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Development of Flood Forecasting Model for Narayani Basin, Nepal

Conference Paper · April 2017

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Binod Parajuli Dilip Kumar Gautam Department of Hydrology and Meteorology Practical Action Consulting

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A Technical Report

On

Development of Flood Forecasting Model in Narayani River Basin, Nepal

Submitted By: Binod Parajuli Hydrologist Flood Forecasting Section Department of Hydrology and Meteorology (DHM), Nepal

May 2016

Executive Summary

This study was undertaken with an aim to prepare a flood forecasting model along with flood hazard and inundation maps in the flood affected region of Narayani and East Rapti River. The ultimate purpose is to enhance the flood forecasting and early warning system in the department of Hydrology and Meteorology identifying flood susceptible areas and support as an early warning decision support system for the communities and other stakeholders. The potential flood hazard and inundation maps enables Department of Hydrology and Meteorology to identify or update the warning and danger levels in the respective flood forecasting stations, hence pre-informing of the impending flood event ‘if and when’ the threshold warning and danger levels exceed. This enables the disaster responders to raise alarm to the communities for evacuation and to take precautionary measures, thus saving lives and properties with longer lead times.

As a decision support tool, the flood forecasting model and flood hazard maps pre-informs the communities and stakeholders at different levels to plan and implement their programs avoiding the potential flood hazard areas. As an instance, vulnerability assessment of the households living within the potential flood hazard zones can be done to develop and implement mitigation and resilience programs. In other case, identify those vulnerable households and landowners for resettlement and/or implement various programs for resilience capacity buildings at the community and household levels.

Department of Hydrology and Meteorology currently have no models for flood forecasting in the country. The United States Army Corps of Engineers (USACE) Hydrologic Engineering Center’s Hydrological Modeling System (HEC-HMS) was examined for streamflow forecasting using Narayani basin. Observed precipitation data was obtained from DHM. Calibration and verification of the modeling system was done through an operational perspective to test the model’s applicability at DHM. Model development was done using observed precipitation and was conducted in several stages. The Nash Sutcliffe for the main Devghat Flood Forecasting Station is 0. 892 for calibration (2008-2011) and 0.893 for the validation (2012-2013) for model without snowmelt consideration. The result is also similar for the snowmelt consideration. After the model error correction using ARIMA modules the Nash-Sutcliffe is 0.97 for both calibration and validation periods. The calibrated model was tested with bias corrected WRF one day precipitation forecast estimations for the same periods. The bias correction scheme was computed and applied at the basin scale. When used as input to the HEC-HMS model the Nash-Sutcliffe is 0.33 for the calibration period and 0.66 for the validation period. But the result is satisfactory when the model error correction is done again for the, which results Nash-sutcliffe to be 0.82 for calibration period and 0.87 for validation period.

With above described applications, the key outputs of the study are highlighted hereunder:

a. The study has developed a flood forecasting model with satisfactory result for Narayani River basin. This indicate that the model can be steadily used for one day flood forecasting. The study has prepared flood hazard and inundation maps of the settlements along the Narayani/East rapti, rivers covering all communities along the River upto Indo-Nepal Boarder. The flood hazard maps were prepared based on the flood forecast modelling and Geographic Information System (GIS) based analysis of flood inundation extent and depth.

b. The warning level of Narayani River was found at 2 years return period with estimated discharge of 8,898 cumecs with the surface water level at 7.5 m from the mean sea level. The danger level is observed in inundation scenario of 5 years return period with the discharge of 10769 cumecs with the surface water level rising to 8.3 m from the datum of the gauging station. Similarly the warning level of East Rapti was found at 5 year return year flood with estimated discharge of 1035 cumecs with the surface water level of 3.0m. The danger level is observed in inundation scenario of 10 return year flood with estimated discharge of 1333 cumecs at 3.4m water level in the gauging station. With this the existing warning and danger level of both the rivers seems to be changed. c. For the inundation scenario at danger level in Narayani River and East Rapti River the flooding scenarios are: Most of the settlements of both the banks of Narayani in Chitwan and Nawalparasi and settlements along right bank of East Rapti River in Chitwan districts are at potential risks of flooding.

TABLE OF CONTENTS

1. Introduction 1 1.1 Background 1 1.1.1 Causes of flood in Nepal: 3 1.1.2 Flood problems in Nepal Terai: 5 1.2 Objective 7 1.3 Expected Output 7 2. Study Area 8 2.1 River System 8 2.2 Climate and Hydrology 9 2.3 Topography 16 2.4 Flood and Inundation 17 2.5 Flood Forecasting and Warning System 18 3. Data Preparation 20 3.1 Downloading and Processing of Digital Elevation Model and land Use Data 20 3.2 Hydro-meteorological Data Preparation 21 3.2.1 Hydro-meteorological Data for Hydrological Model 21 3.2.2 Hydro-meteorological Data for Hydrodynamic Model 22 4. Development of Hydrological Model 23 4.1 Methodology Flow Chart 23 4.2 Terrain Preprocessing Using HEC-GeoHMS 23 4.3 HEC-GeoHMS Project Setup 24 4.4 Basin Processing 24 4.5 Extracting Basin Characteristics 24 4.6 Hydrologic Parameters 27 4.7 HMS 28 4.8 HEC-HMS Modelling 29 4.8.1 Editing a Basin Model 30 4.8.2 Creating a Meteorologic Model 31 4.8.3 Assigning the Discharge, Water level and rating Table 32

4.8.4 Control Specifications and Model Run 32 4.9 HEC-HMS Calibration and Validation 32 5. Development of Hydraulic Model 37 5.1 Methodology Flow Chart 37 5.2 Flood Frequency Analysis of Discharge Data in Different Return Period 37 5.3 Preparation of DEM 40 5.4 Land Cover/Use 41 5.5 Manning’s Roughness n 42 5.6 Hydrodynamic Modelling using HEC-RAS 43 5.6.1 Theoretical Background 43 5.6.2 One dimensional flow calculations in HEC-RAS 43 5.6.3 Pre-processing to develop the RAS GIS import file 44 5.6.4 Post-processing to generate GIS data from HEC-RAS results 44 5.6.5 HEC-RAS Simplifications of St. Venant Equation 44 5.6.6 Steps Involved in Hydrodynamic Model setup 45 5.6.7 Flood Danger Level and Warning Level Assessment 47 Flood Danger Level and Warning Level of Narayani River: 47 6. Conclusion and Recommendation 54 6.1 Synopsis of the Results and conclusion 54 6.2 Recommendation 55

ACKNOWLEDGEMENTS

I wish to express my sincere gratitude to Dr. Rishi Ram Sharma, Director General, Department of Hydrology and Meteorology (DHM) and Mr. A.R Subbiah, Director of RIMES (Regional Integrated Multi-Hazard Early Warning System) for providing us an opportunity to attend the secondment program on “Hydrological and Hydrodynamic Modelling for Operational Flood Forecasting” in RIMES, Thailand. This project bears on imprint of many peoples. I sincerely wish to express my deepest sense of gratitude especially to Dr. Dilip Kumar Gautam, Hydrology- Team Leader (RIMES), Hydrologist Dr. Anshul Agrawal (RIMES) Mr. Itesh Das (RIMES) and Mr Niraj Shakya as well as other staff members of RIMES who rendered their help during the period of my secondment. The financial support from the project “Development of flood forecasting generation and application system for disaster mitigation in Nepal” is gratefully acknowledged. I would like to thank DHM and RIMES for providing necessary data to conduct this research. Lastly I would like to thank Mr Dinkar Kayastha, Hydrologist and secondment colleague from DHM for his constant co-operation during the study period.

1. Introduction

1.1 Background

Nepal is a small country with an area of 147,181 sq. km. Its mean width is 193 km only. In such a short stretch, the elevation varies from 60m to 8848m. Nepal is a rich country in water resources. Nepal is also characterized by sources of many small to large-sized rivers, which flow from north to south. There are over 6,000 rivers and their total length exceeds more than 45,000 km. Of these rivers, about 1,000 are more than 10 km long and approximately 100 are more than 160 km long. The entire territory of Nepal is a part of the Ganges basin.

The rivers of Nepal (Figure 1.1) can be classified into three categories:

1. Rivers originating from Himalayas: e.g. Koshi, Narayani, Karnali, and Mahakali. These are perennial rivers. They originate from the Himalayas and, after descending from the hills, flow through the Terai plains. During the monsoon (June-September), these rivers cause damage to the communities residing within their floodplains. 2. Rivers originating from the Mahabharat range: e.g. Kankai, Kamala, Bagmati, West Rapti, and Babai. During monsoon, these rivers also cause a great deal of damage in the communities residing within their flood plains in the Terai region. 3. Rivers originating from the Siwalik range: e.g. Ratu Khola, Lakhandehi Khola,. These rivers have little flow during the dry season, and some of them are almost dry. However, they are sometimes responsible for flash flooding during the wet season, causing extensive damage to the communities residing in the Terai plains. The surface water available in Nepal is estimated to be around 224.7 billion m3 per annum, or in terms of flow rate, it is 7,125 cumecs. Nepal receives an average yearly precipitation of more than 1200 mm. About 80% of the total precipitation occurs during June to September and Nepal faces “too much water" problems during this period and “too little water” problems during the rest of the year. It is a known fact that with the absence of storage reservoirs (or flood control reservoirs) and river regulation and proper watershed management practices in the mountains and hills of Nepal, much of the rainfall which occurs during the monsoon from June to September for a duration of four months is converted to runoff and drained by channels, rivulets and rivers that create flash floods and inundation on flatter topography, especially in Terai, causing loss of lives and damage to infrastructures every year. Thus, there is an 1

unmanageable abundance of water in those four months and water shortage for various usable purposes like irrigation, drinking water and hydropower for the remaining eight months. In some river basins, there is an acute shortage of water particularly in the months of March to May. Generally, the eastern part receives more rainfall and the precipitation declines towards the western part of the country. Thus some areas are susceptible to floods and landslides while others are prone to droughts.

Figure 1.1: River system of Nepal

The Terai plain is considered as the main fertile land, which consists of deep alluvial soils. It runs from Mechi to Mahakali but is fragmented at two places, Chitwan and Dang, because of the extension of Siwalik (Chure) Range up to the boundary with India. Also, the whole reach of Terai plain has been fragmented into several parts due to a number of rivers flowing north to south and creating problems of flood, inundation, river bank erosion and so on. Due to these problems, every year during the rainy season, Nepal has to bear an immense loss of lives, crops, public property and fertile soil. The Hydrological and Hydraulic Modelling for operational flow forecasting is hence very much required in the country particularly to save the life and properties from floods as well as to plan to manage the too much and too little water situations.

