63800912 Inception Report Version 3/ HCA / 2017-06-30

ESTABLISHMENT OF END-TO-END FLOOD EARLY WARNING SYSTEM IN KOSHI AND WEST RAPTI RIVER BASINS IN NEPAL

Inception Report

Dept. of Hydrology & Meteorology Inception Report

June 2017

63800912 inception report version 3/ HCA / 2017-06-30

This report has been prepared under the DHI Business Management System certified by Bureau Veritas to comply with ISO 9001 (Quality Management)

Approved by

Flemming Jakobsen

Dept. of Hydrology & Meteorology Inception Report

June 2017

ESTABLISHMENT OF END-TO-END FLOOD EARLY WARNING SYSTEM IN KOSHI AND WEST RAPTI RIVER BASINS IN NEPAL

Inception Report

Prepared for Dept. of Hydrology & Meteorology

Represented by Dr. Rishi Ram Sharma, Director General Koshi embankment Photo by DTL

Report authors Team-Leader Hans Christian Ammentorp, Deputy Team Leader Khada Nanda Dulal

Project manager Flemming Jakobsen

Quality supervisor Oluf Jessen

Project number 63800912 Approval date 04-07-2017 Revision 3.0 Classification Open

DHI (India) Water & Environment Pvt Ltd•NSIC Bhawan, IIIrd Floor, NSIC - STP Complex•Okhla Industrial Estate•IN- 11 00 20New Delhi• India Telephone: +91 11 4703 4500 • Telefax: +91 11 4703 4501 • • www.dhigroup.com

63800912 inception report version 3/ HCA / 2017-06-30

CONTENTS

1 Executive summary ...... 4

2 Introduction ...... 5 2.1 Background ...... 5 2.2 Study basins ...... 5 2.2.1 Koshi River basin ...... 5 2.2.1.1 Issues of Flooding in Koshi ...... 7 2.2.2 West Rapti River basin ...... 7 2.2.2.1 Issue of flooding in West Rapti basin ...... 8 2.3 Inception phase activities ...... 9 2.4 Structure of the Report ...... 9

3 Literature Review ...... 10 3.1 DHM’s role in flood forecasting and early warning ...... 10 3.2 Glacial lake outburst flood (GLOF) early warning system for Tsho Rolpa...... 11 3.3 Flood early warning system on the Bhote Koshi ...... 12 3.4 Community-based flood early warning systems ...... 12 3.5 ICIMOD’s contribution in flood early warning ...... 12 3.6 Efforts made by Department of Water Induced Disaster Management (DWIDM) ...... 13

4 Data availability ...... 14 4.1 Topographical data ...... 14 4.2 Hydro-meteorological data ...... 14 4.2.1 Koshi River basin ...... 15 4.2.2 West Rapti River basin ...... 19 4.2.3 Satellite rainfall products as supplementary rainfall data...... 21 4.2.4 Handling missing rainfall data ...... 22

5 Approach and Methodology ...... 23 5.1 Task 1 ...... 23 5.1.1 Structure of an Early Warning System and assessment approach ...... 24 5.1.1.1 Risk Knowledge ...... 24 5.1.1.2 Monitoring and Warning Service ...... 24 5.1.1.3 Dissemination and Communication ...... 25 5.1.1.4 Response Capability ...... 25 5.1.1.5 Field visits ...... 25 5.2 Task 2 ...... 26 5.3 Task 3 ...... 27 5.4 Task 4 ...... 27 5.4.1 Data collection and processing ...... 27 5.4.2 Hydrologic modelling ...... 28 5.4.2.1 Data for hydrological modelling ...... 28 5.4.3 Hydrodynamic modelling ...... 30 5.4.4 Real-time updating ...... 31 5.4.5 Model calibration ...... 32 5.4.6 Operational forecasting ...... 33 5.5 Task 5 ...... 34 5.6 Task 6 ...... 36 5.7 Task 7 ...... 36

6 Project implementation plan ...... 38

7 Risks and issues ...... 1

8 References ...... 2

FIGURES

Figure 1 Location of Koshi Basin ...... 6 Figure 2 Location of West Rapti basin ...... 8 Figure 3 The network of rainfall and river gauging stations in Koshi basin...... 15 Figure 4 The network of rainfall and river gauging stations in West Rapti River basin ...... 19 Figure 5 Preliminary delineation of sub-catchments in the Koshi and West Rapti basins. The triangles represent real-time river gauging stations ...... 27 Figure 6 MIKE 11 NAM Hydrological model components ...... 28 Figure 7 The Seamless Weather Generator ...... 29 Figure 8 MIKE HYDRO River based map of the January 2015 flood in Malawi ...... 30 Figure 9 Sample flexible mesh grid for 2D flow simulation in MIKE FLOOD (Chao Phraya basin, Thailand) ...... 31 Figure 10 Example of data assimilation application - top: initial hindcast water levels prior to applying data assimilation, bottom: updated hindcast following data assimilation (i.e. differences between simulated and observed water levels are reduced) resulting in improved water level forecast ...... 32 Figure 11 Examples of background map types incorporated in the user interface of the forecasting system ...... 34 Figure 12 Sample forecast overview, where sub-catchments and river gauging stations are colour- coded according to forecasted runoff or flow...... 34 Figure 13 Sample web-site, where the amount of sub-catchment rainfall and the forecasted discharge at the gauging stations is indicated in colour-codes (green, yellow, red). A graph showing each forecast can be seen by clicking on the area or point...... 35

TABLES

Table 1 Threshold runoff and water level for warning and danger level at forecasting stations of DHM ...... 10 Table 2 River gauging stations in Koshi River basin ...... 15 Table 3 Koshi River basin rainfall stations established by Meteorology section of DHM ...... 16 Table 4 Koshi River basin real time rainfall stations ...... 18 Table 5 Koshi basin temperature stations ...... 18 Table 6 Hydrological stations in West Rapti River basin ...... 19 Table 7 Rainfall stations within West Rapti basin ...... 20 Table 8 Real time rainfall stations within West Rapti basin ...... 20

APPENDICES

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APPENDIX A – Minutes of meeting

APPENDIX B – Field Trip to West Rapti Basin

APPENDIX C– Questionnaires

iii

1 Executive summary

The present project aims at developing an End-to-End Flood Early Warning System (FEWS) for the Koshi and West Rapti river basins under Component C of Building Resilience to Climate Related Hazards. Being originally planned for 24 months, the project will be implemented over a period of 14 months only.

The scope of work includes seven major tasks:

1. Assessment of the Disaster Management Institutional Framework in Nepal and establishment of operational mechanisms 2. Comprehensive risk assessment of the threats caused by flood hazard in the two basins 3. Review of the System Integrator (SI) Report on Observation network and assessment of network adequacy 4. Integrated Flood Forecast Modelling System 5. Communication and Dissemination of Flood forecast and Early warning System 6. Design and development of an Operational Decision Support System (ODSS) 7. Capacity Development

The Koshi River basin is characterised by large variations in altitude including snow-covered areas and glaciers. About 80% of the annual precipitation falls between June and September, varying significantly in time and space. Sudden cloudbursts of up to 500 mm/day are common. Floods occur and are often associated with embankment breaches, such as the disastrous 2008 flood. The basin is further prone to GLOFs.

The smaller West Rapti River catchment is without snow. Floods occur quite frequently and have been reported to be particularly destructive in villages bordering India. Flood induced inundation, sedimentation and bank cutting are the major problems of the lower basin.

An extended network of real-time stations providing rainfall and river data is available in both basins for the forecasting system. The adequacy of this will be evaluated and recommendations for further expansion given, if appropriate. Data from the Tibetan part of the Koshi catchment will not be available, and it may not be possible to obtain real-time information from remote parts of all catchment inside Nepal. Satellite rainfall data will therefore also be collected and tested as a supplement to the ground stations to enable improved accuracy of catchment runoff simulations.

Hydrological and hydrodynamic models will be developed using available data on topography and meteorological and hydrological conditions. Additional data collection or surveys may be conducted if the initial model performance indicate a need for this in given areas.

As the 2017 monsoon will be the only wet season within the project, the Consultant aims at developing a preliminary flood forecasting system already by July 2017, so this may be tested in real-time and a reliable system delivered. The Consultant has mobilised additional staff to enable this.

Special attention will be given to the use of the forecasts and warnings by the concerned organisations and communities to take early action in order to reduce losses of lives and property. Pre-disaster workshops and drills will further be conducted, supported by leaflets and other information, to strengthen the awareness and understanding of the new early warning system.

This Inception Report describes the current status of flood early warning in the basins, the basis for improvements, and outlines the approach and implementation plan to develop the FEWS.

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2 Introduction

2.1 Background

Flood is one of the major natural disasters of Nepal. The major causes of flooding in Nepal are intense rainfall, glacier lake outburst flood (GLOF), floods due to landslide damming, inundation in Terai area due to the obstruction of natural flow and failure of infrastructures. Furthermore, the global climate change is expected to exacerbate the magnitude and frequency of extreme events, like flood. In order to address the issues of flooding, the Department of Hydrology and Meteorology (DHM) intends to establish an end-to-end flood early warning system in Nepal in two river basins, Koshi and West Rapti, under Building Resilience to Climate Related Hazards (BRCH) project, funded by the Pilot Program for Climate Resilience (PPCR) with support from the World Bank. The BRCH project is under the component 2 of the Strategic Program for Climate Resilience. The BRCH project has four components, and the early warning part falls in the component C: Enhancement of the Service Delivery System of the DHM.

The overall objective of the study is to reduce losses of lives and properties from flood hazard by improving the capacity of DHM in developing and implementing effective people-centered early warning systems. Specifically, the study aims at establishing a fully operational real time “End- to-End” Flood Forecasting and Early Warning System (FFEWS) in Koshi and West Rapti basins.

The scope of work includes seven major tasks:

2.2 Study basins

Characteristics of the two rivers basins are given below.

2.2.1 Koshi River basin The Koshi is a transboundary river, which originates in Tibet (China), then flows through Nepal and finally drains to India. It is one the major tributaries of the River Ganges. It is a snowfed perennial river and has the largest river basin of Nepal. It covers the eastern part of Nepal (Figure 1). It is also known as Sapta Koshi in Nepal, meaning a river with 7 streams. The seven streams are: Sunkoshi, Tamakoshi, Dudhkoshi, Indrawati, Likhu, Arun and Tamor. Three major tributaries, namely Sunkoshi from west, Arun from North and Tamor from East meet at Tribeni in Nepal, after which the river is named as Sapta Koshi or simply Koshi. The Arun, the longest of the three tributaries passes through Tibet, named there as Phung-chu, drains the highest peak of the world i.e. the Mount Everest. The Tamor drains the second highest peak, the Kanchanjunga and the Sunkoshi drains the eastern part of Kathmandu valley in Nepal. The area

of the Koshi basin, as computed from the basin delineated using SRTM DEM, at Nepal-India border is 59354 km2, out of which 27500 km2 lies in Nepal.

Figure 1 Location of Koshi Basin

Below the confluence at Tribeni, the Koshi flows in a narrow gorge for a length of about 10 km till it debouches into plains, near Chatara in Nepal. Further down, the river runs in the relatively flat plains of Nepal Terai consisting of sandy soils. The river flows through Nepal for 50 km below Chatara to Hanumannagar, before it enters Bihar state of India. In the portion below Chatara, the river divides itself into several channels spread over a width of 6 to 16 km.

The Koshi barrage, called Birpur Barrage at Bhimnagar, built between 1959 and 1963, is one of the most important structures built under a bilateral agreement between Nepal and India. It is an irrigation project on the Koshi River. A valuable bridge over the barrage opened up the East- West highway in the eastern sector of Nepal. Embankments were constructed upstream and downstream of the barrage. Upstream of the barrage in Nepal side, 32 km eastern afflux embankment and 12km western afflux embankment were constructed. Embankments on both sides downstream of the barrage with a length of 387 km have been constructed to check the westward movement of the river. The embankments have been kept wide apart, about 12 to 16 km to serve as a silt trap.

