
worse
than
30mspacing
spacingcase.
case.Therefore,
Therefore,it itcancanbe be
thethe30m
concludedthat
thatusage
usageof of150W
150WHPS
HPSis ismost
most
concluded
suitableinstead
insteadof ofhigh
highpowered
powered250W
250WHPS
HPS
suitable
lamps.
lamps.
LED
Street
Lamp
Technology
4.14.1 LED
Street
Lamp
Technology
LightEmitting
EmittingDiodes
Diodes(LEDs)
(LEDs)arearethethelatest
latest
Light
technologyto toappear
appearin inthethestreet
streetlighting
lighting
technology
industry.
This
technology
is popular
high
industry.
This
technology
is popular
forfor
its its
high
energy efficiency,
efficiency, maintainability,
maintainability, and
and
energy
flexibility.The
Themore
morerecent
recentLED
LEDmodels
modelscancan
flexibility.
produce
over
lumens
light
watt
and
produce
over
100100
lumens
of of
light
perper
watt
and
expected
work
above
70%
their
initial
areare
expected
to to
work
above
70%
of of
their
initial
light
output
even
after
50,000
hours.
Indeed,
light
output
even
after
50,000
hours.
Indeed,
Haitz’s
Law
predicts
that
light
output
Haitz’s
Law
predicts
that
thethe
light
output
of of
LEDs
increases
a factor
every
years,
LEDs
increases
byby
a factor
of of
20 20
every
10 10
years,
while
cost
decreases
a factor
over
while
thethe
cost
decreases
byby
a factor
of of
10 10
over
same
period
time
time
this
thethe
same
period
of of
time
[5].[5].
AtAt
thethe
time
of of
this
research,
LEDs
beginning
installed
research,
LEDs
areare
beginning
to to
be be
installed
in in
outdoorlighting
lightingin inmost
mostof ofthethecountries
countries
outdoor
because
ability
lamp
fixture
provide
because
of of
thethe
ability
of of
lamp
fixture
to to
provide
greater
control
light
dispersion
and
greater
greater
control
of of
light
dispersion
and
greater
maintenancesavings
savingscompared
comparedto totraditional
traditional
maintenance
sources.
sources.
4.24.2
Street
lighting
design
using
computer
Street
lighting
design
using
computer
simulation
method
simulation
method
Most
importantly,
design
street
lighting
Most
importantly,
thethe
design
of of
street
lighting
system
must
appropriate
respective
roads
system
must
be be
appropriate
forfor
respective
roads
& streets
and
should
provide
sufficient
level
& streets
and
should
provide
thethe
sufficient
level
illumination
(Lux
level)
and
uniformity
of of
illumination
(Lux
level)
and
uniformity
of of
lightspecified
specifiedin inthethereputed
reputedstreet
streetlighting
lighting
light
standardssuch
suchas asBSBSENEN13201and
13201andIESNA
IESNA
standards
Standard
Grid
RP–8.
Standard
Grid
RP–8.
Table
2 -2Summary
of of
illumination
measurements
Table
- Summary
illumination
measurements
Average
Average
Maximum
Maximum
Minimum
Minimum
Average/Minimum
Average/Minimum
(AMU)
(AMU)
Maximum/Minimum
Maximum/Minimum
(MMU)
(MMU)
Standard
Standard
Deviation
Deviation
Coefficient
Coefficient
of of
Variation
Variation
(CV)
(CV)
250W
250W
HPS
HPS
250W
250W
HPS
HPS
150W
150W
HPS
HPS
( 57m
( 57m
spacing)
spacing) ( 30m
( 30m
spacing)
spacing) ( 30m
( 30m
spacing)
spacing)
Lux
Lux
Lux
Lux
Lux
Lux
26.70
26.70
45.60
45.60
16.60
16.60
57.00
57.00
3.90
3.90
6.80
6.80
14.60
14.60
16.11
16.11
0.60
0.60
13
3 3
67.00
67.00
21.00
21.00
2.20
2.20
3.20
3.20
11.05
11.05
0.24
0.24
30.00
30.00
8.00
8.00
2.10
2.10
3.80
3.80
6.95
6.95
0.42
0.42
ENGINEER
ENGINEER
ENGINEER
These
design
decisions
should
bebased
based
These
These
design
design
decisions
decisions
should
should
be be
based
on onon
meeting
oflocal
local
lighting
requirements
while
meeting
meeting
of of
local
lighting
lighting
requirements
requirements
while
while
achieving
maximum
energy
efficiency.
achieving
achieving
maximum
maximum
energy
energy
efficiency.
efficiency.
An AnAn
optimization
methodology
through
computer
optimization
optimization
methodology
methodology
through
through
computer
computer
simulation
toolnamed
named
Lighting
Reality
(LR)
simulation
simulation
tooltool
named
Lighting
Lighting
Reality
Reality
(LR)(LR)
software
hasbeen
been
applied
inthis
thisstudy
study
software
software
hashas
been
applied
applied
in in
this
study
to to to
identify
optimal
lamp
type
and
wattage
for
identify
identify
optimal
optimal
lamp
lamp
typetype
and
and
wattage
wattage
for for
the
thethe
existing
lamp
positions
Galle
road
section.
existing
existing
lamp
lamp
positions
positions
in Galle
in inGalle
road
road
section.
section.
Street
lamp
design
subjected
meet
specific
Street
Street
lamp
lamp
design
design
is subjected
is is
subjected
to meet
to to
meet
specific
specific
horizontal
illumination
uniformity
and
horizontal
horizontal
illumination
illumination
uniformity
uniformity
andand
luminance
requirements
according
guidance
luminance
luminance
requirements
requirements
according
according
to guidance
to to
guidance
published
by international
international
standards
published
published
by byinternational
standards
standards
[6]. [6].[6].
Therefore,
actual
figures
were
further
verified
Therefore,
Therefore,
actual
actual
figures
figures
were
were
further
further
verified
verified
by byby
comparing
with
simulation
values
arrived
comparing
comparing
with
with
simulation
simulation
values
values
arrived
arrived
by byby
using
Lighting
Reality
software,
which
offers
using
using
Lighting
Lighting
Reality
Reality
software,
software,
which
which
offers
offers
the thethe
key
benefits
enabling
the
design
lighting
keykey
benefits
benefits
of enabling
of of
enabling
the the
design
design
of lighting
of of
lighting
schemes
with
wide
selection
oflighting
lighting
schemes
schemes
with
with
a wide
a awide
selection
selection
of of
lighting
manufacturers’
products,
conforming
manufacturers’
manufacturers’
products,
products,
andand
ofand
conforming
of of
conforming
to to to
all
major
international
standards
including
all all
major
major
international
international
standards
standards
including
including
IES IESIES
Standard
Grid
RP-8
and
EN
13201
Standard
Standard
Standard
Grid
Grid
RP-8
RP-8
and
and
BS
BS
ENBS
EN
13201
13201
Standard
Standard
[7,8].
modal
layout
Lighting
Reality
Pro
[7,8].
[7,8].
A modal
A Amodal
layout
layout
of Lighting
of ofLighting
Reality
Reality
ProPro
software
is shown
Figure
software
software
is shown
is shown
in Figure
in in
Figure
2. 2. 2.
Hence,
suitable
LED
wasreviewed
reviewed
from
Hence,
suitable
from
Hence,
suitable
LEDLED
waswas
reviewed
from
the thethe
manufacturer’s
database
LR
software
verify
manufacturer’s
database
in in
LR
software
to to
verify
manufacturer’s
database
in LR
software
to verify
whether
it compatible
is compatible
with
selected
standards.
whether
is
with
selected
standards.
whether
it isitcompatible
with
selected
standards.
Therefore,
LED
andHPS
HPS
lamp
fixture
were
Therefore,
lamp
fixture
were
Therefore,
LEDLED
andand
HPS
lamp
fixture
were
chosen
compare
light
intensity
distribution
chosen
to tocompare
light
intensity
distribution
chosen
to compare
light
intensity
distribution
along
theselected
selected
Galle
road
section
forboth
both
along
Galle
road
section
along
the the
selected
Galle
road
section
for for
both
30m
& 57m
57m
lamp
spacing
in opposite
opposite
lamp
spacing
30m30m
& &57m
lamp
spacing
in inopposite
configuration.
British
Standards
(BS
EN
13201),
configuration.
British
Standards
EN
13201),
configuration.
British
Standards
(BS (BS
EN
13201),
recommend
theoverall
overall
uniformity
and
and
recommend
uniformity
recommend
the the
overall
uniformity
(U0)(U(U
0) 0)and
longitudinal
longitudinal
longitudinal
uniformity
uniformity
uniformity
(U1)(Umeasured
(U
) measured
at the
at atthethe
1) 1measured
2 and
2 and
2 0.40
2
2 2
road
road
road
surface
surface
surface
as as
0.35
as0.35
cd/m
0.35cd/m
cd/m
and0.40
cd/m
0.40cd/m
cd/m
respectively
respectively
respectively
for for
vehicular
for
vehicular
vehicular
roads
roads
roads
likelike
Galle
like
Galle
Galle
road
road
road
(ME5)
(ME5)
(ME5)
[6]. [6].
In
[6].In
order
Inorder
order
to to
achieve
toachieve
achieve
even
even
even
greater
greater
greater
energy
energy
energy
savings,
savings,
savings,
CMC
CMC
CMC
could
could
could
substitute
substitute
substitute
111W
111W
111W
LEDLED
LED
fixtures
fixtures
fixtures
for for
the
forthe
250W
the250W
250W
HPSHPS
HPS
lamps
lamps
lamps
as as as
investigated
investigated
investigated
above
above
above
by comparing
byby
comparing
comparing
Philips
Philips
Philips
– City
– City
– City
soulsoul
LED
soul
LED
(ECO113-28/740,
LED
(ECO113-28/740,
(ECO113-28/740,
11300
11300
11300
lm, lm,
cool
lm,
cool
white)
cool
white)
white)
andand
GE
andGE
lighting
GElighting
lighting
HPSHPS
lamp
HPSlamp
lamp
(LU250/XO/T/40,
(LU250/XO/T/40,
(LU250/XO/T/40,
33000
33000
33000
lm)by
lm)by
lm)by
simulation
simulation
simulation
results
results
results
of of
Lighting
ofLighting
Lighting
Reality
Reality
Reality
software
software
software
as shown
as as
shown
shown
in Figure
in in
Figure
Figure
3 &34.&
3 One
&
4. 4.
One
One
cancan
expect
canexpect
expect
to see
to tosee
the
seethe
same
thesame
same
luminance
luminance
luminance
at all
at atallall
points
points
points
by having
byby
having
having
62 %
62of
62
%energy
%
of of
energy
energy
saving
saving
saving
[9,10].
[9,10].
[9,10].
Figure
– Modal
layout
Lighting
Reality
Pro
software
Figure
–2Modal
layout
of of
Lighting
Reality
software
Figure
2 – 2Modal
layout
of Lighting
Reality
ProPro
software
Figure
Figure
Figure
3 - Simulation
3 -3Simulation
- Simulation
results
results
results
for forfor
luminance
luminance
luminance
measurement
measurement
measurement
for for
GE
for
GEGE
lighting
250W
HPS
lamp
lighting
lighting
250W
250W
HPS
HPS
lamp
lamp
ENGINEER
ENGINEER
ENGINEER
ENGINEER
Figure
Figure
Figure
4 – 4Simulation
–4Simulation
– Simulation
results
results
results
for forfor
luminance
luminance
luminance
measurement
measurement
measurement
for for
Philips
for
Philips
Philips
111W
111W
LED
LED
fixture
fixture
111W
LED
fixture
4
14
4 4
4.3
Luminance calculation
The road luminance and illumination
measurements are critical parameters that
4.3
Luminance calculation
affect the quality of road lighting. Those
The road luminance and illumination
should be measured in the field and analysed
measurements are critical parameters that
inaffect
driver’s
In the
case Those
study,
the perspectives.
quality of road
lighting.
Lighting
Reality
software
simulation
was
should be measured in the field and analysed
verified
with
selected
Galle
road
section
in driver’s perspectives. In the case study,
illumination
measurements
to provide
Lighting Reality
software simulation
was
sufficient
comparative
studies
verified with
selected Galle
road between
section
expected
values and
actual values.to provide
illumination
measurements
sufficient
comparative
studies
2.
Measurement of luminance level of
existing HPS lamps fixed in Galle
road section
2. Measurement of luminance level of
3. LED lamp is the kind of recently
existing HPS lamps fixed in Galle
developed energy efficient lamp in
road section
newlamp
generation
and it
special
3. LED
is the kind
of has
recently
features
such
as
dimming
facilities,
developed energy efficient lamp in
longgeneration
life and continuous
new
and it has technology
special
improvement.
in this
research,
features
such as Hence
dimming
facilities,
existing
replacement
long
life andlamps
continuous
technology by
equivalent LED
selected
as the
improvement.
Hencewas
in this
research,
best option.
The replacement
selection criterion
existing
lamps
by is
equivalent
was selected
as the life
indicated LED
in Table
4. Estimated
best
option.
The selection
is
spans
of existing
lampscriterion
are extracted
indicated
in Table
4. Estimated
life
from Energy
efficient
Street lighting
spans
of existing lamps
are –extracted
guidelines-USAID,
India
2010 [12].
between
The British Standards and IESNA Standards
expected values and actual values.
recommend a minimum illumination of 7.5
Themeasured
British Standards
and IESNA
Lux
at the road
surfaceStandards
for ME5
recommend
a
minimum
illumination
7.5
class vehicular roads. In this design, ofGalle
Lux
measured
at
the
road
surface
for
ME5
road was classified as ME5 class road having
class
vehicular
roads. Inofthis
road
surface
classification
R3. design,
Table 3 Galle
gives
road
was
classified
as
ME5
class
road having
the comparison of simulated values
with
road surface classification of R3. Table 3 gives
actual by 250W HPS lamp replacement with
the comparison of simulated values with
111W LED lamp which were used in opposite
actual by 250W HPS lamp replacement with
configuration in the said section.
from Energy efficient Street lighting
The manufacturers
of high
powered
SSL type
guidelines-USAID,
India
– 2010 [12].
white LED fixtures supplied to various
The manufacturers of high powered SSL type
countries predict the life span of the LEDs
white LED fixtures supplied to various
used in the fixture ranging from 50,000 to over
countries predict the life span of the LEDs
100,000 hours (roughly 12 to 24 years at 4380
used in the fixture ranging from 50,000 to over
hours hours
per year).
But 12
thetolife
100,000
(roughly
24 span
years assessed
at 4380 in
this
research
was
taken
as
50,000
hours
hours per year). But the life span assessed which
in
is research
the lowest
value
that hours
manufacturer's
this
was taken
as 50,000
which
It wasvalue
assumed
LED fixtures
isclaimed.
the lowest
that that
manufacturer's
would still
require
some that
levelLED
of maintenance
claimed.
It was
assumed
fixtures
costs still
and require
periodic
routine
for cleaning,
would
some
level visits
of maintenance
inspection,
control
circuitvisits
repair,
so forth.
costs
and periodic
routine
for and
cleaning,
inspection,
control
repair,
and so
Additionally,
as circuit
a fixture
consists
of forth.
multiple
Additionally,
a fixture
consists
of multiple
componentsas(LEDs,
driver,
housing,
coating,
components
(LEDs,
driver,
housing,
coating,
etc.), the expected useful life of the fixture
etc.),
useful
life ofofthe
theLEDs
fixture
maythe
not expected
be the same
as that
alone.
111W LED lamp which were used in opposite
configuration
in the
said
section.
Since
the existing
lamp
post
spacing cannot be
altered,
selection
of
street
lamps
been
Since the existing lamp post spacinghave
cannot
be
done
by
evaluation
of
simulated
&
actual
altered, selection of street lamps have been
luminance
lighting &
design
of
done by measurements
evaluation of in
simulated
actual
this
study.
Results
outcome
by
the
simulation
luminance measurements in lighting design of
showed
thatResults
111W outcome
LED is by
also
for
this study.
thesuitable
simulation
showed
that 111W
also suitablewith
for
57m
spacing
and LED
it is is compatible
57m spacing
and HPS
it ishaving
compatible
with
standard.
But, 250W
57m spacing
standard.
But,
250W
HPS
having
57m
spacing
is not suitable since it is not appropriate for
is appearance
not suitable since
it is beauty
not appropriate
for
the
of road
due to low
the
appearance
of
road
beauty
due
to
low
lighting level. The results of illumination
lighting
The lamps
results are
of inillumination
shows
that level.
250W HPS
overdesign
shows that 250W HPS lamps are in overdesign
according to the BS standards and 150W HPS
according to the BS standards and 150W HPS
lamps are good enough to cater the standards.
lamps are good enough to cater the standards.
Those actual and simulated results confirmed
Those actual and simulated results confirmed
that
this replacement is acceptable for energy
that this replacement is acceptable for energy
efficient
efficient- street
- streetlighting
lightingsystem.
system.
5.5.
may not be the same as that of the LEDs alone.
Due to the lack of unified international
Due
to the lack
of unified and
international
technical
standards
product
technical
standards
and
product
specifications, there are many kinds of LED
specifications, there are many kinds of LED
lighting products. Hence, broken lights and
lighting products. Hence, broken lights and
drivers should generally be replaced as a
drivers should generally be replaced as a
whole,resulting
resultingin inmaintenance
maintenance
difficulties
whole,
difficulties
and rising
risingcosts.
costs.However
However
luminous
and
the the
luminous
efficiencyofofLED
LEDstreet
streetlamps
lamps
efficiency
has has
beenbeen
increasing yearly
yearlyand
andprices
prices
falling.
increasing
are are
falling.
Therefore,
this
study
discusses
investment
Therefore,
this
study
discusses
the the
investment
valueofofLED
LEDstreet
streetlamps
lamps
present
value
at at
the the
present
market
marketvalue
value
Economic
in Case
Case
Economic Analysis
Analysis in
studies
studies
This
research
This
researchincludes
includestwo
two case
case studies;
studies;
1.1. Island
available
Island wide
wide survey
survey of available
existingstreet
streetlamps
lamps and
and
existing
Table3 3– –Comparison
Comparisonof
ofillumination
illumination (lux)
Road
class]
Table
(lux)measurement
measurement[ME5
[ME5
Road
class]
Actual
Actual
Lamp
type
Lamp
type
150W
150W
HPS
HPS
30
57
30
57
45.60
16.60
28.30
53.76
9.81
18.64
7.5(min.)
67.00
30.00
55.77
70.91
18.64
23.02
-
21.00
8.00
8.98
30.15
4.47
13.36
7.5(min.)
250W HPS
HPS
250W
Spacing (m)
Spacing
(m)
57
57
Average
26.70
45.60
Maximum
57.00
67.00
Minimum
3.90
21.00
Min. /Avg.
0.15
0.46
Average
Maximum
Minimum
Min. /Avg.
Min. /Max.
Min.
/Max.
Status
with
Status
with
standard
standard
26.70
57.00
3.90
0.15
0.07
0.07
Not
Not
comply
comply
Simulated
Simulated
30
30
30
16.60
30.00
8.00
250W
250WHPS
HPS
57
28.30
55.77
8.98
30
53.76
70.91
30.15
Standard
Standard
value
value
111W
LED
111W
LED
30
57
9.81
18.64
4.47
30
18.64
7.5(min.)
23.02
-
13.36
7.5(min.)
0.72
0.4(min.)
0.58
-
0.46
0.48
0.32
0.56
0.46
0.72
0.4(min.)
0.31
0.26
0.43
0.24
0.58
-
Comply
Comply
0.16
0.16
Not
Not
comply
Comply
Comply
Comply
0.31
Comply
0.48
0.26
Comply
0.32
comply
515
5
0.56
0.43
Comply
0.46
0.24
Comply
Comply
ENGINEER
ENGINEER
ENGINEER
Table 4 - Existing lamp replacement by LED
Type of lamp
Rated Power (W)
AverageLife Span (Hrs.)
No of lamp fittings
Lamp input power including ballast (W)
Replacement LED input power (W)
Power reduction (%)
LED useful life time ( hours)
Lamp Details
Incandes
cent
100
1000
33024
100
15
85
50000
Fluores
cent
40
5000
84825
60
28
53
50000
CFL
23
8000
120567
23
15
35
50000
Mercury
vapour
150
5000
133044
185
75
59
50000
Sodium
vapour
250
12000
16635
295
111
62
50000
LED fixture and the existing lamp fitting. The
resulting Simple Payback Periods and Net
Present Value (NPV) are calculated by
Discounted Cash Flow (DCF) analysis in the
lamp replacement scheme as per lamp basis
and it is summarized in Table 6[13].
Since the assumed life of the LED fixture is
greater than the longest time period
considered (12 years), end-of-life replacement
costs were not included in this analysis.
Fixture replacement frequency was then based
on an annualized probability of failure.
Annual maintenance costs were calculated
based on the probability of fixture failure
during and after the warranty period. It was
assumed that the cost of replacement for LED
fixture failure under warranty would be only
labor cost, while cost of replacement after
warranty included labor and fixture
replacement cost. Life span and failure
frequencies of existing lamps were verified by
available maintenance recording data received
from CMC and several local authorities. The
calculations are summarized in Table 5.
The payback periods in this particular case
study correspond to roughly 50,000 hours of
operation and are based on bulk-purchased
fixture costs. Individual fixture purchases, or
purchases in small numbers, would carry
increased lamp fixture cost, and thereby
lengthen the simple payback period.
In addition, the calculated simple payback
periods
are
sensitive
to
estimated
maintenance savings, which are in turn highly
dependent on the specific installation
scenario. As a result of these uncertainties and
the noted sensitivity, ranges were calculated
for each economic scenario considered around
the estimated annual maintenance savings.
In the lamp replacement scenario, the initial
investment for existing lamp installation is the
lamp fitting cost plus the cost of installation.
Since the cost of installation is assumed to be
the same for both lamp types, the total
incremental cost of installation for LED fixture
is the difference in material costs between the
Table 5 - Annual maintenance cost calculation of LED fixtures
Existing street lamps
Incandescent
Watts per lamp including ballast
Annual energy usage
Annual energy cost
100
CFL
60
23
Mercury
Vapour
185
Sodium
vapour
295
(kWh)
438.00
262.80
100.74
810.30
1292.10
(Rs)
8322.00
4993.20
1914.06
15395.70
24549.90
1100.00
500.00
450.00
1000.00
1100.00
950.00
450.00
1400.00
3100.00
4300.00
Annual maintenance cost (Rs)
Avg. annual Lamp cost
Fluorescent
(Rs)
Equivalent LED lamp fixtures
Watts per lamp fixture
15
Annual energy usage
65.70
122.64
65.70
328.50
486.18
1248.30
2330.16
1248.30
6241.50
9237.42
650.00
450.00
650.00
550.00
750.00
5000.00
7500.00
5000.00
45000.00
65000.00
Annual energy cost
(kWh)
(Rs)
Annual maintenance cost (Rs)
Lamp fixture cost
ENGINEER
ENGINEER
(Rs)
28
16
6
15
75
111
Table 6 - Lamp replacement economic analysis
Type of lamp
Incandescent lamp replacement by
15W LED lamp
Fluorescent lamp replacement by
28W LED lamp
CFL replacement by 15W LED lamp
Mercury vapour lamp replacement by
75W LED lamp
Sodium vapour lamp replacement by
111W LED lamp
6.
Incremental
Cost (Rs.)
Total annual
saving (Rs.)
Simple Payback
Period ( years)
12 – year
NPV (Rs.)
5000.00
7523.70
0.66
51698.36
7500.00
2713.04
2.76
12945.38
5000.00
465.70
10.74
- 1490.05
45000.00
9604.20
4.69
27376.94
65000.00
15312.48
4.15
53031.94
However environmentally, CFL disposal
effects must be taken into consideration since
above evaluation is based only on economic
gains.
Therefore,
except
CFL,
LED
replacement assessed in this option shows
significant energy and maintenance savings
potential, achieving 40% to 80% savings
compared to the existing street lamps.
Results
According to the street lamp survey in 2010,
approximately 390000 street lamps in different
types were used island wide, consuming
155GWh/year of electricity and representing
1.55 % of total electricity consumption in Sri
Lanka. Energy consumption for street lighting
in year 2009 was 108 GWh as per statistics
digest of CEB and this shows the percentage
increase of street lamp installation could be
30% annually [15]. Most probably the newly
installed street lamps also may be consisting
with inefficient technologies; the energy loss
will be increased annually and these should
be minimized to obtain an energy efficient
street lighting system. So, there are three
options which are identified to fulfil this
ambition, such as:
6.2
Option 2 – Replacement of all
existing street lamps by solar
powered LED lighting system
In this scenario, economic analysis was done
for replacing existing street lamps with stand
alone solar powered LED lighting systems.
The solar energy potential as renewable
energy can be selected to power this system so
that solar energy in Sri Lanka is highly reliable
and available throughout the daytime [17].
Even though, the apparent maintenance cost
of standalone system is very low, actual cost
may be much higher because system contains
rechargeable battery and electronic controller.
Other than that, components of standalone
system work throughout the day due to
electricity accumulation during daytime and
discharging it in night time. So, periodic
inspection needs to be done, especially on
batteries and electronic circuits.
6.1
Option 1 - Replacement of all
existing street lamps by equivalent
LED fixtures
Economic
performance
was
evaluated
primarily by simple payback of the LED
luminaries versus existing street lamps.
Considering the calculation results mentioned
in Table 6, it was understood that CFL bulb
replacement is not economical. DCF analysis
(NPV calculation) shows the figure becomes
negative and hence it is not recommended to
replace existing CFL by LED equivalent to get
an energy efficient street lighting system.
Table 7 - Lamp replacement economics for stand-alone systems
Type of lamp
Incandescent lamp replacement by
15W LED stand along system
Fluorescent lamp replacement by
28W LED stand along system
CFL replacement by 15W LED stand
along system
Mercury vapour lamp replacement
by 75W LED stand along system
Sodium vapour lamp replacement
by 111W LED stand along system
Incremental
Cost (Rs.)
Total annual
saving (Rs.)
Simple Payback
Period ( years)
12 – year
NPV (Rs.)
175000.00
8222.00
21.28
-104156.62
175000.00
4293.20
40.76
-138008.42
175000.00
1164.06
150.34
-164970.09
250000.00
15195.70
16.45
-119068.99
250000.00
23869.90
10.47
-44329.30
7
17
ENGINEER
ENGINEER
practical where the location is suitable for
each mode or combine of them.
The prices claimed by manufacturers for
stand-alone solar powered system vary with
the quality and the durability. Hence
maintenance and incremental cost were
considered according to the average values of
above factors. Hence the resulting simple pay
back periods and NPV are calculated for
stand-alone system in the same way as done
for DCF analysis for the existing lamps. These
calculations are summarized in Table 7.
This research has considered all the above
facts and the percentage of energy reduction
in each type of existing street lamps which
could be converted to equivalent LED
technology is shown in Table 9.
