Flood in the Terai Belt of Nepal

Mini – Project on Flood in the Terai Belt of Nepal








JAXA Sponsored study on

Integration of GIS and Remote Sensing with Flood Simulation Models for Flood Hazard Mapping and Mitigation
:
A Case Study of Bagmati River, Nepal





Submitted to
Geoinformatics Center (GIC)
Asian Institute of Technology (AIT), Bangkok




Prepared by

Tanka Prasad Kafle
Department of Water Induced Disaster Prevention
Lalitpur, Nepal
Kalyan Gopal Shrestha
Department of Survey Kathmandu, Nepal





February 2006

TABLE OF CONTENTS


Acknowledgement
Acronyms
Abstract
1. INTRODUCTION.. 1
1 Background. 1
1.2 The River Systems of Nepal 1
1.3 The Bagmati River and Study Area. 3
1.4 River Morphology. 4
1.5 Flood Problems. 5
1.6 Drainage Congestion. 6
1.7 Impact of Flooding. 6
2. OBJECTIVES AND EXPECTED OUTCOMES. 7
2.1 Objectives of the Study. 7
2.2 Study Schedule. 7
3. METHODOLOGY AND DATA.. 9
3.1 Methodology. 9
3.2 DEM/TIN Preparation. 9
3.3 Extraction of Terrain Information. 9
3.4 Flood Frequency Analysis. 9
3.5 Flood Flow Simulation. 9
3.6 Preparation of Inundation Area and Flood Depth Map. 9
4. FIELD WORK.. 13
4.1. Field Visit 13
4.2 Validation of Flood Depths. 14
5. RESULTS AND DISCUSSION.. 15
5.1 Flood Discharges for Different Return Periods. 15
5.2 Extraction of River Cross-Section. 15
5.3 Computation of Water Surface Profiles. 17
5.4 Preparation of Flood Hazard Map. 17
5.5 Area Affected by Flood. 21
5.6 Hazard Indicators. 21
5.7 Assessment of Agricultural Damage. 23
5.8 Importance of Digital Elevation Model (DEM) 23
5.9 Flood Hazard Map Based on Inundation Area and Flood Depth. 23
5.10 Population Affected by Flood. 27
5.11 Flood Hazard Map Based on Population affected. 28
5.12 Interactive Effect of Different Variables. 30
5.11 Flood Hazard Map Based on Affected Land Cover Type. 30
5.12 Flood Hazard Map Considering all Variables. 34
6. MITIGATION MEASURES. 37
6.1 Flood Damage Mitigation Measures. 37
6.2 Construction of Levees. 37
6.3 Early Warning System.. 37
6.4 Flood Plain Regulation and Zoning. 39
6.5 Flood Proofing. 39
6.6 Raised Platforms for Shelter 40
6.7 Restructuring the Cropping Pattern. 40
7. LIMITATIONS. 40
8. CONCLUSION AND RECOMMENDATIONS. 41
REFERENCES. 1

LIST OF FIGURES

Figure 1: River Systems of Nepal……………………………………………………………..2
Figure 2: Study Area. 3
Figure 3: Drainage Map of Bagmati Watershed. 4
Figure 4: Flow chart of Methodology. 11
Figure 5: Overall Methodology. 12
Figure 6: GCPs. 13
Figure 7: Validation of flood depth results. 14
Figure 8: DEM of the study area. 15
Figure 9: Typical river cross section. 16
Figure 10: Flow area along the river reach under study for a fifty-year flood. 16
Figure 11: Water surface profiles for floods of various return periods. 18
Figure 12: Channel and over bank flows along the river 18
Figure 13: XYZ plot generated by HEC-RAS simulation for Q50. 19
Figure 14: Flood Depth Map. 20
Figure 15: Flood Depth Map of Gaur Municipality. 21
Figure 16: Flood Hazard Map based on Inundation Area and flood depth. 25
Figure 17: Population Distribution within the Flood Affected Area. 28
Figure 18: Hazard Ranking Based on Affected Population. 29
Figure 19: 2 and 3 Dimensional Multiplication Mode of Variables for Ranking. 30
Figure 20: Land use Map. 31
Figure 21: Hazard Ranking Considering Inundation Area, Flood Depth and Land Cover 32
Figure 23: Changes in Hazard Ranks with Combination of Different Variables. 37
Figure 24 : Rating curve. 38
Figure 25: Location of gauging station. 38
Figure 26: Schematic Concept of Raised Platform.. 40

LIST OF TABLES
Table 1: Flood discharges for various return periods. 15
Table 2: Extent of inundation of Gaur Municipality. 21
Table 3: Summary of Inundated area. 23
Table 4: Hazard ranking for Rautahat district 26
Table 5: Hazard ranking for Sarlahi district 27
Table 6: Summary of Land Cover Types of the Flood Affected VDCs. 30
Table 7: Percentage of Land Cover of Different Categories and Hazard Ranks. 33
Table 8: Percentage of Land Cover of Different Categories and Hazard Ranks. 34




List of Acronyms


CBS : Central Bureau of Statistics
DWIDP : Department of Water Induced Disaster Prevention
GL : Ground Level
GIS : Geographic Information System
HEC-RAS : Hydrologic Engineering Center’s River Analysis System, (1D hydraulic water surface profile model for steady and unsteady flow for a full network of natural and constructed channels).
HFL : High Flood Level
HMGN : His Majesty’s Government of Nepal
JAXA : Japan Aerospace Exploration Agency
km. : kilometer
LRMP : Land Resource Mapping Project
NGO : Non-government Organization
sq. km. : square kilometer
TIN : Triangular Irregular Network
UNDP : United Nations Development Programme
VDC : Village Development Committee
vs. : versus


AKNOWLEDGEMENT



The assistance of Japan Aerospace Exploration Agency (JAXA) in performing this study is gratefully acknowledged by us.

