Grant 0299-NEP: Water Resources Project Preparatory Facility

Transcription

1 Document Produced under Grant Project Number: May 2016 Grant 0299-NEP: Water Resources Project Preparatory Facility Final Report Volume 1.1 Prepared by Pvt. Ltd. For Ministry of Irrigation, Government of Nepal Department of Irrigation, Government of Nepal This document does not necessarily reflect the views of ADB or the Government concerned, and ADB and the Government cannot be held liable for its contents.

2 GOVERNMENT OF NEPAL Ministry of Irrigation Department of Water Induced Disaster Prevention Technical Assistance Consultant s Report Grant No NEP: Water Resources Project Preparatory Facility May 2016 Package 3: Flood Hazard Mapping and Preliminary Preparation of Flood Risk Management Projects Final Report VOLUME 1 Prepared by Lahmeyer International in association with Total Management Services

3 GOVERNMENT OF NEPAL Ministry of Irrigation Department of Water Induced Disaster Prevention FINAL REPORT VOLUME 1 MAIN REPORT Water Resources Project Preparatory Facility Package 3: Flood Hazard Mapping and Preliminary Preparation of Flood Risk Management Projects Grant No NEP MAY 2016

4 This consultant s report does not necessarily reflect the views of the ADB or the Government concerned, and ADB and the Government cannot be held liable for its contents. All the views expressed herein may not be incorporated into the proposed project s design.

5 i ABBREVIATIONS ADB Asian Development Bank AEP Annual Exceedance Probability AOGCM Atmosphere-Ocean General Circulation Model APL Annual Probability of Loss AR4 IPCC Fourth Assessment Report AR5 IPCC Fifth Assessment Report ASTER Advanced Spaceborne Thermal Emission and Reflection Radiometer ATE Automated Terrain Extraction BCR Benefit Cost Ratio CBA Cost Benefit Analysis CBS Central Bureau of Statistics CCKP Climate Change Knowledge Portal (World Bank) CGIAR-CSI Consortium for Spatial Information CMIP5 Coupled Model Inter-comparison Project Phase 5 CRED Centre for Research on the Epidemiology of Disasters DEM Digital Elevation Model DGPS Digital Global Positioning System DHM Department of Hydrology and Meteorology DoA Department of Agriculture DWIDP Department of Water Induced Disaster Prevention EM-DAT Emergency Events Database FHFRM Flood Hazard/Flood Risk Map FHRMP Flood Hazard Mapping and Risk Management Project FHR Flood Hazard Rating FHM Flood Hazard Map FoV Field of View (Camera) FRM Flood Risk Map GCM Global Climatic Model GCP Ground Control Point GDP Gross Domestic Product GIS Geographical Information System GLOF Glacier Lake Outburst Flood GUI Graphical user interface HADGEM2 Hadley Centre Global Environment Model version 2 HADCM3 Hadley Centre Coupled Model version 3 HEC Hydrologic Engineering Center HEC-HMS HEC - Hydrological Modelling System HEC-RAS HEC River Analysis System HPI Human Poverty Index HDI Human Development Index IGES Institute for Global Environment Strategies IRR Internal Rate of Return GCP Ground Control Point GoN Government of Nepal

6 ii ICIMOD IMF IPCC IRS LiDAR LRMP MCADD METI MoHA MoI MoSTE NAPA NASA NGII NGO NPR NPV NTDB RBMP RCM RCP RF RPC SRTM USGS VDC WRPPF International Centre for Integrated Mountain Development International Monetary Fund Intergovernmental Panel on Climate Change Indian Remote Sensing Light Detection And Ranging Land Resource Mapping Project Mountains of Central Asia Digital Dataset Ministry of Economy, Trade and Industry, Japan Ministry of Home Affairs Ministry of Irrigation Ministry of Science Technology and Environment National Adaptation Plan for Action to Climate Change National Aeronautics and Space Administration National Geographic Information Infrastructure Non-Governmental Organisations Nepali Rupee Net Present Value National Topographic Database River Basin Management Project Regional Climate Model Representative Concentration Pathways Rational Function Rational Polynomial Coefficient Shuttle Radar Topographic Mission United States Geological Survey Village Development Committee Water Resources Project Preparation Facility

7 iii CONTENTS VOLUME 1 MAIN REPORT VOLUME 2 APPENDIX A RAINFALL ANALYSIS AND CLIMATE CHANGE TRENDS APPENDIX B HYDROLOGICAL ANALYSIS AND MODELLING VOLUME 3 APPENDIX C HYDRAULIC MODELLING, HAZARD AND RISK MAPPING VOLUME 4 APPENDIX D BASIN SCREENING AND RANKING APPENDIX E CONCEPT NOTES FOR BIRING BASIN APPENDIX F CONCEPT NOTES FOR MAWA RATUWA BASIN VOLUME 5 APPENDIX G CONCEPT NOTES FOR LAKHANDEHI BASIN APPENDIX H CONCEPT NOTES FOR EAST RAPTI BASIN APPENDIX I CONCEPT NOTES FOR WEST RAPTI BASIN APPENDIX J CONCEPT NOTES FOR MOHANA BASIN

8 iv MAIN REPORT CONTENTS I. EXECUTIVE SUMMARY... 1 II. INTRODUCTION... 6 A. Background... 6 B. Project Components and Output... 7 C. Sequence of Reporting... 8 D. Delays due to Political Unrest and Fuel Shortages... 8 E. Layout of the Report... 9 III. DATA AVAILABILITY A. Satellite Imagery and DEMs B. Scanned Topographic Maps C. Other GIS Layers D. Surveyed Cross-sections E. Hydrometeorology F. Sediment Data G. Climate Change Data H. Other Data I. Background reports IV. GENERATION OF DIGITAL ELEVATION MODELS A. Introduction B. Available Data CARTOSAT Images Ground Control Points GIS Data Layers C. Projection System D. Photogrammetry processing Evaluation of Image Quality Preparation of the Block file by selecting the Geometric Model Settling up internal geometry Adding GCP and automated tie point generation Adding GCP and automated tie point generation DEM Extraction V. CLIMATE CHANGE ANALYSIS AND HYDROLOGICAL MODELLING A. Rainfall Evaluation B. Climate Change Effects on Rainfall AR4 Output from DHM Climate Portal AR5 GCMs from World Bank Climate Change Portal CMIP5 (AR5) Validity of GCM Results with respect to Flood Calculations Evidence based instrumental trend analysis Pragmatic Approach C. Hydrological Modelling HEC HMS Modeling D. Sediment Analysis... 45

9 v VI. HYDRAULIC MODELLING AND GENERATION OF HAZARD AND RISK MAPS A. General B. Hazard Rating C. Flood Risk Map D. Greenbelt VII. BASIN SCREENING A. Introduction B. The Flood Record Database C. Frequency of Flood Events by Basin D. Reported Flood Damage as an Estimate of Vulnerability E. Socio-economic Characteristics of Basin Modeled Areas F. A Test of Robustness of Ranking G. Conclusions VIII. IDENTIFICATION OF PRIORITY PROJECTS A. Introduction B. Type of Interventions IX. COST BENEFIT ANALYSIS A. Methodology of the CBA B. Without-project Population and Land Use in Priority Basins C. Description of With-project Interventions D. Results of the CBA in Priority Basins E. Sensitivity Analysis X. PRIORITY PROJECTS A. Introduction B. West Rapti Basin C. Mawa Ratuwa Basin D. Lakhandehi Basin E. Biring Basin F. Mohana Basin G. East Rapti Basin XI. SUMMARY AND RECOMMENDATIONS A. Summary B. Recommendations for further work in the Terai XII. REFERENCES

