Report on flood hazard model

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CIRM in collaboration with the Institute of Water Modelling, Dhaka, Bangladesh published a report on Flood Hazard Model for an Index Based Flood Insurance Products for Sirajganj District, Bangladesh. …

CIRM in collaboration with the Institute of Water Modelling, Dhaka, Bangladesh published a report on Flood Hazard Model for an Index Based Flood Insurance Products for Sirajganj District, Bangladesh.

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  • 1. TABLE OF CONTENTS Table of Contents ........................................................................................................................................................... i List of Figures............................................................................................................................................................... iii List of Tables ................................................................................................................................................................ iv Abbreviations and Acronyms ........................................................................................................................................ v1 INTRODUCTION ...................................................................................................................................................... 1 1.1 General ........................................................................................................................................................... 1 1.2 Background Of The Study .............................................................................................................................. 1 1.3 Study Area ...................................................................................................................................................... 2 1.3.1 Geographical Location ............................................................................................................................... 2 1.3.2 River System .............................................................................................................................................. 3 1.3.3 Geology And Topography .......................................................................................................................... 5 1.3.4 People And Livelihood ............................................................................................................................... 5 1.4 Objectives, Scope Of Works And Outputs ...................................................................................................... 5 1.4.1 Objectives .................................................................................................................................................. 5 1.4.2 Scope Of The Works .................................................................................................................................. 6 1.4.3 Output ........................................................................................................................................................ 6 1.5 Literature Review ............................................................................................................................................ 6 1.5.1 Bangladesh And Its Hydrological Features ................................................................................................ 6 1.5.2 Floods In Bangladesh ................................................................................................................................ 8 1.5.3 Flooding And Drainage In The North West Region .................................................................................. 122 METHODOLOGY, DATA AND INFORMATION USED .......................................................................................... 13 2.1 Concept Of Flood Hazard Model .................................................................................................................. 13 2.2 Methodology: Development Of Flood Hazard Model .................................................................................... 13 2.2.1 Tools Used For The Study ....................................................................................................................... 15 2.2.2 Selection Of Events ................................................................................................................................. 16 2.2.3 Generation Of Flood Maps....................................................................................................................... 16 2.3 Methodology: Flood Vulnerability Index ........................................................................................................ 16 2.3.1 Criteria For Flood Vulnerability ................................................................................................................ 16 2.3.2 Yearly Index Map ..................................................................................................................................... 18 2.3.3 Probabilistic Vulnerability Index Map ....................................................................................................... 19 2.4 Data And Information Used .......................................................................................................................... 19 2.4.1 For Rainfall-Runoff Model Development .................................................................................................. 19 2.4.2 For Hydrodynamic Model Development................................................................................................... 19 2.4.3 For Flood Map Generation ....................................................................................................................... 203 DEVELOPMENT OF FLOOD HAZARD MODEL ................................................................................................... 21 3.1 Introduction ................................................................................................................................................... 21 3.2 Existing Super Model .................................................................................................................................... 22 3.2.1 Hydro-Meteorological Data Input ............................................................................................................. 22 3.2.2 Rainfall-Runoff Model .............................................................................................................................. 23 3.2.3 Hydrodynamic Model ............................................................................................................................... 23 3.2.4 Boundary Generation ............................................................................................................................... 23
  • 2. ii Table of Contents 3.2.5 Performance of The Super Model ............................................................................................................ 24 3.3 Sirajganj Flood Hazard Model ...................................................................................................................... 25 3.3.1 Incorporation Of Floodplain Channel & Cross-Section ............................................................................ 25 3.3.2 Watershed /Catchment Runoff Distribution To River Network ................................................................. 28 3.3.3 Boundary Generation For Sirajganj Flood Hazard Model ........................................................................ 29 3.3.4 Calibration And Validation Of Sirajganj Model ......................................................................................... 32 3.3.5 Flood Inundation Maps/ Data Generation ................................................................................................ 37 3.4 Breach Model................................................................................................................................................ 38 4 OUTPUT, RESULTS AND DATA SHARING.......................................................................................................... 40 4.1 Output ........................................................................................................................................................... 40 4.1.1 Output of Flood Hazard Model ................................................................................................................. 40 4.2 Yearly Flood Vulnerability Index Map ........................................................................................................... 43 4.2.1 Index For Major Flood .............................................................................................................................. 43 4.2.2 Index For Normal or Average Flood Year ................................................................................................ 44 4.2.3 Index for Below Than Normal Flood Year ................................................................................................ 44 4.2.4 Probabilistic Index Map ............................................................................................................................ 45 5 CONCLUSION ....................................................................................................................................................... 49 5.1 Conclusions .................................................................................................................................................. 49 5.2 Limitations..................................................................................................................................................... 50 5.3 Recommendations ........................................................................................................................................ 50 6 REFERENCE ......................................................................................................................................................... 52 Annex-A Annex-B Annex-C
  • 3. Table of Contents iiiLIST OF FIGURESFigure 1-1: Study area ....................................................................................................................................................... 3Figure 1-2: River system of North-West Region of Bangladesh ..................................................................................... 4Figure 1-3: Topography and major river system of Bangladesh ........................................................................................ 7Figure 1-4: Flood regime and type of Bangladesh ............................................................................................................. 7Figure 2-1: Flow diagram showing methodology to produce Vulnerability Index Map using daily flood maps for 152days of monsoon period. .................................................................................................................................................. 18Figure 3-1: River network of FFWC Super Model ........................................................................................................... 22Figure 3-2: The updated and non updated river reaches in Super Model ...................................................................... 23Figure 3-3: Evaluation of FFWC Model performance at .................................................................................................. 25Figure 3-4: Comparison of simulated water level of Brahmaputra at Sirajganj (top) Ganges at Rajshahi (middle) andand Meghna at Bhairab Bazar (bottom) ........................................................................................................................... 25Figure 3-5: Sirajganj Flood Hazard Model river network ................................................................................................. 26Figure 3-6: Floodplain channels incorporated in the dedicated Sirajganj Model ............................................................. 