Hence, it was realized through this study that
it is possible to implement efficient street
lighting system by combining automatic lamp
controls with LED lamps for existing street
lamps except CFL.
The analysis shows that it is currently
uneconomical to integrate a solar powered
street lighting system with LED for each
existing street lamp. The deployment of such a
system increases the payback from 10 years to
onwards and hence the incremental energy
savings from selected LED lights are
insufficient to justify the cost on pure
economical basis.
7.
Even though LED usage around the world is
becoming matured and competitive, that
technology is still rather new to Sri Lanka.
Although the manufactures assure a very long
life span for LED products, they often provide
warranty only for 3 to 5 years. However, it is
likely that improvements in production or
added requirements could also affect the cost
of LED fixtures.
Despite the electrical savings, the present high
upfront cost of PV based LED street lighting
systems would be a barrier to their current
adoption. Somehow, if solar powered
technologies
were
implemented
in
conjunction with the LED lamps, there would
be potential reductions of at least 70% in CO2
emissions and zero energy costs from national
grid for street lighting as compared to
traditional technologies.
The most challengeable concern to implement
above system may be finding the capital cost
to initiate the system. Although the costs of
the product and installation are ultimately
recovered through the energy saving of the
street lamps, the local authority would still
hesitate to pay for the purchase and
installation of the LED street lights. Therefore,
an incentive program development by the
Government of Sri Lanka (GOSL) may further
encourage LED street lamps and standalone
solar
powered
system
development
adoptions. Nowadays, Urban Development
Authority (UDA) has initiated to install solar
powered street lighting systems in remote
areas which cannot be reached by the existing
national power grid as well as in jogging areas
where people do exercises.
6.3
Option 3 – Introduction of proper street
lighting control system
Nowadays a street lighting management
system does not properly exist in most of the
local authority areas. Therefore commuters
can see some lamps alight during the whole
daytime. Therefore, the 3rd option consists of
street lamp controlling management system
by 3 modes of operation such as; photocell
switching, timer switching and programmable
timer switching for partial night street lighting
instead of manual operation. The photocells
and timers are freely available in the local
market and those can be easily fixed to
existing street lamps or LED replacement
without
any
significant
modification.
Economic analysis was done to verify the
energy reduction for street lamps which were
counted in the survey and a summary is
shown in table 8.
It was found that proper inventory updating
system of street lamps has not been conducted
either by local authorities or by CEB. Survey
revealed that the expansion of street lamp
account would be 30% annually. Hence an
accurate
recording
system
should
be
implemented. In addition to the replacement of
existing lamps by LED equivalents, some street
lamps might have been installed for a purpose
that no longer exists, or they might be
significantly over-or undersized for current
needs. Therefore, some methods could be
applied to verify the operation and status of the
The research revealed that a street lamp
controlling management system also should
be implemented by using above discussed
three modes. These modes could be taken into
ENGINEER
ENGINEER
Conclusion
8
18
Table 8 - Energy saving by different modes of controlling in street lamps
Mode of operation
Daily energy saving
(kWh)
Percentage of
energy saving
(%)
Simple
Payback Period
(Years)
83034
14.3
2.42
Mode 2 - Timer switching
103793
17.9
3.75
Mode 3 - Programmable timer switching
126611
21.8
1.16
Mode 1 - Photocell switching
Table 9 - Comparison of energy saving & CO2 reduction by LED replacement with auto
controlling
Mercury Sodium
Parameter
Incandescent Fluorescent
Vapour
vapour
No. of lamps installed
33024
84825
133044
16635
100
60
185
295
15
28
75
111
11.9
11.9
11.9
11.9
233.60
225.89
1217.91
254.72
14.86
4.24
59.87
5.82
248.46
230.13
1277.78
260.54
2956.71
2738.59
15205.60
3100.49
79.85
49.39
58.58
61.06
Reduction of CO2 emission (ton)
4917.9
4755.6
25640.2
5362.6
street lighting system by electronically
tracking and reporting using modern database
system such as Geographical Information
System (GIS). As initial step, all parties
involved in the LED upgrades need to get an
accurate inventory of the street lights installed
in the system, and to correct any mistakes. A
Centralized Management System (CMS) can
also provide the capability to control LEDs
individually, by streets, and by zone, to dim,
performance monitor and reprogram LED
fixtures individually as well as to provide the
central node to other current or future city
infrastructure. This is one effective way to
increase the energy savings and bill savings
from the upgrades.
[4] Morante, P., "Mesopic Street Lighting
Demonstration and Evaluation Final Report",
Lighting Research Center, pp 27-32, 2008.
Total watts per lamp
Wattage of equivalent LED
Avg. lifetime of equivalent LED (years)
Total annual energy cost saving (Rs.Mn.)
Total annual maintenance cost saving (Rs.Mn.)
Total annual cost saving(Rs.Mn.)
Total cost saving during lifetime of LED(Rs.Mn.)
Percentage of total saving(%)
[5] Jackson, M., "Research Report: LED Lighting",
Woodside Capital Partners International, pp 310, 2012.
[6] Lighting Reality software,
www.lightingreality.com
[7] British Standards, BS EN 13201 1-4, Road
Lighting
[8] American National Standard Practice for
Roadway Lighting. ANSI / IESNA RP-8-00,
Approved 6/27/2000, P. 8
[9] Philips LED catalogue www.ecat.lighting.philips.com/l/led/function
al-lighting/citysoul-led/22412/cat//
References
[10] Luminaires Catalogue, International Edition
2010/2011, GE Lighting, pp 43 – 45.
[1] CEB Report, Statistical Digest – 2010, Statistical
Unit, General Manager’s branch, 2011.
[11] Douglas Hartley, Cassie Jurgens, Eric Zatcoff,
Street light report, "Life cycle assessment of
street lighting technologies", University of
Pittsburgh, 2009.
[2] Clinton Climate Initiative, Outdoor Lighting
Program, pp 11-12.
[3] LED Street Light Research Project, Pittsburgh,
pp. 22, September 2011.
[12] Energy Efficient Street Lighting Guidelines,
USAID ECO – iii Project, version 2, pp 2-4, 2010
19
9
ENGINEER
ENGINEER
[13] Herbohn, J., Hattison, S., "Introduction to
Discounted Cash Flow Analysis and Financial
Functions in Excel", 11(2), pp 111-116
[14] CEB Report, Statistical Digest – 2011, pp 511,Statistical Unit, General Manager's branch,
2012
[15] International Commission in Illumination, CIE
publications 140-2000, Technical Report, Road
lighting calculations.
[16] Ceylon Electricity Board, Annual Report &
Accounts-2010, System control Branch, pp.55103
[17] Peiris, T. S. G., Thatill, R. O., “An alternative
Modal of Solar Radiation”, Coconut Research
Institute, 26-34, 1994.
[18] Dowling, K., "The Future of LED Lighting",
Illumination Engineering Society, 2009.
[19]Highway Lighting, Bureau of design and
environment manual, December 2002, 56(2) –
56(5).
[20] Energy Efficient Street lighting Guidelines,
USAID ECO- iii Project, Version 2,
pp 2-4,
2010.
[21] Tichelen, P. V., Geerken, T., Jasen, B., " Public
Street Lighting – Final Report", pp 145-149,
2007.
[22] Efficient Street Lighting Design Guide,
Lighting Research Center, pp 4-5, 2003.
[23] Roadway Lighting Design manual, Minnesota
Department of Transportation, pp 28-34, 2006.
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01, pp.
pp.[21-30],
[page range],
ENGINEER- -Vol.
Vol. XLVIII,
XLVIII, No.
No. 01,
2015 2015
TheInstitution
Institution of
©©The
of Engineers,
Engineers,Sri
SriLanka
Lanka
Mitigation of Delays Attributable to the Contractors
in the Construction Industry of Sri Lanka Consultants’ Perspective
D. A. R. Dolage and T. Pathmarajah
This study focuses on determining important causes of construction delays
Abstract:
attributable to contractors in large construction projects in Sri Lanka and the degree of severity of
these causes. The causes of delay have been found based on the perceptions of the engineers working
for three state affiliated establishments namely, Department of Buildings (BD), Road Development
Authority (RDA) & National Water Supply and Drainage Board (NWSDB).The severity of each cause of
delay is measured and represented through a severity index (SI). The causes of delay were determined
and ranked in the descending order of severity. According to the findings, Poor project planning &
scheduling (SI -82.54) is the most influencing factor causing delays in construction projects. In the
descending order of severity, the other causes of delay are Low profit margin (SI -80.28), Inadequate
cash flow management (SI -78.31), Handling of too many project sat a given time (SI -75.21), and
Incompetence of the key staff (SI -74.93).Spearman rank correlation coefficient was used to determine
the degree of agreement on the ranking of severity of causes of delay among the organisations.
The highest degree of agreement is between BD &NWSDB (0.77). There exists an intermediate degree
of agreement between RDA & NWSDB (0.73) and the lowest is between RDA & BD (0.70).The study
finally makes 10 recommendations to mitigate construction delays.
Construction delays, Construction industry, Causes of delay
contribute to the overall construction delays.
1.
Introduction
The previous studies reveal that project delays
are mainly due to non completion of projects
Delay in completing construction projects is
on time by the contractor.
rampant across the world. They are invariably
accompanied by cost and time overruns.
A vast majority of major construction projects
Naturally, construction project delays have
carried out in Sri Lanka are funded through
undesirable effects on smooth functioning of
foreign loans which entail payments of
projects, such as adversarial relationships
interest. When a project is delayed, it incurs
among project participants, distrust, litigation,
costs by having to pay for additional salaries
arbitration
and
cash-flow
problems.
for staff and escalated material prices due to
Construction projects often get abandoned or
inflation. Hence, if delays are contained, profits
terminated due to the construction delays. If
could be increased, which can be utilised by the
the contractors follow systematic contractual
contractor for their business development and
procedures and proper project management,
economic growth for the country. Therefore,
the project delays can be minimised.
the study aims to identify the major causes of
Construction delays can be minimised only
construction delays attributable to the
when the causes of delay are identified and
countermeasures are taken.
Keywords:
Eng. (Dr.) D. A. R. Dolage, CEng, FIE(Sri Lanka),
BScEng. (Moratuwa), MSc (Reading), MA
(Colombo), MBA (SJP), DBA (UniSA), Senior
Lecturer, Department of Civil Engineering, The Open
University of Sri Lanka.
Eng. T. Pathmarajah, CEng, MIE(Sri Lanka), BSc
Eng. (Peradeniya), MTech (OUSL), Chief Engineer,
Road Development Authority, Sri Lanka.
Time management of a project is usually an
important requirement for both the owner and
the contractor of a particular project. Although
the inaction of the client and the consultant
and other factors such as unfavourable
government policies and „acts of God‟ also
ENGINEER
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contractors in Sri Lanka and the ways of
mitigating delays in construction projects.
proper construction planning, cash flow
management, human resource development
and further training in specialised skills,
frequent site meetings and joint site
inspections.
The main objectives of this study are;
1.
2.
3.
2.
To identify and rank the causes of delays
attributable to contractors in the
construction industry of Sri Lanka.
To assess the degree of agreement of
rankings of causes of delays among state
sector construction organisations.
To make recommendations to prevent or
mitigate construction delays based on the
analysis of its significant causes.
A study was conducted by Pathiranage and
Halwatura (2010) to identify the factors
influencing the duration of road construction
projects in Sri Lanka and propose ways to
mitigate delays. This study found that the
local road construction projects have
experienced from 56 to 88 percent of average
time overrun compared to the original
(planned) project duration. According to the
study, project financing by the client and the
cash flow problems of the contractor is the
most significant factor causing construction
delays. A recent study by Dolage and
Rathnamali (2013), revealed the most
significant factors causing time overrun, as per
the perceptions of all involved parties, are;
„rainy weather‟, „poor liquidity of the
contractor‟ and „inaccurate planning and
scheduling of projects.
Literature Review
2.1
Causes of Construction Delays
A plethora of both local and international
research studies conducted on causes of
delays in construction projects were
reviewed. Evidently, no study has been
carried out to examine the delays
attributable to the contractors in Sri Lanka,
hence there is a potential research gap.
Although similar studies have been carried
out in other countries, a study devoted to
examine the same aspect in the local
context is of great importance. This is
because of the differences in economic
policies, project characteristics, practical
problems and resource availability of Sri
Lanka in comparison to other countries.
2.2
Methodological Approaches
Most of the previous researchers have
adopted questionnaire survey methods to
obtain answers to the research questions. The
questionnaires have been designed to evaluate
the significance of causes for delays in project
completion, based on the perceptions of
respondents. Pathiranage and Halwatura
(2010)
identified
the
factors
causing
construction delays from the literature and
from a pilot survey in which the participants
were experienced highway specialists in Sri
Lanka. In this study, a questionnaire was
developed to assess the perception of
contractors on the percentage delay and the
relative significance index of factors
influencing the duration of road construction
projects in Sri Lanka.
Chan and Kumaraswamy (1998) conducted
a study to evaluate the relative importance
of 83 potential delay factors associated with
construction projects in Hong Kong and
found five critical delay factors, namely:
poor risk management and supervision,
unforeseen site conditions, slow decision
making, client-initiated variations, and
work variations.
A study was conducted by Jayawardane and
Pandita (2003) on the topic of evaluating and
mitigating the factors affecting construction
delays. According to this study, both
contractors and consultants have collectively
ranked rainy weather, manpower skill and
material shortage as the top ranking causes of
construction delays. In order to minimise such
delays, the study recommends the following;
Dolage and Perera (2009) carried out a study
on delays in the pre-construction phase of
state sector building projects by adopting a
questionnaire survey to evaluate the
perceptions of respondents of causes of delay.
Prior to the distribution of the questionnaire,
interviews were conducted with four
consultants, three clients and three contractors
to identify the factors causing delays in the
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pre-construction stage. Based on the outcome
of these interviews, a questionnaire was
developed to assess the perceptions of the
respondents. The relative importance of
various causes of delay was measured using
relative importance index.
experienced in project execution, 24 potential
causes of delay were identified. The
pertinence of these causes were verified
through senior engineers, involved in the
construction projects implemented by three
government owned, major infrastructure
construction organisations; BD, RDA and
NWSDB.
The selected causes were classified into three
main categories, namely, management related
causes, finance related causes and construction
related causes, based on the origin, as follows:
2.3
Research Gap
Most of the previous studies have analysed
the overall project delays caused by the
responsible parties with generic delays such
as excusable or non excusable construction
delays without considering the contract value.
Management Related Causes (MRC)
1. Poor project planning & scheduling
2. Incompetence of key staff
3. Poor decision making by management
4. Poor coordination with sub contractors
5. Poor coordination among staff
6. Delays in material supply
7. Disputes with other parties
8. Internal organisational problems
9. Poor skill development
10. Fraudulent practices in the organisation
In a study on construction delays, carried out
in Florida, Ahamed (2003) shows that different
parties are responsible for the overall project
delay as follows; Contractor 44%, Owner 24%,
Government 14%, Shared (between owner &
consultant)12% and Consultant 6%.
A study carried out on delays in public
utility projects of Saudi Arabia by Khalil
(1999), shows that different parties are
responsible for the overall project delay in the
following manner; Contractor 44%, Owner
22%, Consultant 14% and others 20%.
Finance Related Causes (FRC)
1. Low profit margin
2. Inadequate cash flow management
3. Inefficiency in billing and collecting
payments
4. Poor estimation practices
5. Inadequate progress reviews
6. Poor cost controlling system
According to Pathiranage and Halwatura
(2010), the contractor is the most responsible
party for road construction delays in Sri Lanka
of all the parties involved. The study also
reveals the responsibility of the client is
perceived to be more important than that of
the consultant. However, no attempt has been
made to examine contractor‟s contribution to
delays in major construction projects, and
proposes mitigative measures for construction
delays in Sri Lanka.
3
Construction Related Causes (CRC)
1. Handling of too many projects at a given
time
2. Faulty work
3. Poor communication with other parties
4. Insufficient quality control
5. Poor supervision of work
6. Insufficient availability of equipment
7. Unqualified workforce
8. Insufficient safety precautions at site
Methodology
3.1
Classification of causes of delay
The causes of construction delays could vary
from country to country because of the
differences in political, economic, social, and
environmental conditions, and government
regulations. In previous studies, different
researchers have examined construction
project delays from a different perspective
and identified a number of different causes of
delay. From these studies and the interviews
that the authors conducted with engineers
3.2
Collection of data
The knowledge required for this research
came from review of literature, professional
experience of the authors and interviews with
the experts. The primary data was obtained
through
a
questionnaire
which
was
distributed to engineers attached to BD, RDA
and NWSDB. The questionnaires were filled
by the heads of divisions or senior engineers
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individual organisations, the agreement on
ranking between organisations was evaluated.
of large projects. The respondents were asked
to indicate the relative importance of each
cause of delay on a five-point Likert scale; the
points are: Strongly disagree -1, Disagree -2,
Neutral -3, Agree -4 and Strongly agree -5.
4.
4.1
Severity indices
The severity index of each cause of delay
was computed with respect to each
organisation, and presented in Table 1. As
per Table 1, the top ten factors causing delays
in construction projects, in the descending
order of significance are as follows: Poor
project planning & scheduling (SI - 82.54),Low
profit margin (SI - 80.28),Inadequate cash
flow management (SI - 78.31),Handling of too
many projects at a given time (SI - 75.21),
Incompetence of key staff (SI - 74.93), Poor
decision making by management (SI 74.08),Insufficient quality control (SI - 74.08),
Insufficient availability of equipment (SI 73.24), Poor supervision of work(SI - 72.11) and
Delays in material supply (SI - 71.83). Figure 1
shows the severity indices of causes of delay
with respect to individual organisations and
when the responses of all three organisations
are combined.
The selected state organisations for the study
have different organisational setups. The RDA
is an authority dealing with construction and
maintenance of large scale projects associated
with A and B Class roads, airports,
expressways and large bridges. The NWSDB
is a statutory board concerned with
construction and maintenance of major water
treatment plants, sewage plants, supply lines,
and water towers, while the BD is a state
department dedicated to handling state sector
building requirements.
3.3
Approach to Data Analysis
Each cause of delay has a corresponding severity
index which is computed using the following
equation:
Severity Index (SI) = ∑aiXi
Where: i= 1,2,3,4,5
a1= 1/5 for 'Strongly disagree', a2= 2/5 for
'Disagree', a3= 3/5 for 'Neutral',a4= 4/5 for
'Agree' and a5= 5/5 for ' Strongly agree'
Xi is the variable expressing the percentage of
frequency for the ith response.
4.2
Spearman Rank Correlation
Coefficient
The Spearman correlation coefficients between
organisations were computed to determine the
degree of agreement on ranking and
presented in Figure 2. There is a high degree
of agreement between BD & NWSDB (0.77),
RDA & NWSDB (0.73) and RDA & BD (0.70).
Spearman‟s rank correlation coefficient is used
to measure the degree of agreement on the
severity of causes of delay between responses
of any two organisations. The rank correlation
coefficient is calculated using the formula:
The degree of agreement in the ranking of
factors between two organisations can vary
owing to the variation of scope of work,
nature and value of projects and the setup of
the organisations. In general, the projects
handled by the NWSDB and the BD are
almost similar in terms of scope of work,
worksite administration, value of the project
and use of materials. But the nature of the
projects executed by the RDA is different from
r =1-(6 ∑d2)/(n3-n)
Where r is the Spearman rank correlation
coefficient between two parties, d is the
difference between the ranks assigned to a
given cause of delay, and n is the number
of pairs of the variables. Using the ranking
of causes of construction delays for the
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Results and Discussion
4
24
Table 1 - Severity indices of causes of delay based on perceptions of respondents
Severity Indices
Causes of delay
RDA
NWSDB
BD
79.26
85.64
83.16
1 Poor project planning & scheduling
79.26
76.82
86.32
2 Low profit margin
77.04
79.27
78.95
3 Inadequate cash flow management
73.33
72.83
81.05
4 Handling of too many projects at a given time
71.85
75.24
78.95
5 Incompetence of key staff
71.11
75.24
76.84
6 Poor decision making by management
77.04
70.43
74.74
7 Insufficient quality control
71.85
76.82
70.53
8 Insufficient availability of equipment
69.63
75.24
71.58
9 Poor supervision of work
68.15
73.65
74.74
10 Delays in material supply
73.33
68.14
71.58
11 Inadequate progress review
67.41
72.15
74.74
12 Faulty work
Poor
coordination
with
sub-contractors
69.63
72.15
70.53
13
67.41
68.14
71.58
14 Poor communication with other parties
64.44
69.60
70.53
15 Unqualified Workforce
70.37
64.12
67.37
16 Poor coordination with staff
67.32
68.80
69.47
17 Poor skill development
66.67
68.14
64.21
18 Poor cost controlling system
65.93
56.81
68.42
19 Poor estimation practices
63.70
66.46
66.32
20 Inefficiency in billing and collecting payments
68.15
64.84
61.05
21 Insufficient safety precautions at site
56.30
64.22
70.53
22 Fraudulent practices in the organisation
65.93
56.81
61.05
23 Internal organisation problems
Disputes
with
other
parties
57.78
67.23
56.84
24
100
RDA
90
BD
NWSDB
All
82.54
80.28
78.31
75.21
74.93
74.08
74.08
73.24
72.11
71.83
70.99
70.99
70.70
68.73
67.89
67.32
64.47
66.48
65.92
65.35
65.07
62.82
61.41
60.85
ALL ORG.
Severity Index
80
70
60
50
40
30
20
10
Delay Cause
Figure 1 - Severity indices of causes of delay
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CRC8
CRC7
CRC6
CRC5
CRC4
CRC3
CRC2
CRC1
FRC6
FRC5
FRC4
FRC3
FRC2
FRC1
MRC10
MRC9
MRC8
MRC7
MRC6
MRC5
MRC4
MRC3
MRC2
MRC1
0
Spearman Correlation cofficient
reluctant to update schedules on a regular
basis.
0.8
0.78
Projects should be planned in such a way
that much of the work is executed in the
months of favourable weather since wet
months are less suitable for construction
work. Most of the time, resources in projects
either become idle or go skimp, due to
improper scheduling. Contractors should
schedule the work in such a way that it
facilitates the continuous and uninterrupted
utilisation of their resources.
0.76
0.74
0.72
0.7
0.68
0.66
RDA & BD
RDA & NWSDB BD & NWSDB
4.3.2
Low profit margin
Profit which is the reward for implementing a
project is the amount of money realised after
setting aside for the expenditure. Profit
invariably depends on the risk and difficulties
associated with the project execution. If the
perceived risk and difficulties to be encountered
in a project are high, a higher profit margin
should be allocated. Besides the profit margin,
which the contractor assigns to the bid
determines his chances of securing the contract.
Due to the increased number of contractors
bidding for a single project, the margin of profit
has squeezed as of late. The consequent resource
problems and possible mistakes in execution of
projects, could affect the profitability of projects.
The government of Sri Lanka receives funds
from donor countries for infrastructure
development with conditions attached. One
such condition is that the respective tender be
awarded to a contractor from the donor
country itself. Such tenders are always
awarded at an exorbitantly high profit margin.
Thereafter, the contractor who won the bid,
negotiates with a few local contractors and
subcontracts the work to the one who quoted
the lowest price. Due to scarcity of work or in
order to enhance cash flows, quite often they
hardly keep a reasonable profit margin. In such
case, the accurate estimation of project cost
before bidding is of great importance to the
contractor. The cost estimate of labour,
construction
equipment,
materials,
subcontracts, taxes, overheads, and surety
bonds need to be calculated accurately and
added to the mark-up to arrive at the final bid
value.
Organisations
Figure 2 - Spearman rank correlation coefficient
those of the NWSDB and the BD in terms of
geographic areas of operation, degree of heavy
machinery usage and scope of work related to
the projects. Therefore, the results of rank
correlation are consistent with the perceptions
expected of the respondents of these
organisations on causes of delays attributable
to the contractors.
4.3
Mechanism of causes of delay and
mitigative measures
This study considered 24 significant
construction causes of delay attributable to
the contractor. Nevertheless, this paper
analysed only the top ten causes with
respect to mechanisms and mitigative
measures. The mechanisms and mitigative
measures for the ten causes of delay are
presented below.
4.3.1
Poor project planning and scheduling
The contractor should implement the project
activities in the proper sequence to complete
the defined stages of the project within the
stipulated time frame, with designated
resources. Contractors often fail to come up
with a practical and practical work program at
the planning stage. Project delays occur mostly
due to inadequate experience of the
contractors with regard to project planning.
Proper scheduling should ensure that
projects
do
not
encounter
resource
bottlenecks at any stage of the project
implementation. The contractors are usually
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4.3.3
Inadequate cash flow management
Inadequate cash flow management by the
contractor could cause delays in the project.
The availability of money on time is quite
important for project success. If sufficient
money for the project expenses is not available,
the due payments will remain unsettled for a
long time resulting in project delays. In these
situations, businesses with high gearing are at a
risk.
resources. Therefore, the contractor should
undertake only a manageable number of
projects, which is commensurate with the
existing capacity.
4.3.5 Incompetence of key staff
Incompetence of key staff is one of the
significant causes of construction delays.
Some contractors are weak in project
planning, implementation and controlling of
site operations due to the incompetence of the
key staff. Although contractors claim at the
bidding stage to be having qualified project
managers, they are unable to provide them
once the project is in progress.
Some public sector organisations take an
unduly long time to settle the progress
payments due to the rigorous internal
procedures that are involved.
Delays in
receiving payments for the work completed
by the contractor, directly affect the
completion period of the project. The
contractor is able to receive the payments for
„material at site‟ and „advance for material
purchase‟ in the progress payment bill if it is
stipulated in the contract documents.
Effective project implementation requires
the services of competent personnel. It will
make the following tasks efficient and
effective; supervision, decision making,
work planning and coordination at the site.
These are the attributes necessary to achieve
successful project performance. Contractors
should ensure that they have the right personnel with correct qualifications and
relevant experience to manage the projects.
The project managers must have experience
and
qualifications
in
construction
management so that they can effectively
utilise the latest project management tools. A
typical project management problem that
results from insufficient capacity of the key
staff is the slow response to the issues that
occur at sites; this will badly impact on the
overall work progress.
4.3.4
Handling of too many projects at a
given time
There are many factors a contractor should
consider before determining the optimum
number of projects that could handled
concurrently, which are as follows; number of
workers, availability of machinery and
financial resources, management capability
and the types of work. Both quality and
progress of construction can become affected if
a contractor undertakes more projects than
their
capacity
permits.