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1.1.1 Causes of flood in Nepal:

Floods are a common natural phenomenon in Nepal. The factors triggering flood hazards in Nepal are: highly concentrated monsoon precipitation, high relief, steep mountain topography, and deep and narrow river valleys. Each year many people are killed and made homeless, and property and infrastructure are damaged by floods. As a result, the overall development of the country has been severely affected by repeated flooding. In the future, the global warming phenomenon is likely to increase the frequency of flooding by increasing the intensity of extreme precipitation events and enhancing the melting of Glacier Lake. The encroachment of areas susceptible to floods to establish human settlements and to carry out infrastructural development in the recent past has increased the exposure of these areas to flood hazards.

Vulnerability to flood disasters is great. Nepal is a least-developed, landlocked, and mountainous country with limited access to socioeconomic infrastructure and service facilities. Inaccessibility, a low level of human development, and mass poverty are prominent reasons for the poor capacity to anticipate, cope with, resist, and recover from and adapt to different types of hazards, floods being among them. In addition, a high population growth rate, among other factors, has led to increasing poverty. As a result, vulnerability to flood hazards is likely to increase unless effective flood mitigation and management activities are implemented. In Nepal, devastating floods are triggered by different mechanisms which can be classified into five major types:  Rainfall and cloudburst  Glacial lake outburst floods (GLOFs)  Landslide dam outburst floods (LDOFs)  Floods triggered by the failure of infrastructure  Sheet flooding or inundation in lowland areas due to an obstruction imposed against the flow a. Rainfall and cloudburst The primary cause of flood in Nepal is widespread and intense monsoon rainfall. Rainfall during the monsoon season is caused by the influence of both the south-east and south-west monsoon. The monsoon lasts for four months from June to September, contributing about 80% of the annual rainfall. Floods are common throughout the country in the latter stages of the summer monsoon when the land is saturated and surface runoff increases. Extremely high intensity precipitation in mountain areas causes landslides on mountain slopes and debris flows and floods along the river valleys.

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Sudden outburst of clouds localized in nature cause disastrous floods. Highly localized rainfall of long duration in the monsoon season often generates water volumes in excess of local drainage capacity, causing localized flooding. The congestion of drainage by infrastructure such as roads, embankments, and bridges, often exacerbates the situation. This type of flood is common in the southern Terai belt, inner Terai, and in the valleys. b. Glacial lake outburst floods (GLOFs) Glacial lakes are common in the High Himal area of Nepal. These lakes often contain huge volumes of water. The lakes are dammed behind moraine ridges which may be more or less stable depending on the amount of ice within these ridges; and their unstable condition may lead to a breakage of the dam, creating a glacial lake outburst flood (GLOF) with the potential to cause great damage downstream.

Altogether 2,315 glacial lakes have been identified in Nepal and, about 14 GLOFs are recorded to have occurred between 1935 and 1991 in Nepal. In total, 20 glacial lakes have been identified as being potentially dangerous at present. c. Landslide dam outburst floods (LDOFs) Formation of temporary lakes due to landslide damming is a common phenomenon in high mountain areas of Nepal. Such a blockage of the river flow is more common in narrow valleys where the slopes are steep on both sides of the river. There were occurred some disastrous LDOFs in the Narayani basin in the past. Some examples are as follows:

 Flood in Budhigandaki River near Laphubesi in 1968

 Flood in Gyangphedi Khola in Nuwakot in 1986

 Flood in Trishuli River in 1985 damaging Trishuli hydropower plant and settlements downstream d. Floods triggered by infrastructural failure Floods triggered as a result of poor infrastructural design are also common in Nepal. There are several reservoirs and structures like bridges constructed in the Narayani basin. Some bigger reservoirs project for hydropower and irrigation are also going under construction and some are under construction. While doing the hydrological studies in the basin these should also be considered. e. Sheet flooding

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Sheet flooding or inundations are common during the summer monsoon in lowland areas in the southern Terai region. The risk of such hazards has been increasing in recent years as a result of increasing development of infrastructure such as roads, culverts, and check dams, and consequent obstruction in the natural flow of surface runoff. Moreover, unilateral construction of roads perpendicular to natural flow without sufficient drainage and construction of barrages, dams, afflux bunds, and dykes on the rivers near the border area between India and Nepal have also exacerbated flooding in Nepal. Inundation of large areas because of overflowing river banks causes extensive damage. The flood water erodes the banks, causing permanent damage to the adjacent agricultural land.

1.1.2 Flood problems in Nepal Terai:

Nepal's Terai region is the part of the Ganges/Brahmaputra River Basin, which is one of the most disaster- prone regions in the world. The Terai region amounting to only 17% of the total area of the country and regarded as the granary of Nepal is continuously suffering from flooding. The rivers in this area become wide and braided with wide spread damages to agricultural lands. The damages are further exacerbated by erosion of banks and deposition of infertile coarse material on the cultivated land. The channel capacity of the rivers in this regime is said to be decreasing due to increased sediment coming from increased erosion rate at upland, thus making these rivers unable to accommodate large floods; as a result the adjoining area suffers from inundation. Besides, natural factors, anthropogenic factors also trigger floods and disasters. Encroachment of floodplains, obstruction of natural flow of rivers and sheet flow, faulty drainage system and river training works also contribute to the increased flooding and disaster. In Terai, devastation due to flood is also increasing due to rapid increase in population and human activities. The flood plains are being increasingly crowded to meet ever-increasing demands of food and fiber, and consequently the flood problem is exacerbated. Similarly, many hydraulic structures (dams/barrage, and bunds) constructed in some places just a few kilometers downstream of Indo-Nepal boarder on the Indian side have also exacerbated the flood situation in the Terai of Nepal. The devastating floods and incessant rains affect Terai region and cause extensive damage to standing crops, physical and social infrastructure, environment, people's lives and livelihood and weaken the capacity of rural poor. Many people who live along the flood plains are poor, and are frequently overwhelmed by floods and other life-threatening extremes of weather. Because of economic reason, the poor and disadvantaged people of the rural communities are forced to settle in the areas adjoining riversides, marginal and vulnerable areas and therefore are the victim of flood disaster every year.

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Although various flood management measures are introduced in many places to prevent the negative consequences of flood disaster, the challenges are still at the forefront. It is generally found that the national government, local administration and the government have been mostly reliant on reactive approach to disaster management focusing mostly on the relief operation. Although relief operation is essential for proper flood disaster management, this is not adequate in itself and thus there is a need of measures for preventing hazards turning into disaster. Moreover, under proactive approach of reducing disaster risk, it is necessary to reduce the vulnerability of the people through improved livelihood opportunities and capacity build up and thus increased resilience. For designing an effective and efficient framework of disaster management there is a need to understand the grassroots problems, the institutional set up, and the livelihood assets of the community including local knowledge in flood management. Under these assumptions, this study aims to identify the current problems at local level, the initiatives undertaken by the community through their local knowledge to manage the flood disaster. While many studies have been conducted for reducing the disaster risk in many river basins of Nepal, most of these studies have emphasized on the structural measures and have failed to address the root cause of disasters.

In this regard, capacity building training for the scientists and technical staff of National Hydro-met Services of collaborating countries like Nepal, organized by RIMES under a collaborative project to establish Flood Forecasting and Early Warning System in different flood prone river basins is really a good initiative. In case of Nepal Karnali, Babai and Narayani River Basins have been selected for the purpose. Since 2008, seconded scientists from RIMES Member and Collaborating States like Nepal have been receiving training in numerical weather and climate prediction, and hydro-meteorological applications at the RIMES Regional Facility in Thailand. This Secondment Program aims at building scientific and technical capacities of scientists, forecasters, and technical specialists from RIMES Member and Collaborating States through capacity building process which involves technology transfer, sharing of knowledge and experience, and on-the-job training. The training program is designed like after the completion, scientists return to their country offices, transferring knowledge and skills among their colleagues, and supporting new developments in their institutions. Which is very important for the overall development of the institution. RIMES has received scientists from Thailand, Bangladesh, Bhutan, Cambodia, Lao PDR, Maldives, Mongolia, Myanmar, Nepal, Philippines, Sri Lanka, Timor-Leste, and Vietnam.

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1.2 Objective

The major objective of this training for Nepal is to capacitate the hydrologists of Department of Hydrology and Meteorology for establishing and enhancing the flood forecasting in different river basins in the countries. Some specific objectives are as follows:  To prepare and manage the data in the required format using HEC-DSSVue  To prepare the flood forecasting models for Narayani, Babai and Karnali River Basin of Nepal using HEC-HMS/HEC-GeoHMS  To correct the model simulation results using error model (ARIMA) to apply for forecast correction and application  Use the long term Rainfall forecast and bias corrected rainfall forecast data to see the model performance  To map the flood inundation in those river basins using HEC-RAS/HEC-Geo-RAS  To know how to operationalize/automate the flood forecasting system using DELFT FEWS systems.

1.3 Expected Output

Following are some of the expected output from this Secondment training program:

 The Training participant form the respective department/countries will have in depth knowledge in using hydrological and hydrodynamic models for flood forecasting

 The training participants will then be able use the training knowledge in their countries for flow forecasting

 The countries will have extended flood forecasting and early warning system to minimize the loss of life and properties

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2. Study Area

2.1 River System

Narayani River basin, also called Gandaki River is a major River basin of Nepal with a catchment area of 36,300 km2. 89% of the catchment lies in Nepal and the rest is in Tibet. This basin occupies central part of Nepal. Figure 2.1 below shows the location and basin map of Narayani Basin. It is a snow fed river, which originates from the Himalayan range. It starts from Photu pass in Mustang in the northern Tethys zone. Trishuliganga, Burhigandaki, Seti, and Marsyangdi rivers from the midland part of Nepal join it. It cuts the Churiya hills at Bahuban area and enters the lower plains before reaching Tribeni. It has been found that this river has been changing its course towards the west in Terai like the Saptakoshi River and this drift amounts to several kilometers. The drainage network of the river basin is shown in Figure 2.2. Less than 2% of the catchment area of Narayani basin is in the Terai part of Nepal. The total length of the river is 360 km and its length is 83 km in the Terai plains. The Narayani River is joined by the East Rapti River and these rivers form two boundary lines of the Chitwan National Park.