26Figure 3-7: Existing river network in Super Model covering the project area (left) and customized river and floodplainnetwork in Sirajganj Flood Model ..................................................................................................................................... 27Figure 3-8: Water level grid (model h-points) of existing Super Model setup (left) and increased model grid points forcustomized Sirajganj Flood Hazard Model (right) ........................................................................................................... 28Figure 3-9: Thematic presentation of catchment runoff distribution approach. Main channel and correspondingcatchment area (left figure), main channel including additional channels (middle figure) and re-distribution of catchmentarea to main and additional channels (right figure) .......................................................................................................... 29Figure 3-10: Boundary location of North West Region of Super Model ........................................................................... 30Figure 3-11: Water level comparison points for calibration and validation of the model .................................................. 32Figure 3-12 to Figure 3-16: Comparison of model simulated water level with observed water level for calibration of floodyear, 2007 ........................................................................................................................................................................ 33Figure 3-17 to Figure 3-22: Chow comparison of model simulated water level with observed water level for validation offlood year, 2004 ............................................................................................................................................................... 34Figure 3-23 to Figure 3-28: Comparison of model simulated water level with observed water level for validation of floodyear, 1998 ........................................................................................................................................................................ 36Figure 3-29: Location of BRE breach position during past major floods. ........................................................................ 38Figure 4-1: Area of XYZ value extraction ......................................................................................................................... 41Figure 4-2: 2007 Flood depth in and around of Sirajganj District; June 07 (left), July 12 (middle) and July 18 (right) .... 41Figure 4-3: 2007 Flood depth in and around of Sirajganj District; July 25 (left), July 29 (middle) and August 03 (right) ......................................................................................................................................................................................... 42Figure 4-4: Flood Vulnerability Index Map for 2007 ......................................................................................................... 44Figure 4-5: Flood Vulnerability Index Map for 1998 ......................................................................................................... 44Figure 4-6: Flood Vulnerability Index Map for 2001 ......................................................................................................... 44Figure 4-7: Flood Vulnerability Index Map for 1997 ......................................................................................................... 44Figure 4-8: Flood Vulnerability Index Map for 2006 ......................................................................................................... 45Figure 4-9: 75% Probability Flood Index Map .................................................................................................................. 45Figure 4-10: 50% Probability Flood Index Map ................................................................................................................ 46Figure 4-11: 75% Probabilistic flooding scenario in terms of percentage of total Thana area of Sirajganj District affectedby six vulnerability indices ................................................................................................................................................ 48Figure 4-12: 50% Probabilistic flooding scenario in terms of percentage of total Thana area of Sirajganj District affectedby six vulnerability indices ................................................................................................................................................ 48
  • 4. iv Table of Contents LIST OF TABLES Table 2-1: Agricultural land classification in terms of flood depth .................................................................................... 16 Table 2-2: Vulnerability scale for depth of flooding .......................................................................................................... 17 Table 2-3: Vulnerability scale for duration of flooding ...................................................................................................... 17 Table 2-4: Unique Index Assigned for Combined or Averaged Depth-Duration Index .................................................... 19 Table 3-1: Boundary data type and availability status for Northwest Region of Super Model ......................................... 30 Table 3-2: Boundary position of Sirajganj Flood Hazard Model with river name and chainage corresponds to FFWC Super Model grid points used .......................................................................................................................................... 31 Table 3-3: Statistical parameter values for model performance (Year 2007) .................................................................. 32 Table 3-4: Statistical parameter values for model performance (Year 2004). ................................................................. 33 Table 3-5: Breach information on BRE in different flood year. ......................................................................................... 39 Table 4-1: Sample output of X,Y and flood depth value (Z) extracted from flood maps .................................................. 42 Table 4-2: Thana wise total area affected by different vulnerability indices for 75% probabilistic flooding scenario ....... 45 Table 4-3: Thana wise percentage of area affected by different vulnerability indices for 75% probabilistic flooding scenario ........................................................................................................................................................................... 46 Table 4-4: Thana wise total area affected by different vulnerability indices for 50% probabilistic flooding scenario ....... 46 Table 4-5: Thana wise percentage of area affected by different vulnerability indices for 50% probabilistic flooding scenario ........................................................................................................................................................................... 47
  • 5. Table of Contents vABBREVIATIONS AND ACRONYMSBWDB Bangladesh Water Development BoardBMD Bangladesh Meteorological DepartmentBRE Brahmaputra Right EmbankmentCSFFWS Consolidation and Strengthening of Flood Forecasting and Warning ServicesDHI Danish Hydraulic InstituteFAP Flood Action PlanFCD Flood Control and DrainageFCDI Flood Control Drainage and IrrigationFFWC Flood Forecasting and Warning CentreFFWS Flood Forecasting and Warning ServicesGIS Geographic Information SystemGoB Government of BangladeshHD HydrodynamicIWM Institute of Water ModellingKhal Small natural water channelKm Kilometerm MeterMIKE 11 1-Dimentional River Modelling Software developed by DHIMIKE 11 GIS Flood Mapping tool of DHIMSE Mean Squared ErrorNAM Rainfall Runoff Model (Danish Abbreviation: Nedbor Afstomings Model)NWRM North West Regional ModelNSE Nash-Sutcliffe efficiencyRHD Roads and Highways DepartmentRR Rainfall RunoffR2 Co-efficient of Determination
  • 6. 1 INTRODUCTION1.1 GENERALBangladesh – a land of promise where full credits belong to its generous and industrious people, however, are often beenclaimed as land of calamities and disaster. Such claim has been so exaggerated sometimes itgives an idea that naturaldisaster like floods, cyclones, droughts, river bank erosion etc. are largely responsible for its underachievement. Socio-politicalsystem of any country or community plays the pivotal role for development and enhances the resilience among the peopleagainst such disaster. Meanwhile, science, technology and its applicability can ensure a sustainable strategic programme forthe policy makers and this is why the present study has a greater importance to come up with an integrated flood managementplan. The deaths and economic losses resulting from large flood like flood in 1988, 1998, 2004 and 2007 and subsequent othermajor floods have forced the need for improved and integrated flood management and mitigation strategy. The impacts offloods are expected to be worsen as the vulnerability of Bangladesh to natural disasters is increasing due to several factorsincluding poverty, worsening environmental soundness, population growth, urban growth, weak governance and institutionalfactors, and climate change and variability (EWS, 2006).Floodplain zoning and flood insurance system has appeared as an effective and community participatory concept over the lastfew decades to mitigate the loss of income and property to flood effected people, property, infrastructure, and enterprises. Mostimportantly it addresses the importance of preserving natural geo-physical settings whether it is water, agricultural, land use orcoverage which is evolved as current state with practices and adaptation of people with nature for hundred thousands of years.In other words, it can facilitate to preserve the harmonic and sustainable interaction between people and nature for any givenarea. With the idea of that, a collaborative research work between Chennai based Centre for Insurance and Risk Management(CIRM), India and Dhaka based Institute of Water Modelling (IWM) has been taken on floodplain zoning and insurance system.The study selects Sirajganj District as its pilot area first to identify the flood hazard that affects the study area; second toestimate the flood loss in terms of peoples’ income and property, agricultural damage; and finally to come up with an effectiveinsurance system based on the findings from first two. In other words, the project aims to produce insurance based flood indexproducts for Sirajganj District.This chapter, therefore, will describe the conceptual background of the project, project area, objectives-scope of works-output.A literature review on overall flooding scenario of Bangladesh, particularly on North West Region of the county; its causes andconsequence; flood insurance products or system that has been in operation in many parts of the world for the last few years orso and experiences of those operation is also presented.1.2 BACKGROUND OF THE STUDYFlood is an annual recurring event during the monsoon in Bangladesh and has often been studied (e.g. Rasid and Paul, 1987;Khalil, 1990; Haque and Zaman, 1993; Paul, 1997; and the excellent overview by Hofer and Messerli, 1997). Normal floods (inbangle it is usually called barsha) are considered as natural assets as they maintain the high fertility of cultivated land, whereasextreme floods or bonna may be considered as natural hazards. Extreme floods are characterized by either unusually highwater levels or long-durations of flooding or early or late arrival of the flood (Jacobson et al., 2004). The average flooddischarges of the three main rivers (individually) are within the range 14,000 to 100,000 m3/s (Sarkar et al., 2003). Formationand erosion of the islands and bars and banks of the rivers are very common features for those major rivers. The averageannual sediment transport through these rivers is nearly 950 Mton per year among which two third is wash load i.e. silt and clay(Sarkar et al., 2003).