The
resultant
inadequate supervision invariably results in
poor quality work and complaints from the
consultant, followed by instructions to
„rework‟. Main contractors mostly delegate
works to subcontractors who may have a low
motivation to perform the works as per the
schedule and required quality. If a contractor
undertakes too many projects, he will have to
concomitantly increase the capacity of
resources. The contractor has to deploy the
available resources across all projects
undertaken. The projects commenced later may
not have sufficient resources left to continue
uninterrupted. Inevitably, the contractor
encounters the difficulty of executing all
projects undertaken in parallel, and ultimately,
none of the projects can be completed within
the stipulated period. This is because, in the
short run, it may not be possible to increase
4.3.6
Poor decision making by
management
The decision to bid for a large construction
project should not be taken until all significant
factors have been considered in an objective and
precise manner. This decision should be
satisfactory from all view points. A l l the key
members of the management staff should
participate in making important decisions
concerning updating and regulating the
company policies.
4.3.7
Insufficient quality control
It is not uncommon in construction projects
that completed work becomes rejected by
consultants due to inferior quality. In such
situations, the contractors are instructed to
put it right at their own cost and time. Such
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situations could lead to disputes as to who
should bear the additional cost of corrective
work and the extra time taken. Delays caused
due to adopting improper construction
methods, supplying of inferior quality
materials, improper testing methods and
defective work are more crucial to the
contractor than to the consultant. The
contractors should be more committed to
conformance to project specifications.
improve
projects.
construction
Construction projects involve a series of
dependent and interrelated activities which
engage important resources such as money,
manpower, machinery etc. If the crucial
materials are not supplied in time, the
respective activity cannot progress, causing
delays in the dependant activities. This may
also result in some machinery going idle,
adding to the cost. The purchasing officer
should follow the relevant procurement
procedure to ensure materials are available at
site, in time and in required quality and
quantity. Some construction materials have to
be imported from abroad. If there is any delay
in importing these materials, it could cause
delays in completing the project.
Sometimes contractors do not use appropriate
equipment in projects because either the
appropriate equipment for the particular
work is not available or too expensive to hire.
In Sri Lanka, most of the foreign contractors
complete projects on time and „as planned‟
because they use appropriate machinery and
equipment for the work.
5.
Conclusions and
Recommendations
In this study, a significant attempt has been
made to identify the important causes of
delays attributable to the contractor and
propose mitigative measures concerning
the construction industry of Sri Lanka.
The contractor must adopt a very effective
maintenance program to minimise major
breakdowns of equipment, thus avoiding big
losses. Poor maintenance of equipment results
in the increasing of downtime and the
decreasing of the life time of the equipment.
ENGINEER
productivity of
4.3.10 Delays in material supply
Purchasing and supplying of materials in time is
very important in construction because any delay
in this could affect the work programme.
Approval has to be sought in time from the
consultant or client before purchasing certain
materials.
4.3.8
Insufficient availability of equipment
Use of equipment is very important to
contractors because this could save time and
money. Many of the contractors do not keep
their construction equipment in good
condition, so they may not be readily
available for the construction work. When the
construction projects undertaken are too many
and too heavy, the number of equipment
available to be engaged in the project may not
be adequate. In this situation, the equipment
could become defective due to overuse and
not having sufficient time for maintenance.
4.3.9
Poor supervision of work
The quality of work can become inferior due
to poor supervision at site. Since there is a
direct relationship between construction output
and the cost, the supervision of the former is
vital. Due to poor supervision of construction
work, it could become substandard or
defective therefore it has a chance of being
rejected. The development of the capacity of
the supervisory staff through workshops and
technical training is an essential consideration.
Quality assurance, motivational programmes
and site safety systems should be established to
ENGINEER
the
The study revealed that improper planning
and scheduling of the contractor is the most
significant delay factor among the 24
important causes of delay identified in this
study.
Based on the findings of the study, the
following recommendations can be made to
mitigate the causes of delays attributable to
the contractor with respect to major
construction projects in Sri Lanka.
1
8
28
The contractor must prepare a realistic
work programme in such a way that it is
commensurate with his capacity and
realistic duration. It means that
scheduling should ensure that the
project does not experience significant
resource bottlenecks. It is essential that
he holds progress review meetings
regularly, involving all parties to ensure
that the work progresses according to
the schedule.
8.
9.
2. The contractor‟s bid value should be
realistic. They must ensure that they
have the financial strength, necessary
resources and capabilities, to complete
the project at the quoted tender sum.
3.
4
5.
6.
7.
The contractor should improve their
productivity, cost control systems, and
quality of work through appropriate follow
up action.
The contractor should develop human
resources through proper technical training
and recruiting qualified and experienced
craftsmen.
10. The contractor should prepare an
appropriate procurement plan for material
purchasing in order to maintain the buffer
stocks of material on site. They also should
engage a material specialist conversant in
contract specifications to decide on the
type materials required for the project.
The Contractor should use their
financial resources effectively and
manage the cash flows by utilising
advanced payments and progress
payments. The Contractor should also
prepare
the
monthly
payment
documents in time.
11. Since the contractors are usually more
responsible for construction delays in a
project, the Contractors Association of Sri
Lanka must prepare Guidelines on
mitigating construction delays.
The contractor must have a good
assessment of their maximum capacity in
terms of previous experience, availability
and capacity of workers, machinery,
management capability, and the size of
their geographic operational area.
References
The contractor should recruit right
personnel with the correct qualifications to
manage their projects. The skills of applying
project management techniques of the
contractor‟s staff have to be updated to
ensure that they are conversant with the
latest techniques. The key personnel at the
managerial level should be invited to
participate with important decision making
regarding the project execution and
regulating the contractor‟s policies. The
contractor's inside information should be
kept in confidence at all times.
The contractor should conform to the
specifications when supplying construction
materials, service fittings and equipment
etc.
The contractor should ensure that the
appropriate machinery and equipment are
available in time. They should adopt daily
and periodic maintenance programs for the
equipment, according to the manuals.
ENGINEER
1.
Ahmed, S., Azher, S., Castillo, M.,
Kappagantula, P. “Construction Delays in
Florida; An Empirical Study”, 2003.
2.
Al-Barak, A. A., “Causes of Contractor‟s
failures in Saudi Arabia”, Master thesis, CEM
Dept., KFUPM. Dhahran, Saudi Arabia, 1993.
3.
Al-Khalil, M., Al-Ghafly, M., “Important
Causes of Delay in Public Utility Projects in
Saudi Arabia”, Construction Management and
Economics,1999;17(5):647–55.
4.
Assaf, S. A., Al-Halil, M., Al-Hazmi, M.,
“Causes of Delay in large Building Construction
Projects”, Journal of Management in Engineering.
ASCE1995, 45-50.
5.
Assaf, S. A., Al-Hejji, S., “Causes of Delays in
Large Construction Projects”, International
Journal of Project Management, 2006, 24(4), 349357.
6.
Chan, D. W., Kumaraswamy, M. M., (1991),
“Comparative Study of Causes of Time
Overruns in Hong Kong Construction
Projects”, International Journal of Project
Management, 1997,55–63.
9
29
ENGINEER
7.
Chan, D. M., Kumaraswamy, M. M.,
“Contributors
to
Construction
Delays”,
Construction Management and Economics (1998),
17-29.
8.
Dolage, D. A. R., and Rathnamali, D. L. G.,
“Causes of Time Overrun in Construction Phase
of Building Projects-A Case Study on
Department of Engineering Services of
Sabaragamuwa Provincial Council”, EngineerJournal of Institution of Engineers Sri Lanka,
XXXXV1 (03), 09-18.
9.
Dolage, D. A. R. and Perera, P. W. S. (2009),
“Delays in the Pre Construction Phase of State
Sector Building Projects”, Engineer-Journal of
Institution of Engineers Sri Lanka, Vol. XXXXII
(3), 2009, 22-30.
10. Jayawardene, A. K. W., Panditha, H. G. W.,
“Understanding and Mitigating the Factors
Affecting Construction Delay”, Engineer-Journal
of Institution of Engineers Sri Lanka, XXXV1 (02),
2003, 07-14.
8. Dolage, D. A. R., and Rathnamali, D. L. G.,
“Causes
of Time Overrun
PhaseDelay
11. Jonathan,
J.
S.,in Construction
“Construction
of Building
Projects-A
Case
Study
on
Computation Method”, Journal of Construction
Engineering
Management Services
Jan/Feb 2001,
Department
of and
Engineering
of 6065.
Sabaragamuwa Provincial Council”, EngineerJournal of Institution of Engineers Sri Lanka,
12. Kumaraswamy, M. M., Chan, D. W.,
XXXXV1 (03), 09-18.
“Determinants of Construction Duration”,
Construction Management and Economics, 1995;
9. Dolage, D. A. R. and Perera, P. W. S. (2009),
209–17.
“Delays in the Pre Construction Phase of State
Sector Building Projects”, Engineer-Journal of
13. Noulmanee,
A.,
Wachirathamrojn,
J.,
Institution of Engineers Sri Lanka, Vol. XXXXII
Tantichattanont, P., “Internal Causes of
(3), 2009, 22-30.
Delays in Highway Construction Projects in
Thailand”, July, 1999.
10. Jayawardene, A. K. W., Panditha, H. G. W.,
“Understanding and Mitigating the Factors
14. Pathiranage, Y. L., Halwatura, R. U., “Factors
Affecting Construction Delay”, Engineer-Journal
Influencing the duration of Road Construction
of Institution of Engineers Sri Lanka, XXXV1 (02),
Projects in Sri Lanka”, Engineer-Journal of
2003, 07-14.
Institution of Engineers Sri Lanka, XXXXIII(04),
2010, 17-30.
11. Jonathan,
J.
S.,
“Construction
Delay
Computation Method”, Journal of Construction
15. Pradeep, S., “Delays in Construction Project and
Engineering and Management Jan/Feb 2001, 60its Consequences”, International Journal of Project
65.
management, 1999.
12. Kumaraswamy, M. M., Chan, D. W.,
16. Sambasivan, M., Soon, Y. W., “Causes and
“Determinants of Construction Duration”,
Effects of Delays in Malaysian Construction
Construction Management and Economics, 1995;
Industry”, International Journal of Project
209–17.
Management, 2006, 25, 517-526.
13. Noulmanee,
A.,
Wachirathamrojn,
J.,
Tantichattanont, P., “Internal Causes of
Delays in Highway Construction Projects in
Thailand”, July, 1999.
ENGINEERY. L., Halwatura, R. U., “Factors
14. Pathiranage,
Influencing the duration of Road Construction
Projects in Sri Lanka”, Engineer-Journal of
Institution of Engineers Sri Lanka, XXXXIII(04),
2010, 17-30.
ENGINEER
15. Pradeep, S., “Delays in Construction Project and
its Consequences”, International Journal of Project
management, 1999.
10
30
ENGINEER - Vol. XLVIII, No. 01, pp. [page range], 2015
ENGINEER
- Vol. XLVIII,
No. 01,Sri
pp.Lanka
[31-37], 2015
©
The Institution
of Engineers,
© The Institution of Engineers, Sri Lanka
Use of Dynamites, Water-Gels and Emulsion Explosives
in Sri Lankan Quarrying/Mining Practice
P. V. A. Hemalal, P. G. R. Dharmaratne and P. I. Kumarage
Abstract:
In the Sri Lankan mining and quarrying industry, gelatine dynamite has been the widely
used explosive for rock blasting purposes. In the recent past, it has been phased out and replaced by
locally manufactured Water-gels(WG). So far, there had been only a very few tests conducted to assess
the suitability and to evaluate the performance of this explosive with other available explosives.
Complaints made by the users of Water-gels have been a cause of concern and prompted research to be
conducted with the aim of evaluating the performance of Dynamites, Water-gels and Emulsion explosives
with the measurement of major performance indicators in local mining and quarrying practice.
In this research, performance comparison of WG, Dynamite and Emulsion explosives with regard to rock
breakage in underground tunnelling and in metal quarrying has been carried out. Comparison of
fragmentation with the evaluation of particle size distribution in concrete block blasting using the three
types of explosives has been one of the main tests. Gap sensitivity, density and the determination of
velocity of detonation (VOD) has also been carried out.
Keywords:
1.
D’Autriche’s Method, Gap Sensitivity, VOD, Explosives
Density measurements and gap sensitivity has
been conducted to cross check the
manufacturers’ specifications on WG.
Introduction
Water-gel(WG) was introduced to Sri Lanka in
2011 as a substitute for dynamite. So far there
had been only a very few tests conducted to
assess the suitability and to evaluate the
performance of this explosive in contrast to
other available explosives.
Measurement of VOD using D’Autriche’s
method was carried out for the first time in Sri
Lanka for Dynamite, Water-gel and Emulsion
explosives.
2.
Water-gel currently produced in Sri Lanka has
been introduced to the industry by the
government. The complaints made by the
users with regard to the performance of watergels have been a cause of concern.
Methodology
2.1
Test Blasting on Concrete Blocks
Concrete blocks of 0.5mx0.5mx0.5m in size
having a 32mm diameter centre hole of 30cm
deep were made to facilitate explosive
charging(Figure 1). Blocks were cured under
same conditions for 28 days. Average
compressive strength of concrete measured by
sample blocks was 40.6 N/mm2.
In this research, performance of water-gel
explosives currently in use has been evaluated
with that of emulsions and dynamite, with a
view to identifying their deficiencies and
propose measures to overcome them with a
view to optimize its usage in Sri Lankan
mining practice.
Eng. P.V.A. Hemalal,
M.Sc.(Hons)(Min.Eng)(Moscow), MIE(Sri Lanka),
FIMMM(UK), CEng(UK & SL) Senior Lecturer,
Department of Earth Resources Engineering, University of
Moratuwa.
Fragmentation ability of explosives has been
compared using blasting in concrete blocks.
Fragments were analysed using SPLIT
software. Concrete blocks were used to obtain
a homogenous material to obtain a better
reproducibility of tests.
Prof. P.G.R. Dharmarathne
B.Sc. (Hons) (S.L.), M.Sc. (New Castle), Ph.D. (Leeds),
C.Eng. (U.K.), FIE(Sri Lanka), F.G.A (U.K), F.G.G (Ger.),
Senior Professor, Department of Earth Resources
Engineering, University of Moratuwa.
Underground tunnelling has been carried out
both with WG and dynamite and tunnel
advances has been compared with identical cut
ole configurations.
Eng. P. I. Kumarage
B.Sc. (Hons) Eng, AMIE(Sri Lanka) , Mining Engineer
31
ENGINEER
1
Figure 3 - Delineated image by the SPLIT
software
Figure 1 - Concrete block dimensions
Three explosive types namely, Water-gel
(WG), Dynamite and Emulsion were charged
in quantities of 25g and 30g to study the
fragmentation level by each explosive. Quarry
dust was used as stemming material and no
ANFO was used.
After the blast, all fragments were collected,
weighed,
photographed,
and
digitally
analysed using SPLIT software.
Figure 4 - Scaling with a reference object
Boundaries of collected fragments were
identified by the software by delineating. The
delineated lines have to be manually edited to
eliminate minor errors using the facilities
given in the software package itself. Scaling is
the identification of the actual size of the
fragments with the help of a given reference
object in the image. (Figure 4).
After completing the image analysis, particle
size distribution curve can be produced
(Figure 5). These data have been exported to
MSExcel for further analysis.
2.2
Underground Test blast of Water-gel
vs. Gelatin dynamite.
There are no complete or successful
comparisons on the use of different types of
explosives in underground situations in local
context. Therefore several test blasts were
carried out in a tunnel at Bogala mines with
identical cut-hole configurations, to evaluate
the performance of explosives in underground
rock blasting.
Figure 2 - Collected concrete fragments after
the blast
ENGINEER
32
2
Figure 5 - Particle size distribution curve produced by the software
Cross-cut tunnel advance (as at June, 2012) of
Bogala
Graphite
Mine,
Aruggammana
Graphit-Kropfmuhl (Lanka) Ltd Sri Lanka, in
191m level was used for this study. Gelatine
dynamite and locally-manufactured Watergels by Kelani Fireworks Company were used
as explosives. Swedish-made millisecond and
half second, number 08 detonators were used
in every blast as initiators.
Burn cut requires high explosives as the free
space available is too small. All the remaining
holes of the blasting round were charged with
0.375 kg of water-gel and 0.4kg of ANFO for
each hole. Since the cut hole is already blasted,
it provides sufficient free space for the
surrounding holes to blast into, and therefore
less strength of explosives is sufficient.
Whole Burn Cut made up of hole No. 2 to 9
and other stopping holes (hole No. 10 to 21)
were initiated with millisecond delays while
perimeter holes (hole No.22 to 37) were
charged with half second delays.
Adopted drill pattern consisted of 37 drillholes
and is shown in Figure 6.
Figure 6 Reamer hole at the centre (hole No.1)
having a diameter of 45mm and charged drill
holes of 35 mm diameter were drilled.
Tunnel face was charged with one explosive
type and the advance was measured. Test was
repeated for other explosive types as well.
In Figure 6, hole Nos.1 to 9 make up cut-hole
round of burn cut configuration. Centre hole
(hole No.1) was left un-charged to facilitate as
a free space for the rock to be blasted into.
Hole No. 2 to 9, the remaining holes of the
burn cut hole, were charged with 0.5kg of
Water-gel explosives each with no ANFO
used.
33
ENGINEER
3
The test determines the ability of an explosive
to transmit detonation through air from one
charge to another some distance away.
Figure 8 - Gap sensitivity arrangement on
field
2.5
VOD Measurement.
Velocity of Detonation is to be measured using
the D’Autriche’s method.
Figure 6 - Drilling pattern
Figure 9 - Schematic arrangement
Dautriche method VOD measurement.
As shown in Figure 9 above, two blasting caps
were inserted to the explosive column of the
cartridge and the separation was measured
(m). A loop was made with a detonating code
with a known VOD. The middle part (centre)
of the code was passed over a lead plate and
taped in place. Once the explosive column was
detonated, the two ends of the cord ignited
successively and the two waves meet head-on
on the lead plate, a distance off centred of the
geometric centre of the code.
Figure 7 - Measuring the tunnel advance after
the blast using a reference mark on tunnel
wall.
2.3
Density measurement.
Density measurements were carried out by
weighing and measuring the volume by water
displacement. A graph was produced with
weight over volume with different observed
values.
2.4
Air Gap sensitivity.
Placing two half cartridges with varying gap
between them, one half inserted with an
electric detonator of No.6 strength and
directed towards the other half was blasted.
The initial gap in air was taken as 2 cm as the
specified gap of the locally made Water-gel
explosive is 2cm. For Water-gel, this test was a
cross check of the given specification.
ENGINEER
for
After blasting, VOD of the explosive canbe
calculated from equation 1, knowing the
Detonating cord separation (m), off-centre
distance (a) and VOD of the Detonating cord,
D(M/s),
VOD=Dm/2a
34
(i)
(1)
4
3.
3.
Results & Discussion
Results & Discussion
3.2 Results of underground tunnel blasting.
3.2 Results of underground tunnel blasting.
% Passing
% Passing
3.1 Results of Concrete Block Blasting
Following
Figure
12 shows
the
particle size
3.1
Results
of Concrete
Block
Blasting
distributionFigure
after 12
blasting
of each
Following
showswith
the 25g
particle
size
type of explosives.
distribution
after blasting with 25g of each
type of explosives.
100.00
90.00
100.00
80.00
90.00
70.00
80.00
60.00
70.00
50.00
60.00
40.00
50.00
30.00
40.00
20.00
30.00
10.00
20.00
0.00
10.00
0.00 0.10
0.10
Size [cm]
Size [cm]
1.00
1.00
Figure 12 - Drilling depth and Advance after
each blast
Figure
12 - Drilling depth and Advance after
each blast
10.00
100.00
WG 25g
10.00
100.00
Dyna 25g
WG 25g
Emul 25g
Dyna 25g
Emul 25g
Figure 10 - Particle Size Distribution graph
for
25g charge
of explosives
in the block.graph
Figure
10 - Particle
Size Distribution
for 25g charge of explosives in the block.
100.00
90.00
100.00
% Passing
% Passing
80.00
90.00
70.00
80.00
60.00
70.00
50.00
60.00
Figure 13 - Number of mucking wagons after
the
blast
Figure
13 - Number of mucking wagons after
the blast
Figure
12 illustrates the drilling depths and
40.00
50.00
30.00
40.00
20.00
30.00
tunnel advances
after the
the drilling
blast. It is
clear that
Figure
12 illustrates
depths
and
dynamite
is capable
advances
beyond
tunnel
advances
afterofthe
blast. Iteven
is clear
that
the drilling
Water-gel
it beyond
always
dynamite
is length.
capable With
of advances
even
remains
a part
of theWith
drilling
length.itAverage
the
drilling
length.
Water-gel
always
advance a with
Dynamite
is length.
113.7% Average
of the
remains
part of
the drilling
drilling length,
it isis92.9%
with of
Wateradvance
with whereas
Dynamite
113.7%
the
gel.
drilling
length, whereas it is 92.9% with Watergel.
Number of mucking wagons, which indicates
the amount
of rock blasted
also higher
in
Number
of mucking
wagons,iswhich
indicates
dynamites
of water-gels
the
amountthan
of rock
blasted (Figure
is also 13).
higher in
dynamites than of water-gels (Figure 13).
Hence Tunnel advance using water-gels is less
than that
of dynamite
the water-gels
same charge
Hence
Tunnel
advancefor
using
is and
less
samethat
cut hole
configurations.
than
of dynamite
for the same charge and
same cut hole configurations.
3.3 Results of density measurements.
3.3 Results of density measurements.
Figure 14 shows the mass and the respective
volumes14for
water-gel.
Hence
of
Figure
shows
the mass
andthe
thegradient
respective
the regression
line is mass/volume
which of
is
volumes
for water-gel.
Hence the gradient
the density.
regression line is mass/volume which is
the density.
10.00
20.00
0.00
10.00
0.00 0.10
0.10Size [cm]
Size [cm]
1.00
10.00
1.00
10.00 WG 30g 100.00
Dyna
30g
WG 30g
100.00
Emul 30g
Dyna
30g
Emul 30g
Figure 11 - Particle Size Distribution graph
for
30g 11
charge
of explosives
in the blockgraph
Figure
- Particle
Size Distribution
for 30g charge of explosives in the block
Figure 11 shows the particle size distribution
for 30g 11
of explosive
Figure
shows thecharge.
particle size distribution
for 30g of explosive charge.
From these graphs, it is clear that in both 30g
and 25g
charge
tests,
D10,that
D30,
From
these
graphs,
it isallclear
in D50
both and
30g
D60 25g
values
havetests,
increased
fromD30,
dynamite
to
and
charge
all D10,
D50 and
water-gel.
Thisincreased
clearlyfromshows
D60
values have
dynamitethat
to
fragmentation
is best clearly
in dynamite
secondthat
in
This
shows
water-gel.
emulsion
and
water-gels
is
the
third.
fragmentation is best in dynamite second in
emulsion and water-gels is the third.
35
ENGINEER
5
5
Table 2 - Resultant VOD values from
D’Autriche’s method
Density of water-gel
140.00
y = 1.189x
R² = 0.999
120.00
Mass (g)
100.00
80.00
60.00
40.00
20.00
Explosive
Type
Gap
between
DC
nodes
(mm)
Off set
gap on
lead
plate
(mm)
VOD
of DC
(m/s)
VOD
(m/s)
Water-gel
Emulsion
Dynamite
100
100
100
84
68
60
6,750
6,750
6,750
4,018
4,963
5,625
0.00
0.0
50.0
Volume (cm3)
It is clear from Table 2 that dynamite has the
highest VOD of 5,625 m/s and Water-gel has
the lowest of 4,018 m/s. VOD of emulsion is in
between with a value of 4963 m/s.
100.0
Figure 14 - Mass vs. Volume for WG
Average density of WG was 1.19g/cc. In the
same manner densities of Emulsion and
Dynamite were 1.21g/cc and 1.29g/cc
respectively.
4.
In underground blasting water-gel is
environmentally friendlier than dynamite. This
is due to the absence of odour of
Nitroglycerine emanating from the cartridge in
the course of charging and post-blast toxic
fumes causing headaches and dizziness in
confined underground mining environments.
Table 1- Average densities of explosives
Explosive Type
Water-gel
Emulsion
Dynamite
Average Density (g/cc)
1.19
1.21
1.29
Gap sensitivity of Water-gel was found to be
better than the expected value of 2cm. The
results were positive even with a gap of 3cm.
From the Table 1, it is clear that dynamite has
the highest density equal to 1.29g/cc.
Density of water-gel and emulsion lies close by
with a gap of 0.02g/cc, although emulsion has
slightly a high density of 1.21g/cc.
Water-gel is a low energy explosive than
dynamite and emulsion. Fragmentation of
water-gel was found to be less than that of
dynamite as demonstrated in surface concrete
block blasting and underground muck pile
analysis. The conclusion to be arrived is that
detonation characterised by the low velocity of
detonation creates a weak fracture system
affecting the level of fragmentation of the rock.
3.4
Results of gap sensitivity for watergel.
After the blast, the immediate environment
where the donor was placed was observed.
The discolouration due to burning of the
location of the receptor was a clear indication
of the detonation of the receptor. Hence, it
could be concluded that the receptor has got
the detonation through air from the donor and,
the test result was positive for an air gap of
2cm.
Tunnel Advance with dynamite was better
than with that of Water-gels. Although the
explosive material cost per blasting round is
less in Water-gel due to its low price, this
advantage has been overrun due to the low
rate of tunnel advancements and consequent
additional blasting rounds required with
water-gels.
Followed by successful results of the first test it
was decided to carry out one more trial
increasing the air gap to 3cm. The result with
this increased gap was also positive.
It can be conjectured that Water-gel is dead
pressed in underground shot hole tunnel
blasting at Bogala mines due to the close
proximity blast holes in the order of few centimeters in the cut hole configuration. Therefore,
explosives
residues
were
a
frequent
observation.
3.5
Results of VOD measurements.
Table 2 below presents the results of the
D’Autriche’stest.
ENGINEER
Conclusions
36
6
Density of Water-gel lies within the range of
the manufacturer, i.e. 1.16g/cc to 1.26g/cc.
and, it is 1.29g/cc and 1.21g/cc with dynamite
and emulsion respectively. It is clear that
density of Water-gel is lower than that of
dynamite.
VOD was successfully measured by the
D’Autriche’s method for the first time in Sri
Lanka. By referring to Table 2 it is clear that
dynamite has the highest VOD and WG has
the lowest.
Acknowledgement
Our gratitude goes to:
Messers. KDA Weerasinghe quarry, Kalutara;
BogalaMines,
Aruggammana,
Limestone
Quarry, Holcim Lanka Ltd., Aruwakkalu;
Explosive controller, Deputy Controller and
Assistant Controllers of explosives - Kalutara
and all other organizations who assisted us in
the course of field work.
Prof. Manoj Pradhan, Department of Mining,
National Institute of Technology (NIT),
Raipur, India is gratefully acknowledged for
advices given on VOD testing of explosives.
References
1.
Persson, P.-A., Holmberg, R., & Lee, J. “Rock
Blasting and Explosives Engineering”, CRC
Press (2001).
2.