Precipitation patterns in the Koshi basin are directly associated with the South Asian monsoon, with about 80% of the annual precipitation falling between June and September. Due to the great variation in the topography, the spatial and temporal complexity of rainfall is large within short distances. The annual arrival of the monsoon rain results in the emergence of springs at various elevations. In the hills, sudden cloudbursts are common and can generate almost 500 millimetres of rainfall in a single day. However, in the rain-shadow regions of the Tibetan plateau, the conditions are dry and desert-like. The Koshi river has seasonal variations in flow and sediment charge. Often these changes are sudden and great; the river can rise 7 to 10

6 63800912 inception report version 3/ HCA / 2017-06-30 Introduction

metres in 24 hours. In the smaller tributaries of the Koshi, the impact of flooding is localised, but can become widespread when there is greater volume, extent, and/or duration of rainfall.

The combination of upstream rainfall and river characteristics governs the behaviour of the Koshi river on the plains. During the monsoon, the Koshi river transports about 120 million cubic metres of sediment. The annual deposition of this sediment has caused the river to shift its course about 115 kilometres to the west in the last 200 years. Climate of Koshi river basin varies from subtropical zone in the south to Tundra in Higher Himalayan region.

2.2.1.1 Issues of Flooding in Koshi Floods from the Koshi River in the past have created havoc in the downstream area of Nepal and India leading to loss of lives and property and causing widespread human suffering. After the completion of the barrage, the maximum past flood recorded is 25849 m3/sec on 5th Oct 1968, which caused breach of embankments at 5 places in India. After the construction of the embankment, the flow of the river was confined within the embankments and no case of embankment overtopping has been observed, although embankment breaches have occurred.

The first breach was on the western embankment in Nepal in 1963 near village Dalwa. In 1991, the western embankment breached near Joginia, Spatari district Nepal. The embankment breach occurring 12.6 km upstream of the barrage near Kusaha on 18th August 2008 caused the disasterous flooding in Nepal and Bihar, India. At the time of breaching, about 80% of the flow was diverted into Kusaha, Laukahi, Ghuski, Sreepur, Haripur, Narshimha, Madhuban and Basantapur villages of Sunsari district, Nepal. On 18th August when the embankment breached, there was no high rainfall and the discharge at the Koshi Barrage is reported to be about 4200 m3/s, which is below the monthly average discharge. At the time of disaster, about 15 km of the East-West highway was obstructed and 3 km was completely destroyed. The floods have had drastic impacts on habitats of wildlife, aquatic, flora and fauna of the Koshi Tappu Wildlife Reserve in Sunsari district. About two thirds of houses were severely damaged, as most of them were huts made of mud, bamboo and thatch. These houses were generally one story high. It caused extensive damage to the optical fiber cable network laid along the highway. In addition, telephone exchange, power plant, main distribution frame transmission system were submerged in the floods and caused disturbances to the communication network in the eastern region of Nepal.

2.2.2 West Rapti River basin The West Rapti River basin located in the mid-western region of Nepal (Figure 2), is a medium sized river basin. The area of the basin, as computed from the basin delineated using SRTM DEM, is 6366 km2 and the length of main stream channel is 257 km. The river originates from the middle mountains of Nepal, then enters to the flat area and finally drains to India to join the Ganges River. The average slope of the basin is 16.8%. The source of runoff is due to the monsoon rainfall and groundwater. It has several tributaries. Major tributaries are: Jhimruk River, Mari River, Arun River, Lungri River, Sit River, Dunduwa River, Sotiya and Gandheli rivulets. Downstream of the confluence of the Jhimruk and Mari Rivers, the river is named the West Rapti River.

Figure 2 Location of West Rapti basin

While the upper West Rapti basin has deciduous climate, the lower basin including Banke district has tropical to subtropical climate. In the study area, the period from March to June is hot and dry, July to August is hot and humid, September to October is pleasant, and November to February is cool and dry. The temperature goes very high up to 46ocelcius in the summer and falls below 2o during winter. The hot wave during the summer and cold wave during the winter reflects harshness of the climate here. The study area receives southeast monsoon rainfall extending from June to September, accounting about 80% of the total annual. The average rainfall for the basin is about 1500 mm.

There are a few projects in the basin. The notable are, Jhimruk hydropower project (located in the upper basin), Sikta and Praganna Irrigation Projects (located in the lower basin). Similarly structures such as a barrage (named Laxmanpur Barrage) and a dyke (named Kalkaluwa bund) exist on the Indian part of the basin. Besides these, there are a few number of flood control structures such as spurs, and dykes constructed in the Nepalese territory.

2.2.2.1 Issue of flooding in West Rapti basin

Flood has remained a unique problem of the West Rapti River for years. These floods have been reported to be particularly destructive in villages bordering India. Flood induced inundation, sedimentation and bank cutting are the major problems of the lower basin. The deposition of sands in the farmland by the torrents originating from the Chure/Siwalik range, inundation due to flooding, blockage of natural flow of natural streams by the afflux bund on the Indian side, and bank cutting at various locations along the river are affecting lives and livelihoods of the people living in the Lower West Rapti Basin. The municipality and the other urbanized areas have been suffering from drainage congestion and inundation problems due to the unplanned growth, faulty design and poor waste disposal practices.

The water level records at Kusum gauging station shows that the danger level (5.4m) was crossed almost every year. The river has affected several villages along the river banks every

8 63800912 inception report version 3/ HCA / 2017-06-30 Introduction

year mainly in Banke district. The most flood prone villages are: Betahani, Holiya, Binauna, Phatepur, Gangapur, Matehiya. After the establishment of the telemetry system by DHM, the loss of lives is reduced. The following are the recent flood events:

• 03- 04 August 2012: water level at Kusum = 7.24 m on 04 August, 2012 • 14-16 August 2014: water level at Kusum = 8.77 m on 15 August, 2015 • 26 August 2016: water level at Kusum = 8.13 m on 26 August, 2015

2.3 Inception phase activities

The contract was signed on 9th April 2017 and project activities initiated a few weeks later. Following meetings with the main DHM representatives, background information, reports, and data has been collected through additional meetings and consultations with the Department of Water Induced Disaster Management (DWIDM), ICIMOD, and the National Emergency Operation Centre (NEOC) and other organisations, see Appendix C. Further information has been collected from the web sites of other key organisations.

A project office has been set up in Pulchowk, Lalitpur, and data collected from DHM and other sources to initiate the model developments and other activities.

2.4 Structure of the Report

Based on information collected from DHM and key stakeholders concerned with flood risk management in the basins, the present Inception Report describes the current conditions and basis for the FEWS development and outlines a work plan to implement the project within the available time.

The following sections are given below:

Section 3 provides a review of literatures related to the issues of flood forecasting in the two basins.

Section 4 gives an overview of the available data to develop and drive the FEWS,

Section 5 describes the approach and methodology to implement the project,

Section 6 describes the proposed project implementation plan, while

Section 7 discusses risks and issues, which may potentially impede the project implementation

An overview of the reports and papers collected so far is given in section 8

3 Literature Review

A range of documents concerning the flood forecasting and early warning in Nepal have been collected and reviewed, see section 8. The main information extracted from these documents is summarised below.

3.1 DHM’s role in flood forecasting and early warning

The Department of Hydrology and Meteorology (DHM) is the lead organization mandated by the government of Nepal to carry out the hydro-meteorological activities in Nepal, including the flood forecasting and issuing the early warning. At present, DHM maintains 175 river gauging stations and 306 precipitation stations. Most of these stations do not have the facility of real time data transmission system (telemetry), however.

With the objective of developing FFEWS, DHM started installation of telemetry at river gauging stations and meteorological stations in 2008. The Flood Forecasting Section under the Division of Hydrology now maintains a network of hydrological and meteorological stations, primarily developed for flood warning in the Terai plain. The water levels in the rivers are monitored using automatic sensors based on pressure and radar technologies. The rainfall data is monitored by using tipping bucket rain gauge. The real time rainfall and water level data is transmitted via the Internet using a combination of Code Division Multiple Access (CDMA) and Global System for Mobile Communication (GSM) technology. The station network is sparse in hilly and mountain areas. DHM is currently expanding the telemetry system with the support from the World Bank under Pilot Program on Climate Resilience (PPCR) and Regional Integrated Multi-Hazard Early Warning System for Africa and Asia (RIMES). As of June 2017, more than 90 rainfall stations and more than 40 water level stations are connected to the telemetry system. The data from telemetry stations maintained by Flood forecasting section and meteorological sections are available in the web-portal www.hydrology.gov.np.

DHM has not yet set up any operational flood forecasting system based on the hydrological and hydrodynamic modeling. The threshold water level at flood forecasting stations of several rivers have been assigned based on the flood inundation mapping and past flood records. Flood inundation mapping was done using hydrodynamic models.

The following table shows the warning and danger level defined by DHM.

Table 1 Threshold runoff and water level for warning and danger level at forecasting stations of DHM

SN River Station Threshold Threshold Water Level (m) Remarks Name Name Runoff (m3/s) DHM Gauge With reference Height to MSL 1 Narayani Narayanghat 7500 6.8 187.78 Warning level 10000 8 188.98 Danger level 2 East Rapti Rajaiya 1000 3.3 345.14 Warning level 1300 3.7 345.54 Danger level 3 Koshi Chatara 5600 5.6 112.25 Warning level 8150 6.8 113.45 Danger level 4 Kankai Mainachuli 1900 3.7 120.09 Warning level 3250 4.2 120.59 Danger level 5 Karnali Chisapani 8200 10 201.64 Warning level 10000 10.8 202.44 Danger level 6 Kusum 1500 5 204.19 Warning level

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West 2000 5.4 204.59 Danger level Rapti 7 Babai Chepang 1500 5.5 308.65 Warning level 2000 6.2 309.35 Danger level 8 Seti Jyamirebari 1000 5.71 1513.17 Warning level 1500 7 1514.46 Danger level

DHM issues early warning to the downstream communities when the water level at the upstream station reaches the predetermined threshold water level. Owing to the location of the stations, the lead time of the forecast is usually short.

DHM has developed capacity on Numerical Weather Prediction (NWP) using Weather Research & Forecast (WRF) model with the assistance from RIMES. Quantitative Precipitation Forecast (QPF) with a lead time of 3 days is available on a daily basis from RIMES.

DHM issues early warning through the website (www.hydrology.gov.np) and mobile-based system to the communities and stakeholders. The website displays water level and rainfall on real time basis from the telemetry stations and updates every 5 minutes. Clusterwise SMS system and toll free number (1155) is also introduced for the dissemination of the information on flood. DHM is collaborating with National Emergency Operation Centre (NEOC) under ministry of Home Affairs (MOHA) at central level for the dissemination of flood early warning. Community-level disaster management committees are formed in each disaster prone village, which belong to a network of District Disaster Relief Committee, local media, the Red Cross, local police, military units, and DHM flood monitoring and forecasting station. Disaster management committees are equipped and trained for warning dissemination, preparedness, and immediate response. With support from Non-Governmental Organizations (NGOs), a number of community based disaster risk mitigation activities have been initiated at the local level in Nepal. The initiation of the International Federation of Red Cross and Red Crescent Societies (IFRC) funded Koshi River Basin community resilience project has brought together different agencies working on community-based disaster risk reduction (CBDRR), water and sanitation and hygiene promotion (WatSan/HP), health, and livelihoods.

Recently, DHM has been engaged in developing hydrological models for flood forecasting. Calibration, validation, and testing of models is completed in 3 major river basins: Karnali, Babai and Narayani in Delft-FEWS platform (HEC-HMS model) in collaboration with RIMES. The model was developed using daily rainfall data. A probabilistic model (hydrological model) was developed for 6 major river basins in collaboration with Lancaster University. Only the real time rainfall data is used in the probabilistic model. Forecast rainfall input has not been used. All these activities are currently in the research/study phase and fully operational flood forecasting model is not in operation. These models are not developed for Koshi and West Rapti basins.

The Global Flood Awareness System (GloFAS), jointly developed by the European Commission and the European Centre for Medium-Range Weather Forecasts (ECMWF), is producing daily flood forecast using LisFlood model, which also includes 8 computations nodes in Nepal. DHM is a member of GLoFAS. The model not been calibrated for Nepal and the output can be used to see only the timing of peak events.

3.2 Glacial lake outburst flood (GLOF) early warning system for Tsho Rolpa

In the 1990s, DHM set up a glacial lake outburst flood (GLOF) early warning system downstream from Tsho Rolpa glacial lake in the Tama Koshi basin in eastern Nepal. This was one of the first GLOF early warning systems in South Asia. The system consisted of a set of sensors and automatic sirens at 19 locations downstream. The sensor was set to trigger an alert to warn communities downstream along the Rolwaling and Tama Koshi rivers when a certain

level was reached in the lake. The system worked for a few years, but inadequate operation and maintenance, vandalism, and others led to the system becoming defunct.