  • 7. 2 Introduction There have been several indications that the importance of sound flood management is expected to increase in the future both nationally and globally. Firstly, climate change studies indicate that risk of flooding is increasing in inlands and costal zones. In order to adapt to these scenarios, society and concerned countries need to be prepared and improve their flood management strategy. Secondly, national and international agendas and agreements are required for comprehensive and progressive flood management practices (Dubrovin et. al., 2006). For South Asia, particularly for Hindu-Khush-Himalayan (HKH) region and its downstream region, this is more relevant than any other parts of the world. Even though the occurrence of future flood disasters cannot be prevented, the magnitude of impact can be reduced by developing apposite flood countermeasures (Dewan et al., 2006). In general, the construction of embankment and dykes along river bank is the popular means of flood management in Bangladesh. It has become apparent during the flood in 1998 that such an approach is inadequate to combat flood disaster. Moreover, many socio-environmental threats are already reported due to the technological fixes and ill conceiving projects aiming to combat against flood with the concept of ‘flood control’ rather than ‘flood management’. Now days, the question of integrated flood management comes out more on the surface among the concerned authorities, experts, intelligentsia as well as among the people. In recognition of this fact, water experts of the country have emphasized on prevention and mitigation measures. Development of effective flood forecasting system, quick rehabilitation programme, flood zoning and hazard mapping for the management of future flood disasters (Nishat, 1998; Hossain, 1998) are among those. It is perhaps recognized that to lessen the negative consequences of floods, hazard areas must be identified and proper countermeasures should be adopted accordingly. Flood forecasting and warning services for the major river systems of the country has been operated successfully for the last two decades, though lots of works yet to be done to make it a meaningful flood mitigation proramme for community level. On the other side, there are few and mostly preliminary works have been done so far in Bangladesh (Dewan et al., 2006) to produce flood hazard maps and estimate economic losses for the past major floods as well as estimate potential economic losses for future such floods. Nevertheless, it is arguably accepted that the advanced hydrologic forecast products, development of flood hazard maps followed by producing flood loss index parameters, flood zoning and subsequent insurance policy, improvement of the drainage pattern of the country are pinnacle fields to be concentrated on as part of the integrated flood management of the country. With the idea discussed above, a research project aiming to produce index based flood insurance products for Sirajganj District has been undertaken. There are three components of the project; first one deal with the development of Flood Hazard Model and the second one will come up with a development of a Flood Loss Model for Sirajganj District using the output of first component. The final one will focus on the development of formidable insurance policy against annual flood loss and on how it could be applied to the stakeholders and users lev`1el. Institute of Water Modelling (IWM), Bangladesh and Centre for Insurance and Risk Management (CIRM), India are jointly conducting this project study. The present report thus presents an inception report of the project activities so far been accomplished which includes methodology of the study, hazard model development, model calibration and validation and the ongoing generation of daily flood depth data for the study area. 1.3 STUDY AREA 1.3.1 GEOGRAPHICAL LOCATION Sirajganj district is located in the northwestern part of Bangladesh, of which the mighty Brahmaputra or Jamuna River following at the right edge of the district. Interestingly enough 10 to 15 km wide Brahmapurtra River along with its floodplain at both sides shares large part of the district’s total area. Geographically, extension of Sirajganj District is within the area of longitude from 89°20’ west to 89°50’ east and in latitude it is 24°00’ south to 24°20’ north. Total area of the district is 2497.92 sq km and is
  • 8. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 3bounded by Bogra District on the north, Bogra and Nator District on the west and southwest, Pabna District on the south,Tangail and Jamalpur districts on the east.Sirajganj subdivision was established in 1845 during the period of British India-Bangladesh, and was included in Pabna districtat that time. It was turned into a district in 1984 after the liberation of Bangladesh back in 1971. The district consists of 4municipalities, 42 wards, 9 upazilas, 79 union parishads (all are local government administrative units), 117 mahallas, 1467mouzas and 2006 villages. The upazilas are Belkuchi, Chauhali, Kamarkhanda, Kazipur, Raiganj, Shahjadpur, Sirajganj Sadar,Tarash and Ullahpara (see Figure 1-1). 1.3.2 RIVER SYSTEM The description of river system of the district must have to start with the river system of North West region of Bangladesh. North West region has 28 rivers with total length of approximately 401 km. Major rivers of the region are Teesta, Upper-Karatoya, Atrai, Charalkata-Jamuneswari, Karatoya and Bangali. There are several other minor rivers in this area. Most of the rivers of this region flow from very steep to flat ground, predominantly from north to south (See Figure 1-2). A quick response of flash flood occurs in the upper portion of the region and inundates floodplains of both sides. Charalkata-Jamuneswari-Karatoya-Bangali River System The Charalkata-Jamuneswari or Jainttnesvari River (often referred as C. Jamuneswari) originates from an inside country small catchment and falls into Karatoya Rriver near Sirajganj. TheFigure 1-1: Study area Bullai having its upstream boundary at Hajipur meets with C.Jamuneswari at Barati and Chicklymeets with that system at Badarganj. The Karatoya River originates at Nalshisa south of Dinajpur-Rangpur railway line andreceives flow of C.Jamuneswari at Sirajganj and flow to Akhira at Ghoraghat. Finally, this combined flow along with flow ofGhagot meets with Bangali River near Mohimaganj. The river Bangali flows parallel to the Jamuna starting from Mohimaganjand ends at Baghabari by falling into the Hurasagar River. Several flood cells, flood depression areas exist in the western sideof Bangali River. Spilling from the Barhmaputra or Jamuna River, though during high floods, generally occurs via breachesdeveloped in the Brahmaputra Right Embankment (BRE), which inundates large areas. Backwater effects from the Jamuna andthe Atrai is dominant in the lower reaches of the system and causes additional flood.
  • 9. 4 Introduction North West Region and Its River System Figure 1-2: River system of North-West Region of Bangladesh
  • 10. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 5Upper Karatoya-Atrai River SystemUpper Karatoya is one of the main rivers of North West Region. Generated from Himalaya territory, it enters into Bangladesh atPanchagarh. It is flashy in nature and flows through a steeper ground slope. It is a perennial river. The lower part of UpperKaratoya River named as Atrai is flowing through slightly steeper to flat land. Atrai River with several tributaries anddistributaries has formed a complex network of rivers before falling into the Hurasagar River at Baghabari almost at the samepoint where the Bangali River also meets with the Hurasagar River. Thus, combined flow of Atrai-Bangali river system falls tothe Jamuna River through the Hurasagar River, the single outlet to the Jamuna. Upper part of Atrai River is influenced by localflow and is flashy in nature whereas the lower part is largely influenced by backwater effect of the Jamuna through Hurasagar.There are several depressions or beels existing around this river and a number of breaches originate every year from the banksof Atrai. This causes changed flow characteristics every year. Important tributaries of Atrai river system are Ichamati-Jamuna,Lower Nagor, Nandakuja, Baral and important distributaries are Dhepa, Sib-Bamai and Fakimi.Ichamati-Jamuna-Tulshiganga-Little Jamuna SystemKharkharia and Ichamati-Jamuna River collect runoff from depression near at Syedpur. The flow of Tushiganga meets withIchamati-Jamuna and then flows with the name of Little Jamuna before joining with Atrai River. Lower Karatoya-Nagor Riversystem is the old course of Karatoya River which is now known as Lower Karatoya River, bifurcates from Karatoya River atGobindaganj and then flow southwards to Bogra and finally falls in Bangali at Khanpur in Sirajganj District. Nagor Riverbranches out from Lower Karatoya River at Shibganj and afterwards taking the name of Lower Nagor it traverses throughChalan beel area and meets with Atrai near Singra.The Jamuna and the GangesThe Jamuna and the Ganges are the Eastern and Southern boundaries of North West Region, respectively. The Jamunaseparates the region from North Central Region and the Ganges separates North West region from the South West Region.Most of the river systems of North West Region fall into the Jamuna River; whereas only Mohananda meets with the Ganges.1.3.3 GEOLOGY AND TOPOGRAPHYSirajganj is relatively a plain land area. There is some low land and marsh land in this district. The land level of the area variesfrom 3-4 meter at south to 15-20 meter at north. Most of the area of this district goes under water during the rainy season.About 10% area of the Chalan Beel is located in the Tarash Upazila of this District. Total cultivable land is 179,964 hectares,fallow land 15,702 hectares, forestry 50 hectares. Out of total cultivated area, single cropped land is 19.54%, double crop59.18% and treble crop land shares 21.28%. 74.34% of the cultivated land is under irrigation facilities either by indigenous localpractices or small to medium scale irrigation projects of Bangladesh Water Development Board (BWDB).1.3.4 PEOPLE AND LIVELIHOODNearly one-third of the district’s households are involved in and dependent on weaving. More than 20,000 families in nineupazilas of the district used to earn their livelihood from production, sale and marketing of clay-goods, but now they are in acuteeconomic hardship. Main occupations of this district are -Agriculture 35.49%, agricultural labourer 21.45%, wage labourer5.77%, commerce 11.98%, service 5.49%, handicraft 5.59%, industrial labourer 2.78%, others 11.45%.1.4 OBJECTIVES, SCOPE OF WORKS AND OUTPUTS1.4.1 OBJECTIVESThe objectives of the IWM study component are summarized as following: • Development of a Flood Hazard Model using the integrated Hydrologic and Hydrodynamic Model for Sirajganj District and simulate the model for the period of 30 years (1978 to 2007). • Generation of daily flood depth data for each of monsoon period of 30 years to provide input variables and parameter values for development of a Flood Loss Model.