Figure 2.1: Location and River System map of Narayani River Basin 8

The Narayani River has many tributaries.

 The Kali Gandaki River drains the area from central Nepal to the higher Himalayas. This river cuts across the higher Himalayan range through a gorge between Dhaulagiri and Annapurna. The river joins Trishuli River at Devghat.

 The Seti River originates from the base of Annapurna Himal. The River flows through Pokhara valley and joins with the Trishuli River prior to Kali Gandaki.

 The Marsyangdi River flows from the north of Annapurna Himal and turns south from the west of Manaslu Himal and joins with Trishuli River at Mugling.

 The Trishuli River rises from Ganesh Himal and flows down to south, southwest and then joins with Marsyangdi River, Seti River and finally the Kali Gandaki River.

 Budhi Gandaki River basin between Marsynagdi and upper Trishuli

 East Rapti river originating from Makwanpur district (Mabharat range)

Among these rivers, some parts of the Kali Gandaki River, the Budhi Gandaki River and the Trishuli River lie in Tibetan territory. The longest river in the basin is the Kali Gandaki River. The Kali Gandaki River cuts the deepest gorge in the world, around 5,000m deep. After that, it bends toward the west at Dhumpu, and then it is deflected to the south and is joined by Myagdi khola at Beni. The Myagdi khola drains out Dhaulagiri Himal. Modi Khola draining Annapurna Himal meets with it at the Kusma village. Nisti Khola drains Chauribuki Patan and flows southeast and then it is named as Barigad, which joins Kali at Taksar. From there the Kali moves to the south and makes an easterly bend at Ridhi Bazaar, where it receives Ridi Khola which flows to the east. From Ridhi bazaar upto Khalte, i.e. nearly 100 km, it flows straight to the east with wide and deep valley and meanders at a couple of places. From there it turns to the south and again to the northeast at Kalinkitar.

2.2 Climate and Hydrology

Climate of Narayani river basin varies from subtropical zone in the south to Tundra in Higher Himalayan region. The monthly average relative humidity of the basin ranges from 61 % in June to 94 % in January. Similarly, temperature records at climatic station ranges from -6.30C in Jomsom, Mustang to 36.90C in Hetauda.

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Figure 2.2: Drainage network of Narayani basin

Almost 80% of rainfall occurs in monsoon period, which spans from June-September. For the rest of the period, there is no or very little rainfall. The spatial variation of annual rainfall is also very high in the basin as the total annual precipitation record ranges from 100 mm in Jomsom to 4880 mm in Pokhara.

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Figure 2.2.1: Location of Meteorological Stations

Figure 2.4: Location Hydrometric Stations of Narayani basin

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The Figure 2.3 above shows the location of temperature and precipitation stations in the basin and Figure 2.4 shows the location of Hydrometric stations in the basin.

Narayani basin has 30 temperature stations. Out of which the temperature station of highest elevation at Jomsom and of low elevation at Hetauda has been taken here for the brief analysis. The mean daily temperature from 2008 to 2013 shows the mean daily temperature at Jomsom is 11.710c. The minimum daily is recorded to be -2.750c and maximum mean daily temperature is 21.930c. In other hand the temperature of the low elevation region of the basin at Hetauda has minimum mean daily temperature to be 10.480c. Whereas the maximum mean daily is recorded to be 360c. The average of mean daily temperature at the station is found to be 23.480c. The figure 2.5 below shows the mean daily temperature plot of Jomsom and Hetauda Stations.

Figure 2.5: mean Daily temperature at Jomsom and Hetauda Station from 2008-2013

The Thiessen Polygon average of daily rainfall stations for year 2008-2013 of minimum receiving precipitation sub-basin and maximum receiving sub-basin are respectively 201mm and 5438mm as shown in Figure 2.6 and 2.7 below. The maximum precipitation receiving subbasin is the Basin W800 that falls in the Modi Catchment whereas the minimum precipitation receiving station fall in Kaligandaki River Basin in its uppermost sub-basin: W1380. This shows the variability in precipitation within Narayani basin. Almost 80% of the total annual precipitation in the basin falls in monsoon four months: June, July, September and October. Rest of the precipitation fall in other seasons. This indicates the possible flood problem during monsoon season in the basin. The sub-basin map is presented in Figure 2.8 below.

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Figure 2.6: Daily Rainfall plot of subbasin W1380

Figure 2.7: Daily Rainfall plot of subbasin W800

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Figure 2.8: 56 major sub-basins of Narayani Basin The gauging site at Devghat (station no. 450) has stream flow record from 1963 to till now. The drainage area of the Narayani is approximately 36300 Km2 at the outlet with Nepal India Boarder. The average monthly variation of flow at this station is shown in Figure 2.9, which shows that the peak discharge occurs in August. The mean annual flow of Devghat station is 1534 m3/s (based on 1963-2014 data).

Figure 2.2.9: Monthly average discharge at Devghat for 1963-2013 period 14

Annual mean yearly flow data from the year 1963 to 2014 is shown in the Figure 2.10 below. Which shows the annual variations of mean monthly flows in the basin.

Figure 2.2.10: Mean Yearly Discharge

Maximum instantaneous discharge data from 1963 to 2014 is shown in Figure 2.11. The maximum instantaneous discharge during this period is 15400 m3/s on 5 Aug, 1974. There can be seen significant annual variation of the peak discharge.

Figure 2.2.11: Maximum Instantaneous discharge

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2.3 Topography

The elevation of the Narayani basin ranges from around 100m with the Nepal India boarder to around 8000m in the northern part near Nepal-China Boarder. Table 2.2.1 and Figure 2.12 below shows the % of area and its spatial coverage according to elevation ranges. This shows almost 17% of the area is above 5000m elevation having permanent snow throughout the year. Almost one third of the total area of the basin lies above 4000m elevation. So the snowmelt contribution in the discharge seems to be high in the Narayani River. But regarding flood forecasting it will have less significance for the cause that the contribution of flow in the peak will be negligible.

Table 2.2.1: Area covered by different elevation zones in Narayani basin

Value Elv Zone (m) Area (%) 1 100-2500 52.67% 2 2500-3000 4.95% 3 3000-3500 4.54% 4 3500-4000 5.40% 5 4000-4500 7.02% 6 4500-5000 8.83% 7 5000-5500 9.31% 8 5500-6000 5.57% 9 6000-6500 1.35% 10 6500-7000 0.25% 11 7000-7800 0.09%

Fig 2.12: Topographic Variations in narayani River Basin

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2.4 Flood and Inundation

The present scope of the study is Narayani River from Narayanghat (i.e. from Narayanghat hydrological station) to about 65 km d/s up to Nepal-India border. The East Rapti River is also considered as tributary considering Rajaiya Station as upstream boundary. The river is located in Dun area and surrounded by the Siwalik Hills. The East Rapti (including other small rivers like Lothar, Manhari, Kayar, Reu) which originates from Makwanpur district joins the Narayani River in the Dun area on its eastern (left) bank. Similarly, rivers like Binai, Arun, Deusat, Girwari, etc. originate from the Mahabharat ranges and join Narayani River on the western (right) bank. The Narayani River receives a lot of sediment such as gravel, sand and clay through these rivers and other small tributaries from the Siwalik Hills. The Narayani River also acts as the regional boundary between Central and Western regions, zonal boundary between Narayani and Lumbini zones and district boundary between Chitwan (on the east) and Nawalparasi (on the west).

Narayani (Gandak) river is not similar to other class-A rivers of Nepal which generally show widening character as we proceed to downstream reach. Moreover, this river has a number of deep pocket depressions unlike other rivers. This river is braided in plain areas lying in between the stretch of Narayangarh Bridge and the confluence Point of Binay River, forming a number of anabranches and islands. Finally, after the confluence of Binay River it passes through the narrow gorge creating a constricted waterway up to Tribeni Dham in southern border of Nepal and then flows to the lower reach of Indo-Nepal Border after Gandak Barrage.

The constriction in the waterway after the confluence of Binay River while passing through the gorge causes swelling of this river during flood time and blocks the flow of flood discharge of its tributaries on one hand, while on the other hand, there are flow control measures at the barrage site.

Chitwan and Nawalparasi districts are among the most severely flood affected areas in Nepal with damage and loss of life increasing annually along the Rapti and Narayani rivers as climatic conditions change. The Narayani River passes through 18 VDCs and 1 Municipality downstream from the East-West Highway. 14 VDCs of Nawalparasi district lie on the right bank and 4 VDCs and 1 Municipality of Chitwan district lie on the left bank along the river downstream from the East-West highway.

The main causes of problems in the study area are due to bank erosion causing loss of crops and fertile land, sedimentation in riverine area, flooding over farm lands and inundation. Such problems create adverse effects and cause loss to crops, properties and lives. Moreover, they cause inconvenience to the inhabited area by damaging many public facilities such as houses, highways, ruler roads particularly in low lying areas.

About 70% of the river catchments area in Terai is farmed. Therefore, the most of the land affected by Narayani River's floods is covered with cultivated land.

In a nutshell, causes of flood, inundation, and soil erosion can be summarized as below:

 Sloping and mountainous terrain with fragile geology

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 Intense rainfall, concentration of irregular rains

 Extension of agricultural practice on sloping terrain and flood plains mostly due to increased population

 Deforestation

 Aggradations of river bed due to settlement of excessive sediment load in flood water received from soil erosion, land-slide, etc

 Contraction of water-way due to riparian activities or human encroachment

 Contribution of more surface run-off due to coverage of land by built up physical infrastructures

 Change in river course due to shoal formation and braided nature of rivers

 Shallow and undefined river bank at the southern border area

2.5 Flood Forecasting and Warning System

The Department of Hydrology and Meteorology (DHM), the only authorized collector and disseminator of hydro-meteorological data of Nepal, has established several hydrological and meteorological stations all over the country. Though the frequency of discharge measurement for developing rating curve is very low. The department is trying to do the best with whatever possible. High frequency discharge and rainfall data collection were started in some stations since 2008 but still the number of stations are not adequate in most of the basins however more station are now being telemetered that shows the department will have dense network of telemetry stations very soon. One of the biggest issue with the flood forecasting in the department is the “Numerical weather forecast” which is not started in a fashion to be used for flood forecasting but the things are going currently in a way to do it. Another big issue with the forecasting will be the data gap from Tibet part of the basin. Narayani basin has also its 11% area lie in Tibet. No systematic snow measurement is being done in adequate stations, a very few stations have measurement but not regular. Another important parameter for the better estimation of flood is the sediment measurement which is also a limitation because the data are not sufficient for bed load measurement.

