Methodology for Assessing Glacial Lake Outburst Flood of Poiqu/Bhote Kosi
Basin, China and Nepal- A case study approach
ABSTRACT
Over the last four decades, there has been immense development along the flood plains and
more elements are being exposed to risks from a GLOF event. Risk assessment is the core of
the disaster risk management process and aims towards identifying potential risk-reduction
measures. Identified risk-reduction actions can be incorporated into development policies and
legal practices in order to meet both development needs and reduce risk.The case study
discusses the methodology used for assessing Glacial Lake Outburst Flood (GLOF) risk in the
Poiqu/Bhote Kosi basin- a transboundary basin between Tibet Autonomous Region of China
and Nepal. The main steps in the assessment include the simulation of the outburst using a
mathematical model; analysis of the flood propagation along the river stretch of 100 km; and
analysis of the socio-economic impacts in the downstream areas of the lake through field study.
INTRODUCTION:
The Himalayas contain the largest deposits of snow and ice after the Polar Region. It contains
numerous glaciers and glacier lakes which makes it a storehouse of freshwater. In Nepal, the
Himalayas share border with the Tibetan Autonomous Region (TAR) of China which also
abounds in many glaciers and glacial lakes. Many rivers of Nepal originate from the glacier and
glacier lakes located in TAR. These water bodies are highly dynamic and sensitive to changes
in climate and other environmental factors.
Majority of the Himalayan glaciers have experienced rapid retreat in past decades. This has
resulted in the formation and growth of many glacial lakes. These glacial lakes are held back by
unstable moraine materials and can burst out leading to a type of flash flood known as a glacial
lake outburst flood (GLOF). It is estimated that there are around 200 such potentially dangerous
glacial lakes in the HKH region; there have been about 35 recorded GLOF events in the past
decades.In Nepal alone 20 glacial lakes have been identified as potentially dangerous. All the
lakes have the potential to outburst and cause flash floods. According to the information
available, Nepal has experienced at least 24 GLOF events in the past. Of these, 14 are believed
to have occurred in Nepal itself, and 10 were the result of flood surge overspills across the
China (TAR) – Nepal border. The first historic GLOF in Nepal occurred in Pokhara valley about
450 years ago. As per recorded data, GLOF events occur once in every three years in Nepal
Among the past GLOFs in Nepal, the GLOF incident in Bhotekoshi/Sunkoshi in 1981 was
recorded as a severe incident causing the loss of lives, properties and infrastructures. With
climate change and existence of significantly larger glacial lakes in the headwaters of the
Bhotekosi/Sunkosi River, it is envisaged that potential GLOFs could be of larger magnitude
compared to the 1981 event.
International center for Integrated Mountain Development (ICIMOD) is committed to sustainable
mountain development and mountain hazard risk reduction. For over two decades, ICIMOD has
been observing and documenting the impacts of climate change on mountain eco system and
mountain communities. In order to create a sustained mechanism for monitoring the changes in
glacial lakes, ICIMOD has developed a methodology for glacial risk assessment and piloted it in
selected locations in the year 2009.
This case study discusses methodology, its application and results in the Bhotekosi/Sunkosi
River.
STUDY AREA:
The case study is located in the Poiqu/bhote Kosi basin, a transboundary basin between Tibet
Autonomous Region of China and Nepal. The total basin area is 3,393 km2 with 60% of the area
within China and 40% within Nepal. The river is called Poiqu in Tibet and Bhote Kosi or Sun
Kosi in Nepal. The only highway linking Nepal and China (called Araniko highway in Nepal)
passes through this basin and is aligned along the Poiqu/Bhote Kosi River. The river basin is
leaf shaped, with an average length of 107km and a width of 33km.
Nine potential dangerous lakes have been identified in this basin, all located within Tibet.
According to an inventory of glaciers and glacial lakes done in 2000, there are altogether 151
glaciers covering 231.58 sq.km area with 19.03 km3 ice reserve. Similarly, there are 139 glacial
lakes which cover an area of 16.39 sq.km area. 59 of these lakes are moraine dammed and
have a higher susceptibility to outburst. Temporal analysis of glacier dynamics in this basin
shows that the number, area and ice reserve are declining but the number of glacial lakes and
its area are increasing (Mool et al., 2005). It is a clear indication that the risk of glacial lake
outburst flood in Bhotekosi/Sunkoshi is likely to increase in the future.