3.3 Flood early warning system on the Bhote Koshi

An early warning system has been set up on the Bhote Koshi River by the Bhote Koshi Power Company (BKPC). The early warning system consists of two sensor stations at the Friendship Bridge, which transmit a warning in the event of a GLOF to sirens located downstream at the headwork and at Hindi village, and a warning cum monitoring station at the powerhouse. A spillway can be opened so that flow is no longer diverted for power production and the powerhouse is shut down. The BKPC carried out community awareness raising activities to inform and prepare the local people, and installed warning signs at four different river crossings selected in consultation with the community. In the event of a GLOF or sudden spillway release, people are advised to move to a place at least 20 m above the normal riverbed level. However, the present dam is located only 6 km downstream from the Friendship Bridge and if a GLOF does occur, the warning system provides only five minutes lead-time to make the preparations.

3.4 Community-based flood early warning systems

Since 2002, Practical Action has been working on flood early warning systems for communities in Nepal. In the initial period, observation towers were set up with a siren system to watch and warn communities of impending flood disasters. This introduced the concept of early warning systems, but the technology has now been improved. In the western region of Nepal, Practical Action and DHM have piloted a community based flood early warning system in the West Rapti basin. Real-time information on water levels at the upstream gauging station operated by DHM is provided to communities to warn them of impending floods. Practical Action has also established a community-based flood early warning system in Banke and Bardiya districts in collaboration with DHM and local NGOs. The institutionalized system includes local governmental and nongovernmental organizations in the network for early warning. A similar system has been installed by Mercy Corps in Kailali and Kanchanpur districts.

3.5 ICIMOD’s contribution in flood early warning

The International Centre for Integrated Mountain Development (ICIMOD) in partnership with the World Meteorological Organization (WMO) and the regional member countries from Bangladesh, Bhutan, China, India, Nepal and Pakistan developed the Hindu Kush Himalayan Hydrological Cycle Observing System (HKH-HYCOS). The aim of HKH-HYCOS is to enhance regional cooperation in hydrometeorological data collection and sharing for flood forecasting to support disaster prevention and flood management at the regional level. Using advanced technologies for data collection and transmission the project has upgraded 38 hydrometeorological stations in four countries to transmit real-time data on river level and rainfall, 12 of which are in the Koshi Basin of Nepal. The real-time data available from the region, satellite based products and weather forecasts are assimilated into rainfall runoff model using MIKE 11. The HKH-HYCOS regional flood outlook provides real-time flood information products in the Ganges Brahmaputra basins, within which Nepal’s major rivers are also covered. ICIMOD has also developed MIKE11 hydrodynamic model of Koshi Basin from Chatara in Nepal to Kursela in Bihar, India (confluence of Koshi with Ganges).

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3.6 Efforts made by Department of Water Induced Disaster Management (DWIDM)

The Department of Water Induced Disaster Management (DWIDM), previously known as Department of Water Induced Disaster Prevention (DWIDP), under Emergency Flood Damage Rehabilitation Project funded by Asian Development Bank (ADB), conducted a study in 2012 on how the flood forecasting and early warning system can be implemented in the Koshi Basin. The study provides a conceptual framework along with the details of the different components of flood forecasting and early warning system. In the study, cross-section survey of the Koshi river from Chatara to barrage was carried out for setting up of a hydrodynamic model for inundation mapping. The study also recommends the number of hydrological and meteorological stations for flood forecasting. The study did not give a clear picture on how the operational flood forecasting system is implemented in Koshi river basin.

DWIDM carried out flood hazard mapping of 25 river basins of Nepal under Water Resources Project Preparation Facility (WRPPF) funded by ADB. The hazard mapping was done on the Terai part up to Nepal-India border. Among 25 basins, West Rapti basin was also included, but not Koshi. DEM of 5m spatial resolution was prepared for the study from CARTOSAT image. The hazard maps developed in the project would be useful to assess flood prone areas for different return periods. The impact of climate change was also considered in the risk mapping. Six priority projects were selected for interventions, in which establishment of early warning system was also recommended as a non-structural measures.

4 Data availability

The Flood Forecasting Section of DHM is already producing and issuing forecasts, in the form of weather forecasts and water level information, as described above, and facilities have been enabled to disseminate warnings to the concerned communities. Quantitative precipitation forecasts (QPF) are available for the next three days.

DHM is further in the process of expanding the network of telemetry stations, providing information on rainfall and river flow in real-time.

4.1 Topographical data

River cross sections are available for the lower Koshi River, within the embankments, and the lower West Rapti, excluding the floodplains, from Department of Water Induced Disaster Management (DWIDM). The latter will likely have to be extended using a DEM. Cross sections are further available at river gauging stations.

Digital elevation models (DEM) will be required for the flood mapping. Data is already available for the lower West Rapti flood plains from DWIDM, whereas a DEM for the flood prone areas of the Koshi river downstream of Chatara is planned to be developed shortly by the DHM. SRTM DEM (90m) of the two basins were also downloaded.

4.2 Hydro-meteorological data

The accuracy of a flood forecasts depends highly on the quantity and quality of the available meteorological, hydrological, and topographical data. Hydrometeorological data is collected from the DHM. An overview of the current status and plans for this data in the two basins is given below.

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4.2.1 Koshi River basin

Figure 3 The network of rainfall and river gauging stations in Koshi basin.

Real-time water level data from 2012 to 2016 is available in Koshi basin. It is important, however, to also get discharge data at the real-time stations for 2015 and 2016, as we will supplement the rainfall data of ground stations with GPM satellite rainfall data (https://pmm.nasa.gov/gpm) in the hydrological modelling. This is only available from mid-2014.

The hydrological stations in Koshi basin is listed below.

Table 2 River gauging stations in Koshi River basin

Station River Name Location Lat (0) Lon Elev Basin Publication Remarks no. (0) (m) area (in hard (km2) copy and digital form) From To 600.1 Arun Uwagaun 27.59 87.34 1294 26750 1985 2006 602 Sabayakhola Tumlingtar 27.30 87.22 305 375 1974 2006 602.5 Hinwakhola Pipaltar 27.29 87.22 300 110 1974 2006

604.5 Arun Turkeghat 27.32 87.19 414 28200 1975 2006 Real time 606 Arun Simle 26.93 87.16 152 30380 1986 2006 610 Bhotekosi Barbise 27.79 85.88 840 2410 1965 2006 Real time 620 Balephi Jalbire 27.80 85.76 793 629 1964 2006 627.5 Melamchi Helambhu 28.04 85.52 2134 84 1990 2006 629.1 Indrawati Dolalghat 27.64 85.71 1225 2006 2008 630 Sunkosi Pachuwarghat 27.55 85.75 602 4920 1964 2006 Real time 640 Rosikhola Panauti 27.57 85.51 1480 87 1964 1987 647 Tamakosi Busti 27.62 86.08 849 2753 1971 2006 Real time 650 Khimtikhola Rasnalu 27.57 86.19 1120 313 1964 2006 652 Sunkosi Khurkot 27.32 86.00 455 10000 1968 2006 Real time 660 Likhu Sangutar 27.34 86.22 543 823 1964 2006 668.4 Taktorkhola Beni 27.53 86.55 2400 73 1986 1991 668.5 Solukhola Salme 27.50 86.58 1800 246 1987 2006 670 Dudhakosi Rabuwabazar 27.27 86.66 460 4100 1964 2006 Real time 680 Sunkosi Kampughat 26.87 86.81 200 17600 1966 1985 681 Sunkosi Hampchuwar 26.92 87.15 150 18700 1991 2006 684 Tamur Majhitar 27.15 87.70 533 4050 1996 2006 690 Tamur Mulghat 26.93 87.33 276 5640 1965 2006 Real time 695 Saptakosi Chatara 26.87 87.16 140 54100 1977 2006 Real time

The rainfall stations in Koshi River basin are listed below. Data is available in real-time from 20 stations at the time of writing this report (2017 May). However, real time data of only 11 stations are available from 2012 to 2016.

Table 3 Koshi River basin rainfall stations established by Meteorology section of DHM

SN Index Name District Lat (0) Lon Elev Data availability no. (0) (m) period 1 1006 Gunthang Sindhupalchok 27.87 85.87 2000 1975 2015 2 1008 Nawalpur Sindhupalchok 27.80 85.62 1592 1975 2015 3 1009 Chautara Sindhupalchok 27.78 85.72 1660 1979 2016 4 1016 Samarthang Sindhupalchok 27.95 85.60 2625 1972 2016 5 1017 Dubachaur Sindhupalchok 27.87 85.57 1550 1971 2016 6 1018 Baunepati Sindhupalchok 27.78 85.57 845 1971 2016 7 1020 Mandan Kavre 27.70 85.65 1365 1947 2016 8 1023 Dolalghat Kavre 27.63 85.72 710 1947 2016 9 1024 Dhulikhel Kavre 27.62 85.55 1552 1947 2016 10 1025 Dhap Sindhupalchok 27.92 85.63 1240 1977 2015

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11 1027 Bahrabise Sindhupalchok 27.78 85.90 1220 1966 2015 12 1028 Pachuwaghat Kavre 27.57 85.75 633 1966 2007 13 1036 Panchkhal Kavre 27.68 85.63 865 1971 2015 14 1049 Khopasi Kavre 27.58 85.52 1517 1971 2016 15 1058 TarkeGhyang Sindhupalchok 28.00 85.55 2480 1974 2015 16 1062 Sangachok Sindhupalchok 27.70 85.72 1327 1981 2015 17 1063 Thokarpa Sindhupalchok 27.70 85.78 1750 1983 2016 18 1101 Nagdaha Dolkha 27.68 86.10 850 1977 2016 19 1102 Charikot Dolkha 27.67 86.05 1940 1959 2014 20 1103 Jiri Dolkha 27.63 86.23 2003 1961 2016 21 1104 Melung Dolkha 27.52 86.05 1536 1959 2016 22 1107 Sinduligadhi Sindhuli 27.28 85.97 1463 1955 2016 23 1108 Bahuntilpung Sindhuli 27.18 86.17 1417 1958 2016 24 1115 Nepalthok Sindhuli 27.45 85.82 1098 1950 2016 25 1123 Manthali Ramechhap 27.47 86.08 495 1992 2016 26 1202 Chaurikhark Solukhumbu 27.70 86.72 2619 1950 2015 27 1203 Pakarnas Solukhumbu 27.43 86.57 1982 1948 2015 28 1204 Aisealukhark Khotang 27.35 86.75 2143 1948 2015 29 1206 Okhaldhunga Okhaldhunga 27.32 86.50 1720 1948 2015 30 1207 Mane Okhaldhunga 27.48 86.42 1576 1948 2015 bhanjyang 31 1210 Kuruleghat Khotang 27.13 86.43 497 1948 2015 32 1211 Khotang bazar Khotang 27.03 86.83 1295 1959 2015 33 1219 Salleri Solukhumbu 27.50 86.58 2378 1948 2015 34 1220 Chialsa Solukhumbu 27.48 86.62 1975 1998 35 1222 Diktel Khotang 27.22 86.80 1623 1973 2015 36 1224 Sirwa Solukhumbu 27.55 86.38 1662 1959 2015 37 1301 Num Sankhuwasabha 27.55 87.28 1497 1959 2014 38 1303 Chainpur (east) Sankhuwasabha 27.28 87.33 1329 1947 2015 39 1304 Pakhribas Dhankuta 27.05 87.28 1680 1976 2015 40 1305 Leguwaghat Dhankuta 27.13 87.28 410 1947 2015 41 1306 Munga Dhankuta 27.03 87.23 1317 1947 2014 42 1307 Dhankuta Dhankuta 26.98 87.35 1210 1947 2015 43 1308 Mulghat Dhankuta 26.93 87.33 365 1947 2016 44 1309 Tribeni Dhankuta 26.93 87.15 143 1948 2015 45 1314 Terhathum Terhathum 27.13 87.55 1633 1966 2015 46 1318 Chepuwa Sankhuwasabha 27.77 87.42 2590 47 1321 Tumlingtar Sankhuwasabha 27.28 87.22 303 1977 2015 48 1322 Machuwaghat Dhankuta 26.97 87.17 158 1949 2015 49 1324 Bhojpur Bhojpur 27.18 87.05 1595 1954 2003 50 1325 Dhingla Bhojpur 27.37 87.15 1190 1950 2015 51 1403 Lungthung Taplejung 27.55 87.78 1780 1947 2015 52 1404 Taplethok Taplejung 27.48 87.78 1383 1947 2015 53 1405 Taplejung Taplejung 27.35 87.67 1732 1947 2015