We are especially thankful to Dr. Lal Samarakoon and Dr. Manzul Kumar Hazarika of Geoinformatics Center (GIC), Asian Institute of Technology (AIT), Bangkok for sharing their expertise and providing encouragement throughout the study period. Special thanks are also due to all faculties of GIC, AIT for helping through their comments and suggestions.

Last but not the least, this study would not have been completed without the co-operation of all staff of Geoinformatics Center, AIT. Their support is highly appreciated.

Linking GIS and Remote Sensing with Flood Simulation Models for Flood Hazard Mapping and Disaster Mitigation


Tanka Prasad Kafle[1] and Kalyan Gopal Shrestha[2]


ABSTRACT
Flood is an intense and recurrent hazard in the Terai of Nepal and the problem is getting more and more acute. The occupation of flood plains by population is ever increasing. It has now been gradually realized that it is more rational to try to minimize the damages due to floods rather than making heavy investments in structural measures in containing the rivers. This requires that all development and agricultural activities in the flood plains must be compatible with the flood risk involved. Flood depth estimation from remotely sensed imagery alone is very difficult, if not impossible. Remotely sensed data, hydrologic models and GIS techniques can be combined to simulate potential flooding and for predicting areas that are likely to be flooded by a flood of a given return period. This study presents an integrated approach making use of them in flood management with particular focus on flood hazard mapping.
The success and utilization of the flood predictions revolves around delineation of inundated area and preparation of flood hazard maps. Hence the issue of preparing a flood hazard map is of utmost concern for flood management. In this study flood risk is defined in terms of fifty-year flood and flood depth is considered as an indicator of the intensity of hazard. The hydrological data, in the form of past flood records, are important to evaluate possibilities of future occurrences of flood events. The flood frequency analysis provides quantitative assessment of the flood problem. A Digital Elevation Model (DEM) was created using Arc View GIS based on the contour and spot elevation data from the digital topographical maps prepared by the Department of Survey of Nepal. The Triangular Irregular Network (TIN) was used in HEC-GeoRAS environment to extract terrain and river information in the form of cross section for using as input to HEC-RAS flood flow simulation. The hydraulic computations made by HEC-RAS were exported to GIS where they were used to create a water surface TIN. The intersection of the water surface TIN and the terrain TIN provides flood plain visualization as inundation area map and flood depth map.
The interactive effect of population density and land cover type being affected by flood is included in the analysis and a final hazard ranking for all the Village Development Committees (the administrative units considered in the study) is prepared. The Early warning system is widely recognized as a vital non-structural measure. It is, therefore, important that the flood plain dwellers be warned of incoming floods with sufficient lead-time and moved to safer places. The study has suggested an easy way to implement early warning system by making use of stage versus discharge curves to interpret hazard maps. Measures have been suggested for flood plain regulation and flood proofing including minimum plinth levels for buildings. The study has identified critical river sections for structural measures. This approach having low cost and simple data requirement can serve as an effective tool to formulate strategies for flood control planning and construction and development of flood countermeasures in a developing country like Nepal.
1. INTRODUCTION


1 Background
Nepal, occupying the central part of the Hindu-Kush Himalayan belt covers an area of 147,181 square kilometer between India and China. On an average it extends 885 km in east- west and 200 km in north-south direction. The altitude ranges from 60 m above mean sea level (amsl) in the terai to more than 8000 m amsl in the Himalayas. The terai plain occupies about 20% of the total area of the country and the rest is hills and mountains. Geomorphologically and ecologically the country can be divided into five distinct regions from south to north namely the Terai, Siwalik Hills, Middle Mountains, High Mountains and High Himalayas.
The average annual precipitation is around 1600 mm of which almost 80% occurs during the period of June-September. The variation ranges from less than 300 mm in the rain shadow dry region to around 5000mm in the wet region. On the physical side, rugged topography, young geology and monsoon climate, all combine to produce high rate of runoff, erosion and sedimentation. At times, tremendous natural forces as earthquakes, floods and landslides are unleashed. Human activities have also resulted in pressure on biophysical resources of the country. Such natural features associated with intense monsoon rainfall as well as man made hazards render the country highly vulnerable to water induced disasters such as floods, landslides, debris flow etc. demanding effective and sustainable countermeasures.
1.2 The River Systems of Nepal
About 6000 rivers and rivulets drain Nepal. These rivers are broadly classified into three categories based on the nature of their source and discharge.
In the first category are perennial rivers that originate in the Himalayas and carry snow fed flows with significant discharge even in the dry season. This includes the Kosi, Gandak, Karnali (Ghaghra) and Mahakali (Sharda) river systems.
In the second category are the rivers, which originate in the midlands of Mahabharat range of mountains and are fed by precipitation as well as ground water regeneration, including springs. Mechi, Kankai, Kamala, Bagmati, West Rapti and Babai rivers fall under this category. Although these rivers are also perennial, they are commonly characterized by wide seasonal fluctuations in discharge.
The third category of river systems includes a large numbers of small rivers in the terai, which originate from the southern Siwalik range of hills. These rivers are seasonal and are characterized by flash floods during the monsoon and mostly dry up during dry season. They drain the areas between basins covered by large and medium rivers. The total catchment area of these rivers is estimated at 23,150 sq. km. A map showing river systems of Nepal is appended at Figure 1.