10 vi LIST OF FIGURES Figure 1: Location of 25 Study Basins... 7 Figure 2: CARTOSAT-1 Satellite Image Coverage in the Study Area Figure 3: Location of DGPS points/cross Sections Figure 4: Stream Gauging Stations at the Upstream End of the Study Areas Figure 5: Sheet Index for the Topographic Base Map Figure 6: Digital Elevation Model - Mawa Ratuwa Basin Figure 7: Digital Elevation Model - East Rapti Basin Figure 8: Various Climate Change Scenarios Figure 9: Location of Rainfall Stations and Grids Used for World Bank CCKP Modelling in the Terai Region Figure 10: Location of Stations used for 24 Hour Maxima Rainfall Trend Analysis Figure 11: 24 Hour Maxima Rainfall Trends in the Terai and Siwaliks Figure 12: Mohana Annual 24 hr Maximum Rainfall Figure 13: HEC_HMS Representation of Basin Figure 14: West Rapti - Calibration Figure 15: West Rapti - Validation Figure 16: Sediment yield at Mainachuli on Kankai River Figure 17: Time to Peak Flow in Biring Basin with Climate Change Figure 18: Maximum Flood Depth - 1 in 50 years plus Climate Change - Mohana Basin Figure 19: Maximum Flood Velocity - 1 in 50 years plus Climate Change - Mohana Basin Figure 20: Maximum Flood Hazard - 1 in 50 years plus Climate Change - Mohana Basin Figure 21: Maximum Flood Risk - 1 in 50 years plus Climate Change - Mohana Basin Figure 22: Greenbelt - Mohana Basin Figure 23: Typical Flood Embankment Figure 24: Typical Solid Spur Figure 25: Typical Sloping Spur Figure 26: Typical Anti-Flood Sluice Figure 27: Typical Check Dam Figure 28: Proposed Flood Mitigation Measures in West Rapti Basin Figure 29: Proposed Flood Mitigation Measures in Mawa Ratuwa Basin Figure 30: Proposed Flood Mitigation Measures in Lakhandehi Basin Figure 31: Proposed Flood Mitigation Measures in Biring Basin Figure 32: Proposed Flood Mitigation Measures in Mohana Basin Figure 33: Proposed Flood Mitigation Measures in East Rapti Basin

11 vii LIST OF TABLES Table 1: Data Available from the Department of Survey Table 2: Open Source GIS Data for Nepal Table 3: Available Hydrometric Stations Table 4: Availability of Demographic and Socio-Economic Data Table 5: Classification of Flood and Inundation Area Table 6: Flood Zone Categories Table 7: Availability of Flood Hazard Maps Table 8: CARTOSAT -1 Sensor Specifications Table 9: CARTOSAT-1 Orbit Characteristics Table 10: Sheet Index of the GIS layers acquired to fill the gaps in the satellite image coverage Table 11: Average Percentage increase in July Rainfall using Sixteen GCMs from World Bank CCKP for the Terai Region Table 12: Average Percentage increase in July Rainfall using Sixteen GCMs from World Bank CCKP for the Himalayan Region Table 13: CCKP 16-Model-based Average Rainfall increases (%) for Climate Change, RCP4.5 Scenario Table 14: List of Stations used for 24 Hour Maxima Rainfall Trend Analysis Table 15: Flood Hazard Thresholds Table 16: Matrix of Flood Risk Scores Table 17: Flood Risk Thresholds Table 18: Frequency of Reported Flood Events by Basin, Table 19: High Impact Flood Events by Basin, Table 20: Consistently High Ranked Basins Flood Frequency and Magnitude Estimates Table 21: Selected Socio-economic Indicators by Basin Modelled Area Table 22: Ranking of Socio-economic Indicators by Basin Table 23: Linear Regression: Flood Magnitude Regressed on Population, Quality of Housing and Livestock Numbers Table 24: Ranking of Basin Model Areas and Selection of Basins for Pre-feasibility Study Table 25: Tabulation of Estimated Economic Benefits with Project from Future Floods with Climate Change Table 26: Tabulation of Estimated Costs by Project, NPR m Table 27: Urban and Rural Population of Priority Basins Table 28: Agricultural and Non-arable Areas of Priority Basins (ha) Table 29: Agricultural Area as % of Arable Area Table 30: Hectares per Rural House Table 31: Proposed With-project Interventions in Priority Basins Table 32: Financial Indicators for Projects in Priority Basins (NPR m) Table 33: Saved Casualties Attributed to Proposed Projects in Priority Basins Table 34: Switching Values for Projects in Priority Basins Table 35: Summary of Key Features of Priority Projects... 91

12 1 I. EXECUTIVE SUMMARY 1. The Asian Development Bank (ADB) and the Government of Nepal have tasked the Water Resources Project Preparation Facility (WRPPF) under the Ministry of Irrigation (MoI) to identify and prepare high priority water resources management projects for potential funding by the government, with assistance from ADB and/or other development partners. It comprises of four main consulting packages of which this study is Package 3: Flood Hazard Mapping and Risk Management Project (FHRMP) 2. To enable WRPPF to achieve their aim, flood hazard and risk maps which take into consideration the impacts of climate change are required to enable decision making and planning of flood management and water resources infrastructure. 3. Of the 102 rivers flowing into the Terai region identified by DWIDP as being prone to flood hazards, this project was required to study 25 specified river basins as shown below. 4. The main tasks included a review of the field surveys outsourced by DWIDP, processing of high resolution satellite ortho-images, development of a digital elevation model (DEM) of the project area to be modelled, hydrological and hydrodynamic modelling, preparation of flood hazard/flood risk maps with climate change and preparation of concept notes for interventions to pre-feasibility level for projects in 6 priority basins to be selected from the 25 study basins. 5..A review of the surveyed river cross-sections identified a number of anomalies which included mismatches against satellite imagery, intersecting cross-sections, gaps in river reaches where no surveys were carried out and cross-sections along the Nepal-India border which was outside the study area. In discussions with the Client and their outsourced surveyors, it was explained that these anomalies were due to access issues, and the lack of well defined border marker posts. It was also explained that the rivers in the Terai are dynamic and change course from one rainy season to another and the surveys were done in 2014 as per the field conditions at the time. It was agreed that only suitable cross-sections would be used for the hydraulic modelling and additional cross-sectional data where required would be extracted from the DEMs generated from satellite imagery. 6. CARTOSAT_1 satellite imagery was provided by the Client as Orthokit GeoTiff format. The images were processed using the ERDAS Imagine LPS package. Only those images which covered our hydraulic modelling extent, which is less than the entire basin area were processed for generating the DEMs as shown in the figure above. A few gaps in the satellite image coverage were identified and it was agreed with the Client that these would be infilled with digital contour data from the Department of Surveys which was provided by the Client. DGPS points from the field surveys and other known locations were used as ground control