  • 11. 6 Introduction • Development of methodology to produce raster based (300m X 300m) distributed Flood Vulnerability Index for Siraj- ganj District using the depth-duration defined vulnerability scale. 1.4.2 SCOPE OF THE WORKS • Development of Hydrodynamic Model using data and information of hydro-meteorology, hydro-morphological and geo-physical settings of the of the study area. Hydro-meteorological data /information include rainfall, water level and discharge data; while hydro-morphological and geo-physical data /information comprises of river and khal (small floodplain channel) alignment and their cross-sections, embanked non-embanked condition, floodplain and wa- tershed information, soil-water interaction, farming practices (mainly irrigable, non-irrigable land), etc. MIKE 11 HD (hydrodynamic) coupled with MIKE 11 NAM (rainfall-runoff) modeling software, developed by Danish Hydraulic Insti- tute (DHI), Denmark is used for this hydrodynamic model development. • Development of Flood Hazard Model for the project area using combined modeling approach like integrating MIKE 11 Hydrodynamic and Flood Depth-Duration generating tool MIKE 11 GIS. • Generating raster based (300m X 300m cell size) daily flood depth data /maps using time series model output of hy- drodynamic model for every model grid points (water level and discharge) and topographic information of the study area (DEM, Digital Elevation Model). Flood depth generation tool named as MIKE 11 GIS, also developed by DHI is used for this purpose. • Producing Flood Vulnerability Index Maps using Arc View /ArcGIS software with the spatial and temporal analysis of daily flood depth data generated from developed Flood Hazard Model (integrating model of MIKE 11 and MIKE 11 GIS) during monsoon period over the period of 1978 to 2007. 1.4.3 OUTPUT Outputs or deliverables from this study can be summarized as follows: • A detailed report describing the study undertaken, objectives, methodology, outputs and conclusion. • Time series model grid point output (water level and discharge) for rivers and floodplain channels incorporated in the hydrodynamic model. • Daily flood depth data for Sirajganj District for 30 years (1978 to 2007) during monsoon period. • Flood maps in terms of flood depth and duration in paper and digital format. • Flood vulnerability index maps in terms of flood depth and duration in paper and digital format. • Database achieve, customized GIS and data analysis tools to automate several steps of daily flood depth generation and flood vulnerability index mapping. • Data and output /results sharing with the partner institution of this project, named as CIRM, India. 1.5 LITERATURE REVIEW 1.5.1 BANGLADESH AND ITS HYDROLOGICAL FEATURES Bangladesh is a developing country in South Asia located between 20°34 to 26°38 north latitude and 88°01 to 92°42 east longitude, with an area of 147,570 sq km. It has a population of about 128 million, with a very low per capita Gross National Product (GNP) of US$ 370 (WB, 2000). It has a border on the west, north, and east with India, on the southeast with Myanmar, and the Bay of Bengal is to the south. The floodplains of the three big rivers, together with smaller rivers and streams, cover about 80% of the country (Brammer, 1990A). Therefore a flat, low-lying topography is the most characteristic geomorphologic feature of Bangladesh (see Figure 1-3 and Figure 1-4); 60% of the country is lower than 6 meters above sea level (USAID, 1988:110).
  • 12. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 7Figure 1-3: Topography and major river system of Bangladesh Figure 1-4: Flood regime and type of BangladeshAccordingly the average river gradient in the delta is very low, about 6cm/ km (GOB, 1992A: 3.1). The precipitation isdominated by monsoonal characteristics. June to September are the most important months of the rainy season. There is asignificant increase of total precipitation as well as duration of the rainy season from west to east, with the onset of themonsoon season in the east as early as May. 80% of the rainfall over Bangladesh occurs between June and October (BWDB,1975: 39). According to Ahmad (1989: 23) the average annual rainfall in the catchment area of the Ganges/Padma reaches is1400 mm, of the Brahmaputra/Jamuna 2100 mm and of the Meghna 4000 mm. The hydrographs of the main rivers arecharacterized by monsoonal features as well the peak discharges are reached in July or August, the lowest flows are measuredfrom December to March. The range between high flow and low flow is significant: the average flood flow of the Brahmaputrareaches ten times, of the Ganges even twenty times, the respective dry season flow! Due to the earlier onset of the monsoon inthe east, the discharge hydrograph of the Brahmaputra rises much earlier, and normally reaches its peak one month before theGanges. In spite of the significantly lower catchment area, the Meghna, too, reaches remarkable discharge figures in themonsoon season.The following particular hydrological features result from the unique geographical situation of Bangladesh: • 7-8% of the catchment areas of the Ganges, the Brahmaputra and the Meghna basins are located within Bangla- desh. 62% are in India, 18% in China, 8% in Nepal and 4% in Bhutan (Hughes et al., 1994). • 1,360,000 million m3 of discharge per year originates outside Bangladesh, 85% of which between June and October (Boyce, 1990: 419-509) is contributed by the Brahmaputra, 40% by the Ganges and nearly 10% by the tributaries of the Meghna (BWDB, 1975: 21). 90% of the water carried by the river systems is brought from outside the country (Choudhury, 1989: 235; Boyce, 1990: 412). • The amount of water which annually reaches Bangladesh would form a lake of the size of the country and of 10.3 meters depth (Ahmad, 1989: 26). • Bangladesh has to drain water from an area which is 12 times its size (Miah, 1988:5; Bingham, 1991:31).
  • 13. 8 Introduction • The estimated annual sediment load is 735x106 tons for the Brahmaputra and 450x106 tons for the Ganges (Dewan, 1989:28). The daily suspended sediment discharge of the Brahmaputra at Bahadurabad amounts to 2-3 million tons from July to August (Hossain et al., 1987: 17). • 1/3 of the area of Bangladesh is influenced by the tides in the Bay of Bengal (Hossain et al., 1987:16). All the information and references presented here are already cited in Floods in Bangladesh (Hofer, 1998). 1.5.2 FLOODS IN BANGLADESH According to the discussion presented in Banglapedia, floods are more or less a recurring phenomenon in Bangladesh and often have been within tolerable limits. But occasionally they become devastating. Each year in Bangladesh about 26,000 sq km, 18% of the country is flooded. During severe floods, the affected area may exceed 55% of the total area of the country. In an average year, 844,000 million cubic meter of water flows into the country during the humid period (May to October) through the three main rivers the Ganges, the Brahmaputra-Jamuna and the Meghna. This volume is 95% of the total annual inflow. By comparison only about 187,000 million cubic meter of stream flow is generated by rainfall inside the country during the same period. In Bangladesh, the definition of flood appears differently. During the rainy season when the water flow exceeds the holding capacity of rivers, canals (khals), beels, haors, low-lying areas it inundates the whole area causing damage to crops, homesteads, roads and other properties. In the Bangladesh context there is a relation between inundation and cropping. Floods in Bangladesh can be divided into three categories: (a) monsoon flood - seasonal, increases slowly and decreases slowly, inundates vast areas and causes huge losses to life and property; (b) flash flood - water increases and decreases suddenly, generally happens in the valleys of the hilly areas; and (c) tidal surge flood – due to cyclonic effects in the coastal belt, short duration, height is generally 3m to 6m, blocks inland flood drainage. The combined annual flood wave from the Ganges, Brahmaputra and Meghna rivers passes through a single outlet, the Lower Meghna River. During the high tidal level in the Bay of Bengal, it reduces the slope of water flowing to the bay and consequently reduces the discharge capacity of the Lower Meghna. The effects of these high river water levels extend over most of the country and are the main determinant of the drainage condition and capacity. The discharge from minor rivers is reduced and surface drainage by gravity is limited to land above the prevailing flood level. Flooding caused by this drainage congestion exists nearly everywhere except in the highland and hilly areas in the northern and eastern parts of the country. General Causes of Flooding (cited in Hofer, 1998) In general, heavy monsoonal rainfall simultaneously over the whole Ganges-Brahmaputra-Meghna (GBM) basins is the main causes of flood in Bangladesh as it receives almost all the runoff generated in those basins’ area (Miah, 1988: 5-6). The flood situation is become worsen when high river discharge combined with heavy rainfall inside the country (BWDB, 1975: 6-10; Hossain et al., 1987: 8; Ahmad, 1989: 20-22). Earthquakes and sediment transport are another important issue causing shift or abandoned of active channels and decreasing water carrying capacity of major river due to heavy sedimentation (BWDB. 1975: 6-10; Hossain et al., 1987: 20; Ahmad, 1989: 20-22). In the reality of climate change era, greenhouse effect resulting in higher rainfall, higher temperatures and consequently increased melting of ice in the Himalayas and brings more and more water to the river system of Bangladesh (Matin and Husain, 1989: 6-7). Causes of floods inside Bangladesh (cited in Hofer, 1998) • Flat low-lying topography, low channel gradient (BWDB, 1975: 6.10; Rasid and Paul, 1987: 159; Ahmad, 1989: 20- 22). • Geological depressions (BWDB. 1975: 6-10; Rasid and Paul, 1987: 159; Ahmad, 1989: 20-22; Dewan, 1989: 6-7). • Local heavy rainfall (Brammer, 1987: 19; Hossain et al., 1987: 19. USAID, 1988: 111; Ives, 1991: 37). • High river discharge (Rasid and Paul, 1987: 158; Ahmad, 1989: 20-22). • Overflowing of river beds and irrigation channels (BWDB, 1975: 6-10; Ahmad, 1989: 20-22; Dewan, 1989: 6-7. Hos- sain, 1989: 781).