54 1406 Memengjagat Panchther 27.20 87.93 1830 1947 2015 55 1419 Phidim Panchther 27.15 87.75 1205 1978 2015 56 1420 Dovan Taplejung 27.35 87.60 763 1947 2015

Table 4 Koshi River basin real time rainfall stations

Index SN no Name Lat Lon 1 1009 Chautara 27.78 85.72 2 1103 Jiri 27.63 86.23 3 1206 Okhaldhunga 27.32 86.5 4 1307 Dhankuta 26.98 87.35 5 1321 Tumlingtar 27.28 87.22 6 604.5 Turkeghat 27.32 87.19 7 610 Barbise 27.79 85.88 8 630 Pachuwarghat 27.55 85.75 9 647 Busti 27.62 86.08 10 670 Rabuwabazar 27.27 86.66 11 690 Mulghat 26.93 87.33 12 695 Chatara 26.87 87.16 13 640 Panauti 27.57 85.51 14 8110 Lukla 27.70 86.72 15 9301 Chanku 27.77 86.26 16 9302 Gongar 27.84 86.22 17 9303 Lamabagar 27.91 86.21 18 9304 Rikhu 27.88 86.23 19 627.5 Melamchi 28.04 85.52 20 9308 Tsho Rolpa 27.86 86.46

Table 5 Koshi basin temperature stations

Index Station Name District Lat (0) Lon (0) Elev Data availability no. (m) period 1024 Dhulikhel Kabhre 27.61667 85.55 1552 1987 2016 1036 Panchkhal Kavre 27.68333 85.63333 865 1978 2015 1103 Jiri Dolkha 27.63333 86.23333 2003 1965 2016 1107 SindhuliGadhi Sindhuli 27.28333 85.96667 1463 1989 2014 1206 Okhaldhunga Okhaldhunga 27.31667 86.5 1720 1962 2015 1220 Chialsa solukhumbu 27.48333 86.61667 2770 1967 2009 1222 Diktel Khotang 27.21 86.8 1623 2007 2015 1303 Chainpur (East) Sankhuwasabha 27.28333 87.33333 1329 1987 2015 1304 Pakhribas Dhankuta 27.05 87.28333 1680 1987 2015 1307 Dhankuta Dhankuta 26.98333 87.35 1210 1987 2015 1314 Terhathum Terhathum 27.13333 87.55 1633 1989 2015 1405 Taplejung Taplejung 27.35 87.66667 1732 1962 2015

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1419 Phidim Panchther 27.15 87.75 1205 1989 2015

It is noted that the number of real-time stations is increasing regularly. New stations will be included in the forecasting system, as they become available.

Potential evaporation data is further available at two stations in the basin.

4.2.2 West Rapti River basin

Figure 4 The network of rainfall and river gauging stations in West Rapti River basin

The data availability in the West Rapti basin is listed below. Real time water level and rainfall data is available from 2011 to 2016.

Table 6 Hydrological stations in West Rapti River basin

Station River Name Location Lat (0) Lon (0) Elev( Basin Publication Remarks no. m) area (km2) From To

330 Marikhola Nayagaon 28.06 82.80 536 1938 1965 2006 Realtime

339.5 Jhimrukkhola Chernata 28.04 82.83 762 683 1971 1995 Realtime 340 JhimrukKohla Kalimatighat 28.04 82.87 692 696 1965 1970 350 Rapti Bagasotigaon 27.89 82.84 381 3380 1976 2006 360 Rapti Jalkundi 27.95 82.23 218 5150 1964 2006 Realtime 375 Rapti Kusum 28.00 82.12 235 5200 Realtime

Table 7 Rainfall stations within West Rapti basin

SN Index Station name District Lat (0) Lon (0) Elev (m) Data availability no period 1 407 Kusum Banke 28.02 82.12 235 1957 2012 2 412 Naubasta Banke 28.27 81.72 135 1971 2015 3 414 Baijapur Banke 28.05 81.90 226 1971 2015 4 419 Sikta Banke 28.03 81.78 195 1978 2015 5 420 Nepalgunj airport Banke 28.10 81.67 165 1996 2015 6 504 Libanggaun Rolpa 28.30 82.63 1270 1957 2015 7 505 Bijuwar tar Pyuthan 28.10 82.87 823 1957 2016 8 510 Koilabas Dang 27.70 82.53 320 1971 2015

Table 8 Real time rainfall stations within West Rapti basin

Index SN no Station name Lat Lon 1 407 Kusum 28.02 82.12 Nepalgunj 2 420 airport 28.1 81.67 3 504 Libanggaun 28.3 82.63 4 505 Bijuwartar 28.1 82.87 5 530 Swargadwari 28.13 82.63 6 527 Sulichour 28.18 82.5 7 537 Lamahi 27.87 82.54 8 438 Dhakeri 28.16 81.77 9 350 Bagasoti 27.89 82.84 10 330 Nayagaon 28.06 82.8

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It is noted that the number of real-time stations is increasing regularly. New stations will be included in the forecasting system, as they become available.

4.2.3 Satellite rainfall products as supplementary rainfall data Rainfall measured from satellites is becoming available in near-real-time at finer spatial scale these years and now represent a viable addition to ground measurements.

Key sources of satellite rainfall data are listed below.

a. TRMM (Tropical Rainfall Measuring Mission)

• Joint mission of NASA and the Japan Aerospace Exploration Agency (JAXA) • Geographic coverage: 600 N-S • Spatial resolution: 0.250x0.250 resolution • Temporal resolution: 3hour • Data span: 2000-till now • Availability: 8 hour after observation

b. GPM (Global Precipitation Measurement)

• International network of satellites, initiated by NASA and JAXA, as a successor to TRMM, improved accuracy • Integrated Multi-satellite Retrievals for GPM (IMERG) product • Geographic coverage: 600 N-S • Spatial resolution: 0.10x0.10 resolution • Temporal resolution: 30 minute • Data span: March 2015-till now • Availability: 6 hour after observation

c. GSMap (Global Satellite Mapping of Precipitation)

• Product by JAXA • Geographic coverage: 600 N-S • Spatial resolution: 0.10x0.10 resolution • Temporal resolution: 1hour • Availability: • Near real time (4-hr data after observation, since Oct. 2008) • Near real time version with gauge-calibration (4-hr data after observation, since Jan. 2017) • Real time version (0-hr data after observation, since Nov. 2015)

GSMap satellite rainfall data was used in Bangladesh for flood forecasting. It was also used as input data to the Integrated Flood Analysis System (IFAS) developed by International Centre for Water Hazard and Risk Management (ICHARM), which was applied in Philippines and Vietnam. Higher resolution satellite data as GPM or GSMap will also be used for supplementing rainfall data, where gauged rainfall is not available.

4.2.4 Handling missing rainfall data The catchment rainfall will be calculated in the modelling software as weighted average of the data available within the catchment. Different combinations will be tested to identify the most appropriate approach. Special combinations will further be derived to handle missing data, so that the best possible assessment of the catchment rainfall is made at all times.

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5 Approach and Methodology

The 2017 monsoon is the only high-flow period within the project. As it is important to test the system in real-time during a wet season we therefore aim at having a preliminary version of the FEWS up and running already by the end of July 2017.

This preliminary version of the system will be used for real-time forecasting in test-mode, so that issues can be identified and a basis for system refinement and adjustment of be established. As the forecast accuracy will be unknown and potentially poor at this time it is recommended to disseminate warnings and information only internally, to selected DHM and Consultant staff.

The project will be implemented as described in the following.

5.1 Task 1

Carrying out in-depth assessment of the Disaster Management Institutional Framework in Nepal and establishment of operational mechanisms with clear roles and responsibilities including the development of effective communication strategies.

A review will be made of the legal and regulatory framework for disaster risk reduction and early warning systems, highlighting gaps in the SOPs, if any, and assessing the definitions of role and responsibilities for key stakeholders.

National strategies and plans for disaster risk management will be evaluated, considering also experience from other countries, and recommendations made of actions to strengthen the linkage between government organisations and other stakeholders involved in FEWS, if required.

These organisations – and their relations - will be described, their capacities assessed, and recommendations made for any potential improvements identified.

The linkage between DHM and all other relevant stakeholders will be described in terms of the horizontal and vertical coordination mechanisms and any gaps highlighted.

The current FEWS applied in the basins will further be assessed on both technical, organisational, and institutional levels, and challenges identified.

Following documents will be reviewed to accomplish the objectives of task 1.

Legal and regulatory framework for DRR in Nepal: • Constitution of Nepal (2015) • Natural Disaster Relief Act (1982) • Local Self Governance Act (1999) • Water Resources Act (1992) • National Water Resources Strategy Formulation (2002) • National Water Plan, NWP (2005) • Water‐Induced Disaster Management Policy (2005) • National Strategy for Disaster Risk Management, NSDRM (2009) • District Disaster Management Plan, DDMP (2010) • National Adaptation Program of Action, NAPA (2010) • Nepal Risk Reduction Consortium, NRRC (2011) • Disaster Preparedness and Response Plans, DPRP (2011) • Local Disaster Risk Management Planning Guidelines, LDRMP (2011) • National Disaster Response Framework, NDRF (2013) • National Early Warning Strategy (2013) • Proposed new act on disaster management

• Three year interim plan, NPC

The legal/regulatory framework will further be compared to the frameworks applied in other countries.

The roles and responsibilities of the following organizations directly involved in flood disaster reduction will be reviewed.

• Ministry of home affairs (MOHA) • National emergency operation center (NEOC) • District emergency operation center (DEOC) • Department of Hydrology and Meteorology (DHM) • Department of Water Induced Disaster Management (DWIDM) • Ministry of Federal affairs and local development (MOFALD) • Health Service Department • Local level (Rural municipality, Municipalities, community) • Non-Governmental organizations (NGO) • Centre of Resilient Development (CoRD) • Disaster Preparedness Network (DPNet) • National Disaster Risk Management Forum (NDRMF) • International Non-Governmental organizations (INGO) • Practical action • Mercy corps • Plan international • Oxfam • United Nations (UN) organizations • United Nations Development Programme-Comprehensive Disaster Risk Management Project (UNDP-CDRMP) • Nepal Red Cross Society

5.1.1 Structure of an Early Warning System and assessment approach There are basically four components of the Early Warning System (EWS)

• Risk Knowledge: Systematically collect data and undertake risk assessments • Monitoring and Warning Service: Develop hazard monitoring and early warning services • Dissemination and Communication: Communicate risk information and early warnings • Response capability: Build national and community response capabilities

5.1.1.1 Risk Knowledge Risks arise from the combination of hazards and vulnerabilities at a particular location. Assessments of risk require systematic collection and analysis of data and should consider the dynamic nature of hazards and vulnerabilities that arise from processes such as urbanization, rural land-use change, environmental degradation and climate change. Identification of vulnerable areas and preparation of risk maps is necessary to concentrate early warning to particular location. Assessment of warning and danger level is necessary to make decision on warning and to guide preparations for disaster prevention and responses.

5.1.1.2 Monitoring and Warning Service This is the core of the system. Continuous monitoring of hazard parameters (flood level, rainfall etc.) is essential to generate accurate warnings in a timely fashion. There should be reliable forecasting models for predicting and forecasting hazards, operating 24 hours a day.

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5.1.1.3 Dissemination and Communication Once the forecast information is received, the warnings must reach those at risk. Clear messages containing simple, useful information are critical to enable proper responses that will help safeguard lives and livelihoods. Regional, national and community level communication systems must be pre-identified and appropriate authoritative voices established. The use of multiple communication channels may be considered.

5.1.1.4 Response Capability Once a flood warning is produced by the system, a clear chain of actions must be in place to ensure transmission of the warning and information to the communities at risk.

It is essential that communities understand this risk, respect the warning service and know how to react. Education and preparedness programmes play a key role. It is also essential that disaster management plans are in place, well practiced and tested. The community should be well informed on options for safe behaviour, available escape routes, and how best to avoid damage and loss of property.

The current status of these elements will be assessed and recommendations given for required strengthening.