13 2 points. DEM s were generated for the hydraulic modelling extent in all 25 study basins. 7. Analysis of long term rainfall data was done to identify any evidence based trends in the data as a result of climate change. The analysis depicted a typical Gaussian distribution with no systematic trend going across Nepal from east to west. There was evidence of a northsouth trend attributable to changes in altitude. 8. A comparison of the results from 16 GCM models showed that all models predicted a zero or even negative trend for July rainfall. In the absence of any discernible trend, and bearing in mind that our area of interest is in the Terai belt, a pragmatic approach was adopted for incorporating effects of climate change. 9. Climate change rainfall data available for Nepal from the UK s HADGEM2 GCM model with the latest AR5 scenarios as a daily time series were downloaded from their website. A simple bias correction was applied to upscale the climate change data series to align with the historical series for the overlapping period of record. The modified climate change daily time series was then adopted for further analysis. 10. Extreme value analysis was done on the daily maxima series to extract the appropriate values for different return periods for the climate change scenarios. 11. HEC-HMS hydrological models were prepared for each study basin. Of these 5 were gauged basins and 20 were ungauged basins. The hydrological models in gauged catchments were calibrated against the partial gauged discharge record and then verified with the remaining series of record. For the smaller ungauged basins, parameters from Babai catchment which is representative of the Terai rivers were used as a reference to assign model parameters. 12. The HEC-HMS models were used to generate flows at various locations for use in the hydraulic models. These inflows were applied at the upstream boundaries of the hydraulic model and at intermediate points at confluences of tributaries as well as distributed flow. 13. HEC-RAS was used for hydraulic modelling. Models were set up and where necessary, additional cross sections were extracted from the DEM s. The models were run for the various scenarios under historic and climate change conditions. 14. The model results were used to generate maps of maximum flood inundation, maximum velocity and flood hazard as well as flood risk. Graphs of time to peak flow for the various simulations for different return periods which can be used to approximate the flood lead times were also plotted. 15. Various relationships were defined to assess the flood hazard which is a function of depth and velocity as well as a debris factor. Similarly, in the generation of flood risk which is a function of flood hazard and flood vulnerability, different weights were assigned to various land uses as a measure of their vulnerability. 16. To align with DWIDP s recently adopted flood management policy, a greenbelt zone or Zone Z1 was identified where development would be restricted to non-residential use. 17. Basin screening to identify 6 priority basins was undertaken on the basis of a number of factors related to the occurence of flooding events, flood severity, socio-economic indicators, and mortality statistics as well as local considerations and the desire to have them distributed across the new State regions. Flood damage data was extracted from the MoHA as well as other international databases such as the Dartmouth Flood Centre.

14 3 18. The 6 priority basins selected were Biring, Mawa Ratuwa, Lakhandehi, East Rapti, West Rapti and Mohana. 19. Field visits were carried out to verify the modelling results and obtain feedback from the residents on the flooding situation and the type of interventions appropriate in the priority basins. Socio-economic surveys were also carried out to obtain feedback and to identify the communities in the basin and those who would be affected by any interventions. 20. Based on the modelling results and field visits, a number of projects were identified in consultation with DWIDP for flood mitigation in the 6 priority basins. These consisted of structural and non-structural measures. They included flood embankments, bank protection works, check dams, anti-flood sluices, bio-engineering works, provision of early warning systems, training and capacity building as well as provision of flood shelters. 21. Designs of structures followed the DWIDP practice and unit cost rates applicable to each priority basin were used. The design standard adopted for the structures is for a 1 in 50 year plus climate change scenario. 22. The hydraulic models for the 6 priority basins were modified to include the flood embankments and maps for the with project scenario were generated. The areas protected from flooding were identified and were used in the economic analysis. 23. Economic analysis was done for the package of measures identified in the priority basins. A general model was prepared for the calculation of incremental avoided losses and incurred benefits between the without-project situation and the future with-project (with flood management) situation for all six Priority Basins. The model developed estimates avoided losses (the difference between losses experienced in the without and with-project situations) which are classified as: Direct losses: experienced as an immediate impact of a flood and dependent on flood magnitude and periodicity, for example damage or destruction of property and crops Indirect losses: losses experienced as a result of changing markets and technologies as a result of a history of periodic flooding, for example changes in food prices and flood prevention strategies. 24. Being directly proportional to a flood of specific magnitude and periodicity, direct losses are calculated in terms of an Annual Probability of Loss (APL). This is the sum of expected damages caused by a probability set of floods: damage resulting from each flood is multiplied

15 4 by the probability of occurrence of each flood. 25. The model also calculates tangible benefits. Tangible benefits are not dependent on flood probability and can be inserted in the Cost Benefit Analysis without adjustment for likelihood of occurrence. They are classified as: Indirect benefits: experienced as a result of changing markets and technologies as a result of flood management, for example improvements in crop technologies as a result of flood protection Direct benefits: resulting from initiatives within the flood management project itself, such as riverside plantations 26. The model also makes an attempt to calculate intangible losses and benefits, which include: Death and health impacts Psychological effects (e.g. fears of loss of life, anxiety about moving to temporary accommodation) Loss of irreplaceable items and items of sentimental value 27. The benefit estimate methodology does not make use of expected increases in land values with-project.but instead calculates and uses as a benefit of the annual change in productivity of land (reduction or elimination of direct losses plus indirect benefit of economic productivity increases) as a result of a publicly funded flood management. This is a major component of land price but excludes any speculative value accrued from land improvement, the costs of which have been assumed by government. 28. The table below shows the financial indicators for the projects in the priority basins for a 10% discount rate. Net Present Value, NPR m Internal Rate of Return Benefit Cost Ratio Financial With Climate Change Economic With Climate Change Financial Rank With Climate Change Economic Rank With Climate Change Financial With Climate Change Economic With Climate Change Financial Rank With Climate Change Economic Rank With Climate Change Financial With Climate Change Economic With Climate Change Financial Rank With Climate Change Economic Rank With Climate Change West Rapti % 10.7% Mawa Ratuwa % 10.5% Lakhandehi % 16.3% Biring % 2.7% Mohana % 20.6% East Rapti % 7.9% With the exception of Biring and East Rapti, all other basins have a positive economic Net Present Value (NPV) and economic benefit cost ratio of greater than Even though Biring and East Rapti have benefit cost ratios less than 1, they may be still be attractive from a social development perspective. If improving the quality of life and asset base of the poorest is a priority, than theoretically a lower social discount rate would be acceptable. East Rapti for example would require a discount rate of 8% and Biring a discount rate of 3% to improve NPV to zero and make the project acceptable for implementation. Lowering the discount rate would represent a subsidy from the country to a well-defined disadvantaged area which policy makers may well consider desirable. Such a social discount rate in some developed countries would be considered more than acceptable, especially those where bank rates are turning negative.

16 5 31. The key features of the priority projects are given in the table below. The total investment cost is US$ 55 m. Investment cost, US$ Benefit- Cost Ratio - Economic with Climate Change Total area of flood protection at 1:50 year flood with climate change, ha Agricultural area of flood protection at 1:50 year flood with climate change, ha Withproject number of houses protected in 2010 from 1:50 flood with climate change Length of embankment designed, km Solid Spurs nos Sloping Spurs nos Check Dams nos West Rapti 18,105, , , Mawa Ratuwa 11,202, ,502 1,286 1, Lakhandehi 7,243, ,302 2,284 1, Bering 10,134, ,221 1, Mohana 3,238, East Rapti 5,028, Total 54,952,712 7,693 7,133 6, All basins will have provision for Bio-engineering works, Early warning systems, Flood Shelter and Training and Capacity Building Anti- Flood Sluices nos 32. These package of flood mitigation measures may be taken forward for further analysis at the feasibility level. Even if the packages for East Rapti and Biring in their entirety may not be attractive, some components of the packages may still be suitable for further analysis. 33. The study has generated a number of useful deliverables including DEMs, flood inundation maps, flood velocity maps, flood hazard maps, flood risk maps, greenbelt maps as well as packages of projects at the pre-feasibility level. We would highly recommend that these outputs are disseminated to a wider audience and shared with agencies working in the Terai. 34. We have also made recommendations based on our experience and observations in the field from site visits, on ways to improve the study outcomes and ensuring that these models are updated as new data becomes available. Some of the recommendations are for the establishment of a centre of modelling excellence at the DWIDP, establishment of a digital inventory of all existing and planned flood mitigation structures to ensure a holistic view of the basin is taken for flood management. It is also recommended that greater liaison is done with the Indian authorities to monitor and understand their operational rules for flood control structures in India near the Nepal border which have an impact on the flooding situation in Nepal.