  • 14. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 9 • Synchronization of high flow of the three major rivers (BWDB, 1975: 6-10; Hossain et al., 1987: 6; Ahmad, 1989: 20- 22). • Backwater effects (BWDB, 1975: 6-10; Hossain et al., 1987: 3-8; Miah, 1988: 80-85; Ahmad, 1989: 20-22). • Soil saturation (Choudhury, 1989: 237). • Old river courses within Bangladesh (Hossain et al., 1987: 17). • Impeded drainage due to high water levels in the rivers (Dewan, 1989: 6-7). • Siltation of the river beds (Hossain et al., 1987: 17; Rashid and Paul, 1987: 159; USAID, 1988: 111; Abbas, 1989: 92; Ahmad 1989: 20-22; Choudhury, 1989: 236; Hossain, 1989: 78). • Changing of river courses (Hossain, 1989: 78). • Riverbank erosion (Hossain, 1989: 78). • Poorly planned embankments for flood protection or roads and railways within the flood plains, upland development works in Bangladesh (Hossain et al., 1987; Miah, 1988: 66-79; Ahmad, 1989: 202-203; Choudhury, 1989: 236; De- wan, 1989: 6-7; Huda, 1989: 122; Pearce, 1991: 40. Hughes et al., 1994: 24). • Breaches of embankments (Hossain et al., 1987: 19). • Water logging due to congestion and failures in drainage systems like pumps or sluice gates (Dewan, 1989: 6-7; Ad- nan, 1991: 1). • Disappearance of wetlands: the floodplains are losing their most skilled environmental managers (Hughes et al., 1994: 19). • Rising of the mean sea level during monsoon period (BWDB, 1975: 6-10: Hossain et al., 1987: 16: Ahmad, 1989: 20- 22). • High tides (BWDB. 1975: 6-10; Hossain et al., 1987: 16: Choudhury, 1989: 236-237; Dewan, 1989: 6-7).Causes outside Bangladesh (cited in Hofer, 1998) • Humid air masses producing orographic rainfall on the slopes of the first Himalayan ridges (Hossain et al., 1987: 7). • Heavy rainfall in the upper catchment of the big rivers (Huda, 1989: 121). • Snowmelt (Choudhury, 1989: 236). • Immense extra-territorial inflows (Hossain et al., 1987: 7; Rasid and Paul, 1987: 158; Ahmad, 1989: 23; GOB, 1992A: 5-11). • Deforestation (Hossain et al.,1987: 17; USAID,1988: 111; Abbas,1989: 91-94; Ahmad, 1989: 26-28; Choudhury, 1989: 236; Dewan, 1989; Haq, 1989: 146; Huda, 1989: 121; Khan, 1989: 152; Latif, 1989: 98; Shahjahan, 1989: 142). • Aggravating the flood situation in Bangladesh through construction of embankments and other structures in India, es- pecially between 1966-1980 (BWDB, 1975:6-10; Ahmad, 1989: 20-22, 28). • Farakka Barrage producing higher flood peak (Hossain et al., 1987: 17; Ahmad, 1989: 28).Chronology of big floods (cited in Banglapedia)1781: Serious flood, which was more pronounced in the western part of Sylhet District. The cattle suffered much from the lossof fodder.1786: Floods in the Meghna wrought havoc to the crops and immense destruction of the villages on the banks. It was followedby a famine, which caused great loss of life at Bakerganj. At Tippera the embankment along the Gumti River gave way. At
  • 15. 10 Introduction Sylhet the parganas were entirely under water, the greater part of the cattle drowned and those surviving were kept on bamboo rafts. 1794: The Gumti embankment burst again, causing much damage around Tippera. 1822: Bakerganj division and Patuakhali subdivision were seriously affected; 39,940 people died and 19,000 cattle perished and properties worth more than 130 million taka were destroyed. Barisal, Bhola and Manpura were severely affected. 1825: Destructive floods occurred at Bakerganj and adjoining regions. There were no important embankments or other protective works against inundation in the district. 1838: Heavy rainfall caused extensive inundation at Rajshahi and a number of other districts. The cattle suffered much from loss of fodder and the people were greatly inconvenienced when driven to seek shelter on high places and when the water subsided cholera broke out in an epidemic form. 1853: Annual inundation was more pronounced than usual in the west of Sylhet District, partly the result of very heavy local rainfall and partly caused by the overflow of the Meghna. 1864: Serious inundation when the embankment was breached and the water of the Ganges flooded the greater part of Rajshahi town. There was much suffering among the people who took shelter with their cattle on the embankment. 1865: Extensive inundation caused by the annual rising of the Ganges flooded Rajshahi District. Excessive rainfall seriously affected Rajshahi town. 1867: Destructive flood also affected Bakerganj. Crop was partially destroyed, but no general distress resulted. 1871: Extensive inundation in Rajshahi and a few other districts. Crops, cattle and valuable properties were damaged. This was the highest flood on record in the district. Cholera broke out in an epidemic form. 1876: Barisal and Patuakhali were severely affected. Meghna overflowed by about 6.71m from the sea level. Galachipa and Bauphal District were damaged seriously. A total of about 215,000 people died. Cholera broke out immediately after flood. 1879: Flooding of the Teesta when the change in the course of the Brahmaputra River began. 1885: Serious floods occurred due to the bursting of an embankment along the Bhagirathi, affected areas of Satkhira subdivision of Khulna District. 1890: Serious flood at Satkhira caused enormous damage to cattle and people. 1900: Due to the bursting of an embankment along the Bhagirathi, Satkhira was affected. 1902: At Sylhet the general level of the river went so high that there was terrible flood. Crops and valuable properties were damaged. 1904: The crops in some parts of Coxs Bazar subdivision and Kutubdia Island were damaged due to an abnormally high tide. This flood was exceptional in severity in Mymensingh. The distress caused on this occasion is probably the nearest parallel to that which resulted from the flooding of the Teesta in 1879, when the change in the course of Brahmaputra began.