5.1.1.5 Field visits Both primary and secondary data will be collected for this study. Secondary data relating to Flood Early Warning Systems will be gathered from national as well as district level in the form of project reports, annual reports, data recorded in respective national level institutions and district level institutions such as District Emergency Operating Committee/District Natural Disaster Relief Committee (DEOC/DDRC), Department of Hydrology and Meteorology (DHM) Basin Office, Nepal Red Cross Society and other INGOs and local organizations working on FEWS. Thorough review of these data available at central as well as district level will be carried out. This data mainly includes legal framework for disaster risk management including plan, policy, and strategy relating to the disaster management, previous studies national/international level, institutional linkages between key agencies working in FEWS at national and community level. Primary data will be collected through field survey. Qualitative tools will be employed to collect data/information in the two basins i.e West Rapti Basin and Koshi Basin. Two main qualitative tools i.e. i. Focus Group Discussion (FGD) and ii. Key Informant Interview (KII) will be employed to collect qualitative data/information. A semi-structured questionnaire will be administered for both the qualitative tools. Besides that, field observation will also be done.

a) Key Informants Interview (KII)

Key informants in this study will include chief/focal person/representative from DHM Basin Office, DEOC/DDRC, Nepal Red Cross Society, DWIDM, INGOs and local organization working on FEWS. A semi-structured questionnaire will be prepared as per the task mentioned in the TOR for the project and administered. The purpose of this will be to understand the real situation of the study area relating to communication and dissemination of flood forecast and early warning system and level of awareness on the same among the community in the two basins. Table 1 provides summary of number and type of respondents that will be interviewed during field survey.

Table 1: Summary of number and type of target respondents in two basins

Tools No. of Total Basin Key Target Respondents Respondents Respondents Chief of Basin Office 1

KII Chief or Focal Person of DEOC/DDRC 1

Chief or Focal Person of Red Cross Society 1 6

West Focal person of I/NGOs 1 Rapti Focal person of DWIDM 1 Gauge Reader (at Kusum Station) 1 FGD Mixed group 2 (Groups) 24 (Approx.) Chief of Basin Office 1 Chief or Focal Person of DEOC/DDRC 1 Chief or Focal Person of Red Cross Society 1 KII 6 Koshi Focal person of I/NGOs 1 Basin Focal person of DWIDM 1 Gauge Reader (at Chatara Station) 1 FGD Mixed group 2 (Groups) 24 (Approx.)

b) Focus Group Discussion

Two Focus Group Discussions (FGDs) will be conducted in severely affected community in each basin. The target respondents for the discussion will be school teacher, community leader, chairperson or member of local disaster management committee (LDMC), representative of Red Cross Society, member of EWS task force and people working on EWS. A mixed group (men and women) of 8 to 12 members will be organized, where group discussion will be carried out in the issues relating to FEWS. This discussion will be able to gather information on status of community based FEWS, level of awareness and knowledge on all four key components of FEWS among the community including both men and women, knowledge of safe place and route. It will also help to gather grass root level information of the community of severely flood prone areas.

Questionnaires are given in Appendix C.

The findings of Task 1 will be described in the Interim Report

5.2 Task 2

Comprehensive risk assessment of the threats caused by flood hazard in the two basins

Historical data of river gauging stations will be collected from DHM and analysed and relations developed between flood levels and the corresponding social and economic consequences. The social and economical impact of flood will be obtained from references such as the disaster reports of MOHA and disaster review report of DWIDM.

A library of GIS data will be compiled, highlighting locations vulnerable to flood. The GIS layers to compile are:

• Landuse/landcover • Settlements • Buildings and infrastructures within 500m of HFL

Flood maps for a long range of flood events (return period of 2, 5, 10, 20, 50, 100, 200, 500, 1000) will be prepared using combined 1D-2D models.

The flood mapping will mainly be performed in early 2018.

The hotspot areas will be identified from the output of social hazard assessment in the field, and flood modelling results. It is important that the communities in flood prone areas take appropriate action when a flood event is forecasted. The coping capacities of selected 4+ hotspot areas in

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each basin will be assessed and strengthened, as required, through improved procedures, mock drills, etc.

5.3 Task 3

Review of the SI Report on Observation network and assessment of network adequacy

The assessment report prepared by SI Observation Team 1 on the observation network will be reviewed with particular focus on the requirements for real-time forecasting.

The accuracy of forecasts is highly dependent on the availability of real-time rainfall data to assess sub-catchment rainfall and the availability of river gauging stations to update river flow in real-time. The hydrological and hydraulic models will be applied to assess the obtainable accuracy, using the existing network of telemetry stations and the potential gain of adding other stations to this network.

The applicability of the quantitative precipitation forecasts provided by DHM for forecasting will be evaluated considering the requirements for early warning and recommendations made accordingly.

5.4 Task 4

Integrated Flood Forecast Modelling System

A preliminary FEWS will be set up and made operational already during the 2017 monsoon, as this is the only rainy season within the project period on which to test the system in operation. The Consultant has mobilised additional resources to make this possible.

Figure 5 Preliminary delineation of sub-catchments in the Koshi and West Rapti basins. The triangles represent real-time river gauging stations

The model development activities include:

5.4.1 Data collection and processing Historical time series of rainfall, water level, discharge, temperature, and potential evaporation data from all stations, including real-time stations, will be collected and processed. The data will

be incorporated in a MIKE Operations database enabling analysis of data consistency, correlations etc.

GIS data on topography, land-use, station locations etc. will similarly be collected and included in the database.

5.4.2 Hydrologic modelling The NAM module is a well-proven hydrological model, which has been successfully applied to catchments under all climatic conditions and with a wide variation of data availability.

NAM is a lumped conceptual rainfall-runoff model simulating overland flow, interflow and base flow as a function of the moisture content in each of four mutually interrelated storages:

• Snow storage (optional) • Surface storage • Root zone storage • Groundwater storage

Figure 6 MIKE 11 NAM Hydrological model components

All dependant variables modelled in the NAM module are saved in simulation result files at each time step of the simulation. Consequently, all the important model variables relating to e.g. soil moisture conditions computed in one simulation will serve as initial conditions for subsequent simulations. In effect, this will ensure that important factors such as the antecedent soil moisture conditions will be portrayed accurately.

5.4.2.1 Data for hydrological modelling A flood forecasting system requires time series of rainfall for each sub-catchment to enable accurate simulation of the runoff. This has traditionally been obtained by applying Thiessen weights to the measurements at rainfall stations in or near the sub-catchment. Large spatial variation of rainfall and the difficulties of establishing stations in remote areas are major causes of uncertainty in this approach, however.

While data of rainfall stations is still important, the use of radar and satellite data can significantly improve the estimates of sub-catchment rainfall. Based on analysis of historical rainfall data, a procedure will be set up to generate a continuous time series containing the best

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possible estimate of the areal rainfall in sub-catchments at any times, ranging from the resent part long into the future, see Figure 7.

Figure 7 The Seamless Weather Generator

Historical data will be collected and analysed to determine how each type of data should be used for a given river basin.

This will include data of the Global Precipitation Measurement mission, which is an international network of satellites that provide the next- generation global observations of rain and snow. Building upon the success of the Tropical Rainfall Measuring Mission (TRMM), the GPM concept centers on the deployment of a “Core” satellite carrying an advanced radar / radiometer system to measure precipitation from space and serve as a reference standard to unify precipitation measurements from a constellation of research and operational satellites. Initiated by NASA and JAXA, GPM comprises a consortium of international space agencies.

GPM rainfall measurements are available in grids of 0.1 degree – some 10 km - with a time step of 30 minutes. After the initial test period, GPM data is now available online about 6 hours after each measurement.

The use of other satellite rainfall data will also be considered. The various sources of real-time rainfall data will be evaluated in terms of their usefulness in modelling the runoff from the corresponding sub-catchments accurately.

If data of any type is missing, the system will automatically shift to using another combination of data sources representing the next-best option, until finally rainfall representing typical values of that time of year is applied, when no data is available.

The applicability of the available QPF values for real-time forecasting will further be assessed.

Temperature data is required for snow simulation. The use of available real-time data will be assessed in comparison with using data of weather forecast models, which typically have better spatial distribution. For potential evaporation, standard annual variations will be applied.

5.4.3 Hydrodynamic modelling The hydrological model is seamlessly integrated with the hydrodynamic model MIKE HYDRO River, which includes comprehensive facilities for modelling river and channel networks, lakes and reservoirs, as well as river structures, such as gates, sluices, and weirs. In highly managed river systems, accurate representation of the river structures and their operation rules is essential.

In addition to incorporating the operation rules of structures in the model we provide an opportunity for the operator to manually overwrite the rules, if the actual operation deviates, e.g. in critical situations.

The models will initially be set up using readily available topography, including the collected cross section data at river gauging stations. In areas with no data, cross sections will be assessed by combining information from DEMs and typical cross sections near-by or along similar rivers. Information from reliable rating curves may further be applied. While this is sufficiently accurate for routing of the flow, model applications may show that more detailed topography is required at specific flood prone locations along the rivers. Surveys will then be scheduled accordingly. Judging from the preliminary model development it is likely that survey of river cross sections at real-time gauging stations up to the highest possible water level will be required.

The MIKE HYDRO River model can be set up to describe all flow paths of the river network sufficiently accurate to enable detailed mapping of floods at and near the rivers, see the example below. These maps are derived by combining the water levels simulated in the models river network and a detailed DEM.

Figure 8 MIKE HYDRO River based map of the January 2015 flood in Malawi

This type of flood mapping is useful in forecasting systems, as the maps can be produced very quickly.

Flood maps will also be prepared in 2D, however, using MIKE FLOOD, which combines one- and two-dimensional flood modelling.

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Figure 9 Sample flexible mesh grid for 2D flow simulation in MIKE FLOOD (Chao Phraya basin, Thailand)

The usefulness of the flood mapping methods in flood emergency situations will be evaluated, considering the required accuracy, speed, etc., to select the most appropriate method to incorporate in the operational forecasting systems.

5.4.4 Real-time updating A crucial part of the flood forecasting system is the MIKE HYDRO Data Assimilation module, which uses real-time data of river gauging stations to update the models. This ensures high forecast accuracy at each station as well as accurate flow to the downstream area, even in cases where rainfall data uncertainties have caused inaccurate runoff estimates or a GLOF has occurred upstream.

Figure 10 Example of data assimilation application - top: initial hindcast water levels prior to applying data assimilation, bottom: updated hindcast following data assimilation (i.e. differences between simulated and observed water levels are reduced) resulting in improved water level forecast

The MIKE HYDRO River DA module for real-time forecasting systems performs two functions:

• Model simulation results up to time of forecast are compared with real time observations, typically over the past few days, and the state variables in the model (water levels and discharges) are automatically corrected so that at the time the forecast is made the model represents the true state of the river system; • Deviations at each gauge are assessed and predictions made as to how the error will propagate into the future, so that corrections can continue into the forecast period and help improve the accuracy further.

The Data Assimilation continuously gathers information and, through automatic self-correction, constantly adjusts to changing real-time data and demands. The models are updated accurately to reflect the current situation in the catchment. The system is then positioned to make the best possible forecasts of water levels and discharges throughout the reservoir, river and flood plain system.

5.4.5 Model calibration The hydrological and hydrodynamic models will initially be calibrated and validated against long time series of historical data, including important flood events. As this generally is daily data, the model calibrations will subsequently be adjusted to apply and match the hourly data of the telemetry system. The system will be set up to utilise all available data at any time, so that any missing data is automatically disregarded.

The calibration will aim at a good water balance, correct shape of the hydrograph, and a good description of peaks in terms of timing and volume. This will require sufficient (real-time) data to assess the catchment rainfall and potential evaporation correctly.

The Data Assimilation module will further be calibrated to perform real-time updating and provide realistic predictions of the errors in the forecast period.

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5.4.6 Operational forecasting The operational forecast and warning system will be developed to automatically import real-time data, execute models, and disseminate results. The dissemination from the preliminary 2017 system will be to selected DHM staff only. If a flood is actually forecasted this year, the Consultant will assist DHM in interpreting the forecast and disseminating warnings accordingly to the communities at risk.

The DHM staff will get valuable experience in operating the system in cooperation with the Consultant during this flood season.

The models can be executed with time-steps down to one second, but usually a time step corresponding to the time interval of the available rainfall information is applied for the hydrological model and a time-step of a few minutes or less for the hydrodynamic models. Simulations are hot-started 1-3 days back to ensure correct initial conditions and efficient model updating. The hot-start collects the soil moisture and values of all other model variables from the previous forecast simulation at a time, when this was based on measured rainfall (rather than weather forecasts) and applies these as initial conditions. In this way, the impact of previous months’ rainfall and snow on soil conditions is automatically taken into account.

