Title: Modelling of Cascade Dams &
Reservoir Operation for Optimal Water Use:
Application to the Omo River Basin,
Ethiopia
Supervisor
Prof. Dr. rer. nat Manfred Koch (Uni-Kassel)
Dr. Yilma Sileshi (AAU, Ethiopia)
November 09, 2012
Kassel, Germany
Outline
1. Background
2. Study Area
3. Objectives
4. SDSM application
5. SWAT Model
6. HEC-ResSim Model
7. References
Modeling of Cascade Dams & Reservoir Operation
1. Background
• Over 45 000 times in the last century, people took
the decision to build a dam.
• Dams were built to provide water for irrigated
agriculture, domestic or industrial use, to generate
hydropower or help control floods (WCD, 2000).
• Hydroelectric power dams currently provide 19% of
the world’s electricity supply.
• Worldwide, water demands have roughly tripled
since 1950, & dams have helped satisfy that
demand.
• Contribute directly to 12–16% of the global food
production (WCD, 2000).
Modeling of Cascade Dams & Reservoir Operation
Background cont...
• In relation to constructed dams, Africa contains
some of the world’s largest dams (e.g., Owen Falls
(Uganda), Kariba (Zimbabwe) & Aswan High
(Egypt). (ICOLD, 2003).
• Furthermore, Ethiopia has 13 hydropower dams
and out of these ten were completed & three are
under construction.
• According to 2005 plan of EEPCo, when the 3
dams complete, the capacity of the hydropower
will increase to the capacity of 3,125 MW which
will satisfy the electricity demand of the country.
Modeling of Cascade Dams & Reservoir Operation
Background cont...
• On the contrary, dams have considerable
influence on d/s river ecosystems, in many cases
extending for hundreds of kilometers below a
dam.
• One of the problem encountered for the Ethiopian
Gov’t has been opposition from International
River (IR)-People-Water-Life in the construction
of Gibe dam III in Omo river which will expect
catastrophic effect on the d/s users & ecosystem.
Modeling of Cascade Dams & Reservoir Operation
Background cont...
• To take account of this problem the WCD called for
a more equitable distribution of the benefits to be
gained from large dams & proposed the inclusion
of all identified stakeholders in the planning &
management of water resources stored in a
reservoir (WCD, 2000).
• To achieve this, dams & reservoirs operation must
take into account the availability of the water
resource in the basin, water uses u/s & d/s of the
dam & must give consideration to political,
organizational, social & environmental factors, as
well as economic factor (McCartney & Acreman,
2001).
Modeling of Cascade Dams & Reservoir Operation
Background cont...
• Hence,
1. New strategies for effective use of the water in the
basin particularly in the Omo River basin will be
needed for water development & management to
avert water scarcities that could depress d/s users
& damage the environment.
2. A large share of water to meet new demands must
come from water saved from existing uses through
a comprehensive reform of water policy.
3. Integrated management must be the primary
approach
to
addressing
sustainable
water
resources, both for subsystem & river basin level.
Modeling of Cascade Dams & Reservoir Operation
2. Study Area
• The Omo-Gibe River Basin
is almost 79,000 km2 in
area
• The basin lies longitude
4°30'N - 9°30'N & latitude
35°0'E - 38°0'E, altitude
of 2800masl.
• The general direction of
flow of the river is
southwards towards the
Omo River/Lake Turkana
Trough, a fault feature.
Modeling of Cascade Dams & Reservoir Operation
3. Objective of Research
Main objective
• The purpose of this study is to model
cascade dams & reservoirs operation in the
Omo river basin to satisfactorily simulate the
operation of dams & reservoirs for optimal
water use.
Modeling of Cascade Dams & Reservoir Operation
Specific objectives
The specific objectives of the proposed study are
To simulate runoff & inflow to the reservoirs in the
Omo river basin using the SWAT model.
To develop & recommend optimal dam & reservoir
operation rule curves for cascade dams &
reservoirs, more soundly based on evaluating the
feasibility
of
various
reservoir
operating
alternatives.
To evaluate the effects of various reservoir
operating alternatives on either preventing flooding
or avoiding precarious low flow at locations d/s of
the reservoirs.