Over the last four decades with the construction of the Kathmandu-Kodari Highway, many
settlements have moved from the hilltops to the road side. Along with the increasing number of
settlements and population, roads, bridges, hydro power stations have also developed. This
development implies that along the flood plain more and more elements are being exposed to
risks from a GLOF event.
The study was conducted in the river corridor over a distance of 100 km downstream from the
lake ending at a town called Dolalghat in Nepal (45km is within Tibet and 55 km within Nepal).
The socioeconomic aspect of the study was conducted only in the Nepalese part of the basin.
PROCESS OF RISK ASSESSMENT:
The risk assessment in the HKH region has been limited to hazard assessment based on mainly
secondary data. The studies on GLOF simulation concentrated mostly on outburst simulation
and routing the flood along the river valley downstream of the lake. A comprehensive GLOF risk
assessment should encompass a hazard assessment of the lake as well as a physical and
social vulnerability assessment of the downstream impact areas.
The methodology for mapping the hazard compromised of:
I.
II.
Selection of data and models
Modeling the scenarios of outburst
III.
IV.
V.
Modeling of flood propagation along the Poiqu/Bhote Kosi valley
Flood mapping
Vulnerability Assessment
I. Data and model selection:
The data necessary for this detail study of glacial lake outburst are Spatial data (Watershed
boundary, drainage network, Inline structures of rivers, Digital Elevation Model (DEM of the
study area, Infrastructures – road, bridge, cannel, dam, service centers, etc.; lake information
(surface area, maximum depth, top/bottom elevation of lake); Moraine information
(inside/outside of slope, dam length and width, unit weight of dam material, outer core of the
dam, frictional angle, etc.) and finally socio economic data. The data for the dam breach was
taken from the SRTM DEM. As the information regarding geotechnical parameters for both
lakes was lacking, the parameters were adapted, similar to Tsho Rolpa GLOF case study
(Bajracharya et al. 2007). To conduct the study various computer applications have been used
(Arcview 3.2A, HEC‐GeoHMS, HEC‐GeoRAS, v3.2.1, NWS BREACH, BOSS DAMBRK,
HECRAS v4 Beta, and AutoCAD).
II. Modeling the scenarios of outburst
For simulating the nature of flood wave in the case of Dam breach, an erosion model developed
by National Weather Service (NWS‐BREACH) was used (Fread 1991). It gives outburst
hydrograph. The input parameters are geometric and dam material properties. Geometrical
parameters were derived from DEM while geotechnical parameters were adopted as in other
similar studies due to unavailability of data. For uncertainty of material properties sensitivity
analysis was carried out. The NWS- Breach model was used to stimulate the outburst
hydrographs. The model is based on coupling the conservation of mass of reservoir inflow,
spillway outflow, and breach outflow with the sediment transport capacity of the unsteady
uniform flow along an erosion formed breach channel. The growth of breach is dependent on
the dam’s material properties such as size distribution, composition, compaction, unit weight
and strength. The outflow hydrograph was obtained through a time-stepping iterative solution
not subject to numerical stability or convergence difficulties. With combination of various input
parameters within ranges, 33 scenarios with NWS‐BREACH were generated. From this
sensitivity analysis was carried out to analyze uncertainty of input parameters
III. Modeling of flood propagation along the Poiqu/Bhote Kosi valley
For the flood routing, after the GLOF hydrograph was derived from the breach model, the nature
of flood propagation in the downstream areas was simulated using BOSS-DAMBRK (Polk
2001). BOSS DAMBRK is a one–dimensional hydrodynamic flood routing software which
accounts for dam and bridge failures, storage effects, floodplain overbank flow and flood wave
attenuation.
The Limuchimi lake and downstream river section of Bhotekoshi/Sunkoshi River up to Dolalghat
bridge (Nepal) was simulated with DAMBRK for the detailed analysis of a flood wave
downstream. A total number of 29 cross sections were selected at different locations along the
river course for which DAMBRK generated flood hydrographs.
IV. Flood mapping
Hec-GeoRAS was used to produce inundation maps based on the hydrographs generated by
DAMBRK. Although Hec‐RAS software can be used for unsteady flow routing, it went unstable
during simulation. The problem may be due to extremely steep river slopes and lack of actual
field data due to which data used in model could not represent actual field at some portion of
river section. To overcome this problem BOSS‐DAMBRK was used for unsteady flow routing
using the results from NWS‐BREACH and the output hydrographs generated at 6 locations
were utilized as input in HEC‐RAS 4 Beta and steady flow simulation was performed so that
simulation result could be exported to Hec‐GeoRAS which is capable for producing inundation
maps in GIS environment. Map 1 shows the flood inundation scenario in the Poique/Bhote.