Figure 1
1.3 The Bagmati River and Study Area
The Bagmati River is one of the representative rivers of the second category. It originates from Latitude27o47'N and longitude 85o17'E at about 16 km north-east of Kathmandu on the southern slopes of the mountain range separating the Bagmati and Kosi basins. At a distance of about 35 km from its origin, the river leaves Kathmandu valley and flows through the Mahabharat range to enter inner terai that consists of the area between the Mahabharat and Churia ranges. As it comes out of the Churia range, the river enters into terai and flows as a border river between Sarlahi and Rautahat districts and drains out of Nepal across the Indian state of Bihar to join the Ganges. Its total length is 597 km of which 195 km lies in Nepal and the remaining portion in India.The Mahabharat range which rise to an elevation of about 3000m on its steep southern slopes is considered to be the wettest area of the catchment the Churia range is the highest sediment yielding area.
The river reach south of its crossing point with East-West Highway at Karmaiya to the Indo-Nepal border constitutes the study area and is the flood plain of the river. The study area consisting parts of Rautahat and Sarlahi districts is shown in Figure-2. The area usually gets flooded during rainy season. For many years, Gaur, head quarter of Rautahat District, has remained as a flood prone area. Flooding in Bagmati area can be attributed mainly to the intense rainfall over its extensive catchment that generates high volumes of run-off that spill out onto the river’s natural flood plains inundating cultivated land and settlements.

NEPAL
NEPAL
NEPAL
SARLAHI
RAUTAHAT














Figure 2: Study Area

In this reach the river is joined by a number of tributaries originating from the Churia hills. They are Paurai, Chandi, Dori, Jhanj and Maunsmara. Catchment area of the river at Indo-Nepal border is 3700 sq. km. Figure-3 shows the drainage map of Bagmati watershed. Mountains, hills and forests in its upper reaches to alluvium planes in the southern part characterize the catchment area of this river. The longitudinal slope varies from 1in 50 near the foothill to 1 in 2500 at Nepal-India border. The bed width is of the order of 700m to 2000m.
A number of settlements are situated on both the banks of the river in the study reach are usually flooded during rainy season. The floodwater that enters into the flood plain flows a long distance towards south before draining back to the river. This river is mostly embanked in the Indian state of Bihar. But in Nepal portion the embankments have not been tagged to high ground. Because of it floodwater gets spilled from non-embanked reaches of the river and flows past behind the embankments defeating the very purpose of their construction.
1.4 River Morphology
The River starts depositing the sediment load and splits into a number of channels as soon as it debouches into plain area. It seems to be fed with larger quantities of sediment than it can carry. The deposited shoals often become so large that they deflect the flow causing the channel to shift its position laterally.
Figure 3: Drainage Map of Bagmati Watershed
Comparison of the current river course with those in the past indicates that the change in the river course is appreciable i.e. of the order of 3 km. This characteristic has made the river to enfold a number of settlements and cultivated land adjacent to it. Consequently, the river has formed a wide flood plain and many channels, either active or dry, along its course from foothill to Nepal-India border.
Bank erosion, spillage and avulsion are usual occurrences.
1.5 Flood Problems
In Nepal, monsoon precipitation and snowmelt from the Himalayas contribute to river flow. Depending on the altitude some catchments are influenced by monsoon rain while others are influenced by rainfall and snowmelt both. On catchments that are entirely below 3000m, usually there is no contribution from snowmelt. The hydrographs of these rivers show no rise in flow until the first monsoon rains. These rivers are characterized by sudden rise and fall of flows in response to monsoon storms. During floods they swell and carry higher discharges and sediment load. After the floods the rivers get reduced to a much lesser width. But in this process they might acquire a different plan form. The continuous change in course is a common feature of such rivers. Due to widely fluctuating discharges and corresponding sediment load, there is always a tendency of the channel to shift towards one or the other bank causing bank erosion. This phenomenon is much pronounced in alluvial rivers having large discharge variations.
Bank erosion in the upper reaches and spilling and consequent inundation in the lower reaches are generally the common problems encountered. Floodwater starts spilling as soon as the river crosses East-West highway. Lateral shifting is another prevailing phenomenon. Often the main cause of damage is the excessive sediment that the river is unable to carry rather than the flood discharge. The sediment gets deposited along the river course in the relatively flat reach of terai causing bed rise thereby causing spillage over the banks even at smaller discharges and at times forcing the river to change its course. Floods in the region occur due to a variety of causes:
· River channels carrying flows in excess of the transporting capacity within their banks primarily due to excessive precipitation in the cathment.
· Backing up of water in tributaries at their outfalls into the main river with or without synchronization of peak floods in those.
· Heavy rainfall coinciding with river spills over a short period of time.
· Landslides blocking stream courses and then sudden release of blockage.
· Heavy local rainfall.
· Inadequate drainage to carry away surface water quickly.
· Aggradation in the riverbed.
· Inadequate waterways road crossings and encroachments in the flood plains.
· Excessive sediment yield from the watershed due to deforestation, cultivation in marginal slopes etc..
· Lack of proper control of land use and developmental works resulting in obstruction of the natural flow.
· Flattening of slopes of the rivers as they enter the plains.