Model simulations continue into the forecast period of e.g. 3 days. It is noted that the accuracy during the last part of the forecast will rely heavily on the applied QPF values.

The flood forecasting system will be set up in MIKE Operations to automatically import real-time data and quantitative precipitation forecasts, perform model simulations, and generate maps of the forecasted extent and depth of flooding. A resilient hierarchy of data sources will be set up to ensure that missing or obviously erroneous data is replaced by the next best option.

The flood maps will be combined with GIS information on population and infrastructure at risk.

Figure 11 Examples of background map types incorporated in the user interface of the forecasting system

The system will run automatically and continuously, producing the output described above. DHM Key personnel and other stakeholders will be informed through sms / email on any threshold exceedance or other issues, requiring attention

Figure 12 Sample forecast overview, where sub-catchments and river gauging stations are colour- coded according to forecasted runoff or flow.

All components of the forecasting system are incorporated in a database, which comes with management facilities for back-up etc.

5.5 Task 5

Communication and Dissemination of Flood forecast and Early warning System

The FEWS will be developed to run automatically and provide results and warnings via e.g. text messages, email, and the web. The actual forecast calculations are proposed to be performed at DHM in Kathmandu. The regional offices will have web-access to the system and may be given full access remotely, if required and in compliance with the SOP, which will be developed in close cooperation with DHM. Hardware and software will be provided accordingly.

34 63800912 inception report version 3/ HCA / 2017-06-30 Approach and Methodology

The required MIKE software will be provided with a license in the cloud, so that DHM can apply the software from any of the offices. Hardware dongles will therefore not be provided. The latest version of the software will be installed towards the end of the project and continue to be applicable in future.

The dissemination of early warning will be designed to be efficient and compatible, if possible, with current good practice.

It is proposed to develop the system to automatically inform system operators, initially, via text messages and email whenever a threshold has been crossed. This includes river levels, which are forecasted to exceed warning or danger level, as well as high events of rainfall or predicted runoff from sub-catchment in the river basin. The operator would then analyse the forecast in the control room or optionally over the internet, using the web version of the software, if the alert is received outside working hours.

Figure 13 Sample web-site, where the amount of sub-catchment rainfall and the forecasted discharge at the gauging stations is indicated in colour-codes (green, yellow, red). A graph showing each forecast can be seen by clicking on the area or point.

If the operator approves the forecast, he/she can then activate dissemination of the warnings and information to stakeholders outside DHM.

This dissemination will typically include:

- Transmission of text messages and/or emails to a list of pre-selected receivers. The messages will hold crucial information and recommendations and will direct the receiver to the public web site for further information. - Upload of key information to a public web side. This may be similar to the view shown in Figure 13 and include: o Information on recent rainfall at gauging stations or measured by satellite. o Information on the forecasted rainfall over the coming days o Information of measured and forecasted river levels at key locations - Other potential methods include sirens, radio/TV, social media, and shouting. A toll free number, through which people may contact DHM for detailed information, is already used quite frequently

Community-based flood early warning systems are already set up in many parts of Nepal, also within the project area. The recent visit to West Rapti basin showed that the local, flood prone communities generally have a good understanding and appreciation of these systems, including awareness on the warning systems themselves, areas in risk of inundation, and evacuation routes. In Fatehpur, the lack of safe places is a concern.

While text messages generally is seen as an efficient means of warning dissemination, extended periods without electricity makes phone charging a matter of concern.

The FEWS will build on and support the existing systems of flood warning through cooperation with the concerned organisations.

For further information on the field visit to West Rapti basin, see Appendix C.

5.6 Task 6

Design and development of an Operational Decision Support System (ODSS)

The required equipment for the workstations will be specified along with staff requirements etc. to ensure efficient communication of flood warnings and information, and SOPs developed accordingly.

A critical element in this will be to express forecast uncertainties, which may be quite high towards the end of the forecast period, in a way, which still prompt appropriate, early action by the concerned organisations and communities.

Using the generated flood maps and other information, evacuation plans will be elaborated in cooperation with local authorities. Pre-disaster workshops and drills will further be conducted, supported by leaflets and other information.

5.7 Task 7

Capacity Development

Operation manuals for all system components will be prepared.

Training in all system components will further be planned (Task 6) and conducted for DHM staff, who are also expected to participate in the project activities.

A tentative schedule of training activities is given below.

Introduction to preliminary FFEWS On-the-job introduction to the preliminary flood forecasting system 2017 for DHM staff. The purpose of this training is to enable the staff to understand, apply and control the forecasting system in real-time.

2-4 August: Introduction to the preliminary forecasting system

6 August: Presentation of the system for senior staff

8-9 August: Application of the system

National Workshop To create awareness and obtain feedback from stakeholders, a national workshop is proposed.

36 63800912 inception report version 3/ HCA / 2017-06-30 Approach and Methodology

Date: 7th August 2017

Tentative programme:

Time Subject By

10:00 Welcome DHM

10:15 Flood Forecasting in Koshi & West Rapti river basins DHI

10:45 The operational forecasting system DHI

11:15 Break

11:30 Community-based warning NDRI

12:00 Discussion

12:30 Project plans DHI

12:45 Closure DHM

Similar workshops will be conducted towards the end of the project in each river basin.

Flood forecast modelling Training in the applied modelling tools covering general introduction and specific training in the developed models for Koshi and West Rapti river basins.

Proposed period: 24th September – 6th October 2017

Subjects:

• MIKE 11 RR for hydrological modelling including snow • MIKE 11 HD for hydrodynamic modelling • MIKE 11 DA for real-time updating

Operational forecasting Training in the developed operational system, performing the forecast calculations and disseminating results and warnings.

Proposed period: 22nd – 27th October 2017

Subjects:

• System set-up • Interpretation of forecast results • Troubleshooting

Flood mapping Training in flood inundation mapping in forecasting systems. Flood mapping, using the latest DEM data, should be set up in both basins before this training.

Proposed period: March 2018

Subjects:

• 2D hydrodynamic modelling • Inundation mapping for forecasting

Additional courses A range of additional course may be conducted depending on DHM preferences. These may include:

• Using satellite rainfall in flood forecasting. • Advanced hydrodynamic modelling. • Mike Workbench for data management etc. • Tailoring web sites for flood forecast systems

Operational use of the FFEWS A final course in the application of the completed forecasting system is proposed. The contents to be agreed with DHM.

Proposed period: May 2018

Based on assessment of institutional capacities and lessons learned during the test-forecasting period of the 2017 monsoon, a sustainability plan will be drafted and discussed with the client and SI.

Operational support is provided during the 2017 monsoon and the performance assessed in terms of up-time, real-time data availability, forecast accuracy etc. Adjustments will be made regularly, as required. Details on the performance will further be collected for post-monsoon processing.

Remote technical support will be provided for 2 years after completion of the project activities

6 Project implementation plan

As described above, the development of the forecasting system will be the main priority in the initial months, so that real-time forecasting can be tested in the 2017 monsoon.

Task 1, concerning the institutional framework, will be carried out in parallel.

The project implementation schedule is given below, covering also the remaining project activities.

The reports are referred to using the following numbers:

1. Inception report 2. Interim (Progress) Report 3. Second Progress Report 4. Mid-term Report 5. Operation and Commissioning Report 6. Third Progress Report 7. Draft Final Report 8. Final Report

Most of the key staff have already been mobilised along with several colleagues to enable development of the preliminary forecasting system by July 2017. As it is not practical to bring all the staff to Nepal, these activities are mainly carried out in this initial phase at DHI India and DHI Denmark, while staff at our office in Kathmandu is interacting with DHM on data issues etc. The Consultant will aim at carrying out all subsequent activities in Nepal.

38 63800912 inception report version 3/ HCA / 2017-06-30 Project implementation plan

The key experts within meteorology and survey have not been given any tasks at this time. The need for input by these and other experts will be assessed shortly after the 2017 monsoon, considering performance of the system during the monsoon and the remaining deliverables, as specified in the Contract.

Current activities and plans for the key experts are listed below. Work carried out by other consultant staff is omitted from this list.

International Experts

Hans Christian Ammentorp The Team Leader is supporting all activities, currently guiding all teams working in Denmark, India, and Nepal to develop the preliminary FEWS. He plans to visit Nepal again in early August 2017, when this is expected to be in operation and to help monitoring the performance during the remainder of the monsoon period.

Jayaraman Potty The Numerical data analyst was proposed to help produce QPF in RIMES, which is his speciality. As DHM is now generating QPF of a better quality, and not using RIMES, this is no longer required, so no activities are currently planned for him.

Gregers Jørgensen The Flood Forecasting Expert has been developing models in cooperation with other experts at DHI Denmark to ensure a first version of the FEWS operational by July 2017. He will continue this and help monitoring and adjusting the system during and after the monsoon.

Anders Klinting The ICT System Expert is developing the operational forecasting system in cooperation with Amit Garg and others to make a first version by July 2017. This includes linking to real-time data and QPF, automatically running models and extracting key results, and disseminating information and warnings. He will monitor the performance and make necessary adjustments during and after the monsoon.

Amit Garg The Hydromet Database management Expert has also been contributing to establishing the operational system, and will continue this. He will visit Nepal in early August 2017 to help make DHM familiar with the preliminary FEWS. The work to set up a database of hydro-meteorological data has further been initiated.

National Experts

Khana Nanda Dulal The Deputy Team Leader is contributing to all activities, and will continue to do so, initially with special focus on Task 1 and 2.

Suresh Marahatta No activities are planned for the Meteorologist at this time.

Binod Prasad Dhakal The GIS expert has provided data for the model development, e.g. in the form of elevation zones for snow modelling. Other GIS data is under preparation.

Ujwal Chandra Gautam The Survey Expert is not yet mobilised, but is likely to be required after the monsoon.

Manjeshwori Singh The GESI Expert is focusing on Task 1. She planned and led the field visit to West Rapti basin. A similar visit to Koshi basin will be conducted shortly.

Raj Mukut Bhusal The Training Expert is also contributing to Task 1 so far. He will later manly contribute to capacity building activities in the basins.

40 63800912 inception report version 3/ HCA / 2017-06-30 Project implementation plan

Tentative schedule No Task 2017 2018 2019 2020 Assessment of institutional framework for disaster management (CMS) 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 1.1 Review of Legal and Regulatory Framework 1.2 Review good practice examples of the National Disaster Management Plans 1.3 Organizational Analysis at the National and Basin level 1.4 Identify linkages among Disaster Risk Management (DRM) agencies 1.5 Assess current status of Flood Early Warning Systems 1.6 Summary and recommendations Risk assessment in the basins (CMS) 2.1 Analyse historical data on floods, link levels to severety 2.2 GIS database on topography, land use, flood maps etc. 2.3 Identify 4+ vulnerable locations in each basin and plan/rehearse emergency actions Review observation network status & plans (DHI/CMS) 3.1 Review SI report 3.2 Recommend strengthening of network as required 3.3 Assess available information Flood Forecasting modelling (DHI) 4.1 Develop models (RT mapping in the 4*2 locations, embankment breach, snow, etc.) 4.2 Integrate FF with knowledgebase, as MC, but freely available, if possible Communication & Dissemination (DHI/CMS) 5.1 Develop web-based FFEW system: see maps on mobile phone, emails, Rich Site Summaries 5.2 Dissemination system, considering existing systems 5.3 Operational strategy to warn communities ODSS for 24/7 operation of the FFEWS (CMS) 6.1 Specify (hardware and) software for 2 regional warning centres, “work-stations” 6.2 Contribute to specify equipment, staff, training requirements 6.3 SOPs for communication and dissemination 6.4 Support evacuation route planning 6.5 Exercises and drills 6.6 Pre-disaster workshops and performance evaluation * * 6.7 Outreach: leaflets, workshops, ... * Capacity development (DHI/CMS) 7.1 Prepare system operation manual 7.2 Training plan and implementation 7.3 Workshops at national and river basin level * * 7.4 Sustainability plan 7.5 Operational support for one flood season and evaluation afterwards. Two years of remote support Reports 1 2 3 4 5 6 7 8 41

7 Risks and issues

The accuracy of forecasts is highly dependent on the data available for system development as well as the data applied in real-time to calculate runoff and river flow. The main issues are:

1. Data accuracy. The models of the forecasting system will be calibrated against the available discharge data, which may deviate from the actual flow due e.g. to uncertainties in rating curves. The Consultant will critically assess all data and seek the help of DHM to validate any dubious data.