Modeling of Cascade Dams & Reservoir Operation
Hydrological & Hydraulic Situation
in the Omo River Basin
Modeling of Cascade Dams & Reservoir Operation
GIBE-I
Modeling of Cascade Dams & Reservoir Operation
GIBE-II
Modeling of Cascade Dams & Reservoir Operation
GIBE-III
Modeling of Cascade Dams & Reservoir Operation
GIBE-IV
Modeling of Cascade Dams & Reservoir Operation
GIBE-V
Modeling of Cascade Dams & Reservoir Operation
.
Lake Turkana
Modeling of Cascade Dams & Reservoir Operation
4. The Statistical DownScaling Model:
application to filling and forcasting
Metrological data
4.1 Introduction
• The Statistical DownScaling Model (SDSM) is a
freely available tool that produces high
resolution climate change scenarios.
• Downscaling is a technique by which properties
of the free atmosphere are used to predict local
meteorological conditions.
• The large-scale information may originate from
systematic weather observations or from climate
model outputs.
Modeling of Cascade Dams & Reservoir Operation
SDSM cont....
• This freely available software enables the
production of climate change time series at
sites for which there are sufficient daily data
for model calibration, as well as archived
General Circulation Model (GCM) output to
generate scenarios.
• SDSM can also be used as a stochastic
weather generator or to infill gaps in
meteorological data.
Modeling of Cascade Dams & Reservoir Operation
Objective
• To filling and forecasting Rainfall and
Temperature data for Omo Metrological
Stations
Modeling of Cascade Dams & Reservoir Operation
Methdology
• The structure and operation of SDSM has seven
tasks to infill and generate data. These are:
1. Quality control and data transformation;
2. Screening of potential downscaling predictor
variables;
3. Model calibration;
4. Generation of ensembles of current weather
data using observed predictor variables;
5. Statistical analysis of observed data and
climate change scenarios;
6. Graphing model output;
7. Generation of ensembles of future weather data.
Modeling of Cascade Dams & Reservoir Operation
RESULT
Modeling of Cascade Dams & Reservoir Operation
Modeling of Cascade Dams & Reservoir Operation
1.1.00
1.1.99
1.1.98
1.1.97
1.1.96
1.1.95
1.1.94
1.1.93
1.1.92
1.1.91
1.1.90
1.1.89
1.1.88
1.1.87
1.1.86
1.1.85
1.1.84
1.1.83
1.1.82
1.1.81
1.1.80
1.1.79
1.1.78
1.1.77
1.1.76
1.1.75
1.1.74
1.1.73
1.1.72
1.1.71
1.1.70
Precipitation (mm)
Asendabo Station-Precipitation Unfilled &
filled data chart
Asendabo PCP Time Series Chart
100
Unfilled
PCP
80
60
40
20
0
Statistical Analysis using Mean, Variance,Sum
& pdf plot of unfilled & Filled Precipition data
Asendabo Precipitation Bar Chart
Asendabo Precipitation Bar Chart
PREC_unfilled
PREC_Unfilled
PREC_Filled
PREC_Filled
13
13
0
0
418
418
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Dec
Asendabo PDF Chart
Asendabo Precipitation Bar Chart
AsendaboObsPCPunfilled.dat
Mean
PREC_unfilled
10000
10000
PREC_Filled
205
205
0
0
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
0
x axis label
Dec
Modeling of Cascade Dams & Reservoir Operation
Generated Precipitation data from 2001-2040
.
Standardised Precipitation Index
PCPNCEP_1970-2000.dat
PCPGCM_2001_2040.dat
5
5
-4
-4
Year
.
Statistical Analysis using Mean, Varience,
Sum & pdf of Observed & Modelled data
.
Observed V Model Mean Precipiritation
Observed Vs Modelled Monthlly Prec Sum
Observed Prec
Model Prec
Observed Prec Sum
12
12
Modelled Prec Sum
347
0
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
347
0
Dec
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Asendabo Prec PDF Chart
AssendaboObsPrec.dat
Observed Vs Simulated Prec Varience
Mean
10000
10000
Observed Variance
Modelled Variance
239
239
0
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
0
0
Dec
x axis label
Modeling of Cascade Dams & Reservoir Operation
1.1.00
1.1.99
1.1.98
1.1.97
1.1.96
1.1.95
1.1.94
1.1.93
1.1.92
1.1.91
1.1.90
1.1.89
1.1.88
1.1.87
1.1.86
1.1.85
1.1.84
1.1.83
1.1.82
.