17 6 II. INTRODUCTION A. Background 35. The Asian Development Bank (ADB) and the Government of Nepal have tasked the Water Resources Project Preparation Facility (WRPPF) under the Ministry of Irrigation (MoI) to identify and prepare high priority water resources management projects for potential funding by the government, with assistance from ADB and/or other development partners. This initiative is consistent with the government s and ADB s priorities for enhancing climate resilience, ensuring food security and promoting inclusive economic growth. It comprises of four main consulting packages: (i) Package 1: Facility Management and Capacity Building (ii) Package 2: Community Managed Irrigated Agriculture Sector Project Additional Financing (iii) (iv) Package 3: Flood Hazard Mapping and Risk Management Project (FHRMP) Package 4: Preparation of River Basin Management Plans and Updating of National Irrigation, Inventory and Master Plan 36. WRPPF has been tasked to assist the Government in ensuring that critically important irrigation, drainage and flood risk management projects are implemented efficiently. To achieve their aim, flood hazard and risk maps which take into consideration the impacts of climate change are required to enable decision making and planning of flood management and water resources infrastructure. 37. DWIDP has identified 102 rivers emerging from the Siwalik Hills which are considered as being prone to flood hazards. Of these, 25 river basins have been considered under this project for preparation of high resolution flood hazard and flood risk maps as shown in Figure This work will be done under Package 3 which consists of two components: (i) (ii) Part 1: Field level cross-section survey to support the preparation of the flood hazard maps for the 25 basins. This work has been awarded separately and does not form part of this consultancy. Part 2: Review of field surveys, processing of high resolution satellite orthoimages, development of a digital elevation model (DEM) of the project area to be modelled, hydrological and hydrodynamic modelling, preparation of flood hazard/flood risk maps with climate change and preparation of concept notes for interventions to pre-feasibility level for six projects. 39. This consultancy is referred to as Package 3 and the scope is as per Part 2 outlined above.

18 7 Figure 1: Location of 25 Study Basins B. Project Components and Output 40. The main objectives of the project are to: (i) (ii) (iii) Produce climate change scenario based flood hazard/flood risk maps for the modelled areas in the 25 priority basins Recommend flood risk management interventions in the key priority areas identified in consultation with DWIDP and MoI. These may comprise both structural and non-structural measures to prevent, alleviate or manage flood risk from floods, sedimentation and river bank erosion especially in the densely populated and agriculture productive areas. Based on a selection criteria determined in consultation with DWIDP and MoI, and that identified in (ii) above, short list six sub-projects for which the consultants will prepare individual concept notes to a pre-feasibility level. This includes preparing: a) Pre-feasibility engineering designs based on recommended bestpractices and technologies b) Improved watershed and water distribution management c) Initial assessment of safeguard requirements

19 8 C. Sequence of Reporting d) Preliminary economic assessments. 41. A number of reports were produced during the course of the study and these are listed below. Inception Report Workshop 1 Progress Report 1 Interim Report Interim Report 2 Draft Final Report Workshop 2 Submitted on 12 June 2015 following remobilization after the Gorkha earthquake on 25 April A revised work schedule was presented. Held on 30 June 2015 to present the findings of the Inception report. A preliminary basin screening methodology was also presented at the workshop. Submitted in July 2015 and mainly reported on the gaps in the coverage of the satellite imagery required for modelling and the basin screening results based on available data. Submitted in Septermber 2015 and highlighted the difficulties due to political unrest and security issues as well as fuel shortages. Progress on the hydrodynamic modelling was reported and the basin screening process to select 6 priority basins was discussed. An additional report was submitted in November 2015 following discussions with the ADB and a contract amendment. The ongoing difficulties due to political unrest, security and fuel shortages as well as increased load shedding were highlighted. Progress on modelling was reported and baseline maps were produced. Submitted in February 2016 and presented the outcomes of the study. Held on 4 March to present the outcomes of the study and project deliverables to a wider audience of stakeholders and to receive feedback. D. Delays due to Political Unrest and Fuel Shortages 42. Considerable constraints were faced by the project during the study period from April 2015 to February In the first instance the study was disrupted by the 7.8 magnitude Gorkha earthquake which required the team to be demobilized and later on further disruptions were experienced due to political unrest, fuel shortages, security concerns in the Terai as well as increased load shedding and unreliable internet services. 43. This meant that some activities had to be done out of sequence and other activities were delayed due to factors beyond the Consultants control. In spite of these constraints, the study team optimised the rescheduling of activities to work around the constraints, minimize the delays and continue making progress. It is in this context that the study was carried out.

20 9 E. Layout of the Report 44. This report is the main report and summarises the key analysis and outcomes of the project. Details of the analysis are given in the accompanying Appendices in separate volumes of the report. 45. The reporting takes a sequential approach which generally mimics the order in which the analysis was carried out. The key steps in this study are: - Data collection and review - Satellite image processing and generation of DEMs - Climate change analysis - Hydrological modelling and generation of base case and climate change flows - Hydrodynamic modelling of base case and climate change scenarios - Basin screening to identify priority basins - Identification of flood mitigation projects in priority basins - Hydraulic modelling of with project scenarios - Design of projects in priority basins - Economic analysis - Preparation of concept notes

21 10 III. DATA AVAILABILITY A. Satellite Imagery and DEMs 47. Two types of data were provided by the Client. These included Rapideye and CARTOSAT_1 satellite imagery. Rapideye imagery covering the entire country was made available. However, these images were not provided as stereo pair images and therefore were not suitable for generating DEMs. 48. The coverage of the CARTOSAT_1 imagery used for the generation of DEMs for the study is shown in Figure 2. It covered a large part of the hydraulic modelling extent required for the study but there were some gaps in the coverage which needed to be supplemented with other sources of data. The generation of DEMs at a high resolution required for the study, covering the hydraulic modelling extent is described in detail in Section III. 49. A DEM with approximately 90m spatial resolution was also available from the NASA Shuttle Radar Topographic Mission (SRTM) program. This data is currently distributed free of charge by USGS and is available for download from the National Map Seamless Data Distribution System, or the USGS ftp site (ftp://e0srp01u.ecs.nasa.gov/srtm/version2/srtm3/). The vertical error of the DEM is reported to be less than 16 m. The SRTM data has some voids particularly in the mountainous area of Nepal, which constitute about 9.6% of the country area with some 32,688 voids accounting for 13,740 km 2. This is because of insufficiency of textural detail of the mountainous terrain. A hole-filling algorithm has been applied to generate continuous elevation surfaces by CGIAR-CSI and the infilled DEM can be used for hydrological modelling applications on a basin wide scale in Nepal. The SRTM data was used for hydrological modelling applications for the study as it covered the entire area of the 25 study basins. However, the DEM generated from SRTM data is not deemed to be of sufficient accuracy for carrying out hydraulic modelling in the flatter Terai region of Nepal where greater accuracy is required. 50. Contour maps from the Survey Department (1992) are also available as digital layers with 20m vertical contour intervals at a scale of 1:25,000 and 1:50,000. Since 1990, the Survey Department has been developing the National Topographic Database (NTDB) as a supporting and organising programme to provide national specifications and standards for topographic data: (scales 1:25,000/50,000), data codes, data formats and data quality. The vertical contour intervals of 20m are not deemed to be of sufficient precision for hydraulic modelling purposes in the flatter Terai region of Nepal. However, this data was made available to the project to supplement the gaps where CARTOSAT_1 imagery was not available. B. Scanned Topographic Maps 51. Scanned topographical maps for Nepal are available from the Mountains of Central Asia Digital Dataset (MCADD) which is a site ( that collects books, journals and maps related broadly to the Himalayas and its outlying attached ranges including the Hindu- Kush, the Karakorams, the Pamirs, the Tian Shan and the Kuen Lun as well as the Tibetan highlands and the Tarim basins. These materials are stored at this site and are freely distributed. This site has a collection of scanned maps of all the topographic maps produced by the Survey Department of Nepal (