Jimeno, C. L., Jimeno, E. L., & Carcedo, F. J. A.
“Drilling and Blasting of Rocks”. Taylor &
Francis. (1995).
3.
Meyer, R., Köhler, J., & Homburg,
“Explosives”, Wiley-VCH. (2007).
4.
Cooper, P. W. “Explosives Engineering”, WileyVCH (1997).
A.
37
ENGINEER
7
ENGINEER -- Vol.
Vol.XLVIII,
XLVIII,No.
No.01,
01,pp.
pp.
[page 2015
range], 2015
ENGINEER
[39-48],
© The
The Institution
InstitutionofofEngineers,
Engineers,
Lanka
©
SriSri
Lanka
An Approach to Seismic Analysis of (Engineered)
Buildings in Sri Lanka
C. S. Lewangamage and H. G. S. R. Kularathna
Abstract:
Even though, Sri Lanka was believed to have no seismic threats, it is now realized that
Sri Lanka can no longer be considered as a country safe from seismic threats following the recent
events that occurred in and around the island.
The present study is therefore aimed at providing guidance on suitable analysis procedure for
buildings in Sri Lanka where the seismic consideration is explicitly warranted for a structure. The
proposed guidelines in this study are based on Euro Code 8 (EN 1998-1: 2004): “Design of Structures
for Earthquake Resistance”. Euro Code 8 was selected for this purpose as it allows national choices in
defining seismic characteristics such as peak ground accelerations, response spectra, etc. in seismic
design procedure. This study mainly focuses on these national choices and suitable values are
proposed and discussed, depending on the available seismic data in Sri Lanka. Whenever there is a
lack of data, suitable approaches are suggested comparing similar seismic codes such as IS 1893-1:
2002 and AS 1170.4: 2007.
Finally, two case studies are carried out in order to illustrate how the developed guidelines can be
used in the seismic design procedure of buildings particularly in Sri Lanka.
Keywords:
1.
Intra-plate earthquake, seismic design guidelines, Sri Lankan National Choices to EC 8.
Introduction
damage caused was 4 billion Australian
Dollars. Therefore, the seismic threats to Sri
Lanka can no longer be ignored and the
necessity for designing structures for possible
seismic hazards in Sri Lanka must be identified.
It is a well known fact that Sri Lanka is located
within the Indo-Australian tectonic plate and it
is far away from the plate boundaries (See
Figure.1). The inter-plate earthquakes which
take place along these boundaries are the most
common and are clearly identified. However,
the location of Sri Lanka would cause rare
chances of occurrence of such inter-plate
earthquake. Therefore, Sri Lanka was
considered to have no seismic threats.
However, no comprehensive studies have been
carried out to develop seismic analysis and
design guidelines for buildings in Sri Lanka.
The only available document for this purpose is
“Earthquake resistant detailing for buildings in
Sri Lanka” published by the Society of
Structural Engineers, Sri Lanka. Therefore,
there is a strong need to establish a national
building analysis and draw up design
guidelines for possible seismic loads in Sri
Lanka.
2.
Literature Review
The evolution of the seismic design procedure
can be summarized in three main phases [1].
The historic approach is to assume the design
seismic forces to be proportionate to the seismic
mass of the structure.
Figure 1 - Tectonic plate boundaries
However, Sri Lanka cannot be ignored
regarding earthquake risks because; intra-plate
earthquakes that take place within the tectonic
plates causing significant damages are still
possible. The intra-plate type earthquakes can
occur at any place without a warning. A good
example is the earthquake (5.9 on Richter scale)
that hit New-castle Australia. This region
wasearlier considered as a no-risk area. The
Eng. (Dr.) C.S. Lewangamage, B.Sc. Eng. Hons(Moratuwa),
M.Eng. (Tokyo), Ph.D (Tokyo), C. Eng., MIE(Sri Lanka),
Senior Lecturer in Civil Engineering, Department of Civil
Engineering, University of Moratuwa, Sri Lanka
Ms. H.G.S.R.Kularathna, B.Sc.Eng.Hons(Moratuwa), M.Sc.
(Moratuwa), Ph.D candidate, University of Cambridge, UK
1
39
ENGINEER
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In the conventional code approach these design
seismic forces are calculated as inertial forces
induced by the ground acceleration. Both these
approaches are based on the force based design
concept. However, the future trend is to adopt a
displacement based design approach where the
non-linear response of the structure is largely
taken into account.
in terms of their probability of exceedance.
There are mainly four performance levels
associated with these guidelines. They are
operational, immediate occupancy, life safety
and collapse prevention levels.
Euro Code 8 (EN 1998-1:2004) establishes two
fundamental performance requirements as the
No-collapse
requirement
and
Damage
limitation requirement. However, within the
framework of Euro codes the concept of limit
state design is still the basis and therefore, the
above two performance requirements lie within
the two limit states, the ultimate limit state and
serviceability limit state. Nevertheless, as
indicated by the above requirements, these two
performance levels are to be checked against
two different levels of the seismic action,
interrelated by the seismicity of the region.
The modern seismic codes systematically adopt
new design concepts such as performance
based design methods and non-linear analysis
methods. Nevertheless, they still use force
based design approach while some of the codes
are now trying to adopt displacement based
design methods. In this review, conventional
force based design approach was studied given
in four main seismic standards namely US
standards (Federal Emergency Management
Agency – FEMA 450: NEHRP Recommended
Provisions for Seismic Regulations for New
Buildings and Other Structures [2]) and Euro
Code 8 (EN 1998-1: 2004) [3], Australian
standard (AS 1170.4: 2007) [4] and the Indian
standard (IS 1893-1: 2002) [5]. All these codes
follow generally a similar procedure (See
Figure .2) but with some differences unique to
their region such as seismicity, soil condition,
etc.
2.2
Specification of hazard and defining
seismic action
Each code specifies the design seismic action in
terms of spectral ordinates with different
definitions and terminologies. In Euro Code 8
the seismic hazard at the site is defined by the
Peak Ground Acceleration (PGA) for rock site
and it is termed as the „reference‟ peak ground
acceleration for 475 year return period
earthquake. The response acceleration values
for the design of buildings are then represented
by an elastic response spectrum. Australian
standard (AS 1170.4:2007) defines the seismic
hazard by peak ground acceleration similar to
the EC 8 but termed as hazard factor (Z) for 500
return period of earthquake and elastic
response spectra are defined to obtain the
spectral acceleration value used for designing
structures.
2.1
Target performance level
FEMA 450-2: 2003 Commentary [6] discusses
explicitly the target performance levels
associated with the provisions given in FEMA
450-1. It is expected that structures designed
and constructed in accordance with the
provisions will generally be able to meet a
number of performance criteria when subjected
to earthquake ground motions of differing
severity. The ground motion levels are defined
Define target performance level
How buildings perform during and after earthquake, Building classification
Specification of hazard and Define seismic action
Ground motion for which buildings are designed
Structural analysis and design criteria
Structural type, shape and configuration, structural analysis methods, design and detailing
Figure 2 - General seismic design procedure common to seismic codes
ENGINEER
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2
40
A similar approach is given in the Indian
seismic standard as well, where the seismic
hazard is defined by means of peak ground
acceleration term as zone factor (Z) associated
with maximum considered earthquake. The
response spectrum is given for obtaining
response acceleration of buildings in the
designing process.
for a 10% probability of exceedance in 50 years
or 475 years return period is around 0.026g for
Colombo. It also proposes that this value can be
used for the whole island since the single
seismic source zone used in the PSHA includes
Sri Lanka.
Uduweriya et al [8] presents a reliable seismic
hazard assessment in Colombo area based on
probabilistic approach and proposes a value of
0.1g as the peak ground acceleration at rock site
for 10% probability of exceedance in 50 years
(i.e. for 475 year return period).
However, within the framework of FEMA 450
the ground motion hazards are defined in terms
of maximum considered earthquake ground
motions which are then presented within the
provisions in terms of the mapped values of the
spectral response acceleration at short periods,
Ss, and at 1.0 second, S1, for a particular soil
type. The structural design is performed for
earthquake demands that are 2/3 of the
maximum considered earthquake response
acceleration and design response spectra as
required in the design process to obtain the
response acceleration for buildings are given.
2.3
Structural analysis and design criteria
After selecting the ground motion, the codes
present a systematic procedure to design
buildings to resist the ground motion. These
provisions are based on structural dynamics
and hence are similar in their concept.
However, the advancement of the seismic
design concepts might be different in different
codes. Each code specifies a preliminary
screening process which decides basically the
need for seismic design for a particular
building, suitable structural analysis method
such as linear/non-linear and static/dynamic
and so forth.
3.
Figure 3 - Hazard curves for Colombo[7]
The above two studies show explicitly different
values for the peak ground acceleration at rock
site for 475 years return period. However, when
these two studies are reviewed the latter study
seems to be proved by the other on-going
studies in the same subject. Therefore, the
reference peak ground acceleration at rock site
(ag,R) is taken to be 0.1g for Colombo area. As
there is no any other study that considers the
whole island, the same peak ground
acceleration value (0.1g) is used for the
buildings in other parts of Sri Lanka.
Seismic Hazard Assessment for
Sri Lanka
4.
It is the conventional approach that the seismic
hazard for a country is specified in terms of the
peak ground acceleration. It is generally given
by the seismic hazard map which divides the
country into several seismic zones each having
different peak ground acceleration values. For
Sri Lanka, such seismic zonation map is not
available in order to obtain the ground motion
values at each location. But two important
studies which propose ground motion values in
Colombo area can be identified.
SriLankan Approach to Euro Code 8
4.1
Use of EC 8 as the basis for seismic
analysis of (engineered) buildings in
Sri Lanka
Design of structures to resist earthquake is
being developed for many years and still new
researches are undertaken all over the world to
improve the buildings performance in the event
of an earthquake. In Sri Lankan context, it is at
its early stage and therefore, it is necessary to
make use of well-established seismic design
procedures used in other countries as they have
carried out lots of studies and gained enormous
experience in this field. Hence, it was
compromised to use Euro code 8 (EN 1998-1:
Peiris [7] proposes the best estimate horizontal
peak ground acceleration curve with associated
confidence intervals (See Figure.3). It shows
that the peak ground acceleration at rock site
3
41
ENGINEER
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aspects. Therefore, importance Class II, III and
IV buildings are recommended to be designed
for possible seismic events (See Figure 4) and
hence, the peak ground acceleration values
need to be provided.
2004): Design of Structures for Earthquake
Resistance as the basis for seismic design of
buildings in Sri Lanka.
There are mainly two important reasons for
selecting the Euro Code 8 for the purpose of
developing national guidelines for seismic
analysis and design of buildings in Sri Lanka.
They are,
 The future trend is to use Euro Codes as the
design standards for structures in Sri
Lanka. Hence, using the Euro code for the
seismic design of buildings in Sri Lanka
would be consistent with the future of the
design standards in Sri Lanka.
 Euro Code 8 allows national choices for
parameters
defining
local
seismic
characteristics as well as the methods for
designing of buildings for local seismic
action. A national annex to Euro Code 8 can
be easily developed with the inclusion of
local characteristics.
According to the proposed methodology in
Figure 4, a seismic action of 475 year return
period is recommended for buildings of
importance Class II. For importance Class III
buildings, a seismic action of 1500 year return
period and for importance Class IV buildings, a
2500 year return period are proposed.
However, the peak ground acceleration values
for the above seismic actions are not yet determined
and therefore the importance factor (γ1) described in
EC 8 can be used to obtain an approximate value
for PGA values for 1500 and 2500 year return
periods from the PGA value for 475 year return
period as it is the only known PGA value for Sri
Lanka which is recommended as 0.1g. The peak
ground acceleration for 1500 and 2500 year
return periods are obtained by multiplying the
above selected peak ground acceleration value
for 475 year return period (ag,475) by importance
factors (𝛾𝛾ͳ ) assigned to the importance Class III
and IV buildings as given in Eq.1.
In adopting the Euro code 8 in a country, there
are a set of parameters to be determined
nationally which accounts for the seismic
hazards of the country. Among them, the most
imperative parameters are the design seismic
action in terms of design peak ground
acceleration for different types of structures and
the elastic response spectra which is used in the
seismic analysis procedure of a structure. In this
study, those two parameters are given special
consideration and suitable values are
recommended based on the available limited
seismic data.
𝑎𝑎𝑔𝑔ǡͳͷͲͲ ȀʹͷͲͲ ൌ 𝑎𝑎𝑔𝑔ǡͶ͹ͷ Ǥ 𝛾𝛾ͳ ................................... (1)
The importance factors are determined using
the approximate relationship (Eq.2) given in EN
1998-1/2.1 [3] as.
𝑇𝑇
𝛾𝛾ͳ ̱ሺ 𝐿𝐿𝑅𝑅 𝑇𝑇 ሻ−ͳȀ𝑘𝑘 ............................................... (2)
𝐿𝐿
Where, TLR is the reference return period (475
years in this case) and TL is defined as the
return period in which the same probability of
exceedance as in the TLR years is achieved. The
exponent kis dependent on the seismicity
associated with the country, but EC 8 specifies
that it is generally in the order of 3. This
relationship is illustrated for three different k
(2.5, 3.0 and 4.0) values in Figure 5 and Table 2
shows the required importance factors for the
return periods specific to each importance class
of the structures.
Based on the identified seismic hazard levels in
Sri Lanka, a suitable approach to seismic
analysis procedure (See Figure 4) is proposed
according to the Euro Code 8. It is noted that in
this study, only linear elastic analysis are
considered.
4.2
Design seismic action
The structures are designed for different design
seismic actions in terms of return period or the
probability of exceedance depending on the
importance of the building in the event of an
earthquake. The structures are classified into
four categories as shown in Table 1. The
importance Class I includes the structures
which do not require an explicit seismic
consideration in the design process. The
importance Class II, III and IV include the
structures identified as important during an
earthquake considering their function, the
consequences of failure and the economic
ENGINEER
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4
42
Determine the importance class of the building (See Table 1)
Importance
Class I
Importance
Class II
Need not be
designed for
seismic
action
Importance
Class III
Design for a seismic
action of 475 year
return period
Select the PGA value
(As nationally
determined)
Earthquake
detailing
Importance
Class IV
Design for a seismic
action 1500 year
return period
Select the PGA value
(As nationally
determined)
Design for a seismic
action 2500 year
return period
Select the PGA value
(As nationally
determined)
Elastic response spectrum (As nationally determined)
Determine the ductility
class (DCM/DCH)
Design response spectrum
(EN 19981:2004/relevant sections)
Structural analysis (EN 1998-1:2004/4.3.3)
Structural regularity (EN 1998-1:2004/4.2.3)
Regular
(EN 19981:2004/4.2.3.2)
Irregular
(EN 19981:2004/4.2.3.3)
Modal response spectrum analysis
(EN 1998-1:2004/4.3.3.3)
Static method
(EN 1998-1:2004/4.3.3.2)
Figure 4 - Proposed seismic analysis approach for Sri Lanka
2.50
I (k=2.5)
Importance factor
2.00
I (k=3)
1.50
I (k=4)
1.00
0.50
0.00
0
1000
2000
Return
period
3000 (Years)
Figure 5 - Representation of the relationship between the importance factor and the return period
for different values of the seismic exponent
43
5
ENGINEER
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Table 1 –Proposed building classification and importance classesbased on the guidelines given in
[4] and [5]
Importance
Class
Classification
I
Buildings of minor
importance for safety of
public and other
property
Examples
Agricultural buildings, isolated structures,
domestic structures
Hotels, offices, apartment buildings of less than 10
storeys high, Factories up to 4 storeys high
Buildings of lowmoderate importance
for safety of public and
other properties
II
Buildings of significant
importance for safety of
public and other
properties
III
Car parking buildings, Shopping centres less than
10,000m2 gross area , Public assembly buildings for
fewer than 100 persons
Emergency medical and other emergency facilities
not designated as post-disaster
Hotels, offices, apartment buildings over 10
storeys high, Factories and heavy machinery
plants over 4 storeys high
Shopping centres of over 10000m2 gross area
excluding parking, Public assembly buildings for
more than 100 persons,
Airport terminals, principal railway stations
Pre-schools, Schools, colleges, universities, Major
infrastructure facilities, e.g. power stations,
substations
Buildings of greater
importance with post
disaster functions for
civil protection
IV
Medical facilities for surgery and emergency
treatment, Hospitals, Fire and police stations,
Ambulance facilities
Buildings housing toxic or explosive substances in
sufficient quantities to be dangerous to the public
if released
Extreme hazard facilities (Dams etc.)
The classification of buildings would be revised based on the outcomes of the detailed study
on seismic hazard assessment for Sri Lanka.
Table 2 - Proposed importance factors and corresponding return period values
Mean return period (in years)
Importance
Importance
Class
factor (γ1)
k = 2.5
k = 3.0
k = 4.0
I
0.80
272
243
195
II
1.00
475
475
475
III
1.50
1309
1603
2404
IV
1.80
2065
2770
4986
ENGINEER
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6
44
4.3
Elastic response spectra
Currently, there is no elastic response spectrum
which represents ground motion for buildings in
Sri Lanka. Therefore, for the purpose of seismic
design of buildings in Sri Lanka, the most
appropriate response spectrum is selected from
the recommended Type 1 and Type 2 elastic
response spectra given in the Euro Code 8, the
recommended elastic response spectrum in
Indian seismic code (IS 1893-1: 2002) and the
response spectra recommended in Australian
code (AS 1170.4: 2007).The comparison of
response spectra normalized by the peak ground
acceleration for approximately equivalent soil
types as recommended in the three codes above
are shown in Figure 6a,b and c.
Spectral Acceleration (g‟s)
Spectral Acceleration (g‟s)
However, within the scope of this study
without a proper seismic hazard assessment for
Sri Lanka it is not possible to predict which
code approach would represent the local
condition of Sri Lanka. On account of that, the
use of Indian seismic code provision can be
justified because it is a well-established seismic
code in South Asian region and importantly Sri
Lanka is situated close to India and it can be
assumed that the seismicity of both countries
would be approximately similar. Further, the
response spectrum at rock site developed for
the Colombo area [8] shows a reasonable match
with the response spectrum recommended in
the Indian seismic code (IS 1893-1: 2002) (See
Figure 7).
Period (s)
Figure 7- Response spectrum for Colombo at
rock site and the corresponding response
spectrum in IS 1893-1: 2002 [8]
Period (s)
Spectral Acceleration (g‟s)
(a)
Therefore, in the absence of a proper study, for
seismic analysis of buildings IS 1893-1:2002
recommended elastic response spectra can be
used. The expressions defining the response
spectra for three soil types in IS 1893-1 are
modified to suit the Euro code 8 as shown in
Equations 3, 4 and 5 and the corresponding
parameters are given in Table 3. The basic
shape of the elastic response spectrum is shown
in Figure 8.
Period (s)
(b)
Spectral Acceleration (g‟s)
ͲǤͲͲ ≤ 𝑇𝑇 ≤ 𝑇𝑇𝐵𝐵 𝑆𝑆𝑎𝑎 ൌ ͳ ൅ ͳͷ𝑇𝑇.................. (3)
𝑇𝑇𝐵𝐵 ≤ 𝑇𝑇 ≤ 𝑇𝑇𝐶𝐶 𝑆𝑆𝑎𝑎 ൌ ʹǤͷ............................. (4)
𝑇𝑇𝐶𝐶 ≤ 𝑇𝑇 ≤ ͶǤͲͲ𝑆𝑆𝑎𝑎 ൌ 𝑆𝑆Ȁ𝑇𝑇.......................... (5)
Table 3 - Soil types and corresponding
parameters defining response spectra (IS 1893)
modified to the format in EC 8
Soil Type
I
Period (s)
(c)
Figure 6 - Comparison of EC 8 Type 1
response spectra with IS 1893-1 and AS 1170.4
response spectra for the approximate
equivalent soil types
(Hard soil)
II
(Medium
soil)
III
(Soft soil)
7
45
NSPT
S
TB
TC
>30
1
0.1
0.4
10-30
1.36
0.1
0.55
<10
1.67
0.1
0.67
ENGINEER
ENGINEER
Figure 8-Basic shape of the horizontal elastic
response spectrum
Figure 8-Basic shape of the horizontal elastic
response
spectrum
In elastic
analysis methods, the elastic
horizontal response spectrum is reduced to a
In
elastic
analysis
methods,
thetakes
elastic
design
response
spectrum
which
the
horizontal
response
spectrum
is
reduced
a
ductile
behaviour
of
buildings tointo
design
response
spectrum
which
takes
the
consideration.
ductile
behaviour
of
buildings
into
consideration.
5.
(a) Cross section of the building
(a) Cross section of the building
Case Studies
5.
Case Studies
In order to understand the significance of
seismic loading in designing buildings in Sri
In order to understand the significance of
Lanka, two commonly found building types
seismic loading in designing buildings in Sri
were analysed in accordance with the above
Lanka, two commonly found building types
proposed approach.
were analysed in accordance with the above
proposed approach.
5.1
Case study 1
A
three
storey school building which is
5.1
Case study 1
categorized
as an important
buildingwhich
due to isits
A three storey
school building
high
consequences
of
failure
during
categorized as an important building due to itsan
earthquake
was selected
the caseduring
study 01.an
high
consequences
of asfailure
(b) plan view of the building
(b) plan view of the building
earthquake was selected as the case study 01.
The test building was analysed by the two
lineartest
elastic
methods,
forceby
method
and
The
building
was static
analysed
the two
modalelastic
response
spectrum
analysis
method,
linear
methods,
static force
method
and
prescribed
in ECspectrum
8. All analysis
the analysis
was
modal
response
method,
performed by
software
(CSI was
2002.
prescribed
in using
EC 8.ETABs
All the
analysis
ETABS Integrated
Design(CSI
Software,
performed
by using Building
ETABs software
2002.
Computers
and
Structures
Inc.
Berkley).
The
ETABS Integrated Building Design Software,
elevation
and
plan
view
of
the
building
as
well
Computers and Structures Inc. Berkley). The
as the three
of the building
elevation
anddimensional
plan view ofmodel
the building
as well
used
in
the
analysis
are
shown
in
9.
as the three dimensional model ofFigure
the building
used in the analysis are shown in Figure 9.
The elastic response spectrum and the design
response
the test
are
The
elasticspectrum
response for
spectrum
andbuilding
the design
response
spectrum for the test building are
shown in Figure10.
shown in Figure10.
According to the static lateral force method of
According
static
lateralbase
force
method
of
analysis in to
ECthe
8, the
seismic
shear
for each
analysis
in ECdirections
8, the seismic
for eachis
horizontal
of base
the shear
building
horizontal
directions of the building is
determined as
determined as
(c) Three dimensional model of the building
Spectral Acceleration (g‟s)
Spectral Acceleration (g‟s)
(c) Three dimensional model of the building
Figure 9 – Three storey school building
Figure 9 – Three storey school building
Period (s)
Period (s)
𝐹𝐹𝑏𝑏 ൌ 𝑆𝑆𝑑𝑑 𝑇𝑇ͳ Ǥ 𝑚𝑚Ǥ 𝜆𝜆.......................... (6)
𝐹𝐹𝑏𝑏 ൌ 𝑆𝑆𝑑𝑑 𝑇𝑇ͳ Ǥ 𝑚𝑚Ǥ 𝜆𝜆.......................... (6)
The value of the ordinate of the design
The
valuespectrum,
of the ordinate
of the designto
response
𝑆𝑆𝑑𝑑 𝑇𝑇ͳ corresponding
response
spectrum,
𝑆𝑆𝑑𝑑 𝑇𝑇ͳT1corresponding
of the buildingtois
the fundamental
period
the fundamental period T1 of the building is
ENGINEER
ENGINEER
ENGINEER
Figure 10 – Elastic and design response
Figure
10 – –Case
ElasticStudy
and design
response
spectrum
1
spectrum –Case Study 1
8
46
8
5.2
Case study 2
An office building which is categorized as
importance Class III (See Table 1) was analysed
in accordance with the modal response
spectrum analysis method in EC 8. The plan
view, elevation and the three dimensional
model of the test building used in the analysis
are shown in Figure 11. All the analysis were
performed using ETABs software (CSI 2002.
ETABS Integrated Building Design Software,
Computers and Structures Inc. Berkley).
obtained from the design response spectrum.
Where m is the seismic mass of the building and
λ is the correction factor which is given in EC 8
as 0.85. The base shear force, Fb, is shown in
Table 4.
Table 4 -Base shear for the test building-Case
Study 1
(Lateral force method of analysis)
Fundament
m
𝐹𝐹𝑏𝑏
λ
al period
𝑆𝑆𝑑𝑑 𝑇𝑇ͳ
(kN)
(t)
(T1)
0.39
1.13
1228
0.85
1179
The seismic base shear values obtained from
the static force method in EC 8 were compared
with the same values obtained in accordance
with two other seismic codes; AS 1170.4:2002
and IS 1893:2002 as shown in Table 5.
Table 5 - Comparison of base shear values
obtained from different codes – Case Study 1
(Static lateral force method of analysis)
Base
shear (kN)
EC 8
AS 1170:
2007
IS 1893:
2002
1179
1175
846
(a) Plan view of the floors above ground level
The test building was also analysed using the
modal response spectrum analysis method as
given in EC8. The seismic base shear values
obtained from the analysis are given in Table 6.
Table 6 -Base shear for the test building-Case
Study 1
(Modal response spectrum analysis)
Fundamental Period
Base Shear Force (kN)
(b) Elevation of the building
(T)
x-dir
y-dir
x-dir
y-dir
1.31 s
1.03 s
336
426
The difference between base shear values
obtained from lateral force method of analysis
and the modal response spectrum analysis is
due to the two different fundamental period
values obtained from the two analysis methods.
In the modal response spectrum analysis, the
masonry walls were considered having no
contribution to the stiffness of the test building
and hence, it gives a higher fundamental
period.
(c)
Three dimensional model of the building
Figure 11 – Case Study 2 – Office Building
9
47
ENGINEER
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When other seismic analysis approaches are
considered, the proposed (reference) peak
ground acceleration value of 0.1g seems to be a
significant value. It necessitates most of the
buildings to be designed for seismic loads and
essentially for important buildings the value is
increased further which resultsan explicit
consideration of seismic loading.
Spectral Acceleration (g‟s)
The elastic response spectrum and the design
response spectrum for the building are shown
in Figure 12 and the seismic shear values
obtained from the analysis are given in Table 7.
The parameters proposed in this study
especially peak ground acceleration values and
the elastic response spectra can be replaced by
the accurate values obtained through proper
seismic studies for Sri Lanka in future.
However, the proposed approach would still be
used with the new values.
Period (s)
Figure 12 – Elastic and design response
spectrum – Case Study 2
Acknowledgements
Table 7 – Seismic shear values at each storey
level
Shear Force (kN)
Storey Level
x-dir.
y-dir.