1.6 Drainage Congestion
Severe rainfall-induced drainage problems occur in naturally low land, and large areas remain under water for a long time. Drainage congestion is mainly due to heavy rainfall of short duration coupled with high flow levels in the main river preventing rainwater from draining quickly. They are also induced by construction of roads, railway tracks and embankments that obstruct natural flows, with encroachment on the riverine areas. Insufficient capacity of drainage channels and natural bowel-shaped topography of land resulting from defunct river courses also contributes to drainage congestion.
1.7 Impact of Flooding
The impact of flooding was not felt to the same extent in the past as it is now. This is due to the rapid increase in population and consequent increase in the human activities. The flood plains are being increasingly crowded to meet ever-increasing requirements of food and fibre, and consequently the flood problem is exacerbated. The main impacts of floods are damage to property, infrastructure and disruption to social and economic activities. According to an estimate about 50% of the total population and a similar proportion of assets are concentrated in flood plains. Moreover poor, underprivileged and marginalized people have settled in the low-lying flood hazard areas and are highly vulnerable to flood disasters.

Each year thousands of families are affected. On an average 310 lives are lost due to floods and landslides and infrastructure and property amounting to millions of rupees is damaged causing negative impacts on the social and economic development of the country. In 1993, a year worst hit by disaster, landslide and flood claimed 1336 lives and caused damage worth more than US$ 100 million. The damage was about 3% of GDP, 13% of the government expenditure and about 53% of the total foreign loan (Silt consultants, 2005). Indirect and secondary effects of extreme events on the local and national economy can be contemplated as reduction in family income, decline in the productivity of business and industrial enterprises, unemployment and decline in national income. In a country where 66% of the households own less than a hectare of land, the estimated loss of more than 5000 hectares of land due to flood and landslides every year is a matter of great concern. Further, relief and rehabilitation efforts have to compete with development programs for funds. It is stated that on an average 12% of the development expenditure of Nepal and about 5% of its GDP are spent on response and recovery to disasters per year.
2. OBJECTIVES AND EXPECTED OUTCOMES

2.1 Objectives of the Study
The main objective is to use make flood hazard maps of the study area by using GIS, Remote Sensing and Numerical Model in combination.
· To create a Digital Elevation Model (DEM) of the study area.
· To perform flood frequency analysis and compute magnitude of floods for different return periods.
· To prepare inundation area map and flood depth map for a flood having a return period of 50 years.
· To compute water surface profiles and identify overflowing river reaches for planning and designing structural measures, if needed.
· To assess population and area under different land cover type affected by flood.
· To prepare flood hazard maps considering topographic, hydrologic and socio-economic parameters.
· To relate flood hazard maps to river stage and use them for early warning.
· To suggest mitigation measures.

The outcome of the study would be useful to planners, local bodies and NGOs/INGOs involved in flood damage mitigation in answering questions such as:
· Which areas are at risk of flooding?
· Which areas are more vulnerable?
· Is it safe to build infrastructures in these areas?
· What is the social, economic and environmental cost of flooding?
· Which intervention measure is the most appropriate?

2.2 Study Schedule
The study schedule is given in the next page.

Study Schedule



3. METHODOLOGY AND DATA

3.1 Methodology
A flow chart of the methodology specific to this study is given in Fiure-4. The overall methodology for flood risk assessment is given in Figure-5. The flood plain analysis was carried out mainly using one-dimensional numerical model HEC-RAS and Arc View GIS. HEC-GeoRAS, an Arc View extension, was used as the interface between the two systems for Pre-processing and post-processing of the data in GIS. Satellite Imageries of the study area were used to obtain information on river morphology, old river courses, and active flood plains and present land use pattern etc. These imageries were geo-referenced in order to use them in the GIS overlay operations. A brief description of the approach is given below.
3.2 DEM/TIN Preparation
A Digital Elevation Model in the form of TIN was created using Arc View GIS based on the contour and spot elevation data from the digital topographical maps prepared by the Department of Survey of Nepal. The scale of the maps is 1:25,000. The main contour interval is 10m and supplementary contours are at an interval of 5m.
3.3 Extraction of Terrain Information
The TIN is used in HEC-GeoRAS environment to extract terrain and river information in the form of cross section for generating a HEC-RAS import file for using as input to HEC-RAS flood flow simulation.
3.4 Flood Frequency Analysis
Bagmati River has been gauged at Karmaiya of Sarlahi district. The annual maximum instantaneous discharges for the period from 1965 to 2004 have been obtained from Department of Hydrology and Meteorology (DHM) and Bagmati Irrigation Project. The predictions of maximum flood discharges that might occur in future are made based on the frequency analysis of these data using various relationships.
3.5 Flood Flow Simulation
HEC-RAS is able to perform one-dimensional hydraulic computation for a full network of natural and constructed channels. It can compute water surface profiles by modeling sub critical, super critical and mixed flow regime and has the ability to import three dimensional river schematic as well as cross section data created from GIS.
Flood flow simulation was carried out by entering flow data and associated boundary condition. Water surface profiles for floods of various return periods were computed with sub critical flow regime.
3.6 Preparation of Inundation Area and Flood Depth Map
The hydraulic computations made by HEC-RAS were exported to GIS where they were used to create a water surface TIN. The intersection of the water surface TIN and the terrain TIN provides flood plain visualization in the form of inundation area map and flood depth map. The maps so prepared were verified in the field.
3.7 Data Used – The following data were collected from various sources and utilized in the study.
A. Satellite data
· ASTER (30/10/2003)
· LANDSAT (12/27/2001)
B. Vector data
· Topographical maps (Scale: 1: 25,000), 1993.
· The digital data set of river, road, land use, settlement, contour, spot height and administrative units based on topographical maps -mentioned above.
· Land system, Land utilization and land capability map published by Land Resource Mapping Project, Nepal, 1986.