22 11 Figure 2: CARTOSAT-1 Satellite Image Coverage in the Study Area

23 The scanned maps contain information on administrative boundaries, river network, landuse/cover, settlements, and road networks. C. Other GIS Layers 53. The Survey Department is transforming its products from traditional paper maps to digital format through its National Geographic Information Infrastructure (NGII) Programme. Datasets available at the Survey Department at a scale of 1:25,000 for the plain areas up to middle mountains, and at a scale of 1: for high mountains include geodetic data, administrative boundaries, transportation networks, buildings, hydrography, topography, utilities and land cover as shown in Table 1. These GIS layers provided the basic data inputs for carrying out spatial analysis for the study. Table 1: Data Available from the Department of Survey SN Types of GIS layers Major attributes 1 Administrative boundary 2 Contour map 20 m elevation intervals Ward boundary, VDC boundary, District boundary, Zonal Boundary, and Regional Boundary, and National border 3 River network Major river, seasonal rivers, sandy areas, river embankments, 4 Land use/cover Forest, Bush, Grasslands, built-ups, cultivated lands, sand, bare, etc. 5 Road networks Highway, Major roads, Feeder roads, Foot trails, Minor foot trails 6 Buildings Houses and buildings 7 Settlements Name of the settlement at the level of wards, district headquarters, market centres, 54. The latest landuse map, updated in 2014 was obtained in digital format from the President s Chure-Terai Madhesh Conservation Programme project. This project carried out extensive work in the Terai region and the landuse map prepared in 2014 was used in this study for preparing risk maps and for identifying the landuse in flood affected areas. 55. Under the Land Resource Mapping Project (LRMP) ( ) which was jointly implemented by the Survey Department and the Government of Canada, scientific surveys were conducted based on interpretation of aerial photographs and ground truthing and various maps were produced at a scale of 1:50,000. These include Land Utilisation, Land Systems, Land Capability, Geology and Climate maps. Supporting reports cover geology, land systems, land capability, land utilisation, agriculture and forestry, water resources, economics, and a summary report. However, these maps have not been updated since they were produced in 1978/79 and due to their non-digital format were only used as supplementary data. 56. Other sources of available open source GIS data are shown in Table 2 below. These layers were used as secondary sources of data. The soil map was used to assess the hydrological parameters for the modelling.

24 13 Table 2: Open Source GIS Data for Nepal Sn Data type Details Source 1 Administrative units International Border, Development Regions, Zones, Districts Diva GIS 2 River networks Water bodies, River network divagis.org/ 3 Road networks Primary and secondary routes 4 Elevation DEM 800X800m (.vrt format) datadown 5 Land cover Raster 800X800 m 6 Hydro 1 K 500 m DEM USGS 7 Land cover 300 m ESA 8 Contours 1:250,000 ICIMOD 9 Soil 1:500,000 ICIMOD 10 Land cover 1:500,000 ICIMOD D. Surveyed Cross-sections 57. The Client supplied river cross-sections in the study area covering all 25 basins as shown in Figure 3. The surveys were carried out in 2014 under a separate contract let by the Client, and was carried out by two Nepali surveying companies using the Digital Global Positioning System (DGPS). 58. The cross-sections were reviewed and were found to have a number of anomalies. Checks were made by plotting the cross-sections on Google images and checking their location and alignment as well as identifying river bank markers on the image and in the crosssection data. Although there was good correlation in many cases, there were a number of anomalies. 59. As can be seen in Figure 3, the surveyed cross-sections provided by the Client which were taken in the study area to aid the hydrodynamic modelling were not regularly spaced and were often taken along the international border between Nepal and India which was not included in our study area. Our understanding is that the cross-sections were to be restricted to areas at least 500m upstream of the international border. We also understand that the border is not well marked and there is some confusion as to where the border is actually located. 60. In discussions with the Client and their outsourced surveyors, we were informed that a comparison of the background satellite images used by them in 2014 when the surveys were carried out and the current images available on Google showed that in some areas there were significant differences in the channel alignment and that this was not unusual for the rivers in the Terai. These rivers change course from one season to another. They also explained that their Terms of Reference required them to concentrate their cross-sections around existing structures and to intersperse the remaining cross-sections to suit accessibility and other constraints encountered in the field. 61. The surveyors also said that there was no requirement to survey structures across the rivers or on the banks and such data has not been provided. They pointed out that there were few structures across the rivers and they all had high clearances and adequate waterway, such as the bridges across the rivers on the East-West highway and would not cause any flow restrictions.

25 It was also pointed out that the channel cross-sections surveyed in 2014 and provided by the Client were more likely to reflect the existing ground conditions in areas away from the main waterway as these would not be affected in the same aggressive manner when rivers were in full flow during the monsoon season. 63. It was therefore agreed with the client that where there were anomalies, some crosssections may need to be discarded, particularly those that were outside the project area and where there were gaps, cross-sections required for hydraulic modelling may need to be extracted from the DEMs generated from the satellite imagery. 64. For this study, it would be assumed that the structures across the main channels do not pose any restrictions to flood flows.

26 15 Figure 3: Location of DGPS points/cross Sections

27 16 E. Hydrometeorology 65. Rainfall data The Department of Hydrology and Meteorology (DHM) is the authorised government institute for collecting and delivering hydrological and meteorological data in Nepal. DHM provides quality controlled hydrological and meteorological data. The available long term rainfall data is the 24 hour cumulative rainfall total which is generally measured once a day at 8:45 A.M. Recently, DHM has also installed telemetric rain gauge stations for hourly readings. The DHM rainfall data are available in electronic format and published year books. Missing data is generally recorded as in the DHM rainfall time series. Rainfall data at a number of stations across the country was collected or compiled from DHM hydrological year books and details are shown in Appendix A and B. 66. Sub-daily rainfall data sub-daily rainfall data was not available for the representative stations in the 25 basins. This meant that storm pattern hyetographs could not be individually assessed. 67. Discharge data Only 5 of the 25 priority river basins are currently gauged as shown in Figure 4. The gauging stations of interest are located at the upstream end of the areas of interest for this study and the periods of record for which data are available are shown in Table 3. In general, gauge heights are recorded three times a day and converted to discharge measurements using the station rating curves. Recently, DHM has upgraded a few hydrometric stations to telemetric systems to collect real time short duration gauge height data. During the monsoon season, DHM also measure instantaneous maximum gauge heights to estimate the instantaneous maximum discharge. The yearly instantaneous gauge heights and corresponding discharges are published in DHM hydrological year books till 2006 and recent data is available in digital format. The daily discharge and instantaneous maximum discharge data collected is shown in detail in Appendix B. Ungauged catchments could not be calibrated. Gauged catchments could be calibrated to the downstream most gauging station in the basin. Table 3: Available Hydrometric Stations River name Station no. Location Period of data Remarks (outlet) availability Kankai 795 Mainachuli Mean daily data, instantaneous Narayani 450 Narayanghat maximum and minimum data; Data up to 2006 is published in East Rapti 460 Rajaiya hydrological year books West Rapti 360 Jalkundi and from is available Karnali 280 Chisapani in electronic format Source: DHM

28 17 Figure 4: Stream Gauging Stations at the Upstream End of the Study Areas 68. Instantaneous maximum discharge is available for the 5 gauged basins and this data can be used for carrying out flood frequency analysis. The rainfall records are of sufficient length (approximately 30 years) to enable long term rainfall-runoff modelling to be carried out to generate a time series of annual maximum discharges in the ungauged catchments which can then be used for flood frequency analysis. 69. Hydrometeorological data has been collated from DHM s published yearbooks until Recent data in electronic format has been requested from the DHM and is currently being processed. 70. Flood Levels Historic flood extent maps and flood level data were not available for the study area. Anecdotal evidence was gathered during site visits to indicate areas that were regularly flooded and the maximum extent of flooding in priority basins. These were checked against model results. F. Sediment Data 71. No sediment data was available in the study area except for a 5 year record for suspended sediment load in the Kankai Basin at Mainachuli which is located upstream of the hydraulic modelling extent. No data was available in the lower reaches of the Terai region. G. Climate Change Data 72. The latest projected rainfall data for Nepal based on representative concentration pathways (RCP) from the IPCC Fifth Assessment Report (AR5) are available on a daily basis and can be downloaded. However, the data are available at a poor resolution and are not bias corrected. This analysis is generally carried out by DHM but as yet they have not attempted to do so. This data was processed by the study team and used for modelling climate change scenarios.