2. Data coverage. Although the coverage of rainfall stations seems to be good, large areas of the river basins are without any stations. Heavy rainfall in these areas will therefore be unknown to the hydrological models, leading to inaccurate assessment of runoff. The Consultant will therefore apply also satellite rainfall data in the model development and real- time operation. The new GPM data, replacing TRMM, will be applied. While this data has full coverage its accuracy in the basins remain to be seen.

3. River cross sections at gauging stations. While cross sections between stations may be derived from a DEM, higher accuracy is required at the real-time river stations, where the hydrodynamic model will be updated in real-time based on the latest, available measurements. An initial enquiry at DHM indicates that information on the river cross sections at the stations is not available. This can have a significant impact on the forecast accuracy.

4. The flood mapping in the lower Koshi basin will be carried out using a digital elevation model, which has not yet been generated. Delay in the procurement of this DEM may delay or even prevent the development of a 2D model for lower Koshi and the associated project activities. DHM is therefore encouraged to ensure a swift implementation of the DEM project.

5. Data availability. Discharge data is available up to 2014, but as this was the first year of the GPM mission, it is important to obtain discharge data for 2015 and 2016 also, particularly at the real-time hydrological stations, so the models may be calibrated for these two years. DHM is requested to make this discharge data available as soon as possible.

6. Delay in FEWS development. A number of issues may occur during system development, related e.g. to inconsistency in the applied data. The Consultant has already allocated highly experienced staff to help address these and will intensify the effort further, if required, to have the preliminary FEWS operation by the end of July 2017.

7. Loss of power supply or internet connection during floods would prevent forecast calculation and/or dissemination. Measures to avoid such losses are recommended.

8. Insufficient capacity of stakeholders. It is important to ensure that all organisations and staff involved in the generation and use of warnings are capable of performing their roles and have the required resources. In accordance with the TOR, the Consultant will assess the situation and provide recommendations. Training courses, workshops, and drills will further be conducted, and the system will be made as automatic and easy to operate as possible, to limit the requirements for staff and resources for system operation.

8 References

Climatological records of Nepal, DHM

Community based flood early warning system for Hindu Kush Himalaya, Resources Manual, ICIMOD, November 2016

Conducting Koshi River Flood Forecasting and Early Warning System- Package 2. DWIDP, August 2012

Danger level and warning level estimation reports, DHM

Disaster and Climate Risk Management Policy Framework: Good Practices, Challenges and Learning, Nepal Administrative Staff College, 2014

Disaster reports, MOHA, 2009-2015

Disaster review, DWIDM, 2015

Flood and sediment management in Kosi river, Dr.Dilip Kumar, Deput Director, FMISC, PATNA (INDIA), IWRA Congress, May 2015

Flood Early Warning System in Practice-Experiences of Nepal, Practical Action, 2016

Flood Early Warning Systems in Nepal- A Gendered Perspective, ICIMOD, 2014

Flood Hazard Mapping and Preliminary Preparation of Flood Risk Management Projects, DWIDM, Water Resources Project Preparatory Facility, 2016

Gautam, D.K. and Phaiju, A.G., Community Based Approach to Flood Early Warning in West Rapti River Basin of Nepal, Journal of Integrated Disaster Risk Management, 3(1), 2013

Koshi River Cross-Section Survey, Hazard Map Preparation, Embankment Breach Analysis, and Soil Sampling and Analysis. Part B: Hazard mapping, DWIDP July 2012

Landslide Hazard Mitigation in the Hindu Kush Himalayas, ICIMOD, 2001

National Disaster Response Framework, Ministry of Home Affairs, July 2013

National Strategy for Disaster RiskManagement in Nepal,Ministry of Home Affairs, March 2008

Policy compilation, Ministry of home affairs (MOHA)

Strengthening Flash Flood Risk Management in the Hindu Kush Himalayas, ICIMOD, 7th World Water Forum, 2015

Surface water records of Nepal, Department of Hydrology and Meteorology (DHM)

Technical summary report prepared by system integrator (SI), PPCR/BRCH, DHM

URLS: www.dhm.gov.np www.hydrology.gov.np www.dwidm.gov.np www.moha.gov.np www.drrportal.gov.np

63800912 inception report version 3/ HCA / 2017-06-30

www.neoc.gov.np www.icimod.org www.wecs.gov.np http://pmm.nasa.gov http://sharaku.eorc.jaxa.jp

APPENDICES

63800912 inception report version 3/ HCA / 2017-06-30

APPENDIX A – Minutes of meeting

63800912 inception report version 3 / Initials / yyyy-mm-dd DHM

DHM

25th April 2017

Presence DHM Rishi Ram Sharma, Director General and National Project Director of PPCR/BRCH Saraju Kumar Baidya, Deputy Director General and Assistant National Project Director of PPCR/BRCH SI Adarsha Prasad Pokhrel HarriPietarila Kamal prakashBudhathoki Consultant Hans Christian Ammentorp Flemming Jakobsen Khada Nanda Dulal Krishna Poudel RajanSubedi

Key points Following introductions, the project and its tasks were discussed, highlighting the limited time period available for project implementation. DHM and the SI promised to cooperate with the consultants for the completion of the tasks within the stipulated time. The consultants showed their concerns about the amount and quality of available data for the development of the FEWS. It was understood in the meeting that a number of other projects such as the generation of fine resolution DEM for Koshi will start soon, which will be necessary in this work.

DWIDM

30th April 2017

Presence DWIDM Madhukar Prasad Rajbhandai, Director General (DG) Consultant Hans Christian Ammentorp Khada Nanda Dulal Krishna Poudel

Key points The consultant briefed about the flood forecasting and early warning system to be developed for Koshi and West Rapti River basins. The DG of DWIDM elaborated on the roles and responsibilities of the DWIDM for the management of flood disasters. The DWIDM had prepared flood hazard maps for a number of rivers, particularly in the Terai area. One of the main activities of the department is the river training works for the mitigation of floods. Upon request from DHM, the department is ready to provide the data and information on these two rivers, which will be useful for the project. Once the system is ready, the DWIDM expects to get access to the flood forecasts so that prompt action can be taken during the event of flood.

A-1

DHM

2nd May 2017

Presence SI Adarsha Prasad Pokhrel Kamal prakashBudhathoki Consultant Hans Christian Ammentorp Flemming Jakobsen Khada Nanda Dulal

Key points During the meeting, the contents to be included in the inception report were discussed. The SI requested the consultant to follow the deadline for the submission of the inception report. It was agreed that a presentation by the consultant should be given on the contents of the inception report on 8thMay, 2017, if possible. SI will contact DHM to make the appointment.

ICIMOD

2ndMay 2017

Presence ICIMOD Mandira Shrestha, Programme coordinator HYCOS Initiative Pradeep Dangol, Research associate KanchanShrestha, Programme Officer Koshi Basin Programme Consultant Hans Christian Ammentorp Flemming Jakobsen Khada Nanda Dulal

Key points ICIMOD has earlier developed a MIKE model for Koshi River basin for flood forecasting, and the staff involved have elaborated further on this model in recent years. Lately, an ALOS DEM has been procured by ICIMOD. They have similarly developed a large-scale model of the Ganges- Brahmaputra basin to provide Flood Outlook.

A number of relevant reports have been issued by ICIMOD and are available on their web site.

A possible involvement of ICIMOD in the present project was discussed, as they might contribute with the existing model and their knowledge and expertise in general. They could be interested in this if they might retain copiesof the developed models at the end of the project. DHI promised to take this up with DHM.

DHM

7nd May 2017

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DHM

Presence DHM Rishi Ram Sharma, DG Saraju Kumar Baidya, DDG Rajendra Sharma, SDH Krishna Bajracharya, SDC BinodParajuli, Hydrologist Sunil Pokharel, Hydrologist SI Adarsha Prasad Pokhrel Kamal prakashBudhathoki Consultant Hans Christian Ammentorp Flemming Jakobsen Khada Nanda Dulal Manjeshwori Singh Krishna Paudel SudeepAdhikari Debasis Sarangi WB Pratima Shrestha

Key points From the consultant’s side team leaderHans Christian Ammentorp presented the contents of the inception report. Following a general introduction to flood risk management, he provided examples of the flood forecasting and early warning systems developed in other countries. He then discussed the data requirements, availability of data, approach and methodology of the study, tasks of the study, work plan, manpower schedule and deliverables.

Comments and suggestions were made by several participants. It was suggested to include data from various sources, f.eks. combining rainfall gauge data, QPF, satellite, radar. Issues raised on the following aspects were also discussed, which will be addressed in the inception report: applicability of 2D model in flood plain, accuracy in calibration, bias correction, impact of GLOF, inclusion of hydraulic structure (barrage) in model, selection of flood prone areas for drill, dissemination mechanism, support after project. The consultants requested DHM to provide cross-section data at gauging stations and provide the final resolution DEM of flood plain area as early as possible for the completion of modelling tasks on time. The consultants will prepare the inception report covering the contents mentioned in the TOR.

A-3

DHM 9th June 2017

Presence DHM Binod Parajuli, Hydrologist Consultant Hans Christian Ammentorp Khada Nanda Dulal Laxmi Prasad Devkota

Key points The consultants outlined plans for a field trip to West Rapti basin (Banke district) and Koshi basin (Sunsari, Saptari district), which is one of the activities to accomplish the output of task 1. From DHM, the focal person of the project Mr. Binod Parajuli made suggestions on the schedule. He will provide the contact numbers of the focal persons in the field and also talk with the chief of DHM basin office for coordination with the consultants during the field trip. The consultant further handed over hardcopies of the revised Inception Report to Mr. Parajuli.

DHM 14th June 2017

Presence DHM Jagadishwor Karmacharya, DDG, Meteorological Forecasting division (MFD) Binod Parajuli, Hydrologist Consultant Hans Christian Ammentorp Khada Nanda Dulal Rajesh Kumar Mahana

Key points The consultant briefed about the necessity of QPF data for making the flood forecast. The DDG of MFD informed the consultant that the DHM has been running WRF model since last year, which gives the QPF of Nepal in 4kx4km grid. The consultant will work together with the MFD of the DHM to hook up the QPF output of the WRF model with the flood forecast model.

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DHM

DHM 21st June 2017

Presence DHM Rishi Ram Sharma, DG Saraju Kumar Baidya, DDG Rajendra Sharma, SDH Binod Parajuli, Hydrologist Sudip Bhattarai, SDE SI Adarsha Prasad Pokhrel Kamal prakash Budhathoki Consultant Hans Christian Ammentorp Khada Nanda Dulal Manjeshwori Singh Rajesh Kumar Mahana

Key points The team leader, Hans Christian Ammentorp, presented the current status of the work. He showed the preliminary results of hydrological model in the Koshi basin. The comments on the revised inception report were elaborated by the DHM. The consultant will submit the final inception report after incorporating the comments around 1st July 2017.

A-5

Field Visit to West Rapti basin, Banke district

Team members Khada Nanda Dulal Laxmi Prasad Devkota Manjeshwori Singh Rajesh Kumar Mahana

18th June, 2017 I. Visited the DHM basin office in Nepalgunj, discussed with the basin chief, Bir B. Chand, on the status of FEWS, and the role of DHM basin office II. Visited the District Emergency Operation Center (DEOC), Banke district, conducted KII with the focal person, Gauri Budhathoki, met with the DDRC focal person to discuss about the flood disaster management III. Visited Nepal Red cross society (NRCS), Banke branch, conducted KII with the chief, Nirnajana Malla, took information on the relief work

19th June, 2017 I. Visited the community at Fattepur village and conducted FGD II. Visited the community at Holiya village and conducted FGD III. Visited practical action office, Nepalgunj and conducted KII with the chief, Lok Narayan Pokharel

20th June, 2017 I. Visited the Kusum hydrological station, conducted KII with the gauge reader II. Visited the DWIDM, Nepalgunj office and took the information on structural measures implemented in the West Rapti basin, Banke part

For findings, see Appendix B.