C. Hydrological data
· Annual maximum instantaneous discharges for the period from 1965 to 2004 acquired from Department of Hydrology and Meteorology, Nepal.
D. Ancillary data
· Information on loss of lives and properties by Disaster in Nepal (1983 – 2003), Ministry of Home, Nepal.
· Census data (2001) from Central Bureau of Statistics, Nepal



· FLOOD HAZARD MAP



HYDROLOGIC DATA
SATELLITE IMAGERY
(ASTER)

TOPOGRAPHICAL DATA
CENSUS DATA
Flood Frequency
Analysis
(Contour + spot ht.)
DEM
Hydrologic
Modeling
Water Surface Profiles
Export Results to GIS
Create Water Surface TIN
Inundation Area Map
Flood Depth Map
Land Use Map
Areas Affected under Different Land Use Pattern
Population Density Map
Inhabitants Affected
Discharge for Different Return Periods
Cross Section of Flood Plain and River
Export to HEC-RAS
Intersect Water Surface TIN with Terrain TIN
+
Vector Data
GIS
HEC- GeoRAS











































































































































y


INPUT DATA












































Figure 4: Flow chart of Methodology





VALIDATE
RESULTS


y

INPUT DATA













































OUTPUT 1













FURTHER STUDY . . . .

OUTPUT 2




HYDROLOGIC DATA

SATELLITE IMAGERY
(ASTER)


TOPOGRAPHICAL DATA

CENSUS DATA
Flood Frequency
Analysis


L1A

Contour + spot ht.

DEM 1


DEM 2

COMPARE

Hydrologic
Modeling

Geometric Data


Water Surface Profiles

Export Results to GIS


Create Water Surface TIN


Inundation Area Map
Flood Depth Map











Inundation Area Map









L1B


Land Use Map









Areas Affected under Different Land Use Pattern









Population Density Map










Inhabitants Affected











EARLY WARNING SYSTEM

· Flood Risk Assessment
· Suggest Mitigation Measures


Ground Elevation

















































Figure 5: Overall Methodology
4. FIELD WORK

4.1. Field Visit
The study team visited the field from 15th to 22nd of December 2005. During the field visit information regarding old river course, inundated areas and flood marks during large floods of the recent past, effect of flooding on infrastructures and settlements were collected. Apart from these local people were asked about socio-economic impact of flooding and their perception of flood hazard assessment. GCPs and the attribute table are given below.
GCPs


















Figure 6: GCPs


4.2 Validation of Flood Depths
A regression analysis was carried out between the observed and modeled flood depths for a discharge of 50-year return period that yielded a correlation coefficient of 0.88. This validation is based on observed flood marks in buildings, bridges etc of an extreme flood event of 2004 on specific sites, which was of the same order as that modeled and discussion with people. Hence not a fully conclusive assessment.





5. RESULTS AND DISCUSSION


5.1 Flood Discharges for Different Return Periods
Flood discharges for different return periods are obtained as follows.

Table 1: Flood discharges for various return periods
In order to obtain the flood discharges at different points along the reach under study, the flood at Karmaiya, the upstream end of the floodplain, should be routed with due consideration given to the lateral inflows and outflows. For want of sufficient information on cross-sectional data and tributary discharges, it has here been assumed that these two effects balance out and a peak flood of same magnitude as given by Normal Distribution has been assumed for the entire river reach.

5.2 Extraction of River Cross-Section
Figure 7: DEM of the study area
The terrain and river information in the form of cross section are extracted from the DEM in

the HEC-GeoRAS environment of GIS. Figure - 8 shows the DEM of the study area.
A typical cross section of the river at 33.757 km from Nepal-India border, the downstream end of the river reach under study is shown in Figure-9. The values in the ordinate indicate elevation above mean sea level.
Figure 8: Typical river cross section
The flow area of the river computed based on the channel and terrain geometry extracted from the DEM resembles to the ground situation of maximum river width in the central portion of the study reach and is shown in Figure-10.
Figure 9: Flow area along the river reach under study for a fifty-year flood
5.3 Computation of Water Surface Profiles
Flood flow simulation was carried out using HEC-RAS, a one-dimensional hydrologic model, by entering flow data and associated boundary condition. Water surface profiles, indicating water surface levels along the river reach under study, for floods of various return periods were computed with sub critical flow regime. Water surface profiles for floods of various return periods are shown in Figure-11.
The profile shows bank levels and flood water levels along the river. The river reach along which the banks are overtopped can be identified. Further analysis shows that major portion of the floodwater overflows the right bank of the river between 10 km and 30 km of the reach as shown in Figure-12. This explains the recurrent and intense flooding in Rautahat district including Gaur, the district headquarter. The water surface profiles can be used for fixing the top level of embankments in case they are to be constructed.
5.4 Preparation of Flood Hazard Map
Flood risk is defined in terms of fifty-year flood (Q50) and flood depth is considered as an indicator of the intensity of hazard. A XYZ plot generated by HEC-RAS simulation for Q50 is shown in Figure-13. The figure shows the area of the flood plain over which floodwater can spread.
The basic and primary issue for flood management is to identify the areas having higher hazard potential. Hazard can be taken as some threat to people, property and environment and vulnerability as the degree of loss to each elements at risk should a hazard of given severity occur. The issue of preparing hazard maps is of utmost concern within the scope of flood management for all involved in flood disaster mitigation to formulate strategies to deal with this natural hazard.
Figure 10: Water surface profiles for floods of various return periods

Figure 11: Channel and over bank flows along the river




































Note: The numbers indicate distance in meter from the downstream end of the river reach (Indo-Nepal border) under study.