(T=1.0 s)
(T=0.74 s)
Roof
201
254
Storey 5
353
463
Storey 4
446
600
Storey 3
524
713
Storey 2
603
814
Storey 1
672
891
Ground level
672
891
Basement 1
672
891
6.
Financial support for this study was provided
by Disaster Management Centre (DMC), Sri
Lanka. The authors wish to thank Prof. M.T.R
Jayasinghe & Prof. W.P.S. Dias, University of
Moratuwa, Prof. P.B.R. Dissanayaka & Prof.
K.G.H.C.N.
Senevirathna,
University
of
Peradeniya and Dr. K.K. Wijesundara, South
Asia Institute of Technology and Medicine
(SAITM) for their intellectual assistance.
References
[1] Durgesh, C. Rai (2000), “Future Trends in
Earthquake-Resistant Design of Structures”,
CURRENT SCIENCE, VOL. 79, NO. 9, 10.
[2] FEMA 450-1, NEHRP Recommended Provisions for
Seismic Regulations for New Buildings and other
Structures, 2003 Edition.
[3] Euro code 8: Design of Structures for Earthquake
Resistance – Part 1: General Rules, Seismic
Actions and rules for Buildings, EN 1998-1: 2004.
[4] AS 1170.4 – 2007, Structural Design Actions,
Part 4: Earthquake Action.
Conclusions
In the proposed national guidelines, a suitable
approach for seismic analysis of buildings in Sri
Lanka is proposed based on the Euro code 8
(EN 1998-1: 2004).
[5] IS 1893-1: (Part 1): 2002, Criteria for Earthquake
Resistant Design of Structures, Bureau of Indian
Standards.
[6] FEMA 450-2, Commentary NEHRP Provisions for
Seismic Regulations for New Buildings and other
Structures, 2003 Edition.
[7] Peiris L.M.N., “Seismic Hazard Assessment and
Seismic Risk in Colombo”, Risk Management
Solutions, London, UK.
[8] Uduweriya, S. B., Wijesundara, K. K.,
Dissanayake, P. B. R., “Seismic Risk in Colombo
– Probabilistic Approach”, SAITM Research
symposium on Engineering Advancements 2013
(SAITM – RSEA 2013)
Several important parameters were determined
for Sri Lanka based on the available seismic
data. They are design peak ground
accelerations for the three seismic actions
having 475 year return period 1500 year return
period and 2500 year return period for which
the buildings in Sri Lanka are proposed to be
designed. For instance, the peak ground
acceleration for earthquake with 475 year
return period has been assumed as 0.1g.
Further, it is proposed to use the elastic
response spectra developed for India in IS 18931 in the seismic analysis of buildings in Sri
Lanka.
ENGINEER
ENGINEER
10
48
SECTION II
ENGINEER - Vol. XLVIII, No. 01, pp. [51-60], 2015
© The Institution
ofXLVIII,
Engineers,
ENGINEER
- Vol.
No.Sri
01,Lanka
pp. [page range], 2015
© The Institution of Engineers, Sri Lanka
Monitoring of Exhaust Gas Parameters of Stationary
Combustion Systems
In View of Environmental Standards
K. T. Jayasinghe
Abstract:
During the last few years, fossil fuel consumption for electricity generation and
industrial process activities has gradually increased with the rapid development of energy and
industrial sectors in Sri Lanka. When the fuel consumption increases, the relative quantities of
emissions released to the environment too will increase. Such types of common emissions are toxic
gases (Pb, Cl2), noxious gases (SOx, NOx), green house gases (CO2, O3), unburned gases (CO, CxHy),
volatiles and respirable particles. Those emissions will harmfully affect, in different ways, the human
health and the environment.
The regulatory bodies have actively monitored the industrial emissions by implementing & amending
old inactivated policies, regulations and standards. As a result of such implementaions, under the
“Section 32 of National Environmental Act No. 47 of 1980” as amended by Acts 56 of 1988 and 53 of
2000, the latest enviormnetal standard for emission regulations for staionary combustion systems has
emerged.
In this regard, this paper aims to broadly discuss the experience gathered by the author in this area,in
(view of) relation to? industrial impacts, instrumentations, pre facility requirement & resource
availability and external interferences. Further the recommendations made in this paper for individual
combustion systems, such as, thermal power plants, standby generators, industrial boilers & thermic
fluid heaters, incinerators and cupola furnances, kilns etc. might be helpful to the regulatory bodies,
industries, instruments & equipment suppliers and monitoring organizations in different ways when
introducing (introduce) those emission standards to the industries.
Finally, the outcomes of this study will help not only the local industries, but also Asian regional
countries which have been operating similar combustion systems, to upgrade their systems to comply
with particular environmental standards, because the proposed local standards have been prepared
based on the other Asian and Europian regions’ environmental standards.
Keywords:
1.
Particulate Matter, Smoke Opacity, Isokinectic, Ringelman, Transmissivity, Themic Fluid
Introduction:
been operated especially in process industries
such as activated Carbon production, rice
processing, Sugar industries etc.
Sri Lankan Statistics reveal that the industrial
growth and electricity generation had
increased by 11.0% and 7.9% respectively in
2010 [SEA Annual Report 2010]. It is expected
that the industrial growth and electricity
generation will further increase in the coming
years due to the introducion of new
development projects and rapid increase in
electricity demand island wide. According to
the current statistics, electricity generation
heavily depends on the thermal power plants
and in 2010 around 60% of the total generation
had been shared by thermal power plants
[SEA Annual Report 2010]. The main energy
sources used in thermal power plants are fossil
fuels and coal. In addition to that few bio fuel
in-house electricity generation facilities have
ENGINEER
Industrial development also contributes to the
exponential increase of fossil fuel consumption
to obtain required thermal and electrical
energy.
The common systems practices are steam &
hot water boilers, thermic heaters, diesel
electricity generators etc. In addition to those
electrical and thermal energy generating
systems, a remarkable number of different
types of stationary combustion systems such
Eng. K T Jayasinghe, CEng., MSc (Energy), MIE(Sri
Lanka), Research Fellow, National Engineering Research &
Development Centre (NERDC), 2P/17B, Industrial Estate,
Ekala, Ja-Ela. Sri Lanka.
51
1
ENGINEER
as incinerators, crematoria, cupolas, kilns,
furnaces etc. are in operation island wide.
measuring regulations & techniques, and
system requirements.
Out of those, many plants are out dated and
they are operated under very low efficiency
levels.
2.1 Source Categorizations & Measuring
Parameters
According to the type of plants available in the
country, stationary combustion systems have
been divided in to 5 categories such as thermal
power plants, boilers, thermic fluid heaters,
incinerators, and cupolas, furnaces, ovens,
kilns etc. The recommended monitoring
parameters and emission levels of each
category depend on the plant capacity and fuel
used.
The
recommended
monitoring
parameters of different combustion sources are
summarized in Table 1.
Setting up of unplanned and inefficient
combustion systems will increase the pollution
gases and contaminants emitted to the
atmosphere. The common emissions released
to the atmosphere are toxic gases (Pb, Cl2),
noxious gases (SOX, NOX), green house gases
(CO2, O3), unburned compounds (CO, CXHY),
Suspended Particles (SP) and respirable
particles etc.
Smoke Opacity
SOX
NOX
CO
HCl
Hg
Pb
Dioxin & Furans
X
X
-
-
-
-
-
X
X
X
X
X
X
X
X
-
Boilers
X
X
X
X
-
-
-
-
-
Thermic Fluid Heaters
X
X
X
X
-
-
-
-
-
Incinerators
X
X
X
X
X
X
X
X
X
X
X
X
X
-
-
-
-
-
Cupolas,
Ovens, Kilns
Furnaces,
[Source – Schedule II – Part I to Part V of National
Environmental Act No. 47 of 1980]
According to Table 1 the common monitoring
parameters of each combustion system are
Particulate Matters (PM), Smoke Opacity,
Oxides of Sulfur (SOX) and Oxides of Nitrogen
(NOX). In additions to these common
parameters, thermal power plants driven by
solid
wastes
and
waste
combustion
incinerators require to monitor CO, HCl, Hg,
Pb and Dioxin & Furans. The recommended
emission levels of each substance are not
discussed in this paper. [Reference: - Section
32.0 of National Environmental Act. No 47.0 of
1980 for the recommended values].
Review of Emission Standards of
Combustion Systems in Sri Lanka
2.2
Measuring Regulations &
Techniques
The emission monitoring methods described in
this standard are based on the standard
conditions, and the monitoring parameters are
The implemented emission standards of
stationary combustion systems have mainly
focused on three major areas such as source
categorizations & measuring parameters,
ENGINEER
X
Thermal Power PlantsAny Fuel Except Solid
Waste
Thermal Power Plants –
Solid Waste Fuel
In fact, this paper is not going to discuss the
policy implementations or regulation practices
by different organizations to monitor the
environmental
pollutions
of
stationary
combustion systems. However, it broadly
discusses the experience gathered by the
author; under different types of stationary
combustion systems, with respect to industrial
impacts,
instrumentations,
pre
facility
requirement etc.
ENGINEER
X
Plant Category
Even though the environmental policies have
been introduced since Colonial times, policies
related
to
emission
from
stationary
combustion systems had not been strictly
practiced by responsible parties. However, the
regulatory bodies have been actively involved,
in the last few decades, to implement such
regulations aiming to control environmental
emissions
from
stationary
combustion
systems.
2.
Particulate Matter
Table 1 - Summarized Monitoring Parameters
of Stationary Combustion Systems
Different kinds of emissions in small and
medium processing plants such as boilers,
thermic heaters, incinerators etc. are rather
difficult to control than the emmisions in
centralized large processing plants in thermal
power generation, co generation, cement
processing etc. In this context, adverse effects
from
small
and
medium
stationary
combustion systems to the environment might
be high.
2
52
3.
estimated based on the reference levels in
order to bring the monitoring parameters by
different organizations to a common standard
format.
Based on the regulations, the emission
parameters shall be,
- Monitored by instrument/ equipment
based
- Converted in to dry basis & normal
condition (0 0C and 760mm Hg)
- Corrected for relevant reference Oxygen
level.
[Schedule
1
of
National
Environmental Act. No 47 of 1980 for
reference Oxygen levels].
However the detailed descriptions of
equations, conversions and regulations are not
included in this paper. [Reference: - Section 32
of National Environmental Act. No 47.0 of
1980 for details].
Monitoring Methodologies and
Techniques
In-depth analysis of monitoring methodologies
and techniques related to PM, Smoke Opacity,
SOX and NOX are important, since all the
combustion systems shall be required to
monitor those emissions as common
parameters. In general, two monitoring
methodologies, instrument/equipment based
and titration based, are available for gaseous
emission estimations. However only the
instrument/ equipment based methods are
described in this paper, since the monitoring
methods described in particular standards are
based on the instrument / equipment method.
3.1
Monitoring of Particulate Matters
(PM)
3.1.1
Test Method and Instrumentation
The common method used for stack PM
monitoring is “In-stack Filtration Method”. In
this method, PM is withdrawn isokinetically
from the source and collected on a glass fiber
filter maintained at a temperature, as specified
by applicable standards, or approved by
particular application. The PM mass which
includes any material that condenses at or
above the filtration temperature is determined
gravimetrically
after
the
removal
of
uncombined water.
2.3
System Requirements and
Limitations
System requirements of this standard are
described in order to control the toxic gases;
especially SO2 and NOX. The key factors
discussed under the system requirements are;
In any case, the stack (chimney) height
shall not be less than 20m
In case of power plants, SO2 shall be
controlled by fuel quality and stack
height, if SO2 emission levels are not
specified in the standards.
Dioxin and Furan emission from
incinerators shall be controlled by
maintaining temperature within 1100 0C
to
1250 0C and 2-3 seconds retention
time in secondary chamber.
The basic components of standard PM
monitoring sampling train are probe nozzle;
probe extension, filter holder, barometer, Pitot
tube, differential pressure gauge, condenser,
metering system, vacuum pump and heating
element. The common arrangement of the
instrument train is illustrated in Figure 1.
Figure 1 – Basic Components of PM Monitoring Sampling Train [Source-Envirotech
APM 621]
ENGINEER
3
53
ENGINEER
3.1.2
Applicability, Limitations and Facility
Requirements for PM Monitoring
The fundamental principle behind any sampling
analysis is that a small amount of collected
sample should be a representative of all the
particles being monitored. Therefore variations
in concentration, temperature or velocity across
the duct, moisture, gas leakage or air infiltration
can affect the measurements. Further the
number of samples, monitoring locations and
port sizes will depend on the homogeneity of
the gas stream. Therefore for accurate
measurements, it is required to follow the basic
and standard methods. [Reference - BS EN
13284-1:2002 or any other acceptable standards].
According to the standards, PM sampling
stations should be located at few meters above
(depends on the stack arrangement) the ground
level. Therefore it is important to facilitate a safe
system set up for both operators and
instruments. In this regard, a safe and
permanent working platform and a lifting
arrangement shall be required to reach the
sampling locations. However, in exceptional
circumstances; such as old plants or where the
owner cannot bear the setting up facility cost
(especially in small scale industries), temporary
structures; scaffolding, mobile crane/lift etc. can
be used. All the platforms, whether permanent
of temporary, shall meet the standard
dimensions, weight criteria, protection, facility
requirements etc. [Reference - EN 13284-1:2002
or any other acceptable standards].
3.2.1
Test Methods, Instrumentations and
Limitations
(a)
Ringelmann Method:Ringelmann Method is a visual assessment
method and the darkness of smoke emitting at
the top of the stack is compared with the
standard shades of grey chart (called
Ringelman) placed at a certain distance from the
observer. The system arrangement is illustrated
in Figure 2.
The Ringlmann method cannot be applied to
many combustion systems operated island wide.
This is because according to the physical set up
Line
of Sight
of the
system,
, most of the stacks are covered or
obstructed by adjacent buildings, trees or any
other objects. Further the accuracy of test results
totally depends on the appearance of a plume as
viewed by an observer, angles of the observer
with respect to the plume & the sun, the point of
observation of attached & detached stem plume,
nature of day light and the wind velocity.
Figure 2 – Ringlemann Chart for Smoke
Opacity Monitoring
(b)
Dual Beam Method
Dual Beam Method is a universally accepted
method to monitor smoke opacity. The basic
principle of this method is to transmit a light
beam through the flue gas (to be tested) and
measure the reduction in its intensity.
Main components of the system are a twin beam
transmitter, a high-intensity light source and
detectors. The system arrangement is illustrated
in Figure 3.
3.2
Monitoring of Smoke Opacity
Smoke Opacity is a property of a substance,
especially unburned Carbon, which renders it
partially or wholly obstructive to the
transmission of visible light and it is expressed
as the percentage to which the light is
obstructed. [New Jersey Air pollution Control
Act N.J.A.C. 26:2C-1]. Based on the standards
[Ref. - Table 1.0], smoke opacity monitoring is
common for any combustion system and shall
be maintained below the recommended levels
such as 10%, 15%, 20% etc.
Usually, two monitoring methods have widely
been practiced to measure smoke opacity. Those
are the “plume visual inspection method”“Ringelmann” and the “Dual Beam Method”.
ENGINEER
ENGINEER
The main issue in this method is locating the
monitoring system across the pre defined cross
section of the stack at a certain height. [This
height is defined to obtain a “Laminar Flow
Region” and the level depends on the system set
up]. Further, pre facility requirements to handle
the instruments, to monitor/measure the
parameters are not incorporated in many
existing combustion systems.
4
54
Figure 3 – Dual Beam Method Smoke Opacity
Figure 3 –Kit
Dual
Beam–Method
Opacity
Monitoring
[Source
Forbes Smoke
Marshall
–
Monitoring
Kit [Source
– Forbes
Marshall –
DCEM
2100 – Unique
Dual Beam
Opacity/Dust
DCEM 2100 – Unique Dual Beam Opacity/Dust
Monitor]
Monitor]
3.3
Monitoring of Dioxins and other
3.3 Gaseous
Monitoring
of Dioxins and other
Components
Gaseousgaseous
Components
The most common
emissions described
The
most
common
gaseous
emissions
NOX.
in this particular standard are
SOX, &described
, & not
NOX.
in
this
particular
standard
are
SOXhas
However, in many cases, this standard
However,
in
many
cases,
this
standard
has
described the marginal figures of SOX, & NOXnot
the marginal
figures
of SO
X, & NOX
anddescribed
has advised
to control
those
gaseous
and
has
advised
to
control
those
gaseous
emissions by maintaining the stack height
&
emissions bybymaintaining
the stack
height &
temperature
incorporating
emission
temperature
incorporating
reduction
utilities.byIn addition
to that emission
it is
reduction
utilities.CO,
In CO
addition
to
that
it is
,
excess
air
levels
important
to monitor
2
air levels
CO2, excess
etc.important
in flue gasto
formonitor
efficientCO,
combustion
systems.
etc. in flue gas for efficient combustion systems.
3.3.1
Test Methods, Instrumentations and
3.3.1 Limitations
Test Methods, Instrumentations and
In general, Limitations
two methods of gaseous components
In general, two
of sampling
gaseous components
determination,
viz.methods
extractive
method
determination,
viz.
extractive
sampling
method
and non-extractive sampling method,
have been
and
non-extractive
sampling
method,
have
been
practiced. Out of those two methods, extractive
practiced.
Out
of
those
two
methods,
extractive
sampling method is the most common and
sampling
is the most
common
widely
used. method
In this method
effluent
gaseousand
widelyareused.
In this
method
effluent gaseous
samples
passed
through
the moisture
and
samples are
passed through
moisture
contaminant
absorbent
filters totheremove
theand
contaminant
absorbent
filters
to
remove
moisture (analysis under dry basis) and to clean the
(analysis
under dry basis)
andbeing
to clean
themoisture
gas sample
respectively
before
the
gas
sample
respectively
before
being
conveyed to the instrument. Then the
conveyed
to
the
instrument.
Then
conditioned gas is passed through differentthe
conditioned
is passed
through
different
chemical
sensorsgas
(in built
sensors)
for necessary
chemical
sensors
(in
built
sensors)
for
necessary
reactions. The composition of particular gaseous
reactions. are
Themeasured
composition
of particular
gaseous
components
based
on the number
are measured
based on chemical
the number
of components
electrons emitted
by different
of electrons
emittedsystem
by different
chemical
reactions.
The common
arrangement
is
reactions.
The common
system arrangement is
illustrated
in Figure
4.
illustrated in Figure 4.
ENGINEER
ENGINEER
5
Figure 4 – Instruments for Exhaust Gas
Figure 4 – Instruments for Exhaust Gas
Monitoring
Monitoring
The location of sampling points to monitor the
The location
of sampling
points
to monitor
gaseous
concentrations
is not
critical
like inthe
gaseous
concentrations
is
not
critical
monitoring PM. Because the variations like
of in
monitoring
PM.
Because
the
variations
velocity profiles do not affect the homogeneity of
velocity
profiles
do not affect
themeans
homogeneity
of the
gaseous
concentration.
This
that
the gaseous
concentration.
This meansbythat
theof
proximity
to bends,
branches, obstruction
proximity
to bends,
obstruction
fanstheand
dampers
are lessbranches,
important.
But the by
fans and
dampers
areairless
important.
But the
sampling
after
dilution
must
be avoided.
sampling
after dilution
air must
be avoided.
Therefore
monitoring
of gaseous
parameters
is
Therefore
monitoring
of
gaseous
parameters
convenient and can be commonly implemented is
be commonly
implemented
in convenient
many typesand
of can
combustion
systems,
since
in
many
types
of
combustion
systems,
since
those do not require any special and expensive
those
do
not
require
any
special
and
expensive
pre-facilities arrangement.
pre-facilities arrangement.
4.
4.
Implementation Difficulties of
Implementation
Difficulties of
New
& Proposed Environmental
New
&
Proposed
Environmental
Standards
Standards
Not only the plant owners or industries, but also
Not onlybodies
the plant
or industries,
but also
regulatory
andowners
monitoring
parties have
regulatory
bodies
and
monitoring
parties
have
come across different issues and difficulties,
come
across
different
issues
and
difficulties,
while implementing such requirements. Few
while
implementing
requirements.
such
important
factors such
are discussed
hereinFew
such
discussed herein
from
theimportant
point of factors
view ofareindustries/plant
from third
the parties
point and
of view
of industries/plant
owners,
instrumentation.
owners, third parties and instrumentation.
5
55
ENGINEER
-
-
-
-
-
--
4.1
Implementation Difficulties
4.1
Implementation
Difficulties standards
The implementation
of environmental
The
implementation
of
environmental
standards
for small & medium industries is rather
difficult
for
small
&
medium
industries
is
rather
difficult
compared with these for large combustion
compared
with
these
formentioned
large combustion
systems due
to the
under
reasons.
systems
due to the
under
mentioned
reasons.
New standard
pre
facility
requirements
such as
New
standardsample
pre facility
requirements
such as
platforms,
points,
safe ladders
etc.
platforms,
points,
ladderssystems
etc.
cannot be sample
introduced
to thesafe
existing
cannot
introduced
to the existing
systems
due tobestructural
weakness,
failures, corrosion,
due
to availability
structural weakness,
failures, corrosion,
space
etc.
space
etc.
Lowavailability
income industries
cannot bear the high
Low
income
industries
cannot
high
capital (expenses) to modify bear
theirtheexisting
capital
(expenses)
to
modify
their
existing
combustion systems to meet standard
combustion
requirements.systems to meet standard
requirements.
Industries that periodically operate (i.e. 2-4
Industries
periodically
times per that
month);
especiallyoperate
foundry,(i.e.
DG 2-4
sets
times
sets
etc. per
willmonth);
have especially
to meetfoundry,
same DG
standard
etc.
will haveliketoother
meet
same standard
requirements
continuous
operating
requirements
like other continuous operating
plants.
plants.
The systems that have been already purchased;
The
systems the
that waste
have been
already purchased;
especially
combustion
incinerators,
especially
the
waste
combustion
incinerators,
crematoria etc. have not incorporated
with
crematoria
etc. have
notand
incorporated
withas
emission control
devices
techniques such
emission
controlwet
devices
and techniques
as
dual chamber,
scrubbers,
standard such
retention
dual
wet scrubbers, standard retention
timechamber,
etc.
time
Theetc.
chimney height can not be extended;
The
chimney
height
can not kilns,
be extended;
especially
in DG
sets, furnaces,
cupola etc.,
especially
sets, furnaces,
kilns, cupola
etc.,
to meet in
theDG
standard
requirement
due to
the
toexisting
meet the
standard
requirement
due to plant
the
system
set up,
space availability,
existing
systemstructural
set up, space
availability,
plant
performance,
failures
etc.
performance, structural failures etc.
Low graded fuel; especially fossil fuels having
Low
fuel;unexpected
especially foreign
fossil fuels
having
highgraded
moisture,
particles
etc.
high
unexpected
foreign
particles etc.
can moisture,
not be controlled
by plant
owners.
can
not be controlled
by charges
plant owners.
Expensive
monitoring
due to the limited
Expensive
monitoring
charges
the demand.
limited
number of
monitoring
partiesdue
andtotheir
number of monitoring parties and their demand.
--
4.2
Monitoring Difficulties in View of
4.2
Monitoring
Difficulties in View of
Third Parties
Parties
Even Third
though
the combustion systems are
Even
though the
are
incorporated
withcombustion
continuoussystems
monitoring
incorporated
with
continuous
monitoring
facility or not, the third party inspection and
facility
or not, thereports
third party
inspection
and
recommendation
are required
to confirm
recommendation
reports are combustion
required to confirm
whether the particular
systems
whether
the the
particular
combustion
systems
comply with
environmental
regulations
and
comply
with the below
environmental
regulations
and
are operated
the standards
emission
are
operated
the standards
emissionbe
levels.
Such below
monitoring
parties should
levels.
Such under
monitoring
partiesEnvironmental
should be
registered
the Central
registered
Authority.under the Central Environmental
Authority.
ENGINEER
ENGINEER
ENGINEER
6
6
56
Out of 47 numbers of registered licensees in
Out
of for
47 numbers
registered
licensees
CEA
the year of2012,
only 12
parties;in 5
CEA
for
the
year
2012,
only
12
parties;
5
government organizations and 7 private
government
organizations
and
7
private
institutions,
have
been
involved
in
institutions,
been practices.
involved
in
environmentalhave
monitoring
However
environmental
many of themmonitoring
are having practices.
capacities However
to monitor
many
of them
are having
capacities
to monitor
fugitive
air quality
but they
do not have
capacity
fugitive
air quality
but they
do not have
capacity
to monitor
combustion
emission.
Out of
those 12
toregistered
monitor combustion
Out of
those 12
parties, emission.
only three
government
registered
parties,
only three
organizations
are having
capacitygovernment
to monitor
organizations
are having
capacity
to monitor
PM and gaseous
emissions.
However,
no one
PM
and
gaseous
emissions.
However,
no
one
has facility to monitor all the basic emission
has
facility
to
monitor
all
the
basic
emission
parameters highlighted in the standards.
parameters highlighted in the standards.
Further the under mentioned difficulties are met
Further
under mentioned
difficulties
are met
by thethe
monitoring
parties while
practicing
the
bymeasurements.
the monitoring parties while practicing the
measurements.
- Personal safety
- - Personal
safetyprotection & safety, handling
Instrument
- difficulties
Instrument protection & safety, handling
difficulties
- Interferences of modified devices, such as
- moisture
Interferences
of modified
as
and water
vapor devices,
releasedsuch
by wet
moisture
and
water
vapor
released
by
wet
scrubbers/wet bottom etc.
scrubbers/wet
bottom
etc.to uneven combustion
- Repeatability
due
- [Variations
Repeatability
to uneven
combustion
of due
process
demand
during
[Variations
monitoring] of process demand during
monitoring]
- Lack of knowledge under different
- combustion
Lack ofsystems
knowledge under different
combustion
- High systems
expenses required to maintain
- accreditation
High expenses
required to maintain
laboratory.
accreditation laboratory.
4.3
Monitoring Difficulties in View of
4.3
Monitoring
Difficulties in View of
Instrumentation
Instrumentation
As discussed under the section 3.0, it is
As
discussed that
under
the instrumentations
section 3.0, it and
is
understood
special
understood
that special
instrumentations
andto
skill operators’
assistance
are required
skill
operators’
required The
to
monitor
the assistance
emission are
parameters.
monitor
the recommended
emission parameters.
instruments
for particular The
tests
instruments
recommended
for particular
are uncommon
and expensive.
Further, tests
some
are
uncommon
expensive.
some
instruments
andand
chemicals,
like Further,
opacity meters,
instruments
chemicals,
opacity
meters,
reagent,
heavylike
metal
detectors
etc.,
SOX& NOXand
&
NO
reagent,
heavy
metal
detectors
etc.,
SO
X
X
are not locally available.
are not locally available.