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APPENDIX B – Field Trip to West Rapti Basin

63800912 inception report version 3/ HCA / 2017-06-30 DHM

Field visit at West Rapti

A field visit at West Rapti, Banke district, was conducted by a team of 4 members from June 18 - June 21, 2017. District level primary data was collected from DHM Basin Office, DEOC, Nepal Red Cross Society and DWIDM at district headquarter, Nepalgunj. Community level data was collected from two severely flood affected VDCs namely Fatehpur and Holiya. Furthermore, Gauging station, Kusum was also visited to observe current status of the station. Face to face interview was conducted with the Chief or representatives of the organizations. At the community level, Focus Group Discussions were conducted with the community people to collect information on the severity of flood, early warning mechanism, effectiveness of the FWES, challenges and room for improvement etc. The response of key representative of the organizations working on FEWS was collected. This includes;

. Mr. Bir Bahadur Chand, Chief of DHM Basin office, . Mr. Gauri Lal Budhathoki, Information Management Officer, DEOC, Banke . Ms. Niranjana Malla, Senior Branch Officer, Red Cross Society . Mr. Prahllad Bishwokarma, Red Cross Society . Mr. Lok Nath Pokharel, Chief, Practical Action office, Nepalgunj . Mr. Gokarna Chand, Engineer, DWIDM . Mr. Bhadra Br. Thapa, Gauge Reader at Kusum Station

Some of the key finding responded by the key informants and communities during KII and FGD in relation to four key components of FEWS are presented below. 1. Risk knowledge:  Hazard map, vulnerability map, and risk map were found to be prepared as mentioned by all respondents in the area.  Community people were involved during the preparation of hazard, vulnerability and risk maps. Involvement of 1 member from each HH, involvement of women’s group. Consequently, majority of people were found to be aware about the maps.  Involvement of women is increasing due to migration of male members which opens door for women to participate in public activities in last 5/7 years. Furthermore, women themselves have found to become active in FEWS.  Women’s needs, concerns, and knowledge included in the community vulnerability assessments conducted for floods.  Hazard map, vulnerability map, and risk maps made organizations working in FEWS easy to work in affected area.  Communities are found to be aware about warning system, inundation area.  People were found to have knowledge about safe place and its route. However, people mentioned that they have no proper safe place in Fatehpur.

2. Monitoring and warning services:  The good part of FEWS were;  Fast and easy broadcasting of information  Safety of people and assets  Able to storage of dry foods Early warning helped people to reduce impact of flood on the property and human life.

 Forecasting and warning products were found to be easily understood by majority of the community. There is a provision of access to warning information by all the community people, all including women, men, elderly, children and differently able people. However, level of understanding is different.

B-1

 In order to ensure that warnings have been reached to the all community people including women, men, elderly and children,  Pre assessment of elderly, pregnant women, children and differently able people has been conducted.  Monitoring and update of information through phone call was collected before delivering the warning message.  3. Communication and dissemination  The key media for disseminating FEWS in the community are as follows;  Siren  Mobile phone  Radio-FM  SMS  Shouting  DDRT- GPS mapping  Over all communication and dissemination of warning information seems better in Holiya than in Fatehapur. 4. Response capability  Mock drill was conducted by Red Cross Society once a year  Availability of rescue equipment but not sufficient.  Assessment of response capability of the community found to be limited.  Detail post-flood assessment and feedback collection is also found to be limited.

Key Challenges FEWS dissemination . Due to lack of electricity and network problem, mobile phone cannot be charged for long time and information cannot be disseminated through mobile phones. . Lack of store rooms/warehouse to store rescue equipment and food items. . Sustainability problem (lack of ownership by community) . Lack of safe place and shelter. . Both auto and manual gauge reader are installed at the gauge station, Kusum, Banke district. If the auto collection has problem data cannot be collected. Due to lack of skilled manpower for repairing automatic gauge, the expert has to come from Kathmandu, and thus the system remains down for a long time. . During heavy rain, the information cannot be collected at night and due to lack of extra support, challenge arises while collecting information manually. Areas for improvement . Provision for mobile charge should be done. . Mass warning through SMS can be done. . Slow network should be improved . Warning on Hoarding Board should be installed . Information dissemination from Police Station . Training on technical part of FEWS should be given to local people . Provision of shelter and safe place should be managed at least for 3-4 months and educate about route for safe place. . Provision for toll free service

B-2 63800912 inception report version 3/ HCA / 2017-06-30 DHM

B-3

APPENDIX C– Questionnaires

63800912 inception report version 3/ HCA / 2017-06-30

Checklists Key Informant Interview (KII)

Name of key informant: Position: 1. Name of the organization:

2. What is your organization’s coverage area (geographical)?

3. Are you working on Flood Early Warning System (FEWS)?

If yes, which components of FEWS does your organization work on?

a. Risk knowledge b. Monitoring and warning services c. Communication and dissemination d. Response capability e. All

4. Risk knowledge:

i. Do you have the hazard map, vulnerability map, and risk map? Yes/No If No, why? If Yes, what are benefits you got from these maps?

ii. Is community involved in the preparation of these maps? Yes/No If yes, are both women and men involved in is preparation? Yes/No If No, why?

iii. Are women’s needs, concerns, and knowledge included in the community vulnerability assessments conducted for floods?

iv. Is the risk reduction strategies prepared?

Yes/No If No, why?

v. Have community’s indigenous knowledge been incorporated in these assessments? Yes/No If yes, please specify the type of knowledge incorporated in them.

If No, please explain why?

vi. Which other organizations have been engaged in these assessments?

Hazard: Vulnerability: Risk:

vii. Do you have any tools (model, maps etc.) for followings;

Assessment of hazard Yes/No Assessment of vulnerability Yes/No Assessment of risk Yes/No Dissemination of alerts Yes/No

5. Monitoring and warning services:

i. Has forecasting and warning services been established? Yes/No If yes, what are the good and bad parts of the warning services?

ii. Are you or yourorganization involvedin the DDRC (District Disaster Reduction Committee)?

63800912 inception report version 3/ HCA / 2017-06-30

iii. How do you ensure that warnings have been reached to the community people, both women and men equally?

iv. Are the forecasting and warning productsunderstood by the community? Yes/No If No, why?

v. Is traditional knowledge of the community considered in forecasting? Yes/No If yes, specify

If No, why?

vi. Is documentation of the hazards data and analysis from regional networks, adjacent territories, and international sources accessible? Yes/No

6. Communication and dissemination

i. What is the channel of communication and dissemination of FEWS?

ii. Who are involved in disseminating flood early warning?

iii. What are the key media for disseminating FEW? Which media is more effective?(FM, TV/Radio, website, Newspaper)

iv. Is there an effective communication systems and equipment installed in the community? If yes which equipment are in use? (telephone, mobile, siren, miking etc.)

v. In your opinion can women access to early warning systems messages on time as men? Yes/No If No, why?

vi. Is there any provision to make sure that women will receive flood alerts/warnings on time? Yes/No

vii. Is there feedback mechanism to show whether the risks and warnings are understood by the community people including women, elderly and disables?

viii. Do you go to the people/community after the flood event and get feedback?

7. Response capability

i. Have you taken part in training on FEWS? Yes/No If yes, Please specify If No, why?

ii. Have you participated in planning for response preparedness and capacity building? Yes/No If yes, what type of plan was it?

iii. Are the flood disaster preparedness and response plans established? Yes/No

iv. Have you organized mock drills activity for enhancing response capability of the community? Yes/No If yes, (frequency/year)

v. Is community response capacity assessed? Yes/No

vi. What are the means of public awareness activities/campaigns with regard to response capacity building?

63800912 inception report version 3/ HCA / 2017-06-30

vii. What is your level of confidence that warnings/alerts received by the community will enable them to respond promptly and properly?

viii. Is public awareness and education campaigns tailored to the specific needs and concerns of women, elderly and disables?

8. Could you please provide us with your experiences on the key strengths, challenges and areas for improvement in early warning systems for the community?

Key strengths Challenges Areas for improvement

9. Information on flood history (last 5 years)

Year of Affected Max. depth of Duration of Loss of Property flood VDCs inundation in inundation lives loss the most (Destroyed affected houses/agri. community Land/ crop product etc.)

10. Human resources and their capacities in the organization

i. How many staffs (technical and non-technical) are there in your organization? Type No. Male Staffs No. Female Staffs Total Staffs Technical Non-technical

ii. Could you please give information relating to capacities of your Technical Staffs as follow? S Positio Qualificati Compete Training Experien Role in Remarks N n on ncy (4 received in 4 ce in FEWS compone components FEWS nts of of FEWS* FEWS*)

*Note: i. Risk knowledge ii. Monitoring and warning services iii. Communication and dissemination iv. Response capability

iii. Could you please give information relating to your organizational capacities as follow? Physical Capacities Financial Institutional Social Capacities resource EWS Yes/No Network Network with various First aid kit Yes/No Linkage with DHM organizations: Telephone Yes/No No of CBOs (Please Rescue Yes/No specify) equipment Yes/No Shelter

63800912 inception report version 3/ HCA / 2017-06-30

No of GOs (Please specify)

11. Technical and human resource capacity at professional level for FEWS:

Professional Qualificati Competenc Training Experien Role level on y 4 received 4 ce component components (Years) s of FEWS*) of FEWS*) Engineers: Civil Computer Electrical Mechanical Other

Hydrologist:

IT Officer:

Meteorologist:

*Note: i. Risk knowledge ii. Monitoring and warning services iii. Communication and dissemination iv. Response capability

12. What is your organization’s disaster coordinating mechanism with DRM agencies and DHM?

Local Offices Central Local DHM Central Local Remarks DHM NEOC NEOC DEOC DWIDM CBOs I/NGOs Private institutions Clubs/groups- women’s’ group, Note: Both Vertical and horizontal linkage

63800912 inception report version 3/ HCA / 2017-06-30

Checklists Focus Group Discussion with community and relevant stakeholders

A. General:

1. Do you have FEWS in your community? Yes/No 2. Is it effective and sustainable?

 Timely warning  Coverage  Affordability  Reliability

3. How is FEWS managed?

4. What are the lessons learned from the existing system?

5. Are there any needs for modification of the system?

B. Key components of FEWS: i. Risk knowledge: 1. Are you aware of the hazard map, vulnerability map, and risk map? Yes/No

2. Have both women and men been involved in the development of hazard and risk maps? Yes/No

3. Have community’s indigenous capacities and knowledge been incorporated in the assessment? Yes/No

4. Has an advocacy campaign been carried out for flood early warning? Yes/No

5. Are you aware of the following; Aware on Yes No Aware on Yes No Evacuation place Flood hazard area Route of evacuation place Shelter

Safe area Flood forecasting

ii. Monitoring and warning services: vii. Does the community involve in monitoring and warning services? Yes/No viii. Do the flood warnings reach to the community people including both women and men equally? Yes/No

ix. Does the community have knowledge of monitoring and warning equipment? Yes/No If yes, how?

If No, why?

iii. Communication and Dissemination

ix. Do you know the channel of communication and dissemination of FEWS? Yes/No

x. Does the community people involve in disseminating flood early warning? Yes/No

xi. Do you know the key media for disseminating FEW? Yes/No If yes, Which media are more effective? (FM, TV/Radio, website, Newspaper, please specify if any other)

xii. In your opinion can women access to early warning messages on time? Yes/No If yes, how?

If No, why? xiii. Is there an effective communication systems and equipment installed in your community? If yes which equipment are in use? (telephone, mobile, siren, miking, etc)

iv. Response Capability

1. Have you taken part in training on FEWS? Yes/No If yes, Please specify If No, why?

2. Have you participated in planning for response preparedness and capacity building? Yes/No If yes, what type of plan was it?

63800912 inception report version 3/ HCA / 2017-06-30

3. Have you taken part in mock drills programme for enhancing response capability of the community? Yes/No If yes, (frequent/year)……….. If No, why?

4. Are there any public awareness and education campaigns on response mechanism conducted? Yes/No If yes, how frequent?

5. Please mentioned about the availability of following infrastructures in your community.

Infrastructure Yes(N) No Remarks Transportation Boat Bus Stretcher Jeep Others Equipment Rope Life Jackets Tube Torch Human Rescue staffs: Resource & Trained training Non trained Training for rescue staffs Health facility First aid Awareness of evacuation place and route Safe place/shelter Water and sanitation Communication Phone tools Mike Siren Wireless radio TV Color flags Mock drill (Frequency/year) Lights Shouting

6. In your opinion what are the limitations, challenges, and areas for improvement in FEW in your area?

Limitations Challenges Areas for improvement

7. Could you please give us information on flood history in last 5 years?

Year of flood Affected area Approx. depth Duration of Loss of lives Loss of of inundation inundation property

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