Figure 12: XYZ plot generated by HEC-RAS simulation for Q50





Flood depth is considered as the most important indicator of the intensity of flood hazard (Islam et al. 2001, Townsend et al. 1998, Wadge et al. 1993 as cited by Sanyal et al. 2004). Flood hazard maps are prepared based on the estimated depth of inundation for a fifty-year flood (9750 Cumecs) by simulating the path of over bank flow from the main channel to the adjacent flood plain i.e. the flood-affected area. The approach assigns higher hazard denomination to areas having higher depth of inundation. The flood depth map for the study area is shown in Figure-14.
Figure 13: Flood Depth Map
Flood hazard maps are prepared for flood discharges of 2, 5, 20, 50 and 100-year floods. But the basis of flood plain management and regulation has been made for the hazard map of fifty-year flood.


5.5 Area Affected by Flood
A large area of Rautahat and Sarlahi district comprising of rural and urban settlement as well as agricultural land gets affected by flood. The most important area affected in terms of human settlement and public service facilities is the town of Gaur, the head quarter of Rautahat district. Figure-15 and Table-2 show the extent of inundation and flood depths in different parts of the municipality due to a fifty-year flood.
Figure 14: Flood Depth Map of Gaur Municipality
Table 2: Extent of inundation of Gaur Municipality

There are 99 village development committees (VDCs) and one Municipality in Rautahat district whose total area is 1033 sq. km. Out of these 68 VDCs and one municipality (641 sq. km.) are within the study area. The inundated area comes out to be 414 sq. km. Similarly the total area of the 100 VDCs in Sarlahi district is 1269 sq. km. And the area of flood affected 36 VDCs is 405 sq. km. The analysis shows that an area of 191 sq. km. gets inundated during design flood. Details of inundation area of all VDCs for Rautahat and Sarlahi districts and their ranking based on hazard indicators computed as follows are given in tables-4 and 5.

5.6 Hazard Indicators
The first hazard indicator HI1 in terms of area for 50 –year flood is calculated as:

HI1 = (FA/TA)x100

Where,
FA is the flooded area of the VDC and TA is the total area of the VDC.

The second hazard indicator HI2 in terms of depth for 50-year flood is calculated as is calculated as:

HI2 = (FD/TA)x100

Where,
FD is the flooded area within the VDC having flood depth greater than 1m and TA is the total area of the VDC.

Hazard ranking is done based on HI1 and HI2 as follows.

HI1 > 50, HI2 > 50 High Hazard

HI1 > 50, HI2 < 50 Medium Hazard

HI1< 50, HI2 < 50 Low Hazard


The Photo given below shows the Gaur Municipality area during flood on July 31, 2003.

(Source: Sharma et. al., 2004)
5.7 Assessment of Agricultural Damage
In an agrarian economic setting of rural Nepal, estimation of agricultural damages requires due attention. It is said that crop losses alone account on average for about 70% of total damage caused by floods (Ghani, 2001). Monsoon flood, from June to September, often ruins the economy by damaging the standing paddy. This increases the importance of remote sensing in assessing crop damage over large spatial extent.
5.8 Importance of Digital Elevation Model (DEM)
In this study, as in majority of other studies, digital elevation model is used to visualize the interface of floodwater with terrain and to simulate the inundation area and flood depth. Hence the results are largely dependent on the accuracy of the DEM and data for creating an accurate DEM are rarely available in developing countries. In this study the DEM is based on digital data of contour and spot elevation (main contour interval is 10m and supplementary contours are at an interval of 5m). Though the flooded area in general and depth at some specific locations were verified in the field based on people’s recollection of an extreme flood event of 2004 that was of the same order as that modelled, comparison with actual flooded area derived from satellite images could not be done due to non availability of satellite images capturing peak floods.
In a flat flood plain, it is likely that a vertical error of 1m in the DEM may lead to an error of 100s of square kms. in inundation area estimation(Sanyal et.al, 2004). Thus for the gently sloping topography, the resolution of the terrain data actually controls the accuracy of inundated area and flood depth. Hence high-resolution satellite imageries or aerial photographs are needed for preparing an accurate DEM, which can meet the precision level of a flood depth investigation.
5.9 Flood Hazard Map Based on Inundation Area and Flood Depth
A flood hazard map is prepared based on the indicators HI1 and HI2 discussed above and is given in Figure – 16. The summary of the findings is also tabulated in table - 3.
Table 3: Summary of Inundated area




Figure 15: Flood Hazard Map based on Inundation Area and flood depth
Table 4: Hazard ranking for Rautahat district
Table 5: Hazard ranking for Sarlahi district5.10 Population Affected by Flood
According to the census data of 2001 the total estimated population in Rautahat and Sarlahi districts are 545,132 and 635,701 respectively totaling to 1,180,833. Out of this the number of people living in the flood affected 88 VDCs. is 483,384. The number of people actually affected by flood comes out to be 208,000. The flood affected VDCs are mapped based on population density and are shown in Figure-17.



Figure 16: Population Distribution within the Flood Affected Area
5.11 Flood Hazard Map Based on Population affected
The population density of the study area varies from 160 per square km. to 2235 per square km. Based on the population density the VDCs are divided as follows:
Class Population density
1 1-750
2 750-1500
3 1500-2250
Hazard ranks were assigned accordingly i.e. a rank of 3 indicates a densely populated area being affected and are shown in Figure-18.