1.1.81
1.1.80
1.1.79
1.1.78
1.1.77
1.1.76
1.1.75
1.1.74
1.1.73
1.1.72
60
1.1.71
1.1.70
Temperature Maximum(°C)
Asendabo Unfilled and Filled Maximum
Temperature data chart
Asendabo TMAX Time Series Chart
Unfilled
TMAX
40
20
0
Statistical Analysis of using Mean,
Variance,Sum & pdf plot of Max Unfilled &
Filled Temp data
Asendabo Maximum Temperature
Asendabo Maximum Temperature Varience
Maximum Temperature_Unfilled
Mimum Temperature_Filled
Max. Temperature_Unfilled
58
Max. Temperature_Filled
58
1810
0
1810
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
0
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Asendabo Max. Temperature PDF Chart
Asendabo Maximum Temperature
AsendaboObsTMAXunfilled.dat
Mean
Max. Temperature_Unfilled
6906
6906
Max. Temperature_Filled
46
46
0
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
0
0
0
38.5
x axis label
Modeling of Cascade Dams & Reservoir Operation
Generated Maximum Temperature
from 2001-2040
.
Generated Temperature Maximum
TEMPNCEP_1970-2000.dat
TEMPGCM_2001-2040.dat
68
68
0
0
Data points
Statistical Analysis using Mean, Varience,
Sum & pdf of Generated data
.
.
Observed Vs Modelled Max Temp Mean
Observed Vs Modelled Max Temp Sum
Observed Max Temp Mean
Observed Max Temp Sum
Modelled Max Temp Mean
Modelled Max Temp Sum
57
57
0
1000
0
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
1000
0
Jan
Dec
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Asendabo Max Temp PDF Chart
AssendaboObsTmax.dat
Obseved Vs Modelled Max Temp Varience
Mean
Observed Max Temp Variance
4000
4000
Modelled Max Temp Variance
18
18
0
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
0
0
x axis label
Modeling of Cascade Dams & Reservoir Operation
-10
1.1.00
1.1.99
1.1.98
1.1.97
1.1.96
1.1.95
1.1.94
1.1.93
1.1.92
1.1.91
1.1.90
1.1.89
1.1.88
1.1.87
1.1.86
1.1.85
1.1.84
1.1.83
1.1.82
1.1.81
1.1.80
1.1.79
1.1.78
1.1.77
1.1.76
1.1.75
1.1.74
1.1.73
1.1.72
1.1.71
1.1.70
Temperature Minimum (°C)
Asendabo Unfilled and Filled Minimum
Temperature data from 1970-2000
.
Asendabo TMIN Time Series Chart
30
Unfilled
TMIN
20
10
0
Statistical Analysis using Mean, Variance,Sum
& pdf plot of Min. Temp
Asendabo Min. Temp Sum
Asendabo Min. Temp Mean
Min.Temp_Unfilled
Min. Temp Sum_Unfilled
Min. Temp_Filled
Min. Temp Sum_Filled
16
16
500
500
0
0
Jan
0
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
SDSM PDF Chart
Asendabo Min. Temperature Varience
Min Temp_Unfilled Varience
AsendaboObsTMINunfilled.dat
Mean
Min. Temp._Filled Variance
5382
16
5382
16
0
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
0
0
-5
22
x axis label
Modeling of Cascade Dams & Reservoir Operation
Generated Minimum Temperature
from 2001-2040
.
Mean Temperature Series
TMINNCEP_1970-2000.dat
TMINGCM_2001-2040.dat
33
33
-10
-10
Data points
Statistical Analysis using Mean, Varience,
Sum & pdf of Generated data
Observed Vs Modelled Min Temp Mean
.
.