DHM has a section of ‘Flood Forecasting Section’. The section is now giving the subjective forecast based on observation of real time data in the upstream stations. Real forecasting has not been started yet due to lack of real time data transmission system, forecasting model and dissemination system. But the department is currently in right direction to do the real model forecasting through this project.

The existing system of monitoring and forecasting, dissemination and response for the flood disaster is shown in Fig 2.13 and Fig 2.14 below.

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Fig 2.13: Real Time Data Monitoring and Transmission System

Fig 2.14: Government Mechanism for dissemination of information and response 19

3. Data Preparation

3.1 Downloading and Processing of Digital Elevation Model and land Use Data

Digital Elevation Model (DEM) is the basic topographic data required for the development of the model using HEC-GeoHMS. Currently the DEM are freely available for resolutions upto 1 arc second. But for this particular study the 3 arc-second DEM has been taken for the reason that this will work fine in case of hydrological model and also 3 arc second DEM is faster to process in comparison to 1 arc second with high efficiency. The 1 arc second data of SRTM for hills and mountain are also having large voids. So the 1 arc second data are only downloaded and prepared for the hydrodynamic modelling using HEC- GeoRAS and HEC-RAS.

The Digital Elevation Model (DEM) from HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales) of 3 arc-second resolution and 1 arc resolution are downloaded from the source: http://hydrosheds.cr.usgs.gov/dataavail.php. This is SRTM DEM which is believed to have higher accuracy than ASTER GDEM to delineate basin and river network. There were several options of the DEM available in the websites. Out of which it has been downloaded the Void- filled. The DEM tiles are taken to ARC GIS for the mosaic operation as shown in Fig 3.1 below. The mosaicked DEM is then clipped for Narayani River Basin (Fig 3.2). Similar process is also done for the 1 arc second DEM to be prepared for the HEC-RAS model.

Figure 1: The 1 arc-second SRTM DEM covering whole basins of Nepal Rivers for mosaic operation 20

Fig 3.2: DEM clipped for Narayani Basin

The Landuse data are important for the purpose of hydrological and hydrodynamic modelling. Which are also downloaded from the following sources: http://www.fao.org/geonetwork/srv/en/main.home?uuid=46d3c2ef-72c3-4f96-8e32- 40723cd1847b

The landuse data could be utilized to infer different parameters of the both HEC-HMS and HEC-RAS model such as for assigning particular value of manning’s n.

Once the mosaic operation is completed, the coordinate system is chosen. As we need to choose a projected system to have coordinates in meters: In case of Nepal, Narayani Basin, Projected Coordinates Systems UTM WGS1984 zone 44N is chosen specifying the “Resampling Technique” as CUBIC.

3.2 Hydro-meteorological Data Preparation

3.2.1 Hydro-meteorological Data for Hydrological Model

HEC-HMS model basically require five sets of data: Rainfall, Evapotranspiration, Temperature (for snow melt model), Discharge, Stage and Rating Table.

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Rainfall: Daily Precipitation data of available 81 stations (Figure 2.3 above) of the Narayani Basin and Hourly Rainfall data of 11 stations are prepared for the model. The data gaps are filled using normal ratio method. Then the thiessen polygon method is used to further calculation the sub-basin precipitation.

Temperature: 30 Stations (Figure 2.3 above) data are used for computing Evapotranspiration as well as for snowmelt component in the HEC-HMS Model.

Evapotranspiration: For most of the sub-basin evapotranspiration is calculated using CROPWAT and CLIMWAT tool. But for the sub basins having temperature station, the evapotranspiration is calculated using Blaney Criddle method in R.

Discharges: For the model calibration and validation Mean Daily and 3 times discharge data are prepared using HEC-DSSVue. There are altogether 27 hydrometric stations (Figure 2.4 above) in the basin out of which 18 stations data are available which are considered for this study

Stage Data: As of the availability of data of 18 discharge stations, same 18 stations stage data have been taken.

Rating Tables: The rating table are also prepared for same 18 stations for further processing.

Since the HEC-HMS model is compatible to read the .dss data file all these time series and rating tables have been imported to HEC-DSSVue and a data base is created.

3.2.2 Hydro-meteorological Data for Hydrodynamic Model

The Hydrodynamic modelling using HEC-RAS require annual timeseries of instantaneous peak discharges. For this study the inundation mapping is done for the terai part of the basin. Hence the instantaneous maximum discharge of Devghat station of Narayani and Rajaiya, Lothar and Manahari stations of East Rapti River Basin have been collected. The Gumbel method is used for frequency analysis.

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4. Development of Hydrological Model

4.1 Methodology Flow Chart

The overall methodology for the hydrological modelling is presented in the flow chart Figure below.

Figure 4.1: Methodology Flow Chart for Hydrological Modelling

4.2 Terrain Preprocessing Using HEC-GeoHMS

For the purpose of Terrain Preprocessing Mosaic Dem clip is loaded to the ArcMap. The Terrain preprocessing uses the DEM to create a stream network and catchments. The steps in HEC-GeoHMS is followed for terrain preprocessing.

The steps in the Terrain Preprocessing menu are performed in sequential order, from top to bottom. For this study standard river network shape file has been taken as Agree DEM as the 90m resolution DEM may not always give accurate river pathway. All of the preprocessing must be completed to delineate the watershed for the HEC-HMS model.

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4.3 HEC-GeoHMS Project Setup

The HEC-GoeHMS project setup menu has tools for defining the outlet for the watershed, and delineating the watershed for the HEC-HMS project. As multiples HMS basin models can be developed by using the same spatial data, these models are managed by defining two feature classes: ProjectPoint and ProjectArea. Management of models through ProjectPoint and ProjectArea let us to see areas for which HMS basin models are already created, and also allow to re-create models with different stream network threshold. It is also convenient to delete projects and associated HMS files through ProjectPoint and ProjectArea option. The procedure within this menu is followed sequentially. The project outlet point is assumed in the River point at the Nepal-India boarder.

4.4 Basin Processing

The basin processing menu has features such as revising sub-basin delineations, dividing basins, and merging streams. We will use hydrological stations and water control structures (reservoirs, diversions) to revise sub-basin delineations which is basically be done based on hydrological stations.

The first step in the basin processing is the basin merge. This process merges two or more adjacent basins into one. Parallaly with the basin merge, we have to also create new basins based on hydrological stations or other requirements. For this study, Narayani basins were sub-divided into 56 sub-basins. After the basin merge and creation is completed the rivers within the basin have to be merged or deleted. Hydrologically HEC-HMS model accept only one river in one sub-basin. So all the tributaries are deleted and the major channel are merged to get the final shape.

4.5 Extracting Basin Characteristics

The basin characteristics menu in the HEC-GeoHMS Project View provide tools for extracting physical characteristics of streams and sub-basins into attribute tables. The following tools are sequentially run for different purpose.

River Length: This tool computes the length of river segments and stores them in RivLen field.

River Slope: This tool computes the slope of the river segments and stores them in Slp field. The inputs for this are RawDEM and River shape file.

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Basin Slope: This tool computes average slope for sub-basins using the slope grid and sub-basin polygons. First, we compute watershed slope using Spatial Analyst Tools => Surface => Slope. The output raster is saved and added the grid to the map document. After the computations are complete, the BasinSlope field in the input Subbasin feature class is populated.

Longest Flow Path: This will create a feature class with polyline features that will store the longest flow path for each sub-basin. For this, we have to select Basin Characteristics -Longest Flow Path in the HEC- GeoHMS. The input are Raw DEM and flow direction grid. Finally a new feature class storing longest flow path for each sub-basin is created as shown in Figure 4.2 below.

Figure 4.2: Longest Flow Path of each subbasin of Narayani River Basin

The longest flow path attributes can be seen in the attribute table.

Basin Centroid: This tool create a Centroid point feature class to store the centroid of each sub-basin. For the purpose we have to select Basin Characteristics-Basin Centroid. Center of Gravity method is chosen for the computation.

Center of Gravity Method computes the centroid as the center of gravity of the sub basin if it is located within the sub basin. If the Center of Gravity is outside, it is snapped to the closest boundary. Longest

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Flow Path Method computes the centroid as the center of the longest flow path within the sub basin. The quality of the results by the two methods is a function of the shape of the sub basin and should be evaluated after they are generated. In case of Narayani, all the centroid fall within the basin as shown in Figure 4.3 below.

Figure 4.3: Basin Centroid of each subbasin of Narayani River Basin

Centroid Elevation: This tool compute the elevation for each centroid point using the underlying DEM. For which the DEM and centroid feature class are the input.

After the computations are complete, we have to open the attribute table of Centroid to examine the Elevation field. The centroid elevation update may be needed when none of the basin centroid methods (center of gravity or longest flow path) provide satisfactory results, and it becomes necessary to edit the Centroid feature class and move the centroids to a more reasonable location manually.

Centroidal Longest Flow Path: This tool compute the polyline feature class showing the flowpath for each centroid point along longest flow path.

With this the computation of basin characteristics is completed.

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4.6 Hydrologic Parameters

The hydrologic parameters menu in HEC-GeoHMS provides tools to estimate and assign a number of watershed and stream parameters for use in HMS. These parameters include SCS curve number, time of concentration, channel routing coefficients, etc. The following steps are followed.

Select HMS Processes: We can specify the methods that HMS should use for transform (rainfall to runoff) and routing (channel routing) using this function. Of course, this can be modified and/or assigned inside HMS.

For this particular study, Deficit and Constant method is chosen for the estimation of Loss (getting excess rainfall from total rainfall), Clark Unit Hydrograph for Transform Method (for converting excess rainfall to direct runoff), Linear Reservoir for Baseflow Type, and Muskingum-Cunge for Route Method (channel routing).

River Auto Name: This function assigns names to river segments.

Basin Auto Name: This function assigns names to sub-basins.

Sub-basin Parameters: Depending on the method (HMS process) you intend to use for your HMS model, each sub-basin must have parameters. These parameters are assigned using Subbasin Parameters option. This function overlays subbasins over grids and compute average value for each basin. We will explore only those parameters that do not require additional datasets or information. For example, we will compute time of concentration using TR55 method.