29 Daily bias corrected projected rainfall based on the IPCC Fourth Assessment Report (AR4) for Nepal are available with DHM. However, this data is not available for public use as it is still to be verified. The projection was carried out using the PRECIS, RegCM and WRF regional circulation models. It may be noted that the AR4 models have now been superseded by the AR5 models. 74. Monthly projected climate parameters including monthly bias corrected rainfall parameters for the AR4 models are however, available and downloadable from the DHM climate change portal ( It provides monthly factors for climate change for different parameters relative to the baseline data. The data are available for grids ranging from 12 km x 12 km grid to 25km x 25 km grid. The length of projection is from 2030 to The DHM climate change portal is designed to facilitate the analysis of climate/meteorological, geographical and projection data using a publicly accessible webbased interface. It allows users to view the climate data on an interactive map and generate different information products including the export of the raw data. This data was not used as it is only available on a monthly time scale and the AR4 models have now been superseded by the AR5 models. H. Other Data 75. Socio-Economic data Data on population, types of houses, agriculture and some socioeconomic data has been published by Central Bureau of Statistics (CBS) from their latest census in A detailed Village Development Committee (VDC) level agriculture database is available at the Department of Agriculture (DoA). Table 4 shows the availability of various types of data which have been used to work out the socio-economic indicators and the basis for flood damage assessments. The data is freely available in published reports and some data can be downloaded directly from the CBS web portal. Table 4: Availability of Demographic and Socio-Economic Data Demographic and socioeconomic data Households, population and average household size Households by outer wall of house Households by foundation of house Population by age group and sex Household with livestock Households with economic activities Literacy rate Population projection Agriculture statistics Irrigation statistics Source CBS CBS CBS CBS CBS CBS CBS CBS DoA MoI 76. Data on demographics and population projections, housing types and some socioeconomic parameters are available at the VDC level. However, details of infrastructure and their geo-locations are not available. 77. Historic flood damage data including human and property losses are available from the Ministry of Home Affairs (MoHA) and the Department of Water Induced Disaster Prevention (DWIDP) for the period from Some of this data is not well documented. Other international disaster network agencies also maintain a database of major disaster events and record damage, area affected and loss data. Such databases include the OFDA/CRED

30 19 International Disaster Database (EM-DAT) and the Dartmouth Flood Observatory database. Data was available for the period from EM-DAT and for variable periods from the Dartmouth Flood Observatory database. 78. The location of flood disaster affected areas in the databases are generalised and range from the ward to the district scale. However, this allows for identification of river basins which would have been flooded during those events and have been used for estimating the relationship between the recurrence period of historical floods and magnitude of flood damages in the study basins. I. Background reports 79. A number of background reports were available for the study. These included: (i) Review of Flood Hazard and Flood Hazard Mapping in Nepal. (Shakya, B., 2013). This document provides a comprehensive background to the flood hazard mapping activities carried out in Nepal by various agencies including DHM, DWIDP, MoHA and ICIMOD as shown in Table 7. Many initiatives were directed towards implementation of community based early warning systems for floods. No account of climate change has been considered in previous modelling and most models are based on a steady state simulation using HEC-RAS or HEC-Geo RAS. The underlying DEM is based on the use of Aster or SRTM data which have a lower spatial and vertical resolution as compared to a DEM derived from CARTOSAT_1 satellite imagery. Very little survey data, if any, was used in the construction of these models and cross-sections were extracted from the DEM. Many of the flood estimates are based on empirical methods and not on the basis of hydrological models. It is not clear whether any of these models have been verified. (ii) (iii) (iv) National Adaptation Program of Action (NAPA) to Climate Change (GoN, MoE, 2010). This report has developed various vulnerability indices for each district relating to various aspects including overall climate change, flood, drought, landslide and glacier lake outburst flood vulnerability. The various indices provide a guide to the overall vulnerability of the area. However, some of the vulnerability indices do not tally with the historic frequency of flooding or severity of flood damage experienced in the various basins and the climate change projections are based on the IPCC Fourth Assessment Report (AR4) which has now been superseded. Climate change, changing rainfall and increasing water scarcity: An integrated approach for planning adaptation and building resilience of smallholder subsistence livelihoods in Nepal (IGES, 2015). This report focuses on the Karnali and Koshi river basins which are within the Ganges River Basin. It assesses water scarcity and its impacts on smallholder subsistence livelihoods in the context of climate change in Nepal and is not relevant to flooding situations. Economic Impact Assessment of Climate Change in Key Sectors in Nepal, Ministry of Science Technology and Environment (MoSTE), (GoN, January 2013). This study is aimed at the national level and focuses on the economic impact of climate change on different sectors viz. water (hydropower, water induced disaster) and agriculture. It has considered two alternative approaches for producing downscaled data - empirical (statistical) downscaling and Regional Climate Model (RCM) outputs. The study considers around 9 models and downscales the data to individual meteorological stations. The methodology has not been widely accepted and recent AR5 models would supersede some of the findings.

31 20 (v) (vi) Case Studies on Flash Flood Risk Management in the Himalayas in support of specific flash flood policies (ICIMOD, 2013). The study is focused on the Hindu Kush Himalaya and looks at the Bhote Koshi/Sun Koshi basins as well as Lal Bakeya and Madi basins in Nepal. It looks at flood risk management of GLOF and flash flooding through structural and non-structural measures. In this context, flood forecasting models developed by DHM play a pivotal role in providing lead times and training of local people to respond. Water Induced Disaster Management Policy (DWIDP, 2016). This document sets out the recently adopted aims and objectives as well as policies of the DWIDP.in relation to water induced disaster management. Some of the key elements are to ensure that there are legal and institutional structures set up to guide the workings of the agency. Disaster prone areas will be categorized on their level of vulnerability and only appropriate development compatible with their vulnerability category will be permitted in such areas. All mitigation works will need to be compatible with a basin plan and support the overall watershed management policy. Table 5 and Table 6 show the various categories of vulnerability being considered and the appropriate activities permitted in each zone. Table 5: Classification of Flood and Inundation Area S.N Vulnerability Category Flood Return period Zone Remark 1 Bank area 2 year Z0 Bank full discharge 2 Highly vulnerable 2-5 year Z1 3 Vulnerable 5-25 year Z2 4 Moderately vulnerable year Z3 5 Not vulnerable 100 year and above Z4 base flood Table 6: Flood Zone Categories S.N Zone Description of permitted use Remark 1 Z0 River bank area Protected area for river flow 2 Z1 Agriculture, vehicle parking, recreational park 3 Z2 All the activities of Z1 and residential area permitted on high plinth Personal and settlement development prohibited 25 yr return period flood level + 50 cm plinth level 4 Z3 All the activities of Z1 and Z2 including settlement development, public buildings, schools, hospitals and emergency centres 5 Z4 It can be used as per its present application 50yr return period flood level +50 cm plinth level Strategic structures such as shelters, utilities, large industries, power stations Note: a) Those areas which do fall under any of the above categories should leave at least 10m to the river bank b) The above rules are applicable even in areas where embankments have been constructed