Figure 17: Hazard Ranking Based on Affected Population
5.12 Interactive Effect of Different Variables
The variables considered in the analysis are Physiography-Hydrology (P.Hyd) expressed through inundation area and flood depth, Land cover type (Lcov) and Population density (Pden). For assessing the interactive effect of P.Hyd and Lcov a ranking matrix of two dimensional multiplication mode is used. Similarly, for assessing the interactive effect of P.Hyd, Lcov and Pden a ranking matrix of three dimensional multiplication mode (Islam et.al., 2002) is used as explained in Figure-19.
Figure 18: 2 and 3 Dimensional Multiplication Mode of Variables for Ranking
5.11 Flood Hazard Map Based on Affected Land Cover Type
The vector layers of settlement and land use were superimposed on the satellite images to update the boundaries of settlements and different land uses. The Land use area for all the VDCs is computed for the following categories:
- Cultivation
- Forest
- Grass_Bush
- Sand_Barren
- Swamp_Lake
- River and Others
The findings are summarized in table- 6.
Table 6: Summary of Land Cover Types of the Flood Affected VDCs.
These categories are further re-grouped into 4 categories as follows considering the potential loss due to flood:
1.Cultivation
2. Swamp_Lake
3. Forest + Grass_Bush and
4. Sand_Barren + River + Others
The land use map is shown in Figure-20.
Figure 19: Land use Map

The percentage area covered by the four re-grouped land use types is computed for all the VDCs. Weighted score is assigned for these re-grouped land categories using the following relationship.
Weighted score = 4xL1 + 2xL2 + 1xL3 + 0xL4
where L1, L2, L3, and L4 are the percentage of area covered by the land use categories Cultivation, Swamp_Lake, (Forest + Grass_Bush) and (Sand_Barren + River + Others) respectively.

The degree of damage by flood to particular land type is taken care of by the coefficients 0, 1, 2 and 4 implying that damage to cultivated land incurs highest loss. These computations are shown in table –7 and table – 7a with weighted score and hazard rank. Points for quantifying hazard rank are computed on the basis of linear interpolation between 0 and 100, where 0 corresponds to the lowest i.e. 0 and 100 corresponds to the highest weighted score i.e. 409.37 as shown in the above-mentioned tables. Hazard ranks of 1-3 are assigned to a particular VDC for 0-33, 33-66 and 66-100 points respectively. After combining the effects of inundation area and flood depth with land cover categories being affected, hazard ranks ranging from 1-9 are obtained as shown in tables 7and 8. The hazard map is shown in Figure – 21.






























Figure 20: Hazard Ranking Considering Inundation Area, Flood Depth and Land Cover
Achalgadh, Badaharwa, Balara, Dumariya, Gadahiya and Mdhopur are among the highest ranking VDCs.
Table 7: Percentage of Land Cover of Different Categories and Hazard Ranks
Table 8: Percentage of Land Cover of Different Categories and Hazard Ranks5.12 Flood Hazard Map Considering all Variables

Finally a hazard map combining population affected with physiographic, hydrologic and land cover type is prepared based on the three-dimensional matrix concept. The ranking of different VDCs are computed and shown in tables 7 and 8. Ten hazard ranks are possible out of which 8 are obtained and shown in Figure – 22. None of the VDCs showed a worst combination of all the variables to obtain a possible rank of 27. (Please refer Figure-19.) Badaharwa, Balara, Bhediyahi, Dumariya, Gadahiya, Garuda Bairiya, Hajmaniya, Jayanagar, Madhopur, Mahammadpur, Mudbalba, Potiyahi, Gaur Municipality, Hathiaul are ranked as the highest flood hazard areas. These indicate priority areas for countermeasures. Comparison of final hazard map with the one without population revealed changes in priority areas for countermeasures.

Figure 21

The changes in ranks considering different variables and their combination at a time can be compared from figure-23.
Figure 22: Changes in Hazard Ranks with Combination of Different Variables6. MITIGATION MEASURES


6.1 Flood Damage Mitigation Measures
The three general strategies for reducing flood losses are:
· By modifying the flood - in order to keep the flood water away from people. This can be achieved through measures for reducing runoff e.g. watershed management, lowering flood peak by constructing flood control reservoirs, by constructing river training works etc.
· By reducing the susceptibility to damage – this can be achieved by keeping people and development works away from flood hazard area. The important measures involved in this strategy are flood plain regulations, flood proofing and flood forecasting and warning with an evacuation plan.
· By reducing the impact of flooding – this is meant to reduce the distress of the people at the time or after the flood through emergency measures such as flood fighting, evacuation, flood insurance and provision of relief and recovery.
The long-term flood regulation measures consisting of both structural and non-structural measures are not addressed here. A flood hazard map providing easily understandable information on inundation area and flood depth together with possible safe shelters, evacuation routes etc. could be useful in minimizing damage in case of an event. Such information would be of immense help for agencies involved in disaster management.
6.2 Construction of Levees
The analysis shows that floodwater mainly spills through the river section between 10 km and 30 km along right bank. This happens even during floods of smaller magnitudes i.e. of 5-year return period. This explains the reason for recurrent flooding in Rautahat district including Gaur, the district headquarter. The length of riverbanks on both sides is 106 km out of which, at least, the above-mentioned 20 km part is to be embanked. The study thus has helped in identifying the river reach to be embanked suggesting proper use of the ever-scarce funds.
6.3 Early Warning System
The flood hazard maps can be prepared for different discharges, which can be interpreted by making use of stage versus discharge curve (Figure-24) of a gauging station in an upstream location shown in Figure-25 and appropriate warnings can be issued accordingly taking advantage of the lead time that would be of the order of 7-10 hours.