The following information are required to estimate travel time: 2-year 24 hour rainfall, slopes, flow distance of precipitation excess on the land’s surface for three flow regimes - sheet flow, shallow concentrated flow and channel flow. These inputs are used to populate a Mocrosoft Excel template spreadsheet.

The user should estimate the 2-year 24-hour rainfall in inches before running the TR55 tools. The “Rain2Yr” field in the sub-basin layer’s attribute table should be populated.

TR55 Flow Path Segments: This function calculates the flow path segments.

TR55 Flow Path Parameters: This function calculates the length and slope for the TR55 flow paths.

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TR55 Export to Excel: This function exports the data for the TR55 flow segments to a Microsoft Excel template workbook.

In the Excel spreadsheet, it is filled in the missing values and edit data to better reflect field conditions. The Excel spreadsheet will be stored automatically in the project directory within a folder named “XLSFiles”. Once the travel time of each subbasin is estimated, then we press the calculator button to transfer the travel times back to HEC-GeoHMS.

The tool updates the time of concentration Tc and BasinLag fields in the subbasin layer’s attribute table.

4.7 HMS

The HMS menu has tools for creating input files for HEC-HMS.

Map to HMS Units: This tool is used to convert units. All the data are converted to SI units using this tool. After this process is complete, we see new fields in both River and Subbasin feature classes that will have fields ending with “_HMS” to indicate these fields store attributes in the specified HMS units (SI in this case). All fields that store lengths and areas will have corresponding “_HMS” fields as a result of this conversion.

Check Data: This tool will verify all the input datasets. After we get problems in any of the above four categories (names, containment, connectivity and relevance), we look at the log file to identify the problem, and fix them.

HMS Schematic:This tool creates a GIS representation of the hydrologic system using a schematic network with basin elements (nodes/links or junctions/edges) and their connectivity.

Figure 4.4: HMS Schematic of Narayani River Basin 28

After the schematic is created, we get a feel of how this model will look like in HEC-HMS by toggling/switching between regular and HMS legend.

Add Coordinates: This tool attaches geographic coordinates to features in HMSLink and HMSNode feature classes. This is useful for exporting the schematic to other models or programs without losing the geospatial information. The geographic coordinates including the “z” coordinate for nodes are stored as attributes (CanvasX, CanvasY, and Elevation) in HMSLink and HMSNode feature classes.

Basin Model: This function will export the information on hydrologic elements (nodes and links), their connectivity and related geographic information to a text file with .basin extension. The output file Babai.basin (project name with .basin extension) is created in the project folder

Meteorologic Model: Even without any meteorologic data (temperature, rainfall etc) at this point, we only create an empty file that we can populate inside HMS using this tool.

HMS Project: This function copies all the project specific files that is created before (.basin, .map, and .met) to a specified directory, and creates an .hms file that will contain information on other files for input to HMS.

This set of files displayed in project report defines the HMS project that are opened and manipulated in HMS directly without interacting with GIS. Typically, we have to modify meteorologic and basin files to reflect field conditions before actually running the HMS model.

4.8 HEC-HMS Modelling

The Narayani.hms file created in the HEC-GeoHMS is opened in the HEC HMS window. After opening the file the basin file seems as shown in Figure 4.5.

Figure 4.5: HMS model in HEC-HMS window of Narayani River Basin 29

Once we explore the Narayani Basin in the explorer the junctions, reaches and subbasins can be seen. As the Muskingum-Cunge method is applied for the routing method we can see it associated if we click any one of the reach.

Similarly, if we click on a Watershed we see Deficit and Constant (for abstractions) and Clark Unit Hydrograph (for runoff calculations) are associated with it. Again, if we click on Transform, we see Time of Concentration parameter in the Component Window. All these methods were applied during the pre- processing of the HEC-GeoHMS All this information, which is now independent of GIS, is extracted from attributes that we created in HEC-GeoHMS.

4.8.1 Editing a Basin Model

This is important part in the Model development. We have to edit as per the information and data. As the sub-basin element is used to convert rainfall to runoff, so the information on methods used to compute loss rates, hydrograph transformation and baseflow is required for each sub-basin element. A canopy component could also be included to represent interception and evapotranspiration. Similarly, a surface component could also be added to represent water caught in surface depression storages. In this case, it is used Simple Canopy and Simple Surface methods.

The loss method allows to choose the process which calculates the rainfall losses absorbed by the ground. Here, it is used the Deficit and Constant method to compute losses and get excess rainfall from the total rainfall.

The Transform method allows to specify how to convert excess rainfall to direct runoff. For this we click on the drop down menu to view the options. This model employs the Clark Unit Hydrograph method, which takes rainfall data, subtracts the losses as specified through the Loss Rates, and converts the excess rainfall to a runoff hydrograph. There is no baseflow method specified for this model, but we can look at the available options. If we specify baseflow, this baseflow will be added to the resulting direct run-off hydrograph to produce total streamflow hydrograph. For which Recession method is generally selected for the mountain catchment..

Once the loss, transform and baseflow methods are chosen for the sub-basin, the next step is to specify the parameters for these methods. We select the Loss tab in the component editor to look at the parameters for the loss method.

For Deficit and Constant method, each sub-basin requires a value for the Initial Deficit, Maximum Deficit, Constant Rate and Percent Imperviousness. If the percent impervious value differs from 0, that percentage of the land area is assumed to have no losses and the loss method is applied only to the remainder of the drainage area.

The time of concentration Tc has been already populated from the attribute table of subbasin layer. We just fill in the storage coefficient.

Similarly selecting the Baseflow tab we to look at the parameters for the baseflow method.

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It is filled in the initial discharge, recession constant and ratio to peak.

After the sub-basin element, we enter and edit the reach elements.

Since the reach element route flows, only one method (routing) is associated with it. The Muskingum- Cunge method is specified here, which is the routing technique used for the reaches in this model. The Muskingum-Cunge routing method is based on conservation of mass and momentum equations. This method is suitable to represent attenuation and translation of flood waves for river reaches with a small slope.

The length and slope of the reach are estimated during preprocessing with GeoHMS. These values are retrieved from the attribute table of River layer. We fill in Manning’s n, bottom width and side slope.

In addition to looking at individual elements and their parameters, we can look at the parameters for all hydrologic elements by selecting Parameters in the menu bar and selecting a method.

Similarly, we fill in all parameters for Canopy, Surface, Loss, Baseflow and Routing methods as below. Initially we give some appropriate values which we lateron change during model calibration.

4.8.2 Creating a Meteorologic Model

Meteorologic models provide meteorologic boundary conditions for the subbasins such as precipitation, evapotranspiration and snowmelt. A new meteorologic model can be created by using the Meteorlogic Model Manager of Components menu. a) Precipitation Method: There are different precipitation methods such as gage weights, inverse distance, specified hyetograph, gridded precipitation etc. Selection of the method depends upon the purpose of the model. For this study, we have selected Specified Hyetograph method as we have daily accumulated rainfall timeseris. The subbasin average precipitation data computed externally using thiessen polygon method in ARC-GIS is imported to the model creating Precipitation Gages for each subbasin. Then it is associated each gage to corresponding subbasin by clicking on Specified Hyetograph of meteorologic model. b) Evapotranspiration Method: It is required for computing the potential evapotranspiration over the land surface. Evapotranspiration is responsible for returning about 50-60% of precipitation back to the atmosphere. Hence, it is an important component for continuous modeling. For event modeling, it may be omitted. Monthly Average method is the simple method to represent evapotranspiration if pan evaporation data are available. However, it can also be used with potential evapotranspiration computed from other climate data. Pan coefficient for each month is required if pan evaporation data are used. Enter monthly evapotranspiration data for each subbasin. Data are provided in the Excel file.

Here for this study two methods are basically used for computing the evapotranspiration data for each subbasin. For the sub basins having temperature station with good quality temperature data, Blaney Criddle method is used for computing the monthly evapotranspiration. For those subbasins having no climate data, CLIMWAT data have been downloaded and the calculation are done in CROPWAT. 31

c) Temperature Index Method: To incorporate snowmelt runoff in the modelling temperature index method is used. Temperature index method dynamically computes the melt rate based on current atmospheric conditions and past conditions in the snowpack; this improves the representation of the “ripening” process. The concept of cold content is incorporated to account the ability of a cold snowpack to freeze liquid water entering the pack from rainfall. The sub-basins are represented with elevation bands.

4.8.3 Assigning the Discharge, Water level and rating Table

Before creating simulation run for calibration and validation, we have to assign observed discharge, water level and rating table data for the junctions having gauging site and at the outlet. The .dss Files of those data were assigned for each station features.

4.8.4 Control Specifications and Model Run

The two controls were created for calibration and validation run; Control 1 for calibration and Control 2 for validation. Since the recent available data of 2008 to 2013 are used for meteorologic model in the Narayani Basin the first four years of data starting from 01 Jan 2008 to 01 Jan 2012 are used for calibration and the rest of the data are used for validation. Hence the control specification was also set as per this and the model was run for calibration and validation.

4.9 HEC-HMS Calibration and Validation

The HEC-HMS model calibration was done for the observed discharge data of 2008 to 2011 for 18 hydrometric stations of the Narayani Basin. The discharge data was derived from observed stage using rating curves provided by the Department of Hydrology and Meteorology, Nepal.

There are three ways of optimizing model parameters: Manual Calibration with Trial and Error, Automatic Calibration with Optimization Trials and Calibration Aids. The model was run for four times: Firstly the model calibration is done for observed precipitation without snowmelt component. Secondly the model was run with snowmelt component and calibration and validation was done again. In the next step the WRF forecast precipitation was assigned to the model and run without changing the parameters. Then after the model run again for bias corrected forecast precipitation data.

For this study the calibration Aids is used for all the sub-basins to calibrate the parameters. Firstly the sensitivity of each parameters is checked and then the values of parameters are adjusted. The parameters are adjusted and run for large number of times to get the best result.

The calibration and validation result along with model error correction for Devghat flood forecasting station for above mentioned first categories are presented in Table 4.1 below.