The emission monitoring instrumentations shall
The
monitoring
instrumentations
shall
be emission
subjected
to an annual
calibration
for
beaccurate
subjected
an annual
calibrationIn for
and to
standard
measurements.
this
accurate
standard instruments
measurements.
regard, and
the particular
shallInbethis
sent
regard,
particular
instruments
shall be out
sentof
to the the
principal
suppliers;
most probably
tothe
thecountry,
principalfor
suppliers;
most probably
out take
of
re calibration
and it will
the
country,
for re calibration and it will take
nearly
2-3 months.
nearly 2-3 months.
Sudden failures of instruments; such as
malfunctioning, sensor failures, physical
damages etc. will also affect the regular
monitoring practices.
5.
maintaining a minimum 20 m stack height and
fuel quality. Usually, standby generators are not
incorporated with such type of taller stacks.
Most of the standby generators are having only
silencer with 6”- 8” diameter & 1’ - 5’ length
(depending on the capacity). Further it is
practically impossible to extend or introduce a
20m chimney to the standby generators, since
such modifications will directly affect the plant
performance.
Typical
arrangements
are
illustrated in Figure 6.
Discussion and
Recommendations
Author has made the under mentioned
recommendations
through
industrial
experiences related to exhaust gas monitoring
and existing plant behaviors of stationary
combustion systems, such as large scale
combustion systems, standby generators,
industrial boilers & thermic fluid heaters,
incinerators and cupolas, furnaces, kilns etc.
5.1
Large Scale Combustion Systems
Almost all the large scale combustion systems
have been incorporated with the particulate
matter and effluent gas controlling mechanisms,
such as bag filters, cyclone separators, wet
scrubbers etc. and inbuilt continuous operating
emissions gas monitoring systems. In addition
to that pre facility requirements such as working
platform, lifting arrangements, sampling ports
etc. have also been made available for periodical
monitoring purposes. Such an arrangement is
illustrated in Figure 5.
Figure 6 - Silencers in Standby Generators
In many industries, diesel generators have been
used only for the emergency purposes (during
the National power failures). Hence the
emission released to the environment is
comparatively less, because the average
operating time and related fuel consumption are
less. Therefore the impacts of gaseous emissions
to the environment through standby generators
are comparatively less.
Even though pre facilities are required to
monitor
PM
(normally
not
available),
instrumentations (Pitot tube, nozzle, filter
holders etc.) do not match with such types of
small stack diameters.
Figure 5 -Pre-Facility Requirements for
Large Scale Combustion Systems
However it will not be a practical issue to
monitor the opacity level using “Ringlemann”
method in such types of shorter stacks. But
monitoring of Opacity will also be an issue, if
the stackheight increases up to 20m [Ref. –
Sections 3.2.1].
Therefore
implementation
of
proposed
standards for large scale combustion systems is
practicable.
5.2
Standby Generators
The available standards guide to control PM,
SOX& NOX emission of standby generators by
ENGINEER
7
57
ENGINEER
5.3
Boilers and Thermic Fluid Heaters
Boilers and thermic fluid heaters are commonly
used combustion systems in industries to obtain
thermal energy demand. Almost all the
combustion systems in these categories are
incorporated with Mild Steel stacks having
diameters ranging from 8” to 24” and height
ranging from 5m to 10m. Some stacks have been
directly extended through the boiler house roof
top and the others are extended by the branch
connection between boiler and the stack. The
arrangements are illustrated in Figure. 7.
systems, not only the fuel combustion emissions,
but other harmful gaseous substances from
waste combustion also are emitted to the
atmosphere. Therefore not only the SOX and
NOX, the other toxic gases too have to be
monitored in incinerators. [Ref.Table 1.0].
However
many
incinerators
have
not
incorporated pre facility requirements to
monitor either PM, opacity or any other gaseous
parameters. Further the systems having water
scrubbers and more than 20 m height stacks are
rarely found.
Even through the emission regulations for waste
combustion are stricter than for the other
combustion systems, it can be seen that non
standardized
plants
(emitting
gaseous
pollutants) are being operated island wide. This
is basically due to non recommended waste
combustion, over charging (waste), employing
unskilled
operators,
mismatched
plant
specifications (stack height, retention time,
number of burners etc.), and incineration
temperature etc. The measurement and
implementation issues discussed under section
5.3 are also applicable in this category of plants.
In addition to that, some stacks are made out of
fire bricks and therefore one cannot introduce
monitoring pre facility and water scrubbing etc.
The arrangement is illustrated in Figure 8.
Figure 7 - Stack Arrangement of Boilers and
Thermic Heaters
However in many stacks, it is practically
impossible to extend the stacks to meet the
standard requirements for gaseous emission
controlling and to introduce pre facility
requirements for PM monitoring. The main
reasons found are structural failure, additional
space requirements and effects to the draught
etc. In addition to that the opacity monitoring by
Ringelman method is not practical in many
cases due to the similar issues discussed under
Section 3.2.1.Therefore only solution to monitor
exhaust gas emissions of boilers and thermic
heaters is to introduce new stacks instead of the
existing stacks to meet the standard
requirements.
Figure 8 – Stack Arrangement of Incinerators
Further the instrumentations available to
monitor HCl, Mercury, Lead; Dioxin and Furans
emission are hardy found.
5.4
Waste Combustion Incinerators
Waste combustion incinerators are the worst
stationary combustion systems among the
different combustion systems discussed in this
standard. Because, unlike the other combustion
ENGINEER
ENGINEER
This standard has also guided to monitor the
secondary chamber temperature around 1,100 0C
- 1,2500C and the retention time is around 2-3
8
58
seconds to control the Dioxins and Furans
seconds
to control
the those
Dioxinstwo
and monitoring
Furans
emissions.
Out of
emissions.
Outthe of
those two
parameters,
temperature
can monitoring
be monitored
parameters,
thetemperature
temperaturesensors.
can beBut
monitored
using high
such type
using
temperature
sensors. But suchare
typenot
of high
sensors
and instrumentations
of commonly
sensors and
instrumentations
available.
In addition toare
that,not
there
commonly
available.
addition
that,that
there
are no any
practicalIn
methods
to to
ensure
such
areplants
no anyoperate
practicalunder
methods
to ensure that such
recommended/designed
plants
operate
under recommended/designed
retention
time.
retention time.
Therefore while considering the above
Therefore
while
considering
the to
above
limitations,
the most
practical method
control
limitations,
mostincinerators
practical method
control a
emission the
from
is to to
introduce
emission
from incinerators
is to
introduce
water scrubber
to the system.
However
it isanot
water
scrubber
to the system.
However
it is notdue
practical
to modify
the existing
incinerators
practical
to modifynumber
the existing
due
to unlimited
of incinerators
design parameter
to variation.
unlimited But
number
of design
parameter
permission
can be
given to
variation.
be givenhaving
to
purchaseBut
or permission
set up newcan
incinerators
purchase
or
set
up
new
incinerators
having
water scrubbers, multi chambers, standard stack
water
scrubbers,
multi chambers, standard stack
height
etc.
height etc.
5.5
Cupolas, Furnaces, Ovens and Kilns
5.5 The stack
Cupolas,
Furnaces, Ovens
arrangements
under and
this Kilns
category of
Thecombustion
stack arrangements
under
this category
systems are
closely
similar toofthe
combustion
systems under
are closely
similar5.3toand
the5.4.
systems described
the sections
systems
described
under
the sections
5.3 and
5.4.
But the
types and
quantity
of gaseous
emissions
Butdepend
the types
of gaseous
onand
thequantity
fuel used,
plantsemissions
capacities,
depend
on process,
the fueland
used,
plantstime.
capacities,
material
operating
However
material
process,
and
operating
time.
However
some processes under this category are not
some
processesoperations
under this
not
continuous
andcategory
those areareoperated
continuous
and those
are operated
once per operations
week or fortnight
or sometimes
once a
once
per week or fortnight or sometimes once a
month.
month.
Domestic level foundry industry belongs to this
Domestic
level
foundry
industry
belongs
to this3-5
category.
Many
plants
have been
operated
category.
plants
have per
beenmonth.
operated
hrsper Many
day and
2-4 times
The3-5
fuels
hrsper
2-4Cu
times
per month.
Theare
fuels
usedday
for and
Al and
melting
processes
burnt
used
and
melting
processes
are burnt
oil for
andAlfor
theCu
cast
iron melting
process
is coal.
oil Like
and for
the cast iron
process
is coal.
an incinerator
notmelting
only the
fuel combustion
Like
an incinerator
notimpurities
only the fuel
combustion
emissions,
but also
of melting
metals
emissions,
butwith
alsothe
impurities
of melting metals
are mixed
exhaust gases.
are mixed with the exhaust gases.
While considering the operating times per
While
considering
theof metal
operating
times and
perthe
month,
the quantity
processing
month,
the of
quantity
of metal processing
and the
amount
fuel combustion,
it is not economical
amount
of fuel combustion,
is not economical
to introduce
pre facility itrequirements
or wet
to scrubbing
introduce systems
pre facility
requirements
or of
wet
to processing
plants
such
scrubbing
systems
to
processing
plants
of
such
category. The arrangement is illustrated in
category.
Figure 9.The arrangement is illustrated in
Figure 9.
ENGINEER
ENGINEER
9
Figure 9 - Stack arrangement of Furnaces
Figure 9 - Stack arrangement of Furnaces
However, out of the parameters mentioned in
However,
out of the
parameters
mentioned
in
this standard;it
is possible
to practice
the opacity
thistest
standard;it
is possible tomethod.
practice the opacity
using “Ringlemann”
test using “Ringlemann” method.
5.6
Crematoria
5.6 In this
Crematoria
standard, it is described that the emission
In this
it is described
that the
emission by
fromstandard,
crematoria
shall be
controlled
from
crematoria
shall control
be controlled
introducing
emission
devices. by
Even
introducing
emission
control
devices.
Even
though the particular controlling devices are not
though
the particular
devices
are notBut
mentioned,
it maycontrolling
be a water
scrubber.
mentioned,
it may
a wateragain
scrubber.
introducing
waterbescrubber
might But
be an
introducing
water water
scrubber
might be an to
issue to release
withagain
toxic contaminants
issue
water with
toxic contaminants
to
theto release
environment.
Therefore
only possible
thesolution
environment.
Therefore
only possible
for crematoria
is to maintain
chimney
solution
crematoria
maintain chimney
heightfor
according
to is
thetostandards.
Further in
height
according
to the standards.
Further
in
general,
crematoria
are single
chamber
general,
crematoria
singleintroducing
chamber a
combustion
system. are
Therefore
combustion
Thereforeto the
introducing
a
secondary system.
burner (attached
stack) to burn
secondary
burner
(attached
stack)
to burn
the exhaust
toxic
gases to
at the
higher
temperature
thewill
exhaust
toxic
gases
higher
temperature
help to
reduce
theatDioxin
emission.
Further
willit help
reduce the
Dioxin emission.
Further
is nottopossible
to implement
any toxic
gases or
it isPM
not monitoring
possible to implement
toxic gases
or
proceduresany
during
cremation
PMdue
monitoring
procedures issues.
during cremation
to cultural/traditional
due to cultural/traditional issues.
6.
6.
Conclusion
Conclusion
The outcomes of this paper will be useful to the
Theregulatory
outcomes of
this paper
will be useful
to the
bodies
for updating
the proposed
regulatory
for in
updating
the proposed
emission bodies
standards
more practical,
flexible,
emission
standards inways.
more practical,
and convenient
For an flexible,
example,
andrequirement
convenientof ways.
For categorizing
an example,the
separately
requirement
of
separately
categorizing
the
periodically operating plants and continuous
periodically
operating
plants
and continuous
operating plants,
since
the quantity
of emission
operating
since the quantity
of emission
release plants,
to the environment
are different.
Further
release
to the environment
different.
Further to
the contents
of this paperare
will
help industries
themodify
contentstheir
of this
papersystems
will helpaccording
industriestotothe
existing
modify
their existing
systems
according to
new standard,
pre facility
requirements
etc.the
Also
new standard, pre facility requirements etc. Also
9
59
ENGINEER
the techniques discussed under measurements
will help monitoring parties to update their
knowledge under the emission monitoring
systems. Finally the author expect contribution
from regulatory bodies, industries and
monitoring
parties
to
mitigate
the
environmental impacts by reducing emission
release to the atmospherevia stationary
combustion systems.
6.
Proposed
Environmental
Standards
for
Stationary
Combustion
Sources;
Central
Environmental Authority, Sri Lanka.
7.
“KM 9106” Flue Gas Analyzer Operation
Manual, Kane International Limited, Kane
House, Swallowfield, Welweyn Garden City,
Hertfordshire, AL 7 IJG.
8.
“ENVIROTECH APM 621” Stack Monitoring
Kit Operation Manual, VAYUBODHAN
UPKARAN (Pvt.)Ltd. A 292/1, OkhlaIndustrial
Area Phase 1, New Delhi – 110 020.
9.
Sri Lanka Environment Outlook 2009, Ministry
of Environment & Natural Resource, United
Nations Environment Programme.
Acknowledgement
I would acknowledge Engineer D R
Pulleperuma, the former Chairman, National
Engineering Research & Development Centre
(NERDC) for providing his valuable input to
make this paper a success. Further I take
pleasure in thanking Engineer D D Ananda
Namal, the Director General, NERDC, for
granting permission to publish this paper. I also
appreciate the comments made by the Director
of the Renewable Energy Department Eng.
Nandana Edirisinghe and Senior Research
Scientist (Mrs.) Nayana Pathiraja, of NERDC, to
make this paper a Success.
References
1.
International Standards; ISO 10155 Stationary
Source Emissions – Automated Monitoring of
mass Concentrations of Particles – Performance
Characteristics, Test methods and Specifications.
2.
International Standards; ISO 7935 Stationary
Source Emissions – Determinations of the Mass
Concentration of Sulfur Dioxide – Performance
Characteristics of Automated Measuring
Methods.
3.
International Standards; ISO 10396 – Stationary
Source Emissions - Sampling for the Automated
Determination of Gas Concentrations.
4.
Technical Guide Not (Monitoring) M I –
Sampling Requirements for Stack Emission
Monitoring; Environment Agency, Version 4,
July 2006.
5.
Technical Guide Note (Monitoring) M 2 –
Monitoring of Stack Emissions to Air;
Environment Agency Version 4, July 2006.
ENGINEER
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10
60
ENGINEER -- Vol.
Vol.XLVIII,
XLVIII,No.
No.01,
01,pp.
pp.
[page 2015
range], 2015
ENGINEER
[61-70],
© The
The Institution
InstitutionofofEngineers,
Engineers,
Lanka
©
SriSri
Lanka
Projecting Turbidity Levels in Future River Flow: A
Mathematical Modelling Approach
T. N. Wickramaarachchi, H. Ishidaira, J. Magome and T. M. N. Wijayaratna
Abstract:
Climate and land use change impacts on river flow were evaluated in this study with
emphasis placed on turbidity. Turbidity levels for the year 2020 were projected for Gin River, one of
the prime sources of drinking water in Southern Sri Lanka. Future land use in the Gin catchment was
predicted using a GIS based statistical regression approach. Regional Climate Modelling system
generated the future rainfall for the SRES A2 and SRES A1B emission scenarios. Streamflow
simulations were carried out using a distributed hydrologic model, and turbidity values were
determined using rating curve based relationship developed between river discharge and TSS (Total
Suspended Solid) concentration followed by Turbidity-TSS linear regression correlation.
Increased turbidity levels are clearly evident under the SRES A2 scenario, following more pronounced
increased streamflows. Projected 75th percentile monthly turbidity values in year 2020 are expected to
increase during May to November compared to the baseline, andin certain months, about
100%increase is noted. 60% of the time, year 2020 turbidity levels have indicated exceedance of the
water quality standards set for the potable water as well the inland waters of Sri Lanka, which would
lead to exert extra challenge on future drinking water production in Southern region of Sri Lanka.
Keywords:
1.
Climate change, Land use change, Hydrologic modelling, Streamflow, Turbidity
Introduction
physical, and biological characteristics, but is
a value-laden term because it implies
quality in relation to some standard. Stream
water quality, however, also will be affected by
streamflow
volumes,
affecting
both
concentrations and total loads [5].Turbidity is
an important indicator of the quality of water.
Thus, monitoring turbidity levels to meet water
quality standards is vital to prevent adverse
effects on human health and aquatic life, and to
enhance aesthetic and recreational values.
Particularly, turbidity in drinking water can
interfere with disinfection and provide a
medium for microbial growth. Turbidity and
streamflow are related because streamflow can
affect suspension of the sediment and related
constituents causing turbidity [6].
Land use composition variation and climate
change impacts on quantity and quality of river
flows have gained significant attention in
watershed hydrology. There is abundant
evidence from observational records and
climate projection studies that water resources
are vulnerable and have the potential to be
strongly impacted by climate change [1].
According to IPCC
AR4 [2], freshwater
availability in Central, South, East and
Southeast Asia, particularly in large river
basins, is projected to decrease by year 2050.
Also it has been shown in several studies that,
many non-climatic drivers including land use
change bring in variety of impacts on
freshwater resources both in quantity and
quality [3].
Eng. (Dr) (Mrs) T. N. Wickramaarachchi, B.Sc. Eng(Hons)
(Moratuwa), MPhil (Moratuwa), PhD (Yamanashi),
MJSCE(Japan), C.Eng, MIE(SL), Senior Lecturer, Dept. of
Civil & Env. Engineering, University of Ruhuna.
Hydrological and sediment load responses to
combined effect of climate change and land use
change in humid tropical region remain less
explored. Yet, environmental change in this
region is supposed to alter the precipitation
regime and other aspects of the hydrological
cycle [4]. Hence studies in humid tropical
watersheds are crucial to understand flow
regime changes and consequent effects on river
water quality.
Water quality is a function of chemical,
Eng. (Dr) H. Ishidaira, B.Sc. Eng(Nagaoka ), M.Eng
(Nagaoka), D.Eng (Nagaoka), Associate Professor, Interdis.
Graduate School of Medicine and Engineering, University of
Yamanashi, Japan.
Eng. (Dr) J. Magome, B.Sc.Eng (Yamanashi), M.Eng
(Yamanashi), D.Eng (Yamanashi), Assistant Professor,
Interdis. Graduate School of Medicine and Engineering,
University of Yamanashi, Japan.
Eng. (Dr) T. M. N. Wijayaratna, B.Sc. Eng(Hons)
(Moratuwa), M.Eng (AIT), D.Eng (Yokohama), C.Eng,
MIE(Sri Lanka), Senior Lecturer, Department of Civil
Engineering, University of Moratuwa.
1
61
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According to Sri Lanka‟s policy frame work,
targets have been set to achieve 94% safe
drinking water supply by year 2015 and 100%
by year 2020 [7]. Identifying plausible impacts
on future river water quality is vital in the
context of drinking water production in
achieving the set targets, despite the facts of
increasing population pressure and declining
water quality and quantity owing to various
anthropogenic activities and natural processes.
year. Rainfall increases from downstream to
upstream of the catchment. In the downstream,
annual rainfall is less than 2500 mm, while it is
above 3500 mm in the upstream.
Gin catchment‟s land is mainly used for natural
and plantation forest, agriculture and
settlements. Cultivations include paddy and
export-oriented crops such as tea, rubber, and
cinnamon. Catchment lies approximately
between 80°08" E to 80°40" E and 6°04" N to
6°30" N, covering 932 km2 and encompassing
four districts namely Galle, Matara, Kalutara,
and Rathnapura. Nearly 83% of the catchment
area belongs to the Galle district and district‟s
water supply system mainly depends on the
water resources in Gin River basin.
The aim of this study is to evaluate the impacts
on future river waterquality, subsequent to
future flow regime alterations in a typical
watershed in the wet zone of Sri Lanka.
Riverwater quality assessment in the study is
done in terms of turbidity. The study site is the
Gin River basin (Figure 1) and turbidity levels
are determined in Gin River flow at Baddegama
(6°11'23" N, 80°11'53" E), intake point to the
water treatment plant. Gin River is the most
important water source to cover the drinking
water supply requirement in the Galle district
in
Southern
Sri
Lanka. Recent studies
exhibited degradation trend of water quality in
Gin River as well significant change in land use
in Gin catchment [8,9]. Lack of previous impact
studies to assess similar environmental changes
in humid tropical catchments including the Gin
catchment makes this modelling effort
important.
3.
Data and Analysis
3.1
Climate (Precipitation) Change
Year 2020 rainfall was estimated from the
PRECIS run using HadRM3P, 25 km x 25 km
resolution Regional Climate Modeling (RCM)
system developed by the UK Met Office Hadley
Centre. Hadley Centre RCM had been
successfully applied to simulate climate in the
Indian subcontinent region [10]. In projecting
year 2020 rainfall for the Gin catchment, two
experiments were run by the UK Met Office
Hadley Centre covering SRES A2 scenario and
SRES A1B scenario.
Gin River’s
Catchment
Location
Rainfall (mm)
100
Baddegama
10
1
0.1
2020_A2
0.01
2020_A1B
0.001
2001-2004
0.0001
0
10
20
30
40
50
60
70
80
90
100
Percentage of time rainfall was equaled or exceeded
Figure 1- Gin River, its catchment location,
and Baddegama river gauging station.
Figure 2- Rainfall vs. percentage of time
rainfall was equalled or exceeded.
2.
This study used a scaling method that
considered daily patterns of rainfall change
simulated by the RCM to estimate climate
change impacted precipitation over the Gin
catchment [11,12]. In the daily scaling method,
ranked daily rainfall differences between RCM
and baseline (2001-2004) were expressed as
ratios relative to the baseline rainfall and these
ratios were then used to scale 30 years historical
catchment rainfall to produce year 2020 rainfall.
Study Area
Gin River originates from the Gongala
Mountains and flows to the Indian Ocean at
Ginthota. Climate conditions in the catchment
are influenced by the monsoon, which has two
seasons each year, Northeast
Monsoon
between
November and
February, and
Southwest Monsoon between May and
September followed by the inter-monsoon
rains during the remaining months of the
ENGINEER
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2
62
Compared to 2001-2004, magnitude of the total
annual rainfall in year 2020 is expected to
decrease on average by about 8% and 40%
under the SRES A2 and SRES A1B, respectively,
with a standard deviation of 174 mm between
the scenarios. Occurrence of high intense
rainfall events (between the 95th and 100th
percentile) is more pronounced under the
SRES A2 (Figure 2).
𝑙𝑙𝑜𝑜𝑔𝑔
Spatial
policies
Conversion elasticity
(Reversibility ofland
use change)
Total
Probability
Land use demand
Future land use demand was quantitatively
determined using population forecast along
with growth ratio; the ratio of developed land
growth to population growth [13].
𝑃𝑃ͳ
(2)
Allocation of land use change
Allocation of land use change was made in an
iterative procedure given the probability maps,
spatial policies and conversion elasticities in
combination with the actual land use map in
1983 and the demand for the different land use
types (Figure 3) [16]. Spatial policies are
employed to indicate the areas where the land
use changes are restricted through policies or
tenure status. The conversion elasticity is
related to the reversibility of land use change.
By reclassifying the available land use types in
the catchment, five major land use types;
„forest‟, „paddy cultivation‟, „other cultivation‟,
„homestead/ garden‟, and „other‟, have been
identified to represent the catchment land use
better. „Other cultivation‟ category includes
export-oriented crops; tea, rubber and
cinnamon. „Other‟ category basically includes
water bodies.
𝑃𝑃ʹ −𝑃𝑃ͳ
ൌ 𝛽𝛽Ͳǡ𝑢𝑢 ൅ 𝛽𝛽ͳǡ𝑢𝑢 𝑋𝑋ͳǡ𝑖𝑖 ൅ 𝛽𝛽ʹǡ𝑢𝑢 𝑋𝑋ʹǡ𝑖𝑖 ൅Ǥ Ǥ ൅𝛽𝛽𝑛𝑛ǡ𝑢𝑢 𝑋𝑋𝑛𝑛ǡ𝑖𝑖
where,𝑃𝑃𝑖𝑖ǡ𝑢𝑢 is the probability of grid cell i for the
occurrence of the considered land use type u; 𝛽𝛽
isthe regression coefficient; and X is the driving
factor [16].
3.2
Change in Catchment Land Use
The study employed a spatially explicit land
use change analysis across the Gin
catchment in projecting year 2020 catchment
land use.
𝐴𝐴ʹ ൌ 𝐴𝐴ͳ ͳ ൅ 𝑅𝑅
𝑃𝑃 𝑖𝑖ǡ𝑢𝑢
ͳ−𝑃𝑃 𝑖𝑖ǡ𝑢𝑢
Probability
(Pi,u)
Allocation
Iteration loop
Demanded area
per land use type
Iteration
variable
Figure 3 - Schematic representation of the
iterative procedure for land use change
allocation in CLUE-S modelling framework
[16].
(1)
where,𝐴𝐴ʹ and 𝐴𝐴ͳ are future and current area of
considered land use type (km2), respectively;
𝑃𝑃ʹ and 𝑃𝑃ͳ are future and current population,
respectively; and Ris the growth ratio, the ratio
between growth rate of considered land use
type between 1983 and 1999 (%) and population
growth rate (%).
Validation of logistic regression analysis was
tested
using
the
Relative
Operating
Characteristic (ROC) analysis.ROCvalues range
between 0.5 and 1; 0.5 for completely random
and 1 for the perfect fit, respectively.
Comparatively high ROC test statistics (ranging
between 0.62 and 0.87) indicated that spatial
distribution of all land use types were
reasonably explained by the selected driving
factors.
Past and present population of the area and the
average annual population growth rates were
obtained from the census of 1981 and 2011 [14].
Future population up to year 2020 was
determined according to the „standard‟ rate of
growth of population, Sri Lanka [15].
Observed land use map in 1999 was used in
validating the predictions. By means of
correlation matrix, 1999 projected land use data
were evaluated as a percentage of locations
predicted correctly.
Result of validation
showed that the agreement between the
observed and projected land use in 1999 was
quite reasonable. Overall, the percentage of
total pixels being correctly projected ranged
from 58% to 72%.
Probability maps
The relative probability of occurrence of a
certain land use type at a particular location
was defined using binary logistic regression
approach
influenced
by
socioeconomic,
proximity and biophysical driving factors
(Table 1).
The probability of a certain grid cell to be
devoted to a land use type is given by;
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Table 1 - Land use change driving factors.
Type
Socioeconomic
Driving factor
Population density
Description
Population density (persons/km2)
Proximity
Distance to nearest river
Distance to nearest road
Direct distance to nearest river (m)
Direct distance to nearest road (m)
Biophysical
Altitude
Slope
Soil texture
Elevation above the Mean Sea Level (m)
Slope (based on 1km DEM)
Sandy clay loam soil, Clay loam soil, and Clay soil
(a)
(b)
Figure 4 - Observed and projected land use.
(a) 1983 observed land use (b) Year 2020 projected land use.
3.3 Hydrologic Modelling
University
of
Yamanashi
Distributed
Hydrological Model (YHyM) with block wise
use of TOPMODEL and Muskingum Cunge
method
(BTOPMC)
was
applied
in
quantifying the impacts of climate and land
use change on the river flow regime.