  • 16. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 111954: On August 2, Dhaka District went under water. On August 1 flood peak of the Jamuna River at Sirajganj was 14.22m andon August 30 flood peak of the Ganges River at Hardinge Bridge was 14.91m.1955: More than 30% of Dhaka District was flooded. The flood level of the Buriganga exceeded the highest level of 1954.1962: The flood occurred twice, once in July and again in August and September. Many people were affected and crops andvaluable properties were damaged.1966: One of the most serious floods that ever affected Dhaka occurred on 8 June, 1966. The flood level was almost thehighest in the history of Sylhet district too. A storm on the morning of 12 June 1966 made the situation grave. About 25% ofhouses were badly damaged, 39 people died and 10,000 cattle were lost, and about 1,200,000 people were affected. OnSeptember 15 Dhaka city became stagnant due to continuous rainfall for 52 hours, which resulted in pools of water 1.83m deepfor about 12 hours.1968: Severe flood in Sylhet District and about 700,000 people were badly affected.1969: Chittagong District fell in the grip of flood caused by heavy rainfall. Crops and valuable property were damaged.1974: In Mymensingh about 10,360 sq km area was flooded. People and cattle were severely affected and more than 100,000houses were destroyed.1987: Catastrophic flood occurred in July-August. Affected 57,300 sq km (about 40% of the total area of the country) andestimated to be a once in 30-70 year event. Excessive rainfall both inside and outside of the country was the main cause of theflood. The seriously affected regions were on the western side of the Brahmaputra, the area below the confluence of theGanges and the Brahmaputra, considerable areas north of Khulna and finally some areas adjacent to the Meghalaya hills.1988: Catastrophic flood occurred in August-September. Inundated about 82,000 sq km (about 60% of the area) and its returnperiod is estimated to be 50-100 years. Rainfall together with synchronization of very high flows of all the three major rivers ofthe country within only three days aggravated the flood. Dhaka, the capital of Bangladesh, was severely affected. The floodlasted 15 to 20 days.1989: Flooded Sylhet, Sirajganj and Maulvi Bazar and 600,000 people were trapped by water.1993: Severe rains all over the country, thousands of hectares of crops went under water. Twenty-eight districts were flooded.1998: Over two-thirds of the total area of the country was flooded. It compares with the catastrophic flood of 1988 so far as theextent of flooding is concerned. A combination of heavy rainfall within and outside the country, synchronization of peak flows ofthe major rivers and a very strong backwater effect coalesced into a mix that resulted in the worst flood in recorded history. Theflood lasted for more than two months.2000: Five southwestern districts of Bangladesh bordering India were devastated by flood rendering nearly 3 million peoplehomeless. The flood was caused due to the outcome of the failure of small river dykes in West Bengal that were overtopped byexcessive water collected through heavy downpour.2004: Nationwide 36 million people (about 25 percent of the population) across 39 districts were affected by the flood many ofwhich were rendered homeless. Approximately 38 percent of Bangladesh was inundated by the time the waters begun torecede in late August, including 800,000 hectares of cultivable land. As of mid-September, the death toll had reached almost800. During the emergency, access to potable water and sanitation facilities was diminished, as thousands of tube-wells andlatrines were affected. The flood also caused heavy damage to major infrastructures such as roads, bridges, railway,embankment, irrigation system, rural infrastructure
  • 17. 12 Introduction 2007: By August 1, flood condition for both Ganges and Brahmaputra Rivers become severe and the flow of these two rivers synchronized each other. By August 3, the main highway connecting Dhaka to the rest of the country was impassable, many districts were flood-affected and 500,000 people had been marooned. By August 7, an estimated 7.5 million people had fled their homes. By August 8, more than 50,000 people had diarrhea or other waterborne diseases and more than 400,000 people were in temporary shelters. The number of people with flood-related diseases was increasing and about 100,000 people had caught dysentery or diarrhoea. By August 15, five million people were displaced, the estimated death toll was nearly 500, and all six of Bangladeshs divisions were affected. 1.5.3 FLOODING AND DRAINAGE IN THE NORTH WEST REGION As it is discussed in FAP study back in early 1990’s, the North West region (NWR) covers 3.5 million hectares, and has a population of 25 million people. It shows considerable variation, in relation to such aspects as climate, topography and water resources. These variations are reflected in the range of flooding problems existing within it. The region has been divided into fifteen planning units in order to provide comprehensive coverage of these problems. Within each unit the flooding situation was assessed by a combination of field visits, primary data collection and analysis of secondary sources. The principle data used related to agricultural cropping, crop and infrastructure damage due to flooding, and water bodies and fisheries. This was supplemented by analysis of hydrological data and the development and use of a hydrodynamic model covering part of the region. The east and south of the region is bordered by the major rivers, the Brahmaputra and the Ganges. The part of the region along the Brahmaputra suffers particularly severely from flooding caused by breaches in the main Brahmaputra Right Embankment (BRE). This type of flooding is very damaging in the disruption it causes to peoples lives, and the losses to agriculture and infrastructure. Similar problems of a more limited scale occur along the Teesta, Dharla and Dudhkumar River in the north east of the region. In the south, breaches from the Ganges are not a major source of flooding. Within the region, flooding and drainage problems are mainly caused by the drainage patterns of the internal rivers. The majority of these drain to the south east to the Lower Atrai/ Lower Bangali system, and thence to the Brahmaputra through the Hurasagar River outfall. Outfall conditions are often constrained during the monsoon by high levels in the Brahmaputra, and this in turn results in backing up and extensive flooding throughout the Lower Atrai and Lower Bangali River. Flooding over three meters regularly occurs over many parts of the Lower Atrai /Bangali sytem (mainly in Sirajganj District). However, while such flooding constrains agricultural production, it is not a problem in the same way as that caused by breaches from the major rivers since it develops more slowly and does not cause the same amount of social disruption. The upper reaches of the region are steeper than elsewhere and are susceptible mainly to flash flooding. In most cases the floods last only for a few days and do not cause a great deal of damage to crops, though they can do to infrastructure.
  • 18. 2 METHODOLOGY, DATA AND INFORMATION USED2.1 CONCEPT OF FLOOD HAZARD MODELWhile flood modelling is a fairly recent practice, the recent development in computational flood modelling has enabled waterexperts and others to step away from the tried and tested "hold or break" approach and its tendency to promote overlyengineered structures. Various computational flood models have been developed in recent years either one-dimensional (1D)models (flood levels measured in the channel) and two-dimensional (2D) models (flood depth measured for the extent of thefloodplain).On the other hand, GIS and remote sensing, satellite images has widely been used to map and model surface water and floodhazard (Aziz et al. 2003; Werner, 2001; Boyle et al. 1998; Green and Cruise, 1995). Remotely sensed data provides theinstantaneous and synoptic view necessary for the estimation of flood and are therefore widely used in flood mapping andhazard assessment (Dewan et al., 2006). Remote sensing data, however, is predominantly invaluable for developing countriesin development planning (Imhoff et al. 1987). Its application is considered vital for third world countries because it is difficult forgovernment to update their database due to the lack of resources with the traditional ground observation method which is bothcostly and time consuming (Dong et al. 1997). Recently, the integrating capabilities of satellite data with GIS have opened upopportunities for quantitative analysis of hydrological events, such as flood, at all geographic and spatial scales.Conceptually as well as in practice Hazard Model is kind of modeling approach output of which is used to estimate the loss(e.g. loss of income, property to people, households, infrastructures and enterprises and so) due to certain type of hazards. Inthis regard, Flood Hazard Model should have to be in a position so that the annual flooding scenario for a particular area couldbe produced and using those scenario losses due to flood can be estimated. Meanwhile, the present chapter will describe theoverall methodology being applied for the development of a Flood Hazard Model for Sirajganj District. Data and information tobe required for such model development is also presented here for a better understanding of Flood Hazard Modelling.2.2 METHODOLOGY: DEVELOPMENT OF FLOOD HAZARD MODELThe development of Hazard Model comprises of two steps; first one is the development of Hydrologic and Hydrodynamic Riverand Floodplain Model followed by the second one which deals with the generation of daily flood depth (inundation) data/ maps.Calibration of the model considers proper selection, adjustment and application of parameters values both for rainfall-runoff andhydrodynamic model and comparison of model output data with observed data for base year. In present study, monsoon periodof 2007 is considered as base period for model development and calibration. Validation of the model is normally carried out bycomparing the model output data with observed data for different time period without changing any parameter values of base orcalibrated model. Calibration period may be past or next year(s) of calibrated year. Reliability as well as applicability ofdeveloped model thus comes under a thorough analysis of calibration of validation of the model. A well calibrated model mustproduce results which show reasonably good matches with the observed data and upon which confidence of further using ofthose model data is largely relied on.Sirajganj District is located at the western side of the Brahmaputra River through which some of the major rivers in the NorthWest Region of the country are flowing. Sirajganj District is unique in its choice for Flood Hazard Modelling to mitigate thefrequently recurrent flooding problem of the area; as whole for watershed planning. Rather than using single event-steady statemodels for hydrology and hydraulics, the present study utilizes continuous simulation and dynamic routing models like MIKE 11HD (Hydrodynamic) coupled with hydrological model named as MIKE 11 NAM (Rainfall-Runoff). The models were selected forthe following reasons. First, the continuous simulation of the hydrologic model is used to capture the effects of antecedentmoisture on runoff volumes and peaks and to account for non-uniform precipitation distributions over the watersheds. It isdifficult to deal with these factors using the typical design storm approach. Second, the effects of huge upstream incoming flow