Figure 23 : Rating curve






























Figure 24: Location of gauging station
6.4 Flood Plain Regulation and Zoning
Increased encroachment of flood plains has been responsible for ever-growing damage over the years. The basic concept of flood plain management is to regulate the land use in flood plains in order to restrict the damage due to floods, while deriving maximum benefit from those. This can be done by determining the location and extent of the areas likely to be affected by floods of different magnitudes/frequencies and to develop those areas in such a fashion that the resulting damage is minimal. Flood plain zoning, therefore, aims at disseminating information with the association of people, civil servants and NGOs on a wider basis so as to regulate indiscriminate and unplanned development in flood plains, both for unprotected and protected areas. Flood-plain zoning recognizes the basic fact that flood plains are essentially ruled by the whims of river flows, and as such all developmental activities in flood plains must be compatible with the flood risk involved.

To regulate flood-plain use, it is recommended to divide the land into three categories:

Category 1 (Prohibitive) - River channel and floodway i.e. the extent to which even the smaller floods (5-years’ flood) spread and areas having flood depths greater than 1.0m during design flood (50-years’ flood).

Category 2 (Restrictive)- Extent to which inundation is caused by design flood but flood depths are less than 1.0m.


Category 3 (Safe) – Areas not inundated by design flood and having flood depths less than 0.5m within the inundation area of design flood.

It is also recommended to use
· First category for pastures, playgrounds etc
· Second category for residential areas and agriculture; and
· The third category land for essential services such as hospitals, electrical installations, water supply, telephone exchange, aerodromes, railway stations, commercial centres, defence installations, industries, etc..

However, it should be realized that people partici­pation is essential for land use regulation and these measures are not easy to apply simply by making rules and through administrative processes. This requires public awareness and cooperation. It is desirable therefore that the above views be made known to the public through NGOs by organizing seminars and symposiums and through mass communication.
6.5 Flood Proofing
It has been suggested that all buildings within the flood affected area be constructed having plinth level 0.50m above high flood level (HFL) for the design flood.

6.6 Raised Platforms for Shelter
These are raised earthen platforms to provide temporary shelter to people and livestock of the affected villages, which get marooned frequently and suffer from acute hardship due to disruption of basic civic amenities and communication links. The platforms are built near or in the villages. Settlements having no access to dry areas within a radius of 1 km are considered to be provided with sheds in such platforms. It is recommended to build them 60 cm above design flood level and to provide with public conveniences. The platforms are connected to either all-weather roads or service roads on embankments for the emergency needs of the people. The raised platforms are to be constructed with the people participation. Figure-26 shows the schematic concept of raised platform proposed in Rajwada village of Rautahat district.
6.7 Restructuring the Cropping Pattern
There is a wide scope for growing crops including rice during the relatively flood-free period of the year, which is more productive because of better response to fertilizer and of more sunshine hours. Therefore, it is advised to restructure the cropping pattern based on local agro-climatic conditions.
HFL
0.70 m
0.60 m
Ground Level


















Figure 25: Schematic Concept of Raised Platform

7. LIMITATIONS


A high resolution and precise DEM is required for obtaining accurate results for which data like high-resolution satellite imageries or aerial photographs are not available in Nepal. The DEM used in this study can have satisfactory information in the over bank areas, but not as good as required in the main river channel.
The inundation area obtained by flood flow simulation could not be verified by comparing with actual flooded area derived from satellite imageries due to non-availability of satellite images capturing floods.
The commonly available optical images could not be used for crop damage assessment due to cloud cover that usually appears during rainy season, the time when crops are damaged.
Though utmost effort has been made to consider the damaging effect of flood upon various variables considered in the analysis, assignment of weights to those variables for arriving at hazard ranks could be argued upon as being subjective.
8. CONCLUSION AND RECOMMENDATIONS


The probabilities of occurrence of floods of different return periods that may cause disaster are computed by frequency analysis of past flood records. In this study flood risk is defined in terms of fifty-year flood and flood depth is considered as an indicator of the intensity of hazard. A GIS environment has been used to study interaction between hydrologic, topographic and socio-economic parameters in a spatial dimension considering Village Development Committees (VDCs), the lowest level political/administrative boundaries, as the unit of study. Inundated areas as well as areas under different flood depths were delineated. Flood hazard maps were prepared considering inundation area, flood depth, land cover type and population affected. Hazard ranking has been done based on three-dimensional multiplication mode matrix. VDCs and river sections to be accorded priority for countermeasures have been identified. Also measures have been suggested for flood plain regulation and flood proofing including minimum plinth levels for buildings. The results obtained provide essential information to formulate strategies for flood control planning and construction and development of flood countermeasures.

This type of flooding requires rapid localized warnings and immediate response by affected communities. Hence, it is recommended that the communities be trained/told about what to do if the warning comes. Without this even a sophisticated warning system is useless.

Further, we recommend continuing the study for complete flood risk assessment, which can be regarded as a cascade of the following operations.
· Improving the DEM using high-resolution satellite images (ALOS – PRISM and PALSAR).
· Alternative validation of the results using satellite images capturing peak floods (ALOS – PALSAR).
· Upgrade land use classification-using images of the main cropping season (ALOS – PALSAR).
· Preparation of flood velocity maps.
· Computation of propagation and residence time.
· Vulnerability assessment of the area.
· Stage versus flood damage estimates.
· Production of flood risk maps.
· Mitigation measures
We expect that with the launch of ALOS, high-resolution satellite images would be made available to create DEM for better accuracy of terrain data that would enhance the quality and reliability of hazard maps and risk assessment.
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[1] Department of Water Induced Disaster Prevention, Kathmandu, Nepal
[2] Survey Department , Kathmandu, Nepal