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Table 4.1: Calibration and Validation Result for Flood Forecasting Stations (No-snow)

HEC-HMS Model (No-Snow) Model Error Calibration Results Validation Results Correction Station Mean Mean Nash RMS Absolute Nash RMS Absolute Nash Sutcliffe Sutcliffe Error Error Sutcliffe Error Error

KumalGaun (KaliG) 0.73 236 131 0.77 252 137

Kotagaun(KaliG) 0.71 319 164 0.73 357 194

Sisaghat(Madi) 0.73 36 22 0.69 39 23

Bimalnagar(Marsyandi) 0.59 124 87 0.46 147 72

Kalikhola (Trishuli) 0.84 575 196 0.66 867 467 Calibration:0.96 Devghat(Narayani) 0.892 587 334 0.893 582 353 Validation: 0.97

Rajaiya( East Rapti) 0.57 36 14 0.3 47 21

The calibration, validation and model error correction result for these stations with snowmelt component are presented in Table 4.2 below.

Table 4.2: Calibration and Validation Result for Selected Flood Forecasting Stations

HEC-HMS Model (with-Snow) Model Error Calibration Results Validation Results Correction Station Mean Mean Nash RMS Absolute Nash RMS Absolute Nash Sutcliffe Sutcliffe Error Error Sutcliffe Error Error

KumalGaun (KaliG) 0.73 236 131 0.77 252 137

Kotagaun(KaliG) 0.7 319 164 0.73 357 194

Sisaghat(Madi) 0.73 36 22 0.69 39 23

Bimalnagar(Marsyandi) 0.79 124 87 0.76 147 72

Kalikhola (Trishuli) 0.76 575 196 0.58 867 467 Calibration:0.96 Devghat(Narayani) 0.882 587 334 0.883 582 353 Validation: 0.97

Rajaiya( East Rapti) 0.57 36 14 0.3 47 21 33

The calibration, validation and model error correction result for these stations for no-snow model applying the WRF forecast and bias corrected WRF forecast precipitation are presented in Table 4.3 below.

Table 4.3: Calibration and Validation Result for Selected Flood Forecasting Stations

HEC-HMS Model (No-Snow)

Calibration / Calibration / Calibration / Validation Results Validation Results Validation Results Station Model Error Bias Corrected Correction Forecast Day 1 Forecast Day 1 Forecast Day 1 Nash Nash Nash Nash Nash Nash Sutcliffe Sutcliffe Sutcliffe Sutcliffe Sutcliffe Sutcliffe 0.48 KumalGaun (KaliG) 0.21 0.38 0.57 0.47 Kotagaun(KaliG) 0.15 0.47 0.58 0.49 Sisaghat(Madi) 0.41 0.6 0.48 0.57 Bimalnagar(Marsyandi) 0.36 0.66 0.42 0.58 Kalikhola (Trishuli) 0.58 0.66 0.52 0.66 0.82 Devghat(Narayani) 0.33 0.61 0.76 0.87

Rajaiya( East Rapti) 0.27 0.1 0.31 0.1

The Calibration plots (2008-2011) for Devghat station for observed precipitation case and bias corrected forecast day1 case along with model error correction for both are shown in Figure 4.6 below.

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Figure 4.6: Calibration Plots for observed and bias corrected forecast precipitation along with model error correction

The validation plots (2012-2013) for Devghat station for observed precipitation case and bias corrected forecast day1 case along with model error correction for both are shown in Figure 4.7 below.

Figure 4.7: Validation Plots for observed and bias corrected forecast precipitation along with model error correction 35

The plot of the model error correction done for Devghat station is presented in Figure 4.8 below.

Figure 4.8: The observed, forecast and corrected discharge for calibration period along with performance indicator plot

The graphical view of the modell error correction for the validation year 2010 is shown in Figure 4.9 below.

Figure 4.9: The observed, forecast and corrected discharge for validation period

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5. Development of Hydraulic Model

5.1 Methodology Flow Chart

Basic data required for the Inundation mapping using HEC-GeoRAS and HECRAS are Spatial Data: Digital Elevation Model (DEM) and Land use. The other data required are the Hydrological Data for Flood Frequency Analysis. The details of the Methods are shown in flow chart given below in Figure 5.1.

Figure 5.1: Methodology Flow Chart

5.2 Flood Frequency Analysis of Discharge Data in Different Return Period

The prediction for the future floods is made on the basis of available past extreme floods using theoretical probability distribution method (Gumbel). The flood frequency analysis was conducted with the extreme discharge from 1963 to 2010 at Devghat station, Rajaiya Station, Lothar Station and Manahari Station. Considering the specific extreme discharge events of the river of 47 years of devghat and rajaiya station, and determining the required statistical parameters, the flood magnitude for any specific return period is calculated and presented in table and figure 5.1 and 5.2 below. The extreme values of flood computed from Gumbel extreme value distribution method is adopted in this study. The flood frequency analysis result for Lothar and Manahari Rivers are presented in Table 5.2 below.

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Figure 5.2: Flood Frequency Analysis of Narayani River at Devghat Station (Data Source: DHM)

Table 5.1: Predicted Discharge of Narayani River at Different Return Periods

Return Discharge Periods m3/sec (T) Q(ext) 2 8899.2 5 10769.4 10 12007.7 20 13195.5 50 14732.9 100 15885.0 200 17032.9 500 18547.4 1000 19691.9

Similarly for the East Rapti, the extreme discharge measured at Rajaiya station is available for years from 1963 to 2010.

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Figure 5.3: 3Flood Frequency Analysis of East Rapti River at Rajaiya Station (Data Source: DHM)

Table 5.2: Predicted Discharge for East Rapti at Rajaiya, Manahari and Lothar Rivers by Gumbel Extreme Value Analysis

Return Discharge Periods m3/sec (T) Rajaiya Manahari Lothar 2 584 535 303 5 1034 883 499 10 1333 1114 629 20 1619 1335 753 50 1989 1621 915 100 2267 1835 1035 200 2544 2049 1156 500 2908 2331 1315 1000 3184 2544 1435

Since the upstream boundary condition for the Narayani River is Devghat Hydrological station and for East rapti River is Rajaiya hydrological stations the flood flows computed from Gumbel method was applied. For Narayani River the possible contribution in the downstream tributaries till the Narayani-East rapti Confluence is negligible hence no later boundary conditions are applied. But in case of East rapti River there are two major tributaries: Manahari and Lothar joining the river in the d/s locations. Both the tributaries have good length of records. So the flood flows in those cross-sections have been changed as lateral boundary condition by just adding the corresponding flood flow in the Rajaiya flow. Finally the corresponding flows of both the reaches: Narayani upper and East Rapti are added and applied at the 39

junction for the steady flow analysis in the d/s reach of Narayani River. Hence altogether five set of flood values in five cross-sections including upstream boundaries, lateral boundaries and junction are prepared for the steady flow analysis in HEC-RAS.

Table 5.3: Different Flood Flows in different Locations of Narayani and East Rapti River

Flood Discharge (m3/s) Return Period ER_Rajaiya ER_Manahari ER_Lothar upper_Narayani Lower_Narayani 2 584 1119 1422 8899 10321 5 1035 1917 2416 10769 13185 10 1333 2446 3075 12008 15083 20 1619 2954 3707 13196 16903 50 1990 3610 4525 14732 19257 100 2267 4102 5138 15885 21023 200 2543 4593 5749 17032 22781 500 2908 5240 6554 18547 25101 1000 3184 5728 7163 19692 26855 Existing Warning Level (6.8m/3.3m) 1279 2300 2700 7443 10143 Existing Danger Level (8m/3.7m) 1661 3000 3500 9992 13492 Record_Max 3260 5800 6500 15400 21900

5.3 Preparation of DEM

A digital elevation model (DEM) is a representation of the earth surface in 3 dimensional way with height as a third dimension along with x and y in rectangular axes. DEM has wide application in a number of fields including hydrology and water management.

For this study the 1 arc second SRTM 30m DEM has been used. The Digital Elevation Model (DEM) from HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales) of 1 arc resolution are downloaded from the source: http://hydrosheds.cr.usgs.gov/dataavail.php. The mosaic operation is done in ARC-GIS and then clipped for the study area.

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5.4 Land Cover/Use

The Land Cover database of Nepal prepared by FAO of 90m grid resolution was used for providing the Manning's n based on the Land Cover categories. The Land use data has 11 land use type as shown in Table 5.4 and Figure 5.4 below.

Table 5.4: Land Use Type of FAO

Sno LC_lable LC_Type 1 AG_Ot Agriculture in valley floor 2 AG_SL Agriculture in sloping land 3 TNE Natural trees needle leaved 4 T_MIX Natural trees mixed 5 SH High shrubs 6 H&S Low shrubs 7 H&S_W Shrubs in wetland 8 BS Bare areas 9 U Urban area 10 SN&I Snow and Ice 11 W_S&P Waterbodies

Figure 5.4: Landuse Map of Study Area (Sourse: FAO) 41

5.5 Manning’s Roughness n

The Manning's n value was obtained from the Table given by Chow (1959) for the natural channels as given in Table 5.5 below.

Table 5.5: Manning’s n for Natural Channel

Minimu Maximu Type of Channel and Description Normal m m 1. Natural streams - minor streams (top width at flood stage < 100 ft) I. Main Channels a. Clean, straight, full stage, no rifts or deep pools 0.025 0.03 0.033 b. Same as above, but more stones and weeds 0.03 0.035 0.04 c. Clean, winding, some pools and shoals 0.033 0.04 0.045 d. Same as above, but some weeds and stones 0.035 0.045 0.05 e. Same as above, lower stages, more ineffective slopes 0.04 0.048 0.055 and sections f. Same as "d" with more stones 0.045 0.05 0.06 g. Sluggish reaches, weedy, deep pools 0.05 0.07 0.08 h. Very weedy reaches, deep pools, or floodway with 0.075 0.1 0.15 heavy stand of timber and underbrush II. Mountain streams, no vegetation in channel, banks usually steep, trees and brush along banks submerged at high stages a. Bottom: gravels, cobbles, and few boulders 0.03 0.04 0.05 b. Bottom: cobbles with large boulders 0.04 0.05 0.07 3. Floodplains a. Pasture, no brush

1.Short grass 0.025 0.03 0.035 2. High grass 0.03 0.035 0.05 b. Cultivated areas

1. No crop 0.02 0.03 0.04 2. Mature row crops 0.025 0.035 0.045 3. Mature field crops 0.03 0.04 0.05 c. Brush

1. Scattered brush, heavy weeds 0.035 0.05 0.07 2. Light brush and trees, in winter 0.035 0.05 0.06 3. Light brush and trees, in summer 0.04 0.06 0.08 4. Medium to dense brush, in winter 0.045 0.07 0.11 5. Medium to dense brush, in summer 0.07 0.1 0.16 d. Trees

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1. Dense willows, summer, straight 0.11 0.15 0.2 2. Cleared land with tree stumps, no sprouts 0.03 0.04 0.05 3. Same as above, but with heavy growth of sprouts 0.05 0.06 0.08 4. Heavy stand of timber, a few down trees, 0.08 0.1 0.12 little undergrowth, flood stage below branches 5. Same as 4. with flood stage reaching branches 0.1 0.12 0.16 4. Major streams (top width at flood stage > 100ft) a. Regular section with no boulders or brush 0.025 0.06

b. Irregular and rough section 0.035 0.1

5.6 Hydrodynamic Modelling using HEC-RAS

5.6.1 Theoretical Background

The HEC-RAS 4.1 is an integrated system of software, developed at Hydrologic Engineering Centre, U.S. Army Corps of Engineers that allows to perform one dimensional steady and unsteady river flow hydraulics calculation, sediment transport mobile bed modelling and water temperature analysis. The system is composed of a graphical user interface (GUI), separate analysis components, data storage and management capabilities, graphics and reporting facilities (US Army Corps of Engineers, 2010). It is designed for interactive use in a multi-tasking environment to perform one-dimensional hydraulic calculations for a full network of natural and constructed channels.