YHyM/BTOPMC has already been successfully
applied to many basins, large to small,
temperate to tropical, around the world [18, 19].
Year 2020 catchment land use
Year 2020 land use projection for the Gin
catchment
envisaged
a
predominant
replacement of cultivated areas in 1983 by
forest and homestead/garden (Figure 4). From
1983 to 2020, drop of cultivated areas from 51%
to 34% is observed. Area covered by the
homestead/garden is expected to rise from 18%
in 1983 to 32% in 2020. This principally reflects
the rapid expansion of homestead/garden to
keep pace with population growth. According
to Wickramaarachchi et al.[9], Gin catchment‟s
land use change can be summarized over the
past thirty years as a result of change in
agricultural
practices
and
increase
in
population. Moreover, the land use change
trends projected in this study are consistent
with
the
changing
trends
in
homestead/garden
and cultivated
areas
between early 80‟s and mid 90‟s, in Galle, as
presented in the ADB report[17].
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In the YHyM, runoff is generated based on the
TOPMODEL concept [20] and flow routing is
carried out using the Muskingum Cunge
method [21]. The hydrological processes in a
grid cell in the BTOP model are illustrated in
Figure 5[19].
The runoff from a grid cell to the local
schematic stream reach is the sum of saturation
excess overland flow (qof) and groundwater
discharge (qb) per unit length of contour line;
4
64
validating the model, respectively. Model
validating
respectively.
performancethewasmodel,
evaluated
by the Model
Nashperformance
was
evaluated
by the ratio
NashSutcliffe Efficiency (E) and the volume
of
Sutcliffe
Efficiency
(E)
and
the
volume
ratio
of
total simulated discharge to total observed
total
simulated
discharge
to
total
observed
discharge (Vr) (Table 2).
discharge (Vr) (Table 2).
2
2
n
(5)
in1 Qobs  Q sim
(5)
i
i
E  1  i 1 Qobsi  Q simi 2
E 1 n
in1 Qobs  Qobs 2
i 1 Qobsi  Qobs
(3)
qof i, t   Suz i, t   SDi, t 
(3)
qof i, t   Suz i, t   SDi, t 
where, Suz is the unsaturated zone storage; and
is the unsaturated
and
where,
Suzsaturation
SD is the
deficit forzone
the 𝑖𝑖 thstorage;
grid cell
at
th grid cell at
SD
is
the
saturation
deficit
for
the
𝑖𝑖
time 𝑡𝑡Ǥ
time 𝑡𝑡Ǥ




i
inn1 Q sim
Vr  in1 Q simii
Vr  in1 Qobs
i 1 Qobsi
isi
where, 𝑄𝑄
(6)
(6)
the observed discharge;𝑄𝑄𝑠𝑠𝑖𝑖𝑚𝑚 𝑖𝑖 is
𝑜𝑜𝑏𝑏𝑠𝑠 𝑖𝑖
observed discharge;𝑄𝑄
where,
𝑄𝑄𝑜𝑜𝑏𝑏𝑠𝑠 𝑖𝑖 is the
𝑠𝑠𝑖𝑖𝑚𝑚 𝑖𝑖 is
the
simulated
discharge;𝑄𝑄
𝑜𝑜𝑏𝑏𝑠𝑠 is the average
average
the
simulated
discharge;𝑄𝑄
observed
discharge;
and 𝑛𝑛𝑜𝑜𝑏𝑏𝑠𝑠is is
thethe
number
of
observed
discharge;
and
𝑛𝑛
is
the
number
of
time steps.
time steps.
Table 2 - HyM/BTOPMC model performance.
Table 2 - HyM/BTOPMC
model performance.
Calibration
Validation
Calibration
Validation
Baddegama Tawalama Baddegama
Tawalama
E%
E%
Vr%
Vr%
Baddegama
67.63
67.63
93.15
93.15
Tawalama
53.75
53.75
105.50
105.50
Baddegama
62.73
62.73
84.94
84.94
Tawalama
48.31
48.31
104.24
104.24
Nash-Sutcliffe efficiency values ranging
Nash-Sutcliffe
efficiency
values acceptable
ranging
between
48% and
67% indicated
between
48% and
67% indicated
acceptable
level of model
performance.
Measured
and
level
of
model
performance.
Measured
and
YHyM/BTOPMC
simulated streamflow
YHyM/BTOPMC
simulated
streamflow
showed a good agreement and overall, the
showed
a good
agreement
andsimulate
overall, the
model was
able to
adequately
the
model
was
able
to
adequately
simulate
the
major hydrological characteristics in Gin
major
hydrological
characteristics
in
Gin
catchment
including
runoff volume,
catchment
including
runoff states
volume,
evapotranspiration
and soil moisture
of
evapotranspiration
and
soil
moisture
states
of
the catchment.
the catchment.
Figure 5 - Runoff generation in a grid cell in
Figure
5 - model
Runoff(the
generation
in a grid cell in
the BTOP
vertical profile).
the BTOP model (the vertical profile).
In this diagram, Pis the gross rainfall, ET0is the
In this diagram,
Pis the gross
ET0is the
the interception
interception
evaporation,
Imax israinfall,
is
the
interception
interception
evaporation,
I
max
storage capacity, Isis the interception
state, Infmax
storage
capacity, Iscapacity,
is the interception
state,
Infmax
rainfall
is the infiltration
Pais the net
is
the
net
rainfall
is
the
infiltration
capacity,
P
on the land surface, ETa is the actual
on
the land surface,
is the capacity
actual
the storage
evapotranspiration,
Srmaxis ET
is
the
storage
capacity
evapotranspiration,
S
rmax
of the root zone, Srzis the soil moisture state in
of thezone,
root zone,
the soil
moisture
state in
in
root
SD Sisrzissoil
moisture
deficit
root
zone,
SD
is
soil
moisture
deficit
in
unsaturated zone, Suzis the soil moisture state in
is the soil moisture state in
unsaturated
unsaturated zone,
zone, Squz
ofis the overland runoff, qifis
unsaturated
zone,
q
is
the overland
of
ifis
the saturation excess
runoff, runoff,
qvis qthe
is
the
the
saturation
excess
runoff,
q
v
groundwater recharge, and qbis groundwater
groundwater
and qbis groundwater
release. θwilt, θrecharge,
fc, θsare soil water contents at
,
θ
,
θ
are
soil
at
release.
θ
wilt
fcfield
s
wilting point,
capacitywater
and contents
saturation,
wilting point, field capacity and saturation,
respectively.
respectively.
3.4
3.4
Turbidity-Total Suspended Solid (TSS)
Turbidity-Total Suspended Solid (TSS)
Correlation
Correlation
Turbidity
measurements are theoretically well
Turbidity
theoretically
well
correlated measurements
to suspendedare
solid
concentration
correlated
to
suspended
solid
concentration
because turbidity represents a measure of water
because
turbidity
represents
a measure
of water
clarity that
is directly
influenced
by suspended
clarity
that
is
directly
influenced
by
suspended
solids. Hence turbidity based estimation
solids.
Hencebeenturbidity
estimation
models have
identifiedbased
as effective
tools
models
have
been
identified
as
effective
tools
for generating suspended solid concentration
for
generating
suspended
solid
concentration
data [22]. Usually, turbidity-TSS relationships
data been
[22]. reported
Usually, on
turbidity-TSS
relationships
have
site by site basis.
have been reported on site by site basis.
  SDi, t  
qb i , t   T0 i  exp   SD i , t   tan  i
(4)
qb i , t   T0 i  exp  mk   tan  i
(4)
mk  

where, SD indicates the saturation deficit;T0 is
where,
SD indicatesand
the saturation
0 is
the transmissivity;
m(k) is thedeficit;T
discharge
the
transmissivity;
and
m(k)
is
the
discharge
decay factor in sub basin k.
decay factor in sub basin k.
A direct correlation between turbidity and
A
direct correlation
between turbidity
and
suspended
solid concentration
has been
suspended
solid
concentration
has
been
documented in many studies conducted around
documented
in many
around
the world [23,
24]. studies
In Sri conducted
Lankan context,
the
world
[23,
24].
In
Sri
Lankan
context,
turbidity-TSS concentration relation has been
turbidity-TSS
concentration
relation has
been
quantified through
linear regression
analysis
quantified
through
linear
regression
analysis
study carried out recently in Gin River at
study
carried
out recently
in GinE)River
at
Baddegama
(6°11'23"
N, 80°11'53"
[25]. In
Baddegama
(6°11'23"
N, 80°11'53"
E) [25].
In
the
above study,
the linear
regression
model
the above study,
the linear
regression
developed
between
turbidity
and model
TSS
developed between turbidity and TSS
The generated overland flow and groundwater
The
overland
flowto
and
flowgenerated
of each cell
are added
thegroundwater
stream and
flow
of
each
cell
are
added
to
the
stream and
then routed to the basin outlet.
then
routed
to
the
basin
outlet.
Model calibration and validation
Modelstreamflow
calibration and
Daily
datavalidation
from 1997 to 2001 and
Daily
streamflow
data from
1997
to 2001 and
from 2002 to 2006 were
used for
calibratingand
from 2002 to 2006 were used for calibratingand
5
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65
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concentration (Equation 7) showed highly
significant (p< 0.0001) strong positive
correlation (R2= 0.98) and strongly suggested
that turbidity is a suitable monitoring
parameter for TSS.
model developed for TSS (Equation 9)
showed higher coefficient of determination
(R2=0.85) reflecting a strong relationship
between the estimated and measured TSS
loads.
Y=1.0457X
Ln(L) = 10.88 + 1.69 LnQ -0.08 LnQ2 + 0.03 Sin(2 π T)
+ 0.30 Cos(2 π T) -0.02 T + 0.02 T2(9)
(7)
where,Y is the TSS concentration (mg/l); and X
is the Turbidity (Nephelometric Turbidity
Units).
where, L is the constituent load; Qis the
is
the
coefficient
of
streamflow;
R2
determination for the regression model;LnQ=
Ln(streamflow) - center of Ln(streamflow); T=
decimal time - center of decimal time.
Explanatory variables are centered to eliminate
the co-linearity.
Relationships are considered to be significant at
p< 0.05.
3.5
TSS Load-Discharge Model
Development
In general, total mass loading over an arbitrary
time period, τ, is given by;
(8)
where,C is the concentration;Lτ is the total
load;Q is the instantaneous streamflow; and t is
the time.
4.
4.1
Integrated Impact of Climate Change
and Land Use Change on year 2020
Streamflow
By driving the calibrated and validated
YHyM/BTOPMC with RCM generated rainfall
and projected land use in the Gin catchment,
year 2020 daily streamflow at Baddegama was
generated.
Figure 6 shows year
2020
streamflow hydrographs for the SRES A2
and SRES A1B scenarios, as simulated by
the
YHyM/BTOPMC. Moreover, the
hydrological response to the two forcing SRES
scenarios as simulated by the YHyM/BTOPMC
is illustrated using the flow duration curves
(Figure 7). Increased peak flow (largely due
to rainfall generated runoff) is more
pronounced for the SRES A2 scenario
compared to the baseline 2001-2004, as a
result of increased extreme rainfall events in
future. According to the simulated annual
water balance, evapotranspiration, ground
water recharge and base flow are expected to
slightly decrease under both scenarios owing to
decreased future rainfall and substantial
replacement of catchment‟s pervious areas in
future. Year 2020 total annual flow volume is
predicted to increase for the SRES A2 scenario
by 4% and decrease for the SRES A1B scenario
by 50% compared to 2001-2004.
Accurate estimation of constituent loads in
streams is crucial for many applications,
including identifying sources of nutrient loads
in the catchments and assessing trends in the
loads [26, 27]. LOADEST, Load-discharge
rating curve [28], a computer programme
developed by the United States Geological
Survey (USGS) was used in this study to
develop multiple regression model and
estimate daily loads of suspended solids. Time
series streamflow data and constituent
concentrations are used in the LOADEST to
develop and calibrate a regression model
that describes constituent loads in terms of
various functions of streamflow and time.
LOADEST has been extensively applied to
estimate constituent loads in rivers around the
world [29, 30].
Time series of TSS concentration observations
and corresponding streamflow observations at
Baddegama were used in developing and
calibrating
the
regression model
using
adjusted
maximum
likelihood estimation
(AMLE) method. AMLE method is contingent
upon the fact that model residuals are normally
distributed. Linearity of the normal probability
plot constructed, suggested that the residuals
follow a normal distribution. The regression
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Results and Discussion
6
66
350
40
300
60
250
200
80
150
100
100
Rainfall (mm)
20
400
Qsim (m3/s)
1000
0
450
Streamflow (m3/s)
500
10
0
10
20
30
40
50
60
70
80
90
100
Percentage of time streamflow was equaled or exceeded
2020_Rainfall_A2
2020_Qsim_A2
2020-12-17
2020-10-28
2020-09-08
2020-07-20
2020-05-31
2020-02-20
2020-04-11
140
2020-01-01
0
100
1
120
50
2020_A2
2020_A1B
2001-2004
Figure 7 - Flow duration curves: Year 2020
and 2001-2004
2020_Rainfall_A1B
2020_Qsim_A1B
Figure 6 - Year 2020 streamflow
hydrographs
250
Qsim – Simulated streamflow
45
Year 2020
Max.
40
150
35
Turbidity (NTU)
75th
30
Average
Median
25
25th
20
100
50
Min.
15
Stream flow (m3/s)
200
2001-2004
5
0
Dec
Oct
Nov
Sep
Jul
Aug
Jun
May
Apr
Feb
Mar
Jan
75 th
0
Figure 8 - Monthly turbidity (Year 2020 and 2001-2004).
- Maximum, minimum, average, median, 25th percentile
and75th percentile turbidity values are shown for year 2020
- 75th percentile turbidity value is shown for 2001-2004
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
10
2001-2004
2020_A2
Figure 9 - 90th Percentile
of monthly streamflow.
-
developed. Using the linear regression equation
developed
(Equation
7),
corresponding
turbidity values were derived.TSS is a pollutant
that responds to flushing more than dilution
within a catchment and therefore, higher river
discharge will mostly facilitate greater erosion
and transportation of the pollutant compared to
dilution. Response of TSS to climate and land
use changes had demonstrated that, higher the
precipitation level, larger the concentration of
TSS in a catchment [32, 33]. In this study,
following the linear relation between TSS and
turbidity, elevated levels of turbidity have been
noted following the increased river discharge
resulted by increased rainfall events. Thus, the
response of turbidity to river flow regime
changes have predicted considerably higher
turbidity values in most of the months in year
2020 compared to 2001-2004, while remaining
months demonstrate decrease.
Though this study included future projections
for both SRES A2 and SRES A1B scenarios, in
most of the climate adaptation studies carried
out, it has been identified that the most
matching scenario for Sri Lankan conditions is
SRES A2. This is further explained by De Silva
et al.[31]. According to Figure 7, flows with
high magnitudes are expected to occur under
SRES A2 scenario and it is understood that
generation of sediments and pollutant loads are
directly related to extreme runoff events. Thus
the present study opted to consider turbidity
levels in future river flow regime for only SRES
A2 scenario at Baddegama (6°11'23" N,
80°11'53" E), intake point to the drinking water
treatment plant.
4.2
Projected Changes in Turbidity
Year 2020 TSS loads were modelled on daily
basis using the TSS load-discharge model
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Year 2020 monthly turbidity values (75th
percentile) show an increase during May to
November, compared to 2001-2004 (Figure 8).
The height of the peak is remarkably increased
in June 2020, and the projected increase in
turbidity is 107% compared to the baseline.
Turbidity increase predicted between May and
November 2020 is 6.5 NTU per month, on
average. These elevated turbidity levels are
clearly evident during the months of increased
streamflow (Figure 9).
Despite the fact that this study considered a
single RCM and two SRES emission scenarios,
future change in hydro-climatological variables
needs to be projected based on outputs from
several different climate models operating
under a variety of scenarios. Taking into
account the climate projection uncertainty
and modelling uncertainties, the predicted
impacts on the hydrological processes and
constituent estimates in the Gin catchment
should be considered as trends and order of
magnitudes rather than exact predictions.
4.3
Comparison of Turbidity Values with
the Water Quality Standards
Turbidity
vs.
streamflow
exceedance
probability shows the range of fluctuation of
turbidity in year 2020 during different flow
regimes in comparison to the water quality
standards (Figure 10). It appears that, 60% of
the time, turbidity levels have indicated
exceedance of the water quality standards set
for the potable water [34] as well the inland
waters [35] of Sri Lanka. These indicate that the
projected turbidity levels subsequent to flow
regime alterations caused by the anticipated
climate and land use change, appear to be more
prominent
at
intermediate
to highest
streamflows. Exceedances are greatest during
the highest flows. It will be challenging to deal
with the year 2020 turbidity levels projected to
occur during the highest flows (>110 m3/s),
requiring
more than 90% remarkable
reductions to comply with the water quality
standards.
50
45
Highest
flows
High flows
Turbidity (NTU)
Low flows
35
30
25
20
15
10
8
5
2
0
0
10
20
30
40
50
60
70
80
90
100
Percentage of time Streamflow was equaled or exceeded
Highest desirable level (2 NTU) for the potable water [34]
Maximum permissible level (8 NTU) for the potable water
[34]
Maximum permissible level (5 NTU) for inland waters of Sri
Lanka (CLASS 1 Waters - Drinking water with simple
treatment) [35]
Figure 10 - Turbidity
exceedance probability.
vs.
The tools and methods used in this study could
be effectively applied in carrying out impact
studies in similar catchments.
streamflow
Fully assessing the direct impacts of climate
and land use change on river water quality is
beyond the scope of this study. Further
researches to determine such direct impacts are
Highest flows > 110 m3/s; High flows > 30 m3/s;
Intermediate flows > 17 m3/s; Low flows > 4.5 m3/s;
Lowest flows > 3.7 m3/s
ENGINEER
ENGINEER
Conclusions
This research provides important insight into
possible alterations in turbidity levels in Gin
River, the primary drinking water source in
Southern region of Sri Lanka, following
variations in future river flow under projected
land use and climate change. Study revealed
that fluctuations of constituents have been
much more strongly related to streamflow
changes, thus year 2020 flow regime alterations
under SRES A2 will greatly elevate the
turbidity levels in the Gin River compared to
the water quality criteria. Remarkable increase
in turbidity levels during the months of June
and November in year 2020 would require
significant reductions to comply with the
drinking water quality standards, which would
lead to exert extra pressure on future drinking
water production in Southern region of Sri
Lanka. Understanding on these excessive
amounts of constituents anticipated in future
river water might be useful for water managers
and planners to adjust operations accordingly
at the water treatment plants. Moreover,
findings of the study could be vital for Sri
Lanka‟s water resources planning efforts
aiming to achieve 100% safe drinking water
supply by year 2020. However, the results
presented in this study should be viewed as
trends and order of magnitudes rather than
exact predictions, considering the uncertainties
associated with future climate projections and
modeling approaches adopted.
Lowest
flows
Intermediate
flows
40
5.
8
68
suggested using a more physically based
modelling approach.
Solids and Fecal Coliform Bacteria Loads in Real
Time”, Proc., Seventh Federal Interagency
Sedimentation Conference, March 25–29, 2001,
Reno, NV, Subcommittee on Sedimentation, Vol.
1, 2001, pp. III-94 to III-101.
Acknowledgements
Authors are grateful to UK Met Office Hadley
Centre for providing climate projections.
National Water Supply and Drainage Board
(Southern),
Sri
Lanka
is
gratefully
acknowledged for providing water quality data
of Gin River and for facilitating water quality
testing. Sincere appreciation is extended to
University of Yamanashi, Japan and Japan
Society for Promotion of Science (JSPS) for
technical and financial support for the study.
7. Corporate Plan 2012-2016, National Water Supply
and Drainage Board, Ministry of Water Supply
and Drainage, Sri Lanka, 2012.
8. Wickramaarachchi, T. N., Ishidaira, H., Magome,
J., & Wijayaratna, T. M. N., “Impact of future flow
regime alterations on iron load occurrence in Gin
River, Sri Lanka”, Journal of Japan Society of Civil
Engineers, Ser. B1 (Hydraulic Engineering),Vol. 70,
No. 4, 2014, pp.I_127-132.
9. Wickramaarachchi, T. N., Ishidaira, H., &
Wijayaratna, T. M. N., “Projecting land use
transitions in the Gin Catchment, Sri Lanka”,
Res. J. Environ. Earth. Sci., Vol.5, No. 8, 2013,
pp.473-480.
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Vol.XLVIII,
XLVIII,No.
No.01,
01,pp.
pp.
[page range],
ENGINEER -- Vol.
[71-81],
2015 2015
©
The Institution
InstitutionofofEngineers,
Engineers,
Lanka
© The
SriSri
Lanka
Coastal Investigations for Sustainable Development of
Fisheries Infrastructure
A. H. R. Ratnasooriya and S. P. Samarawickrama
Abstract:
Plans have been formulated by the government to increase the fish production and the
national targets indicate significant increases in marine fisheries production. The expansion of the
marine fishing fleet and the development of appropriate fisheries infrastructure for the operation of
such craft would play a vital role in achieving the future targets for fish production. A number of
studies were thus conducted to assess the feasibility of developing sustainable fisheries infrastructure
in various parts of the country. The attention in these investigations was mainly focussed on related
coastal engineering aspects in order to minimise the adverse impacts on the facility as well as the
neighbouring coastline to ensure the sustainability and effectiveness of any proposed development.
Attempts were made to assess, qualitatively, the exposure of the sites to the nearshore wave climate
and the resulting coastal processes related to sediment (sand) transport in the vicinity. The forms of
coastal constructions required were identified and the severity of potential impacts due to such
developments was considered to assess the suitability of the sites for potential development. The
details of selected investigations conducted in eastern, northern, south-western and southern regions
are presented and the recommendations are elaborated.
Keywords: Coastal, Fisheries Infrastructure, Sustainable Development.
1.
Introduction
Plans have been made by the Ministry of
Fisheries and Aquatic Resources to increase
the fish production and the national fish
production
targets
indicate
significant
increases in marine fisheries production. The
expansion of the marine fishing fleet and the
development
of
appropriate
fisheries
infrastructure facilities for the operation of
such crafts would thus play a vital role in
achieving the future targets for fish
production.
Fisheries activities are carried out along almost
the entire coastline of Sri Lanka extending over
1,600 km. A large coastal population is
engaged in fisheries activities and, with more
than 250,000 active fishermen [7], the fisheries
sector forms an important part of the national
economy. It accounted for 1.8 % of the Gross
Domestic Product of the country in 2013 [7].
Marine fishing, dominating the fisheries sector,
contributes to more than 85 % of total fish
production [7] and is carried out by a variety
of fishing crafts. These include smaller fishing
crafts-Beach Seine Boats (NBSB), NonMotorized
Traditional
Boats
(NTRB),
Motorized
Traditional
Boats
(MTRB),
Outboard Motor Fibre Reinforced Plastic Boats
(OFRP) and larger fishing crafts-One Day
Boats with Inboard Engines (IDAY) and Multi
Day Boats (IMUL)(Figure 1). The total marine
fishing fleet exceeded 53,000 crafts in 2012 [7]
and is based in various fishery infrastructure
facilities in the form of Fishery Harbors,
Anchorages and Landing Sites along the
coastline of the country. Smaller fishing boats
are generally concentrated at a large number
of Landing Sites scattered along the coastline.
The IMUL Boats and IDAY Boats are generally
based at various Fishery Harbors and
Anchorages. In 2012, 19 Fishery Harbors and
many Anchorages were in operation [6].
Figure 1 - Different Types of Fishing Crafts
Eng. A. H. R. Ratnasooriya, AMIE(Sri Lanka),
B.Sc.Eng.(Hons) (Moratuwa), M.Phil (Moratuwa), Senior
Lecturer, Department of Civil Engineering, University of
Moratuwa, Sri Lanka.
Eng. (Prof.) S. P. Samarawickrama, C. Eng., MIE(Sri
Lanka), B.Sc.Eng.Hons.(Moratuwa), PhD(London), DIC,
Professor, Department of Civil Engineering, University of
Moratuwa, Sri Lanka.
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Fisheries activities in the northern and eastern
regions of the country were severely affected
by the conflict that prevailed in the area for
nearly three decades, but have recommenced
and expanded since the end of the conflict in
2009. Many of the fisheries infrastructure
facilities in these regions are in a dilapidated
state and are in need of restoration and
expansion. A number of studies were thus
conducted recently, during the period 20092011,to assess the feasibility of developing
sustainable fisheries infrastructure in various
parts of the country.
severity of potential impacts due to such
developments was considered to assess the
suitability of the sites for potential
development.
3.
The fisheries infrastructure facilities provide
essential shelter for mooring and/or beach
landing and loading/unloading activities of
fishing crafts and shore facilities for related
support activities. Fishery Harbors mainly
cater for the requirements of larger fishing
crafts and such facilities usually consist of a
basin area of sufficient size and depth usually
protected by breakwaters, quay walls to
facilitate loading/unloading operations and
shore facilities for other related activities.
Fishery Anchorages and Landing Sites mainly
cater for the requirements of smaller fishing
crafts but larger crafts could also use such
facilities depending on the depths in the
mooring areas. These facilities usually consist
of a sheltered basin with natural or breakwater
protection for safe mooring and shore facilities
for other fisheries related activities.
In this paper, the methodology adopted in the
investigations is presented first, which is
followed by a discussion of coastal aspects
associated
with
fishery
infrastructure
development. The details of coastal aspects,
nearshore wave climate and coastal sand
transport and shoreline behaviour, are then
presented. After a discussion on shoreline
response to coastal constructions in general,
the details of investigations conducted at four
locations in different parts of the country are
presented. The recommendations made by the
investigations are then summarized under
concluding remarks.
2.
The level of coastal infrastructure requirement
to provide the necessary protection is closely
related to the nearshore wave climate of the
area. Depending on its severity, the
requirement may vary from enhancing the
natural shelter provided by features such as
headlands and reefs to full breakwater
protection.
Method of Investigations
The investigations were conducted at the sites
for which improved facilities were requested
by the local fishing communities, relevant
authorities or other stakeholders. The attention
in these investigations was mainly focussed on
related coastal engineering aspects in order to
minimise the adverse impacts on the facility as
well as the neighbouring coastline to ensure
the sustainability and effectiveness of any
proposed development. In addition, socioeconomic aspects, space requirements for
shore facilities and other aspects related to the
development of fishery infrastructure facilities
were also considered in these investigations.
The coastal areas of the country are
predominantly sandy beaches and the
construction of fisheries infrastructure in the
form of breakwaters, jetties etc could cause
alterations in sand movement patterns of the
area. Such alterations could lead to adverse
impacts in the form of coastal erosion and/or
accretion in the area as well as siltation in the
sheltered area, raising concerns related to the
sustainability and the effectiveness of the
development.