32 21 River Name Flood Hazard Mapping Location Narayani 27 41'59.38"N 84 25'12.69"E West Rapti Tinau Babai 27 51'41.99"N 82 27'31.49"E 27 34'33.57"N 82 59'12.22"E 28 4'52.84"N 82 14'48.34"E Bagmati 27 1'39.93"N 85 23'52.60"E Kamala Kankai Lothar Kankai Tinau Dono River 27 0'3.09"N 86 13'50.53"E 26 37'7.50"N 87 55'9.47"E 27 35'6.02"N 84 43'54.11"E 26 37'7.50"N 87 55'9.47"E 27 37'33.57"N 82 59'59.22"E 27 38'37.69"N 82 59'43.33"E Narayani 27 41'59.38"N 84 25'12.69"E West Rapti Karnali Koshi 27 51'41.99"N 82 27'31.49"E 26 37'7.50"N 87 55'9.47"E 26 19'31"N 87 12'00"E Bagmati 27 42'36.84"N 85 16'14.26"E Bagmati 27 42'36.84"N 85 16'14.26"E Ratu Mohana 26 o o Table 7: Availability of Flood Hazard Maps Cross Section Generated from DEM Generated from DEM Generated from DEM Generated from DEM Generated from DEM Generated from DEM Generated from DEM 1 surveyed Generated from DEM DEM Implementing Agency Aster 30m MoHA Aster 30m MoHA Aster 30m MoHA Aster 30m MoHA Aster 30m MoHA Aster 30m MoHA Aster 30m MoHA Survey Dept. 1: Survey Dept. 1: surveyedgenerated surveyedgenerated +50 Survey Dept. 1:25000 Survey Dept. 1:25000 University Thesis University Research Funding Agency GFDRR/ World Bank GFDRR/ World Bank GFDRR/ World Bank GFDRR/ World Bank GFDRR/ World Bank GFDRR/ World Bank GFDRR/ World Bank University Research Remarks Field survey was not mentioned Field survey was not mentioned Field survey was not mentioned Field survey was not mentioned Field survey was not mentioned Field survey was not mentioned Field survey was not mentioned GPS survey carried out Method HEC Geo RAS HEC Geo RAS HEC Geo RAS HEC Geo RAS HEC Geo RAS HEC Geo RAS HEC Geo RAS HEC Geo RAS NAPA - HEC Geo RAS DWIDP Nepal gov. - HEC RAS DWIDP Nepal gov. - 4 surveyed SRTM 90 DHM Nepal gov. Inundation Map HEC Geo RAS 1 surveyed SRTM 90 DHM Nepal gov. FHM HEC Geo RAS 4 surveyed 1m vertical SRTM 90 DHM Nepal gov. Inundation Map HEC Geo RAS 4 SRTM 90 DHM Nepal gov. Inundation Map HEC Geo RAS 30 ALOS 2.5m satellite image 30 ALOS 2.5m satellite image 1 surveyed Generated from DEM DWIDP Nepal Gov. field surveyed for cross section DHM Nepal Gov. field surveyed for cross section SRTM 90 ICIMOD ICIMOD Research project Genesis Mercy Corps Nepal Hec Geo RAS Hec Geo RAS Hec RAS

33 22 IV. GENERATION OF DIGITAL ELEVATION MODELS A. Introduction 80. Digital Elevation Models (DEMs) are required for carrying out hydrological and hydrodynamic modelling. To ensure reliable results, high resolution DEMs are necessary. This is of particular relevance in the context of this study as (i) (ii) the topography in the Terai region of Nepal where the study areas are located is relatively flat to gentle. In such areas, small variations in the water levels can mean a large difference in the area that would be inundated. the rivers in the study area are dynamic in nature and often change course from one season to another as channels are modified due to bank erosion, deposition of debris and sediments or scour effects. 81. A number of techniques are available to obtain reliable DEMs which are based on processing high resolution satellite imagery in conjunction with Differential Global Positioning System (DGPS) ground control points. Other methods may include interpolation of contours and spot height, LIDAR processing and photogrammetry. The derivation of DEMs from contour and spot height might be more accurate but requires extensive survey for data generation and processing, which is expensive and time consuming. An alternative robust method for DEM generation which is widely adopted by practitioners is photogrammetric stereo models using satellite images. This method has been applied in this study. B. Available Data 1. CARTOSAT Images 82. CARTOSAT-1 images are acquired by the Indian satellite which is the 11th one in the Indian Remote Sensing (IRS) series designed to provide quality Earth imagery for telemetry and digital mapping. The data sets were provided as Orthokit GeoTiff format and referenced to the WGS84 ellipsoid and datum. The CARTOSAT-1 satellite is a dedicated stereo platform and carries two panchromatic sensors capturing images, namely Fore (26 degrees) and Aft (5 degrees). Images are recorded almost simultaneously in both directions along the satellite s orbit plane or with an inclination, if needed. This gives excellent stereo viewing geometry. The sensors cover a swath about 30 km wide with the resolution of 3 m (+26 degrees) and 2.5 m (-5 degrees). Each data is composed of two images namely band A and band F images. The sensor specifications are given below in Table 8.

34 23 Spatial resolution Table 8: CARTOSAT -1 Sensor Specifications Fore (+26 deg) 2.5 m cross-track 2.8 m along track Camera Aft (-5 deg) 2.2 m cross-track 2.2 m along track Spectral sensitivity nm nm Quantization 10 bits Swath width 29 km 26 km Number of detector elements Detector size 7 * 7 µm 7 * 7 µm Focal length 1945 mm 1945 mm Camera field of view (FOV) 2.4 o 2.4 o Detector integration time ms ms 83. CARTOSAT-1 operates in a sun synchronous orbit at an average altitude of 618 km with an orbit revisit time of 126 days, but a 5-day revisit time can be achieved by tilting the satellite to the east or west of nadir. The orbit characteristics are presented in Table 9. Table 9: CARTOSAT-1 Orbit Characteristics Nominal altitude 618 km Orbit per day 14 days Orbit repetition 126 days Revisit time 5 days Equatorial crossing on descending pass am local time Orbital eccentricity Orbital inclination o 84. CARTOSAT-1 data were acquired to cover the Terai region of the 25 basins included in this study. The spatial coverage of the images are shown in Figure 2. It should be noted that despite extensive data search, some of the project basins are not covered by the CARTOSAT images. It was agreed with the client that the gaps would be filled in by the GIS data from the Survey Department which was also provided by the Client. The relevant sheet numbers provided to fill the gaps in the satellite image coverage are shown in Table 10.

35 24 Table 10: Sheet Index of the GIS layers acquired to fill the gaps in the satellite image coverage Sheet Index A01 A01 A05 A05 A04 A02 A01 C13 A06 C13 A08 A05 A16 A14 A02 A02 A06 A09 B03 A04 A02 C14 A07 C14 B08 A09 B15 B13 A06 A03 A07 C05 A06 A05 D13 A10 C15 B12 A10 B16 B14 A08 A04 A08 C09 A07 A06 D14 A11 D13 C08 A14 C16 C13 B01 A05 A09 A08 a10 B06 D14 D08 A15 D15 C14 B02 A06 A10 A12 b01 B07 A16 D16 D13 B07 A07 A11 B01 b02 B10 B03 D14 B08 A08 A12 B02 b05 B11 B05 C01 A11 B05 B03 b06 B15 B09 C02 A12 B06 B04 b09 C06 B10 C03 B01 B07 B07 C01 C07 B14 C04 B02 B08 B12 C02 C10 B15 C08 B03 B09 C02 C05 C11 C05 D01 B04 B10 C03 C06 D06 C06 D02 B05 B11 C04 C10 D07 C10 D03 B06 B12 C08 D01 D10 C15 D04 B07 C01 D01 D02 D11 C16 D08 B08 C02 D02 D05 D05 C01 C03 D04 D09 C02 C04 D07 D10 C03 C05 D08 D15 C04 C06 C06 C07 2. Ground Control Points 85. The photogrammetry processing of the satellite images for DEM extraction requires ground control points (GCP). These are the clearly identifiable points in the images for which the three dimensional ground coordinates are known in a given coordinate system i.e. WGS84. These GCPs are used to calculate the position and orientation of the imaging sensor at the moment of exposure. 86. For this study, GCPs were taken from the Digital Global Positioning System (DGPS) survey of the river cross sections that were provided by the Client. The surveys were carried out in 2014 under a separate contract by two surveying companies in Nepal. 87. These DGPS points and cross sections were screened and where appropriate were used as GCPs for this study. The distribution and location of GCPs are shown in Figure As discussed in Section II previously, a number of anomalies were identified during the review of the river cross-section data provided. The surveyed cross-sections provided by the Client to aid the hydrodynamic modelling, which were meant to have been taken in the study area up to 500m upstream of the international border, were not regularly spaced and were often taken along the international border between Nepal and India which was not included in our study area.