  • 19. 14 Methodology to the river system of the project area, flood plain storage, permanent water body and complex backwater effect from Jamuna River have a significant impact on the overall hydrology and flooding scenario of the project area. Thus, an unsteady flow model has been adopted for use in Flood Hazard Modelling. MIKE 11 HD produces continuous flow and stream stage information based on historical precipitation and inflow records estimated /generated at the boundary location of project model domain. From this data, flow and stage duration is readily available for every result saving time step; for instance in this case every 3 hours time step for whole monsoon season. In other way, the continuous simulation approach allows to generate daily flood depth data /maps properly using the floodplain mapping software like MIKE 11 GIS. Hydrologic information, by means of the MIKE 11 NAM (Rainfall-Runoff) Model, developed by DHI Water and Environment, Denmark requires input data such as rainfall, evaporation etc. The Rainfall-Runoff Model is applied to estimate the runoff generated from rainfall occurring in the catchment by NAM method (please see scientific background of NAM Model in Annex-A). NAM is a lumped conceptual model that simulates continuous runoff, base and interflow by simple water balance approach for various land cover types for a continuous period of precipitation record. The model incorporates infiltration, interflow, depressional storage, soil storage, overland flow, evapotranspiration, and changes in antecedent soil moisture in determining rainfall-runoff. Thus NAM hydrological model simulates rainfall-runoff processes occurring at the catchment scale and forms Rainfall-Runoff (RR) module of the MIKE 11 River Modelling system. Hence, the resulting output from MIKE 11 NAM is a continuous time series file (TSF) of runoff for every sub-basin been modelled in response of meteorology (rainfall, evaporation) gauges and soil-moisture content, characteristics of agro-geological land cover covering the whole model domain area. Hydraulic analyses are achieved using MIKE 11 Hydrodynamic module (HD). MIKE 11 HD uses an implicit, finite difference scheme for the computation of unsteady flows in rivers and estuaries (please see scientific background of MIKE 11 HD in Annex-A). The module can describe sub-critical as well as supercritical flow conditions through a numerical scheme which adapts according to the local flow conditions (in time and space). Advanced computational modules are included for description of flow over hydraulic structures, including possibilities to describe structure operation. The formulations can be applied to looped networks and quasi two-dimensional flow simulation on flood plains. Thus MIKE 11 HD model is applied to compute water level, discharge and flow velocity at every model grid points (water level, discharge /velocity point). The MIKE11 HD solves the vertically integrated equations of conservation of energy and momentum called the ‘Saint Venant Equation’ that describe the flow dynamic in a river system. The Model takes into account the river connectivity, river cross-sections, flood plain level and observed discharge at inlet and stage at outlet locations of the modelled river network. The observed discharge and stage applied respectively at the inlet and outlet are called boundary to the model. The runoff generated in the NAM model from rainfall occurring inside the basin is taken care of as inflows into the river system. Historical rainfall and stream flow data along with computer modeling are used to evaluate the flooding scenario of the project area. All models are calibrated with recorded time series water level data at Bangladesh Water Development Board (BWDB) maintained river stage monitoring stations. These gauges are also used both for flood forecasting and model calibration purposes in FFWC (Flood Forecasting and Warning Centre) Super Model. FFWC Supper Model has been in operation for national flood forecasting and warning services during monsoon for the last two decades. Existing FFWC Super Model is used as base for developing dedicated Sirajganj Flood Hazard Model. Hence, based on the Super model and collected detailed information from field a dedicated flood model of Sirajganj has been prepared. At first, the FFWC Super Model is simulated for 30 consecutive years (from 1978 to 2007) for generating the boundaries of the dedicated Sirajganj Flood Model. In order to better representation of physical system governing the flooding scenario, detail floodplain information is incorporated in the dedicated Sirajganj Flood Hazard Model for the project area. Since flood information generates for many model grid points (e.g. water level points) for 30 years of monsoon simulation, accurate recurrence intervals can be developed for them in the model. Generations of flood inundation maps /data are carried out using MIKE 11 GIS. MIKE 11 GIS is an advanced tool for the spatial presentation and analysis of one-dimensional (1D) flood model results for use in the flood management planning process. The MIKE 11 GIS system integrates the MIKE 11 river
  • 20. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 15and floodplain modeling technologies with the spatial analysis capabilities of the ArcView Geographic Information System(GIS). MIKE 11 GIS is ideally suited as a decision support tool for river and floodplain management through its enhancedroutines that provide precise and efficient means of mapping and quantifying flooding impacts on communities, infrastructure,agriculture, fisheries and on the environment.The analysis and outputs developed using MIKE 11 GIS are important inputs for a range of floodplain managementundertakings including flood risk assessment, flood control, flood forecasting, floodplain preservation and restoration, drainagestructure projects and project design specifications. MIKE 11 GIS is based on a bi-directional data exchange between MIKE 11and ArcView. At its most basic level, MIKE 11 GIS requires information from a MIKE 11 model (river network), MIKE 11 floodsimulations and a Digital Elevation Model (DEM). Hence, based on the discrete information from MIKE 11, MIKE 11 GISconstructs a grid based water surface and compares this data with the already available DEM to produce flood depth andduration mapped surfaces. For this project, cell size of grids of DEM as well as flood inundation maps is 300m X 300m. Otheruseful inputs are maps of rivers, infrastructure, property type, land use, satellite imagery and other more project specific data(please see the scientific background of MIKE 11 GIS in Annex-C)2.2.1 TOOLS USED FOR THE STUDYMIKE 11 GIS has been utilized for the spatial presentation and analysis of one-dimensional (1D) flood model results. The MIKE11 GIS system integrates the MIKE 11 river and floodplain modelling technologies with the spatial analysis capabilities of theArcView GIS.MIKE 11MIKE 11, developed by DHI Water & Environment, is a modelling package for the simulation of surface runoff, flow, sedimenttransport and water quality in rivers, floodplains, channels and estuaries. The hydrodynamic module is commonly applied as aflood management tool, simulating the unsteady flow in branched and looped river networks and quasi two-dimensional flow onfloodplains. Once a model is established and calibrated, the impact of changes of artificial or natural origin on flood behaviorcan be quantified and displayed as changes in flood levels and discharges. MIKE 11 is based on an efficient numerical solutionof the complete non-linear St. Venant equations for unidirectional flows along the channel. Flood levels and discharges as afunction of time are calculated at specified points along the branches to describe the passage of flood flows through the modeldomain.MIKE 11 GISMIKE 11 GIS imports simulated water levels and discharges from MIKE 11 result files. Based on the discrete information fromMIKE 11 result file, MIKE 11 GIS constructs a raster grid based water surface and compares this data with topographicinformation such as DEM to produce flood depth and duration mapped surfaces. The outputs of MIKE 11 GIS are compatiblewith ArcView GIS. MIKE 11 GIS produces three types of flood depth data /maps: • Flood depth (inundation) data /map. • Flood depth duration data /map. • Flood comparison mapFlood depth (inundation) data /map show the variation in flood depth over the floodplain, in sharp contrast to the flood-freeareas. Inundation maps provide a clear and concise picture of the depth and the extent of an inundation.Flood depth duration data /map are similar to Inundation maps, but they also take into account the duration of the flooding.Duration map indicates in each point, for how long the area has been inundated.Flood comparison map shows the difference between two flood depth maps.