Observed Vs Modelled Min Temp Sum
Observed Min Temp Mean
Modelled Min Temp Mean
Observed Min Temp Sum
Modelled Min Temp Sum
16
16
500
500
0
0
Jan
0
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Asendabo Min Temp PDF Chart
Observed Vs Modelled Min Temp Varience
AssendaboObsTmin.dat
Observed Min Temp Variance
5662
Mean
5662
Modelled Min Temp Variance
16
16
0
0
0
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
x axis label
Modeling of Cascade Dams & Reservoir Operation
Summary
By the same procedure
• 18 Precipitation station were filled and
generated
• 13 Maximum and Minimum temperature station
data were filled and generated
5. Hydrological Model SWAT
5.1. Introduction
• SWAT is a hydrological model that attempt to
describe the physical processes controlling the
transformation of precipitation to runoff.
• The major hydrologic processes described by
this model include: Canopy interception,
Evaporation,
Transpiration,
Snowmelt,
Interflow, Overland flow, Channel flow,
unsaturated subsurface flow and saturated
subsurface flow.
Modeling of Cascade Dams & Reservoir Operation
Introduction cont...
• SWAT was used to assess and predict the
impact of land management practices on
water in Omo river basin with varying soils,
land use and management conditions over
long periods of time.
Modeling of Cascade Dams & Reservoir Operation
5.2. Objective
• To simulate runoff & inflow to the
reservoirs in the Omo river basin.
Modeling of Cascade Dams & Reservoir Operation
5.3. Methodology
• Input files needed for
daily stream flow
computation were :
• the digital elevation
model (DEM),
• land cover,
• soil layers,
• daily values of
precipitation, max.&
min. air temp, solar
radiation, RH, & WS,
• Hydrological flow data.
Modeling of Cascade Dams & Reservoir Operation
Methodology cont...
•



Missing metrological data were filled
using WXGEN weather generator model of SWAT,
SDSM, and
Hydrological flow data were filled by Multiple
regression of R program
• The Digital Elevation Model (DEM) was used to
create stream network, subbasin & delineate the
watershed boundary & also calculate the sub
basin parameters.
• Threshold value of 2%, 5% & 5% were taken for
land use, soil & slope in order to keep the
number of HRUs to a reasonable number for
modeling the water assessment of the basin.
Modeling of Cascade Dams & Reservoir Operation
Methodology cont...
• Runoff was predicted separately for each HRU
& routed to obtain the total runoff for the
watershed, and
• Calibration, Validation & Uncertainity of the
model using SWAT_CUP 4.3.7.
Modeling of Cascade Dams & Reservoir Operation
5.4. Results
1. Model Calibration and Validation of
Abelti Sub watershed
• Abelti sub-watershed has an area of 15,495 km²
and 30% of the total watershed delineated at
Omorate.
SWAT Land Use
AGRC
Area (ha)
92603.24
% Watershed
Area
Soil
1.37 Chromic Luvisols (LVx)
Area (ha)
%
Watershed
Area
173730.74
2.57
Dystric Vertisol (VRd)
228955.24
3.39
16.62 Eutric Vertisols (VRe)
304403.79
4.51
AGRL
1122014.08
FRSD
115774.54
1.72 Humic Alisol (Ntu)
385865.94
5.72
RNGW
124815.46
1.85 Humic Nitisols (NTu)
406320.23
6.02
WATR
85006.00
1.26 Lithic Leptosols (LPq)
40937.38
0.61
Modeling of Cascade Dams & Reservoir Operation
Model Calibration and Validation of
Abelti Sub watershed
• Using SWAT model
the area was
delineated into 9
sub watersheds,
which were further,
divided into 122
HRUs.
• Simulated flow at
the outlet was
compared with the
observed flow.
Modeling of Cascade Dams & Reservoir Operation
Flow Calibration At Abelti
Modeling of Cascade Dams & Reservoir Operation
Sensitivity Analysis
Modeling of Cascade Dams & Reservoir Operation
2. Model Calibration and Validation of
Karodus Sub watershed
• Karo Duse sub-watershed covers 64,518 km²
and 95.6% of the total watershed delineated
at the Omorate.
• Land use and land cover was reclassified into
%
7 broad categories
Watershed
% sub
SWAT Land
Use
AGRC
AGRL
FRSD
FRST
RNGR
RNGW
WATR
Area
% Watershed % sub
(ha)
Area
basin
92603.2
1.4
272001
0.3
40.3
661280.