36 It was also pointed out that the channel cross-sections surveyed in 2014 and provided by the Client were more likely to reflect the existing ground conditions in areas away from the main waterway as these would not be affected in the same aggressive manner when rivers were in full flow during the monsoon season causing significant changes in bed levels and even changes to the river channel course in some cases. 90. Whilst every effort was made to use all the available surveyed cross-sections, some data had to be discarded as the cross-sections were either outside our study area or were located away from the existing river channels. Similarly, adjustments were necessary to be made in the derived DEMs when there were discrepancies in the information from the surveyed cross-sections, field conditions and satellite imagery. 3. GIS Data Layers 91. GIS data layers prepared by the Survey Department were also provided by the Client for this study. Preparation of these data was started in the early 1990s as a part of the National Topographic Database (NTDB) programme and covered most of the country at scales of 1:25,000 and 1:50,000. The Survey Department launched NTDB as a supporting and organizing programme to provide national specifications and standards for topographic data: (scales 1:25,000/50,000), data codes, data formats, data quality, etc. and the products of the NTDB programme are considered to be the fundamental datasets for Nepal. 92. The Survey Department is transforming its products from traditional paper maps to digital through its National Geographic Information Infrastructure (NGII) Programme. It was realised that increasingly map analysts and users use GIS to produce and share digital spatial database. This necessitated the development of the NGII. The Survey Department started the NGII programme, which is a combination of technologies, policies and people bound in an institutional framework to promote production and sharing of the geospatial data. 93. The fundamental spatial dataset of the NGII is the NTDB programme which includes digitization of the topographic base maps of scale 1:25,000 for the plain areas up to middle mountains, and of scale 1: for high mountains. The Survey Department disseminates data in digital format which is organized at sheet levels of the datasets and consists of geodetic data, administrative boundaries, transportation networks, buildings, hydrography, topography, utilities, land cover, toponomy and designate areas. The basic components of a NGII are the fundamental database, socio-economic (attributes) database and the metadata base shared and made available to/by adopted standards. 94. The GIS layers of administrative boundary, river network, land use, settlements, and houses were made available. Topographic GIS data was also made available in order to fill the gaps in the satellite image coverage. Figure 5 shows the index map for the topographic data. The sheets consisting of the following data: (i) (ii) (iii) (iv) (v) (vi) (vii) Contour Administrative boundary River Settlements Houses Transport system Landuse

37 26 Figure 5: Sheet Index for the Topographic Base Map

38 27 C. Projection System 95. All of the spatial data provided has been projected in the following projection system Projection: UTM Spheroid: WGS84 Datum: WGS84 UTM Zone: 44 (Western), 45 (Eastern) Horizontal unit: meters D. Photogrammetry processing 96. ERDAS Imagine LPS package is one of the widely used tools in photogrammetry to generate DEM from CARTOSAT imagery. This software has been used to generate the DEM of the study basins: 97. There are a sequence of steps that are required to be undertaken in the generation of the DEM from satellite images. 1. Evaluation of Image Quality 98. There are some basic image quality requirements for the stereo satellite images: (i) (ii) (iii) the two images should be very similar in terms of radiometry and sharpness, to enable comfortable stereo viewing and effective automated matching; streaking, banding, saturation, noise and other radiometric artifacts should be minor enough to enable stereo viewing and successful matching, and at least one image from the stereo pair should be acceptable for use in generating an orthorectified product. Rapid qualitative assessments were performed for the images provided by the Client and used in the study to ensure that the images were suitable for use. In all cases, the stereo pairs met the general requirements mentioned above. The radiometry was acceptable, there were no observable streaking or banding issues. The two images were very similar in appearance. 2. Preparation of the Block file by selecting the Geometric Model 99. The first step in DEM generation is creation of a block project file defining the geometric model as a Rational Polynominal Coefficient (RPC) model. CARTOSAT-1 stereo scenes are provided with Rational Polynominal Coefficient (RPC)1 within the Rational Function (RF) sensor model. The RPC file contains third degree polynomial coefficients that related the image to the object space considering the imaging sensor geometry. These RPCs are sensor derived and terrain independent. Rational Polynominal satellite sensors are simple empirical mathematical models relating image space (line and column position) to latitude, longitude and surface elevation. The block project is projected in the WGS84 coordinate systems. The details of the projection systems are given below: Projection: UTM Spheroid: WGS84 Datum: WGS84 UTM Zone: 44 (Western), 45 (Eastern) 1 Along with imagery, the major item of importance for the Orthokit product is the pair of RPC files that come bundled with the scenes. RCPs are the coefficients use by photogrammetric software to represent the ground-to-image viewing geometry.

39 28 Horizontal unit: meters 3. Settling up internal geometry 100. The software performs interior and exterior orientation of stereo pairs by extracting information from the RPC file. Interior orientation defines the internal geometry of a sensor, as it existed at the time of image capture and exterior orientation is the position and angular orientation of the sensor that captures the image: 4. Adding GCP and automated tie point generation 101. LPS supports both manual and automated GCP and tie point collection. The software selects a matching point in one image, finding its conjugate point in the other (Stereomate) image. During image matching in LPS, a correlation window exits on the reference image and a search window exists on the neighbouring overlapping image. The cross-correlation coefficients are calculated for each correlation window among the search window. The correlation coefficient is considered as the measure of similarity between the image points appearing within the overlapping areas of image pairs GCP points are imported from the cross section file, and tie points are generated based on the GCP and image correlation. 5. Adding GCP and automated tie point generation 103. The triangulation was run after adding GCPs and tie points. The triangulation process establishes the relation between images, sensor model and ground points. This process was run to check the accuracy for GCPs and tie points. 6. DEM Extraction 104. The DEM extraction was carried out following the photogrammetric processing of the imagery. The Automated Terrain Extraction (ATE) tool is used for DEM extraction. The output DEM is defined of the following resolutions - vertical resolution = 1 m and horizontal resolution = 5 m. A recent study described the best resolution as twice the satellite s image pixel size to avoid degradation of the DEM structure Adaptive ATE which was introduced to LPS from its 10.1 version uses a global DEM to initialize a surface model and iteratively refines it with image registration on different pyramid levels. Matching results from the current pyramid is used to update terrain range at the next lower pyramid. Thus the accuracy of matching improves with each iteration An example of the DEM generated for Mawa Ratuwa Basin is shown in Figure It should be noted that the DEMs generated only cover the extent of the river reaches in the Terai region for which hydrodynamic modelling is required to be carried out. Figure 7 shows the DEM generated for the East Rapti Basin. It can clearly be seen that as the upper reaches of the catchment are not required to be modelled under this study, processing of additional satellite images covering the upper reaches was not done. Similarly, there are strips where the satellite images do not overlap and subsequently, there are gaps in the DEM generated in those areas. In East Rapti Basin, the areas between satellite images or strips with no coverage have not needed to be filled in as those areas are not affected by flooding from the main East Rapti river, being on high ground DEMs were generated from satellite images to cover the hydraulic modelling extent in all 25 study basins at a vertical resolution of +/- 0.5m. These DEMs provided a key input for carrying out the subsequent hydraulic modelling and processing of the model results.

40 29 Figure 6: Digital Elevation Model - Mawa Ratuwa Basin

41 30 Figure 7: Digital Elevation Model - East Rapti Basin