5.6.2 One dimensional flow calculations in HEC-RAS

Steady Flow water surface profiles: This component of modelling is developed for the calculation of water surface profiles for steady gradually varied flow. In Steady state modelling, the model calculates water levels at discrete cross-sections as according to the flows prescribed by the user. The one dimensional energy equation is used to compute the unknown variable (stage). Energy losses are evaluated by friction (Manning’s equation) and contraction/expansion (coefficient multiplied by the change in velocity head).

The energy equation is based on principle of conservation of the energy and it states that the sum of the potential and kinetic energy at particular cross section is equal to the sum of the potential and kinetic energy at any other cross section plus or minus energy loss or gains between the sections. Then the water surface profiles are computed from one cross-section to another by solving the equation with an iterative procedure.

Unsteady flow simulations: This component of modelling is capable for the simulation of one dimensional unsteady flow. In unsteady flow modelling, two equations are needed to calculate two 43

variables, stage and flow. The unsteady flow simulation was developed primarily for sub critical flow regimes but now with new version it can perform mixed flow regime such as sub critical, supercritical, hydraulic jumps and draw downs(US Army Corps of Engineers, 2010).Unsteady modelling also concerned with the change of stage and flow with the change in time and distance downstream.

5.6.3 Pre-processing to develop the RAS GIS import file

For the hydraulic computation, the geometric data of river must be imported and flow data must be entered. The required geospatial data can be processed from HEC Geo-RAS, a GIS extension tool. The spatial GIS import file created in Geo-RAS are river, reach, and stations identifiers, cross-sectional cut lines, cross-sectional surface lines, cross sectional bank stations, downstream reach lengths, main channel, cross sectional roughness coefficient etc. These datasets are produced and processed from the existing digital elevation model (DEM).

5.6.4 Post-processing to generate GIS data from HEC-RAS results

Once the hydraulic computation is done, the water surface and velocity results again may be imported to HEC-Geo-RAS for spatial analysis. The automated delineation of flood plain can be done with the RAS output files. Based on the HEC-RAS output files the cross section theme and bounding polygons can be generated and the water surface TIN is generated using these cross-sections and bounding polygon themes. Then the flood plain polygons and inundated depth grids can be generated from water surface TIN.

5.6.5 HEC-RAS Simplifications of St. Venant Equation

The Navier-Stokes equations that define the behaviour of fluid are formed by the mass conservation equation and the momentum conservation equations(Rabade, 2012). HEC RAS has a computational program that solves and simplify of these equations. These one dimensional equations are known as Saint-Venant equations and it gives values of velocity and depths as the Navier-Stokes equations do. Therefore it is used in hydrodynamic models that study the movement of free surface water in longitudinal dimension such as in rivers and channels. HEC-RAS has an option called flow distribution which used the Divided Channel Method that allows the sub-division of each of three existing parts; main channel, left floodplain and right flood plain. The mean velocity will be calculated in those subsections. Again for the each sub section, the calculations will be done with the expression given by

With

Where = volumetric flow rate

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= hydraulic conductivity

= Area

= Hydraulic Radius

= Manning Coefficient

= Longitudinal slope

The evaluation of flood area in HEC –RAS for certain volumetric flow rate will be depending on the geometry of the bed, slope and other factors.

5.6.6 Steps Involved in Hydrodynamic Model setup

To perform the hydrodynamic modelling in HEC RAS, following steps has been followed in Pre- processing and post processing stages.

Pre-processing In pre-processing phase all the geometric data and other required themes for HEC RAS model were prepared in ARC GIS environment with HecGeoRAS and exported to .sdf format to be imported in HEC RAS. The themes included cross section, river centreline, bank line, flow path and TIN generated from Digital Elevation Model.

The river centreline, bank line and flow paths were prepared from the DEM and World imagery in ARC- GIS and imported to the HEC GeoRAS layers. The cross section cut lines were constructed at an interval of around 200m in both the rivers under study. The Manning’s coefficient was obtained from literature referring to the values for Plains Rivers and from the table by Chow (1959) for natural channels. The Manning's coefficient for different land use categories were populated and extracted for each cross section in HEC GeoRAS. After preparation of all required themes the data was exported to ‘.sdf’ format to be imported in HEC RAS. Figure shows the view of geometric data in long profile of Narayani and East Rapti River.

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Figure 5.5: Long profile and cross section location of Narayani River

Hydrodynamic Modelling The geometric data prepared in pre-processing phase of HEC GeoRAS was imported in HECRAS for the hydrodynamic modelling. The Hydraulic data including flow data and associated boundary condition were given into flow plan of HEC RAS. In the flow plan Discharge data for different Return Periods including warning and danger level flood as well as maximum recorded flood in the gauging station was given to the selected cross section of the river. For Narayani River the flow data was given at the u/s section and a flow change location was given at the junction cross section at Narayani-East Rapti Junction. Similarly, for East Rapti River the flow data was provided at u/s section and d/s section of each Manahari and Lothar junctions. The steady state flow simulation was then performed for water surface profile calculation for various magnitudes of discharge in the u/s with a mixed flow regime. Once the water surface profiles were calculated, the results were exported to GIS format for Post Processing.

Post Processing In the post-processing phase, HEC-RAS results were imported into HEC GeoRAS Platform after having the layer set up with DEM-GRID as the terrain input. The water surface for each water surface profiles is first generated for different return periods viz. warning level flood, danger level flood, maximum record flood, 2, 5, 10, 20.50,100,200,500, and 1000 years based on the water surface elevation at each cross section as calculated in HEC RAS. The flood Inundation Map and Flood plain boundary is then generated for each water surface profiles based on the water surface TIN generated from the Digital Elevation Model. 46

5.6.7 Flood Danger Level and Warning Level Assessment

According to the Flood Forecasting Section of Department of Hydrology and Meteorology the flood warning level is the flood that just passes over the river bank but does not affect the nearby settlements. The danger level is that level of flow at which the flood water rises above the main stream channel and enters the settlements affecting people and their properties (Gautam, 2013).

To access the Danger level and Warning Level, Hydrodynamic Modelling was performed using HEC- RAS and HEC Geo RAS model to generate the scenarios of flood inundation at warning level flood, danger level flood, maximum record flood, 2, 5, 10, 20, 50, 100, 200 500 and 1000 Years Return Period.

Flood Danger Level and Warning Level of Narayani River: For Narayani River the first cross section available at devghat area is selected for forecasting the danger and warning level during flood. For hydrodynamic modelling following Discharge has been given at the u/s cross section of the river.

The historical flood discharge (instantaneous maximum observed discharge) observed at Devghat station was analysed for the assessment of the flood warning and danger levels of Narayani River. From the analysis of the historical data, the threshold level for warning level and danger level was determined as 8898 cumecs and 10769 cumecs respectively. The determination is based on the inundation scenario downstream of the

NarayaniProject Plan: Plan 01 25-May-16

.07 .025 .07 250 Legend

WS 1000 Year_Flood WS 500 Year_Flood

240 WS 200 Year_Flood WS 100 Year_Flood WS Record_Max_Flood WS 50 Year_Flood 230 WS 9.5/5 WS 20 Year_Flood WS 9/4.5 WS 10 Year_Flood 220 WS 8.5/4 WS 5 Year_Flood WS DangerL

Elevation Elevation (m) 210 WS 2 Year_Flood WS WarningL 0 m/s 2 m/s 200 4 m/s 6 m/s 8 m/s 190 10 m/s 12 m/s Ground Bank Sta 180 0 100 200 300 400 500 Station (m) Figure 5.6: Inundation scenario at forecasting Station selected for Narayani River

The water level at the selected forecasting station in Narayanghat for Narayani River for different return period is shown below.

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NarayaniProject Plan: Plan 01 25-May-16

.07 .025 .07 250 Legend

WS 2 Year_Flood 0 m/s

240 2 m/s 4 m/s 6 m/s 8 m/s 230 10 m/s 12 m/s Ground

220 Bank Sta

Elevation Elevation (m) 210

200

190

180 0 100 200 300 400 500 Station (m) Figure 5.7: Water level at forecasting Station for the inundation scenario of 2 YRP

NarayaniProject Plan: Plan 01 25-May-16

.07 .025 .07 250 Legend

WS 5 Year_Flood 0 m/s

240 1 m/s 2 m/s 3 m/s 4 m/s 230 5 m/s 6 m/s 7 m/s

220 Ground Bank Sta

Elevation Elevation (m) 210

200

190

180 0 100 200 300 400 500 Station (m) Figure 5.8: Water level at forecasting Station for the inundation scenario of 5 YRP

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NarayaniProject Plan: Plan 01 25-May-16

.07 .025 .07 250 Legend

WS 100 Year_Flood 2 m/s

240 3 m/s 4 m/s 5 m/s 6 m/s 230 7 m/s Ground Bank Sta

220

Elevation Elevation (m) 210

200

190

180 0 100 200 300 400 500 Station (m)

Figure 5.9: Water level at forecasting Station for the inundation scenario of 100 YRP

NarayaniProject Plan: Plan 01 25-May-16

.07 .025 .07 250 Legend

WS 1000 Year_Flood 2 m/s

240 3 m/s 4 m/s 5 m/s 6 m/s 230 7 m/s 8 m/s Ground

220 Bank Sta

Elevation Elevation (m) 210

200

190

180 0 100 200 300 400 500 Station (m)

Figure 5.10: Water level at forecasting Station for the inundation scenario of 1000 YRP

After analysing the inundation scenario of 2 to 1000 Yrs. Return period, it is found that at Narayanghat on 2 year Return Period the surface water level would be at bank full stage with discharge of 8898 cumecs water. The surface water level from datum of the gauging station would be 7.5m. Whereas, in inundation scenario of 5 years return period at discharge of 10567 cumecs, the surface water level will rise to 8.3 m inundating approximately 0.8 m in banks bank. The underlying table given below will summarise the Warning level and Danger level data of forecasting station at Devghat.