Map 1: Flood Inundation map- Pioque/Bhote Koshi Basin. Source: Glacier Lake
outburst Flood Modeling of lumu Schimi lake Poiqu/ Bhote Kosi Basin
V. Vulnerability Assessment
The property and infrastructures exposed to the flood hazard zone were quantified and mapped.
The final flood map was used to extract the land cover from the land cover map produced by
Department of Survey at 1:50,000 and 1:25,000 scale provided by ICIMOD. The vulnerability
was estimated by the land cover type which is exposed by GLOF risk. The specific spots were
identified and a field visit was done for checking the result at some of vulnerable points.
The pre-assessment of the potential damage was estimated by studying the land cover map
and the area exposed to GLOF risk. For the Socio-economic risk assessment, the past GLOF of
1981 was taken as a baseline event. There is no systematic information available on this event
but newspapers recordings and discussions with elderly people provided useful information of
that event. Both secondary and primary sources of information have been used. Published and
unpublished reports, newspapers, books, maps etc. were collected and reviewed. A two week
long field survey was conducted to collect primary information.
Property damages are the most common form of damages in GLOF or flood events. Damages
are grouped into several categories, namely, direct, indirect, secondary, intangible and
uncertainty damages. Tangible/Direct damages are immediate and can be external or structural
in nature. Tangible damages can be estimated in monetary units. Indirect damages are induced
damages resulting from the direct damages. An example of indirect damage is closure of
business or additional cost due to the flood event. Secondary damages are when different
groups of people depend on different services that originate from the area where the damages
have occurred. For example, if a hydropower gets affected and the electricity supply is reduced
impacting consumers and also affecting the total GDP. Intangible damages reflect negative
impacts on social life of individuals and communities along with loss of important heritage sites
and environmental qualities.
RESULTS
The most likely breach scenario suggests the peak discharge will be about 7900 m 3/s. During
the peak flood period, the flood level can rise up to 15 m above the river bottom at various
locations along the river.
Nearly 900 households with the total population of 5800 will be directly affected if the floods with
the same magnitude of 1981 GLOF occur. Additional 1653 households with a population of
10531 will be affected if the flood with higher magnitude occurs. Since the Araniko Highway
along the Sunkoshi/Bhotekosi River are exposed to the flood damage, the flow of vehicles,
goods and people is likely to be affected along with a number of VCDs that lie in that region. In
addition, many more people involved in international trade with China and the tourism activities
along Tatopani and Khumbu region will be affected. Many people in other districts depend on
this highway for supply of manufactured goods and agriculture inputs and export of fruits,
vegetables and milk.
In case of a GLOF event, two
hydropower dams in the region and all
the power plants are likely to be
affected which will cut down on the
supply of electricity to local areas,
small towns and Kathmandu city. This
will lead to the disruption in livelihoods
and economic activities. Other basic
needs like drinking water supply and
communication
cables
will
be
damaged in the likely event of a
GLOF, leading to negative health
impacts and further affecting the
income of the individuals not only from
that region but also who are involved
in trade and tourism activities. Graph 1
shows the estimated risk in different
areas or estimated value of elements
at risk
Graph 1: Estimated Amount of GLOF Risk
Source: An Assessment of Glacial Lake Outburst Flood in the Bhote Kosi Basin (2008)
Direct damages will be by far the largest. When real estate and infrastructures are taken
together direct damages account for 75% of total damages at the 1981 flood level. When the
flood level is assumed to increase by 10 meters the direct damages account for 79% of the total
damages. Within the direct damages the hydro power station damage accounts for the biggest
chunk of damage (61%). The secondary damages account for 25% of the overall damages
which indicates that the impact of the flood will go beyond the flood prone area. The estimated
total value of properties exposed to GLOF risk is 11.150 million rupees (USD 159 million) under
the condition that the magnitude of likely GLOF is the same as of 1981. If the GLOF with flood
level 10m higher than that of 1981 occurs then the estimated property at risk is about 13,846
million rupees (USD 197 million). The share of hydroelectricity projects, international trade and
private and public buildings is comparatively high. Hydropower projects share more than 72%
(60% infrastructure loss plus 12% revenue loss) of the total amount of the elements exposed
followed by international trade (12%) and private and public building (9.13%) at the 1981 flood
level. There will be a drastic increase in the share of private properties-buildings, land and crops
and roads if the magnitude of the GLOF was increased by 10 percent. Because of the difficulties
in estimating monetary value of livelihood support system- household income, health and
comfort, are not incorporated into the estimation. So, the actual monetary value of damages will
be higher than estimated in the study.