In the absence of recorded coastal engineering
information (primary data) at many of the
locations considered, investigations were
mainly based on field studies, analysis of
available secondary information and local
knowledge gathered through local community
consultations. Attempts were made to assess,
qualitatively, the exposure of the sites to the
nearshore wave climate and the resulting
coastal processes related to sediment (sand)
transport in the vicinity. The forms of coastal
constructions required were identified and the
ENGINEER
Fisheries Infrastructure and
Coastal Aspects
4.
Nearshore Wave Climate
The wave climate in the coastal waters of
Sri Lanka is characterized by two wave
systems, the swell and the monsoonal waves.
The resultant wave climate inclines towards
the more dominant system. The swell,
approaching
from
southerly
direction
2
72
throughout the year, is characterized by waves
of relatively large periods and low amplitudes.
The monsoonal waves are characterized by
waves of relatively smaller periods and higher
amplitudes. Two monsoonal periods are
dominant-the south-west monsoonal period
from May to September and the north-east
monsoonal period from November to March.
The coastal areas extending from the western
region to the south-eastern region are directly
exposed to the swell as well as the more
dominant south-west monsoonal waves. The
rest of the coastal areas are less exposed to the
swell and sheltered from the south-west
monsoonal waves. The coastal areas extending
from the northern region to the south-eastern
region are mainly exposed to the refracted
swell and relatively less severe north-east
monsoonal waves. The north-western coastal
region is relatively well protected from these
wave systems. The presence of sand bar
formations along the Adam‟s Bridge, shallow
depths and the shelter provided by the Jaffna
Peninsula and the land masses of the islands
located on the western side of the peninsula
have restricted the penetration of waves into
the north-western coastal waters in the Palk
Bay area.
5.
of the diverse features in
environment of the country.
the
coastal
Seasonal erosion and the steepening of the
beaches during the monsoonal periods is also a
common characteristic in many of the beaches
in the country. Offshore movement and
deposition of beach sand take place during
these periods mainly due to the action of
monsoonal waves. Beach recovery due to
onshore movement of sand under the swell is
apparent during the non-monsoonal periods.
6.
Coastal Constructions and
Shoreline Response
The stability of the shoreline can be assessed in
terms of the „sand budget‟ of a coastal cell
considered in the area of interest. Coastal
erosion and accretion can be considered in
terms of sand imbalance due to changes in
inflow and outflow rates. Such imbalances
caused by the disturbances to the longshore
transport have been identified as a major cause
for erosion.
Coastal constructions, in the form of groynes,
jetties or breakwaters could cause disturbances
of
longshore
sand
transport.
Such
constructions in areas of high level transport
could lead to severe impacts associated with
erosion, accretion and siltation. These impacts
have become apparent in recent coastal
infrastructure developments of Kirinda
Fishery Harbor, Oluvil Port/Fishery Harbor
and the Wadduwa Loading Out Point. The
mitigation of the resulting adverse impacts
would usually involve the structural
interventions in the form of series of groynes
or offshore breakwaters or other interventions
such as sand nourishment,all of which would
require substantial expenditure.
Coastal Sand Transport and
Shoreline Behaviour
Nearshore currents, both longshore and
on/offshore, generated by the interaction of
the approaching waves with the sea bed and
the resulting coastal processes of refraction,
breaking etc, are the main causes of sand
transport in coastal areas. In Sri Lanka, studies
conducted have revealed a general trend of net
sand movement northwards along the southwestern and western coasts, eastwards along
the southern and northwards along the southeastern and southerly parts of the eastern
coastline during the south-west monsoon.
During the north-east monsoon, a general
trend of sand movement southwards along the
eastern, south-eastern and western coastlines
and westwards along the southern coastline
has been revealed.
It is evident from these considerations that the
assessment of the level of sand transport
processes in a locality would play a vital role
in identifying the suitability of sites for
fisheries infrastructure development with
coastal constructions. The infrastructure
developments at such locations would cause
relatively low levels of adverse impacts
leading to the long term sustainability and
effectiveness of the facilities.
However, the longshore sand transport rates
depend on a number of factors including wave
characteristics (height, period, angle of
approach
etc),
bathymetric
features
(influencing refraction, breaking etc) and
beach characteristics (geometry, size and
availability of sand etc). Significant local
variations of these factors are apparent in view
Mathematical modelling techniques supported
by detailed records of measured coastal data
can be used for a more quantitative assessment
of the level of coastal and transport and
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potential impacts of coastal constructions (in
spite of the limitations in simulating complex
coastal phenomena associated with sediment
transport). However, due to the absence of
relevant primary data and other constraints,
the investigations were mainly based on field
studies and analysis of available information
of shoreline behaviour with the deductions
confirmed
through
local
community
consultations whenever possible. The details of
such investigations conducted at the locations
listed below and shown in Figure 2 are
presented.
i.
Vakarai Area on the Eastern Coast
ii.
Point Pedro Area on the Northern Coast
of Jaffna Peninsula
iii.
Galbokka on the South-WesternCoast
iv.
Suduwella on the Southern Coast
the attention focused on the possibility of
constructing coastal structures required in the
form of jetties, groynes, quay walls,
breakwaters etc.
Figure 3 - Location of Vakarai Central
(Source of Image: Google Earth Website)
As indicated, the site is located at the outlet of
a lagoon near the centre of a coastal cell
formed by two natural headlands. The coastal
area is characterised by wide sandy beaches
and sand deposits in shallow areas of the
lagoon near the outlet and a wide sand bar
across the outlet. The sand bar blocks the
outflow from the lagoon but breaches during
the north-east monsoon to release flood
waters. Once breached, the outlet remains
open for a few months. Marine fishing is
carried out in the area by a large number of
smaller crafts which are usually beach landed
in the vicinity. Due to shallow depths in the
channel through the breached sand bar, only
the smaller crafts are able to access the
sheltered areas in the lagoon for mooring
purposes. Lagoon fishing is carried by a large
number of smaller fishing crafts. Beach seine
fishing is also carried out in the sandy beaches
of the area.
(ii)
(i)
(iii)
(iv)
Figure 2 - Locations of Investigations
7.
The site is located away from the areas
sheltered by the headlands and is seasonally
exposed to both swell and north-east
monsoonal waves as indicated in Figure 3.
Significant seasonal variations of coastline
positions and steepening of beaches indicate
high level of longshore and on/offshore
sediment transport in the vicinity. In spite of
small tidal range in coastal waters of the
country, a potential exists for ebb and flood
tidal currents through the channel across the
breached
sand
bar
formation
with
accompanying sediment transport patterns.
Significant variations in the form of the outlet
and the lagoon sand deposits in the vicinity
were also evident. The abundance of sand and
the dynamic and complex nature of coastal
processes and the high level of sediment
Investigations in Vakarai Area on
the Eastern Coast
7.1 Investigations in Vakarai Central
Vakarai, with a significant fishing community,
is located between Valachchenai and
Trincomalee in an area where no Fishery
Harbor or Anchorage facilities are located [2].
With expanding fisheries activities since 2008,
a proposal has been made to develop a Fishery
Harbor/Anchorage facility in the area to meet
the emerging needs of fisheries sector. Vakarai
Central has initially been identified for this
purpose. The location of Vakarai Central is
shown in Figure 3. Investigations were
conducted with the objective of assessing the
feasibility of developing appropriate fisheries
infrastructure facilities at this location, with
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74
activity in the vicinity became clearly evident
by the investigations.
the site in Palachanai was identified as the
most suitable site for development.
Coastal constructions in the form of jetties or
breakwaters in such dynamic coastal
environments would most likely lead to high
levels of adverse impacts. These impacts in the
form of severe erosion/accretion and siltation
due to the disturbance caused to natural
transportation processes could also affect the
nearby beach seine and beach landing
operations. Any structural interventions,
usually in the form of groynes, to maintain an
uninterrupted lagoon outlet throughout the
year in order to provide mooring facilities for
fishing crafts in the lagoon, are also likely to
cause similar impacts leading to issues
concerned
with
effectiveness
and
sustainability of the development. The changes
in mixing patterns of sea water in the lagoon
due to such interventions could severely affect
the fishing activities and ecological aspects
associated with the lagoon. In view of these
considerations, the site in Vakari Central was
not recommended for fishery infrastructure
developments in the form of Fishery Harbors
or Anchorages.
Figure 4 - Alternative Locations of
Investigations
(Source of Image: Google Earth Website)
7.3
Investigations in Palachanai
Palachenai is located in a bay formed between
two headlands, next to the northern headland
formed by a rocky formation extending into
the sea, as shown in Figure 5(a).
7.2
Investigations in Alternative Sites
In view of the complexities involved with the
site identified in Vakarai Central and the need
to develop
Fishery
Harbor/Anchorage
facilities in the Vakarai area, the possibility of
selecting an alternative site was also explored.
Investigations were thus conducted at a
number of locations in the area. These sites,
functioning as landing sites with minimal
facilities, had been identified by fishery sector
authorities to explore the possibility of further
development. The locations are listed below
and shown in Figure 4.
Northern Headland
Palachenai
Bay Area
Southern
Headland
i
ii
Kathiraweli
Mahaweli River Outlets (North of
Kathiraweli)
iii Palachenai
iv Kandalady
v
Vakarai
vi Panichankerny
vii Pethalai
(a)
Northern Headland
Palachenai
Investigations, similar to those conducted at
Vakarai Central, were conducted for these sites
as well in order to assess the potential for
development of fisheries infrastructure. Based
on a comparative evaluation of the level of
potential for development at these locations,
Rocky Formation
(b)
Figure 5 - Location of Palachenai
(Source of Images: Google Earth Website)
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8.
The site is partially sheltered by the rocky
headland from north-east monsoonal waves.
Northward sand transport is also curtailed by
the headland as evident by the small scale
seasonal coastal erosion on its northern side.
The bay extends over a length of
approximately 3.5 km and no large water
bodies drain into the bay area. A small rocky
formation, shown in Figure 5(b), exists at
approximately 750 m from the northern
headland. It restricts sediment movement and
forms a smaller coastal cell in the vicinity of
Palachenai. Even if a reasonable level of
sediment activities is envisaged in the larger
bay area, sand movement in the vicinity of
Palachenai could be restricted due to the
possible trapping of sediments at this rocky
formation.
Prior to the conflict that prevailed in the
region, Jaffna Peninsula had been one of the
most productive fishing regions in the country.
Its contribution to the national fish production
had declined since mid-1980s due to the
disruptions caused to the fisheries activities by
the conflict[3],[4]. The fishery infrastructure
facilities in the region are in a dilapidated
state, due to damages caused by the conflict
and years of neglect and are in need of
restoration and development. Since the end of
the conflict in mid-2009, the fishing sector in
the northern region has shown signs of
recovery with increased fish production. The
fishing fleet in the area, soon after the end of
the conflict, consisted of only smaller boats. In
spite of the potential for offshore fishing by
larger boats, such boats were not in operation
due to the restrictions imposed by security
conditions and the absence of adequate
facilities in the region. However such boats
have recently commenced operations and a
need exists for the development of appropriate
fisheries infrastructure facilities. Point Pedro
region had been one of the most productive
fishing areas in the peninsula [3],[4] and
investigations were conducted to assess the
potential
for
fishery
infrastructure
development in the area. The investigations
were conducted in the Divisional Secretary
(DS) Division of Point Pedro (Vadamarachchy
North).
Based on these considerations, the site at
Palachenai was identified as suitable for
fishery infrastructure development. The
existence of rocky outcrop providing natural
protection during the north-east monsoonal
period and a smaller bay area giving a
relatively low level sand movement are the
positive factors for such a development. The
construction of a fishery infrastructure facility
is unlikely to aggravate coastal erosion on the
northern side of the headland. However, a
small scale coast protection scheme can also be
recommended together with any fishery
infrastructure development. The conceptual
layout of a fisheries infrastructure facility
shown in Figure 6 was proposed for further
investigations.
Sheltered
Basin
Investigations in Point Pedro
Area on the Northern Coast of
Jaffna Peninsula
Breakwater
Groyne
Figure 7 - Area of Investigations in
Point Pedro
Figure 6 - Conceptual Layout of Proposed
Development
(Source of Images: Google Earth Website)
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8.1 Coastal Characteristics and Fisheries
Activities
a number of naturally sheltered basins in the
area suitable for mooring of fishing craft.
The coastline of the area of investigations
extends from Thondamanaru along the
northern coastline of the peninsula towards
the northeastern edge of Munai and along the
eastern coastline beyond Kathkovalam over a
length of 20 km as shown in Figure 7.
Many of the Landing Sites in Point Pedro DS
Division are located in such basins along this
part of the coastline as indicated in Figure 9.
These include the Landing Sites in
Thondamanaru, Valveddithurai, Athikoviladi,
Polikandy West, Polikandy East, Sakkodai,
Imparsiddy, Suppermadam, Koddady and
Munai. Mainly smaller fishing boats are
operated from these Landing Sites. However,
depending on the depths in sheltered areas
behind the seaward edge of the reef formation,
some of the larger boats, which have become
operational recently are also based in some of
the sites, in spite of the absence of proper
facilities for the operation of such crafts.
The coastline on the eastern side of peninsula
is directly exposed to north-east monsoonal
waves and difficulties in mooring/beach
landing of fishing boats are experienced by the
fishing communities. As a result, relatively a
lesser number of Landing Sites are located
along this coastline. A wide, straight, sandy
coastline exists in the area and investigations
revealed significant seasonal variations of the
beach profile indicating level of sediment
transport. Under such dynamic conditions of
the coastline, construction of coastal structures
is likely to cause coastal erosion/accretion
problems and such constructions without
extensive
investigations
were
not
recommended.
The coastline along the northern side of
peninsula in Point Pedro is characterized by
rocky/sandy beaches and a reef formation
located close (< 300 m approximately from the
coastline) and parallel to the coastline as
shown in Figure 8.
Figure 9 - Landing Sites along Northern
Coastline in Point Pedro Area
(Source of Image: Google Earth Website)
8.2
Current Status of Fisheries
Infrastructure and Recommendations
The Indian Ocean Tsunami in 2004 has caused
significant damages to the reef formation
along the northern coast and spreading of
broken rock in sheltered basins has caused
difficulties in using the Landing Sites due to
reduced depths and partial blockage of access
channels. The cyclone in 2008 has caused
further damages and significant hardships are
experienced by fishing communities due to the
dilapidated state of many of the facilities.
Attempts have been made to rehabilitate the
facilities by clearing the basin areas and access
channels to facilitate navigation and mooring
of boats with varying degree of success.
(a)
(b)
Figure 8 - Northern Coastline: Point Pedro
Area
The improvement of fisheries infrastructure at
Landing Sites, for the operation of mainly the
smaller fishing crafts, in the area could
generally be achieved by strengthening the
natural protection provided by the reef
formation. Raising the crest level of reef
formation and strengthening of its seaward
slope with the use of larger armour may be
needed to provide effective protection.The
(Source of Images: Google Earth Website)
Although the coastline, by its orientation, is
potentially exposed to north-east monsoonal
waves, protection against coastal erosion due
to wave action is provided by the reef
formation along most of the coastline. The
presence of reef formation has also resulted in
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9.
clearing of scattered rocks from the access
channels and sheltered basins would also be
needed. Deepening of access channels and the
basins may also be required at some of the
sites. In such situations, due attention needs to
be paid for any adverse environmental issues
associated with dredging of reef formations. A
possibility also exists for the use of excavated
and cleared material for the use in the
strengthening of protection measures.
An investigation was conducted to assess the
feasibility of developing a Fishery Landing Site
in Galbokka in Rathgama in the Galle District.
The site had been identified based on the
availability of land to develop shore facilities
due to the relocation of a school severely
damaged by the Indian Ocean tsunami in 2004
[5]. The location of the site is shown in Figure
11.
In addition, a socio-economic need also exists
for
the
development
of
appropriate
infrastructure facilities, in the form of a Fishery
Harbor or Anchorage, to cater for operations
of larger fishing crafts. The only Fishery
Harbor facility in Jaffna Peninsula is located in
Myliddy on the northern coast of the peninsula
to the west of Point Pedro. Fishery activities
are not currently carried out at Myliddy. Even
if it is operational, the potential exists for other
Fishery Harbor developments in the region,
mainly due to the relatively smaller size of the
harbor basin in Myliddy which may not be
capable of meeting the needs of the expanding
fleet of larger fishing crafts in the area. In view
of these considerations, recommendations
were made for the development of a Fishery
Harbor/Anchorage facility in Point Pedro area
at an appropriate location, to be identified
based on socio-economic, environmental and
coastal
engineering
considerations.
Appropriate protection measures, usually in
the form of breakwaters would be required in
such a development to provide a sheltered
basin of adequate extent and depth against
north-eastern monsoonal waves. A typical
conceptual layout in the form of that shown in
Figure 10 can be recommended for such a
development. No severe adverse impacts
associated with coastal erosion are envisaged
due to such a development in view of the
protection provided by the coastal reef
formation in the area.
Figure 11 - Proposed Site in Galbokka
(Source of Image: Google Earth Website)
The site is located in a wide sandy beach next
to a rock outcrop as shown in Figure 11. From
the rock outcrop, the beach extends
uninterrupted for a few kilometres in the
direction of Dodanduwa.
The investigation revealed a significant
seasonal variation in the beach, in the order of
up to 40 m in the vicinity of the project site,
indicating high level of sediment activity. A
beach profile with a steep gradient is formed at
the site during the southwest monsoon, which,
together with adverse wave conditions, makes
it difficult for landing/mooring of fishing
crafts. Due to the orientation of the beach at
the site, as indicated in Figure 11, it is directly
exposed to the south-west monsoonal waves
and no sheltering effect is provided by the rock
outcrop.
In view of the exposed nature of the site, it is
evident that appropriate costal structures are
required in any proposed development to
provide a safe mooring and landing
environment at the site. The layout of such
structures will depend on local bathymetric
and wave conditions but, based on the site
conditions observed and considerations of
exposure and protection requirements, a
conceptual layout in the form of that shown in
Figure 12 can be identified for further
investigations.
Figure 10 - Conceptual Layout of Proposed
Development
(Source of Image: Google Earth Website)
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Investigations in Galbokka on the
South-western Coast
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Fishery infrastructure facilities are usually
developed in locations with a certain degree of
natural protection and lower levels of
sediment movement. The developments
enhance the natural protection while causing
minimum disturbances to sediment transport
patterns to limit the adverse impacts in
surrounding areas.
The sandy beach at the site extending from the
outcrop is interrupted by another smaller
outcrop nearby (Figure 12) forming a smaller
coastal cell in which relatively lesser extent of
sediment movement is apparent. The larger
outcrop provides partial protection from
south-west monsoonal waves which can be
enhanced by a coastal structure extending
from the outcrop as shown in Figure 12.From a
coastal engineering point of view, it is
apparent that this site is more suited for
development of fisheries infrastructure but,
similar to the proposed site, detailed
investigations are required to assess the
development potential in detail.
10 Investigations in Suduwella on
the Southern Coast
Suduwella in Kottegoda Bay was a Landing
Site in the Matara District [1]. The expansion of
fishing operations into deep sea with larger
fishing crafts has led to the need to provide
adequate infrastructure facilities for safe
mooring and loading and unloading
operations of such crafts operated in the area.
The Kottegoda Bay (Figure 13) bounded by
two headlands and facing southeasterly
direction, had been identified as a suitable
location for such a development. The southern
part of the bay, Suduwella, (Figure 13) is
relatively sheltered due to partial protection
provided by the southern headland against
south-west monsoonal waves. However, wave
breaking and overtopping on a shallow steep
faced reef, located closely and to the northeast
of the southern headland, have resulted in an
offshore directed current which has adversely
affected the in and out navigation as well as
mooring of larger fishing crafts within the area
sheltered by the rocky outcrop. Due to shallow
water depths, navigational difficulties and the
absence of shore facilities, loading and
unloading activities of larger fishing crafts
were carried out away from the shore using
smaller boats during the period of
investigations in 2009.
Figure 12 - Conceptual Layout(s) for Further
Investigations
(Source of Image: Google Earth Website)
The costs associated with developing the
facilities and providing impact mitigation
measures can be kept relatively low by
selecting
appropriate
locations
for
development.
However, no such natural protection exists at
the site in Galbokka, located in a sandy beach
with high levels of sediment movement. The
protection for mooring and landing and
loading/unloading operations needs to be
provided entirely by coastal structures which
could disturb the sediment transport patterns
leading to potential coastline changes and
erosion problems. In such a case, coast
protection systems, usually in the form of
groynes, may need to be included in the
overall development plan. In view of these
considerations, it is evident that the costs
associated with any proposed development at
the site proposed in Galbokka are likely to be
significantly higher than the costs involved
with a development of similar nature at a site
with some form of natural protection.
9.1
Investigations in the Alternative Site
In view of the potential adverse impacts
associated with the developments at the
proposed site, as an alternative, the technical
feasibility of another site was investigated. It is
located next to the proposed site on the
opposite side of the rock outcrop, as shown in
Figure 12.
Figure 13 - Location of Suduwella in
Kottegoda Bay
(Source of Image: Google Earth Website)
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The bay had been subjected to severe coastal
erosion over the years which has necessitated
the construction of a long revetment to protect
the coastline. A fragile sandstone reef fronts
the revetment, which is indicative of the severe
loss of sand due to wave action. The only
beach area within the bay exists at the
southernmost corner in Suduwella, within the
shelter of the southern headland.
extending the southern breakwater beyond the
rock outcrop.
In the layout of the Option 2 (Figure 14(b)), a
harbor confined to the southern part of the
bay,
where
fishery
activities
were
concentrated, was conceptualized.
The
proposed harbor area is protected mainly by a
southern breakwater which originates at the
southern headland, connects with the rock
outcrop and extends further in a northeasterly
direction.
The harbor entrance faces the
northeasterly direction and is located in the
gap between a secondary breakwater/groyne
the main breakwater. Neither of these options
had been implemented due various constraints
associated with development. Investigations
were thus conducted to identify a suitable
development option within the constraints
imposed to meet the stakeholder requirements.
After extensive studies, in which attention was
focused on coastal and harbor engineering,
socio-economic and environmental issues, a
conceptual layout, which is a modification of
the Option 2 proposed earlier, was
recommended for detailed design studies.It
wasto be implemented in two stages, if
necessary in view of any financial constraints.
The designs were subsequently carried out
and a Fishery Harbor facility was constructed
(first stage) which is currently in operation
(Figure 15).
Investigations were conducted to assess the
feasibility of developing a Fishery Harbor of
adequate capacity, which should provide safe
navigational access and shelter throughout the
year with minimal maintenance requirements
and adverse environmental impacts.
(a)
Option 1
(b) Option 2
Figure 14 - Development Options for
Suduwella
(Source of Images: Google Earth Website)
Studies had been carried out previously and
two alterative layouts of development, one
contained within the southern part of the bay
and the other incorporating the entire bay, had
been considered for further investigations.
Figure 15 - Suduwella Fishery Harbor
(Source of Images: Google Earth Website)
11. Concluding Remarks
The details of investigations conducted
recently to assess the feasibility of developing
sustainable fisheries infrastructure in various
parts of the country are presented. These
investigations were conducted in Vakari area
on the eastern coast, Point Pedro area on the
northern coast, Galbokka on the south-western
coast and Suduwella on the southern coast. In
the absence of recorded nearshore data at
many of the locations considered, the
In the layout of the Option 1 (Figure 14 (a)), the
entire bay area was incorporated into a harbor
protected by two breakwaters. The entrance
was placed between the large rock outcrop
towards the southern end of the bay and the
head of the northern breakwater to facilitate
the fishing crafts to use the path followed
earlier by the fishermen. It was subsequently
revised to provide safer access conditions by
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80
Lanka by Uni-Consultancy Services, University of
Moratuwa, October 2009.
investigations were mainly based on field
studies, analysis of available secondary
information and local knowledge gathered
through community consultations. Although
socio-economic aspects, availability of land for
shore facilities and other related aspects were
also considered in assessing the feasibility,
attention was mainly focussed on related
coastal engineering aspects to minimise the
adverse impacts on the coastline in order to
ensure the sustainability of the proposed
development. As the investigations in Vakarai
area revealed that the site identified initially is
not favourable for development, based on
further investigations, a location in Palachenai
was identified as more suitable for further
investigations for development. Investigations
in Point Pedro area revealed that many of the
existing Landing Sites can be developed
further by enhancing the natural protection
offered by the reef formation in the area. The
need of a Fishery Harbor/Anchorage facility
for the area was also became evident and the
form of constructions required for such a
facility
was
identified
for
further
investigations. The investigations conducted in
Galbokka revealed the potential for significant
adverse impacts due to coastal constructions at
the site initially identified for development, in
view of which, an alternative site next to it was
identified for further investigations for
development. For the site in Suduwella, an
initially proposed development option was
modified to meet the stakeholder requirements
within
the
constraints
imposed
and
recommended for design studies. These were
subsequently conducted and a Fishery Harbor
facility was constructed which is currently in
operation.
2. Feasibility Study for the Development of Fishery
Harbor/Anchorage at Vakarai in Batticaloa
District, Final Report submitted to United Nations
Office for Project Services (UNPOS) in Sri Lanka by
Uni-Consultancy Services, University of Moratuwa,
January 2010.
3. Fisheries Infrastructure Development in Jaffna
Peninsula, Final Report submitted to United
Nations Office for Project Services (UNPOS) in Sri
Lanka by Department of Civil Engineering,
University of Moratuwa, September 2009.
4. Pre-Feasibility Study for Fishery Harbor
Development in Point Pedro, Jaffna District,
Final report submitted to Japan International
Cooperation Agency (JICA) by Uni-Consultancy
Services, University of Moratuwa, July 2011.
5. Samarawickrama, S. P., “Pre-Feasibility Study
for Proposed Galbokka Landing site at
Rathgama in Galle District for the use of Smaller
Boats”, Final Report submitted to Ceylon Fishery
Harbor Corporation (CFHC), October 2010.
6. http://www.cfhc.lk, Visited 28 April 2014.
7. http://www.fisheries.gov.lk,Visited
April 2014.
Acknowledgement
The authors wish to thank the officials in the
Ceylon Fishery Harbor Corporation (CFHC),
Department of Fisheries and Aquatic
Resources(DFAR), United Nations Office for
Project Services (UNPOS) in Sri Lanka and
Japan International Cooperation Agency(JICA)
for providing assistance to conduct the
relevant
investigations
on
fisheries
infrastructure development.
References
1. Feasibility Study for the Development of Fishery
Harbor/Anchorage at Suduwella, Kottegoda,
Matara District, Interim Report submitted to United
Nations Office for Project Services (UNPOS) in Sri
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VOL: XLVIII,, No. 01
January 2015
ISSN 1800-1122
VOL: XLVIII,, No. 01
Printed by Karunaratne & Sons (Pvt) Ltd.
January 2015
ISSN 1800-1122