5
9.8
69943.8
1.0
292470.
2
4.3
242747
1
18.8
186396.
5
2.8
Soil
Area (ha)
1.4
Chromic Luvisol
Dystric leptosol
351598.7
14272.9
5.2
0.2
5.5
0.2
42.2
Dystric Vertisol
228955.2
1.7
3.5
Eutric Cambisol
146060.0
1.6
2.3
Eutric Fluvisol
Eutric Leptosol
438059.3
11503.9
6.5
0.2
6.8
0.2
Eutric Vertisols
12.3
12.8
20.5
21.4
31.6
33.0
13.6
14.3
10.3
1.1
37.6
Humic Alisol
2.9
Humic Nitisol
827509.7
1381854.
1
2130999.
1
Lithic Leptosol
919362.5
4.5
Area
Modeling of Cascade Dams & Reservoir Operation
basin
Model Calibration and Validation of
Karodus Sub watershed
• Using SWAT model
the area was
delineated into 24
sub watersheds,
which were further,
divided into 311
HRUs.
• Simulated flow at
the outlet was
compared with the
observed flow.
Modeling of Cascade Dams & Reservoir Operation
Flow Calibration At Karodus
Modeling of Cascade Dams & Reservoir Operation
Sensitivity Analysis
Modeling of Cascade Dams & Reservoir Operation
6. HEC-ResSim (Reservoir System
Simulation) Model
6.1. Introduction
• HEC-ResSim (USACE) is a modeling software
program used to assist in planning studies for
evaluating existing & proposed reservoirs,
reservoir operations, & to assist in sizing the
flood risk management and conservation
storage requirements for each project.
• It is intended to meet the needs of real-time
reservoir regulators for a decision support
tool, as well as the needs of modelers doing
reservoir projects studies.
Modeling of Cascade Dams & Reservoir Operation
Introduction cont...
• There are three modules that make up HECResSim to simulate the dam & reservoir
operations.
• These are watershed set up, reservoir network
and simulation. Each module has a unique
purposes & an associated set of functions
accessible through menus, toolbars and
schematic.
Modeling of Cascade Dams & Reservoir Operation
ResSim Module Concepts
.
Modeling of Cascade Dams & Reservoir Operation
6.2. Objective
To develop & recommend optimal dam &
reservoir operation rule curves for cascade
dams & reservoirs
To evaluate the effects of various reservoir
operating alternatives on either preventing
flooding or avoiding precarious low flow at
locations d/s of the reservoirs
Modeling of Cascade Dams & Reservoir Operation
6.3. Methodology
• Insertion of the map layers in to the HECResSim model
• Schematization & configuration of stream
alignment & configurations of the projects
• Developing network schematic
• Describing the physical & operational elements
of the reservoir model & analyze the
alternatives
• Configuration of simulation to isolate the
output analysis,
• Simulation of the dams & reservoirs network,
Modeling of Cascade Dams & Reservoir Operation
Watershed Setup & Stream
Alignment
Modeling of Cascade Dams & Reservoir Operation
Methodology cont…
• Evaluation of the effects of various reservoir
operating alternatives on flooding at locations
d/s of the reservoirs,
• Calibration & Verification of the model,
• Development of a model that represents the
cascade dams & reservoirs,
• Delivery of optimal water use operational model
for Omo River Basin and
• Interpretation of the results.
Modeling of Cascade Dams & Reservoir Operation
6. References
• Akter, T. & Simonovic, S. P., (2004). Modelling
uncertainties in short-term reservoir operation
using fuzzy sets and a genetic algorithm.
Hydrological Science Journal 49(6): 1081-1079.
• Arnold, J.G., Srinivasan, R.S., Muttiah, & J.R.
Williams. (1998). Large area hydrologic modeling
and assessment part I : Model development. J.
American Water Resource. Assoc. 34(1): 73-89.
• Arunkumar, S., & Yeh, W. W. G. (1973).
Probabilistic models in the design and operation of
a multi-purpose reservoir system.
Modeling of Cascade Dams & Reservoir Operation
Thanks
For
Your
Attention!
Modeling of Cascade Dams & Reservoir Operation