The figures on the right present
the damages estimation by the
sites/blocks. Damages are
highest in Hindi because the
Bhotekosi hydro power plant is
located in this block.
Khadichaur is second, and
again Sunkosi hydro power
project is located in this block.
Table 1: Damages Estimation of Flood in Bhote Kosi Valley
Sectors
Elements
Direct
Damag
es/Real
Estate
Khet
Bari
Housing Plot
Pakki-house
Kachhi-house
Total
Direct
Damag
es
/Public
Infrastr
ucture
Road
Trail
Embankment
Motorable Bridge
Suspension Bridge
Water Mills
Drinking water
schemes
Hydropower station
Transmission line
Fibre cable
Total
Indirect
Paddy
1981 Flood Level
10 m + 1981 Flood
Level
Rs '000'
Share (%)
Rs '000'
Share (%)
109250
15925
16350
858700
159650
1159875
0.98
0.14
0.15
7.70
1.43
10.40
398450
91975
80285
1867800
525750
2964260
2.89
0.67
0.58
13.55
3.81
21.51
240000
700
4000
60000
22500
1200
1750
2.15
0.01
0.04
0.54
0.20
0.01
0.02
605000
10700
4000
210000
37500
4500
5500
4.39
0.08
0.03
1.52
0.27
0.03
0.04
6755000
122500
8058
7215708
60.58
1.10
0.07
64.71
6755000
336875
20510
7989585
49.01
2.44
0.15
57.97
2801
0.03
11776
0.09
Damag
es
/Agricul
tural
Sector
Wheat
Maize
Millet
Potato
Fruits
Vegetables
Livestock
Total
Second
aryDam
ages
Custom
Hydropower
Total
Total
418
1152
248
20
1092
4158
8040
17928
0.00
0.01
0.00
0.00
0.01
0.04
0.07
0.16
2095
5332
1657
761
3266
18828
29000
72716
0.02
0.04
0.01
0.01
0.02
0.14
0.21
0.53
1367000
1389600
2756600
12.26
12.46
24.72
1367000
1389600
2756600
9.92
10.08
20.00
Rs '000'
11150111
100.00
13783161
100.00
US$ (Rs 75= $US 1)
148668
183775
Source: An Assessment of Glacial Lake Outburst Flood in the Bhote Kosi Basin (2008)
CONCLUSION:
In light of some incidents of past economic losses from GLOF events and the identification of
number of potentially dangerous glacial lakes, donors, project financiers and companies require
a comprehensive risk assessment for new development projects. Decisions regarding any
investment in early warning systems and insurance require a good understanding of an existing
GLOF risk. Risk assessment is the core of the disaster risk management process and aims
towards identifying potential risk-reduction measures. Risk assessments integrated into the
development planning process can identify actions that meet both development needs and
reduced risk. Identified risk-reduction actions can be incorporated into development policies and
legal practices.
The case study shows that technical and social techniques can result in better risk assessment.
A systematic risk assessment provides understanding of both hazard (physical) and vulnerability
(social and physical) and can form a good basis for mitigation planning. The methodology used
in this case study can be replicated with appropriate modification according to the context. The
case study also shows that in some cases (when GLOF risks are situated in populated areas)
the socio-economic impacts of GLOF risks cannot be ignored. The case study further highlights
the transboundary nature of the issue in certain cases and the need for regional collaboration.
Sources: ICIMOD (2009) Glacier Lake Outburst Flood Modeling of Lumu Chimi Lake Poiqu/Bhote Kosi
Basin, ICIMOD unpublished report; ICIMOD (2009) GLOF Risk Assessment in Bhote Kosi (Sun Kosi)
Basin, ICIMOD unpublished report; ICIMOD (2000) Monitoring of Glaciers and Glacial Lakes from 1970s
to 2000 in Poiqu Basin, Tibet Autonomous Region, PR China.
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Methodology for Assessing Glacial Lake Outburst Flood of Poiqu