Table 5.6 Flood Danger Level and Warning Level of Narayani River

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Return Period Discharge Surface Water Inundation Threshold Cumecs level from Mean above bank full Sea Level stage at forecasting Station 2 Yrp 8898 7.5 Nil Warning Level

5 Yrp 10567 8.3 Approx. 0.80m Danger Level

This shows that from the historic flood events, the recurrence of flooding exceeding the discharge of 8898 cumecs is likely to be 2 years. Similarly, the recurrence of flooding exceeding 10567 cumecs is likely to be 5 years. This infers that the floods in Narayani River could reach up to the warning level and danger level in the recurrence cycle within 2 and 5 years respectively.

Similarly, after analysing the inundation scenario of 2 to 1000 Yrs. Return period, it is found that at Rajaiya on 5 year Return Period the surface water level would be at bank full stage with discharge of 1035 cumecs water. The surface water level from datum of the gauging station would be 3 m. whereas, in inundation scenario of 5 years return period at discharge of 1333 cumecs, the surface water level will rise to 3.4 m inundating approximately 0.4 m in banks. The underlying table given below will summarise the Warning level and Danger level data of forecasting station at Rajaiya.

Table 5.7: Flood Danger and Warning Level of East Rapti

Return Period Discharge Surface Inundation Threshold Remarks Cumecs Water level above bank from Mean full stage at Sea Level forecasting Station 5 Yrp 1035 3m Nil Proposed Existing Warning Level Warning Level: 3.3m

10 Yrp 1333 3.4m Approx. 0.40m Proposed Existing Danger Level Danger Level: 3.7m

Figure 5.11 and Figure 5.12 below shows the inundation map for warning and danger level flood events. The inundation map for 100 year flood and 1000 year flood are presented in the Figure 5.13 and Figure 5.14. The area of inundation for 100 year return period flood along with the warning, danger and maximum record flood in the basin are shown in Table 5.8. Table 5.9 shows how much area of different landuse type in the basin affected by 100 year return period flood. The maximum area affected seems to be forest but there is still significant area (6007 Km2) inundated for agriculture. The settlements also lie within it.

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Figure 5.11: Warning Level Inundation map of Narayani and East Rapti River

Figure 5.12: Danger Level Inundation map of Narayani and East Rapti River

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Figure 13: Inundation map of Narayani and East Rapti River for 100 Year Flood

Figure 14: Inundation map of Narayani and East Rapti River for 1000 Year Flood

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Table 5.8: Area of Inundation for 100 Year flood

Flood Total Inundation Area (Km2)

2 Year 187

Warning Level 204

Danger Level 236

100 Year 292

200 Year 305

500 Year 323

1000 Year 337

Table 5.8: Area of Inundation for 100 Year flood for different landuse type

Area inundated by 100 Yr flood

Land Use Type (KM2)

Agriculture

(AG_OT) 6007

Bare Land (BS) 23027

High Shrubs (SH) 543

Forest

(T-mix) 23569

Water Body (W_S&P) 22846

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6. Conclusion and Recommendation

6.1 Synopsis of the Results and conclusion

This study was undertaken with an aim to prepare a flood forecasting model along with flood hazard and inundation maps in the flood affected region of Narayani and East Rapti River. The ultimate purpose is to enhance the flood forecasting and early warning system in the department of Hydrology and Meteorology identifying flood susceptible areas and support as an early warning decision support system for the communities and other stakeholders. The potential flood hazard and inundation maps enables Department of Hydrology and Meteorology to identify or update the warning and danger levels in the respective flood forecasting stations, hence pre-informing of the impending flood event ‘if and when’ the threshold warning and danger levels exceed. This enables the disaster responders to raise alarm to the communities for evacuation and to take precautionary measures, thus saving lives and properties with longer lead times.

As a decision support tool, the flood forecasting model and flood hazard maps pre-informs the communities and stakeholders at different levels to plan and implement their programs avoiding the potential flood hazard areas. As an instance, vulnerability assessment of the households living within the potential flood hazard zones can be done to develop and implement mitigation and resilience programs. In other case, identify those vulnerable households and landowners for resettlement and/or implement various programs for resilience capacity buildings at the community and household levels.

Department of Hydrology and Meteorology currently have no models for flood forecasting in the country. The United States Army Corps of Engineers (USACE) Hydrologic Engineering Center’s Hydrological Modeling System (HEC-HMS) was examined for streamflow forecasting using Narayani basin. Observed precipitation data was obtained from DHM. Calibration and verification of the modeling system was done through an operational perspective to test the model’s applicability at DHM. Model development was done using observed precipitation and was conducted in several stages. The Nash Sutcliffe for the main Devghat Flood Forecasting Station is 0. 892 for calibration (2008-2011) and 0.893 for the validation (2012-2013) for model without snowmelt consideration. The result is also similar for the snowmelt consideration. After the model error correction using ARIMA modules the Nash-Sutcliffe is 0.97 for both calibration and validation periods. The calibrated model was tested with bias corrected WRF one day precipitation forecast estimations for the same periods. The bias correction scheme was computed and applied at the basin scale. When used as input to the HEC-HMS model the Nash-Sutcliffe is 0.33 for the calibration period and 0.66 for the validation period. But the result is satisfactory when the model error correction is done again for the, which results Nash-sutcliffe to be 0.82 for calibration period and 0.87 for validation period.

With above described applications, the key outputs of the study are highlighted hereunder:

 The study has developed a flood forecasting model with satisfactory result for Narayani River basin. This indicate that the model can be steadily used for at least one day flood forecasting.

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 HEC-HMS model is proved to be a powerful tool for Flood Forecasting in Narayani Basin  Rainfall Bias Correction and Model Error Correction has significantly improved the model results  The study has prepared flood hazard and inundation maps of the settlements along the Narayani/East rapti, rivers covering all communities along the River upto Indo-Nepal Boarder. The flood hazard maps were prepared based on the flood forecast modelling and Geographic Information System (GIS) based analysis of flood inundation extent and depth.  The warning level of Narayani River was found at 2 years return period with estimated discharge of 8,898 cumecs with the surface water level at 7.5 m from the mean sea level. The danger level is observed in inundation scenario of 5 years return period with the discharge of 10769 cumecs with the surface water level rising to 8.3 m from the datum of the gauging station. Similarly the warning level of East Rapti was found at 5 year return year flood with estimated discharge of 1035 cumecs with the surface water level of 3.0m. The danger level is observed in inundation scenario of 10 return year flood with estimated discharge of 1333 cumecs at 3.4m water level in the gauging station. With this the existing warning and danger level of both the rivers seems to be changed.  For the inundation scenario at danger level in Narayani River and East Rapti River the flooding scenarios are: Most of the settlements of both the banks of Narayani in Chitwan and Nawalparasi and settlements along right bank of East Rapti River in Chitwan districts are at potential risks of flooding.

6.2 Recommendation

From the study and modelling of the flood inundations, the study team recommends the followings:

 For most of the stations underlying in the upper catchment, the calibration and validation has very poor result, one of the reason could be the gap of precipitation station. It can be a recommendation here to take bias corrected satellite precipitation for those areas.  Snow model may not be incorporating the glacier melt component It is recommended to see a best possible option to capture it.  The Rainfall Forecast is highly overestimated for Day 2 and Day 3. It is recommended the further calibration of WRF.  If the model is run for higher resolution precipitation data (like 6 hourly, 3 hourly, hourly), the model would be better calibrated and validated particularly for the smaller sub-basins in the upper.  If the DELFT FEWS customization for Nepal Basins are done in time the trial operational flood forecasting could be started from the beginning of the coming monsoon.  The Inundation mapping shows the existing warning and danger level in the river are quite less then what actually would be. However some of the areas seems to be inundated even in normal flood situation. If the Levee alignment is accurately given in the HEC-RAS this would give the better result.  The 30m SRTM DEM is still not perfect for the hydraulic modelling. If fine resolution DEM is provided or detail cross-section survey is carried out and a DEM is prepared based on the survey data it would give a better result.

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 Identification and Verification of households and land owners in the inundation zones through field survey and vulnerability assessment will give clearer picture on the potential risks from the flood models. If prior surveys have already been conducted, identifying the households in the flood inundation zones and assessing the data would give risk information. This can be done if this project is further extended or by the government budget.

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References Adhikary, B. R. (2013). Flooding and Inundation in Nepal: Issues and Concerns: Hydro Nepal. Dhakal, S. (2013). Flood Hazard in Nepal and New Approach of Risk Reduction. International Journal of Landslide and Environment , 13-14. Dotson, H. W. (1990). Hydrologic Aspect of Flood Warning-Preparedness programs. Garg, S. K. (2012). Hydrology and water resource engineering. Gautam, D. K. (2013). Determination of Threshold Runoff for Flood Warning in Nepalese Rivers. Journal of Integrated Disaster Risk Management . ICIMOD. (2010). Land Cover of Nepal. Luna Bharati, P. G. (2012). Hydrological Charaterization of the Koshi Basinand the Impact of Climate Change: Hydro Nepal. NERC. (2014). Flood forecasting challenges in Nepal-Operation probabilistic flood forecasting model of the Karnali river basin in nepal. NERC Science of the Environment , 13-32. US Army Corps of Engineers. (2012). HEC-GeoRAS GIS tools for support of HECRAS using ARCGIS 10.0, User's Manual, Version 10. US Army Corps of Engineers. (2010). HEC-RAS, River Analysis System, User's Manual, Version 4.1

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ANNEXS

(will be put in final report)

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