  • 21. 16 Methodology 2.2.2 SELECTION OF EVENTS The objective of the current investigation is to produce index base flood insurance products for Sirajganj District, statistical and analytical analysis of floods in these areas for the last 30 years dating from 1978 to 2007 are carried out. As for the statistical analysis for a particular event, at least 30 samples are required, therefore flood depths for each of the raster grid (300m X 300m) of the study area for monsoon period (June to October, 153 days) for the last 30 years are considered to be most omportant input data. As such, flood depth data for 30 years have been generated using the hydrodynamic model results. However, most common practice of categorizing flooding events into normal or average (flood of 1 in 2.3 years return periods), moderate flood (1in 5 to 10 year return period), sever flood (1 in 25-49 years return period) and extremely sever flood (1 in 50- 100 year return period flood) is use of statistical analysis of water level, discharge or flood depth data of important location(s). The present study, on the other hand, makes an attempt to use a statistical analysis of every 300m X 300m grids covering the whole study area and would produce probability of certain types of flooding to be occurred for each of the grid points considering flood depth and duration. 2.2.3 GENERATION OF FLOOD MAPS In the next step, different types of flood maps would be prepared for selected different flooding scenarios for the selected areas. Three types of flood maps have been prepared for each of the flood prone regions and these are: • Flood depth maps for normal and extreme flooding scenarios. • Flood depth duration map. • Flood depth maps for calculating duration of inundation. 2.3 METHODOLOGY: FLOOD VULNERABILITY INDEX 2.3.1 CRITERIA FOR FLOOD VULNERABILITY For producing any index based flood insurance products for a given region, ranking or scaling of flood vulnerability for different flood scenarios should have to be carried out. Criteria for flood vulnerability have been introduced both in terms of flood depth and flood duration. The accepted WARPO (Water Resources Planning Organization) classification in terms of flood depth has been used for agricultural lands (Table 2-1). For households, flood depth more than 50 cm has been considered as flooding. Flood depths and duration for any given flood event exceeding 30 cm and 3 days respectively have been taken into account to address the vulnerability regarding the agricultural loss. Thus the inundations for a period of 3 days or longer with flood depths higher than 30 cm threshold value have been taken into consideration in the calculation of flood vulnerability. Vulnerability Index level 1 both for depth (31 to 60 cm) and duration (4 to 10 days) shown in Table 2 and 3 will signify the agricultural loss, while Vulnerability Index higher than 1 will refer the loss in agriculture, homestead, and others. However, loss depends on landuse patterns also; the presented or proposed Indices only take into account the depth and duration of flood. Therefore, the indices are not fully object oriented; rather they represent the flooding scenario in terms of different combination of flood depth and duration for the project area. Table 2-1: Agricultural land classification in terms of flood depth Land classification Depth of flooding (meter) F0 0.01 – 0.30 F1 0.30 – 0.90 F2 0.9 – 1.80 F3 1.80 – 3.60 F4 > 3.60
  • 22. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 17 Vulnerability Index (depth of flooding) To take account the agricultural land classification shown in Table 2-1 into the Vulnerability Indexing, new scales have been proposed in this study which is different from the scale used in one of IWM’s previous study (IWM, 2007). Vulnerability Index based on depth of flooding would be calculated using the scale shown in Table 2-2 and Table 2-3.Table 2-2: Vulnerability scale for depth of flooding Table 2-3: Vulnerability scale for duration of flooding Depth (cm) Scale Duration (Days) Scale 0 – 30 0 0–3 0 31 – 90 1 4 – 14 1 91 – 180 2 15 – 30 2 181 – 360 3 31 – 45 3 361 – 560 4 46 – 60 4 561 – 760 5 61 – 90 5 > 761 6 > 91 6 Vulnerability Index (duration of flooding) The Vulnerability Index has also been derived based on duration of flooding. The scales used to calculate Vulnerability Index as regards duration of flooding have been provided below in Table 2-3. With aim of this certain criteria have been devised to rank each and every grid (300m X 300m) depending on its vulnerability to flooding. Methodologies have been developed to calculate Vulnerability Index based on both duration and depth of flooding. Finally, combined vulnerability index has been calculated by adding the Vulnerability Index for duration of flooding and Vulnerability Index for depth of flooding. Here a clear distinction between the agricultural land classification done by WARPO and the depth-duration ranges considered for indexing flood vulnerability should kept in mind. However, overlaying the flood vulnerability maps on agricultural land type classified map based on criteria shown in Table 2-1 and other land use pattern areas (homestead, city, agricultural, non-agricultural land, perennial or terrestrial water body (beel /haor), etc.), overall hazard status or indices have been figured out. Vulnerability Index (combined) The combined Vulnerability Index of each land type (agricultural or land use type) would be calculated by taking the average value of two Vulnerability Indices (for duration and depth of flooding). Thus equal weights have been assigned on both the Vulnerability Indices during the calculation of combined vulnerability. Now the methodology is going to be presented here which has been adopted in this study to produce Flood Vulnerability Index Map for a particular year as well as probabilistic Vulnerability Index Map considering 30 sets of yearly Vulnerability Index Maps.
  • 23. 18 Methodology 2.3.2 YEARLY INDEX MAP There are as many as 152 daily Flood Maps are produced for every monsoon (June 01 to Oct 30) over the period of 1978 to 2007. At first step, these 152 Flood Maps are re-classified to Depth Scale Maps in which flood depths are changed to scale 0 to 6 depending on the ranges of depth assigned for each scale. The vulnerability scale for depth of flooding is shown in Table 2-2. Then a recurrence analysis is done for each depth scale; like how many days a particular cell is experienced to a particular depth scale out of 152 days. This recurrence analysis actually gives the duration of a particular depth scale for a certain cell. Thus it produces 6 Duration Maps, each of which corresponds to particular Depth Scale. There remains a limitation regarding the duration which has been found after recurrence analysis. It does not give any idea of how many days out of total days found are consecutive. Nonetheless, uncertainty regarding consecutive or non-consecutive duration for a particular depth scale is ignored here. It just accounts the total number of days irrespective of whether it is in early monsoon, mid of the monsoon or late monsoon. The next step is to classify these 6 Duration Maps for 6 Depth Scale according to the vulnerability scale for duration of flooding shown in Table 2-3. It has now produces 6 Depth- Duration Scale Maps in which for each depth scale (0 to 6), duration scales (0 to 6) are attained. In other words, for unique depth scale duration scale are attained for each cell. The combined Vulnerability Index is calculated by taking the average value of two Vulnerability Indices (for duration and depth of flooding). Meanwhile, 6 sets of Vulnerability Figure 2-1: Flow diagram showing methodology to produce Vulnerability Index Map us- ing daily flood maps for 152 days of monsoon period. Index maps are produced with a combination of different depth and duration scales. Returning the maximum value of combined 6 Vulnerability Index Maps, final Vulnerability Index Map has been found. This is the Vulnerability Index Map been produced for a particular year and can be called as Yearly Vulnerability Index Map. Now, the Vulnerability Index Maps which have been generated under this study, however, only represent the degree of flooding scenario for a particular year in which combined effect of Depth and Duration are only summed up by averaging the two corresponding scales. That’s why the combined Vulnerability Index considering both Depth and Duration scale can be found for different matrices of Depth and Duration Index. For instance, for Vulnerability Index 2, it can be formed either for Depth Scale 1, Duration Scale 3; or Depth Scale 2, Duration Scale 2 and Depth Scale 3, Duration Scale 1. Whether the impacts in terms of loss regarding these various sets of Depth-Duration Index are same or not; how much it is varied from each other that might be an interesting research to be carried out in future. But at this moment, all three sets of Depth-Duration Index are assigned as 2. This is the first approach being taken into account for finding combined Vulnerability Index. The second approach is to
  • 24. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 19reclassify the ranges of combined Index into a certain Index value. In this case, higher value either for Depth Scale or DurationScale is given more weightage for setting a combined Index. Table 2-4 show the ranges of averaged or combined scale whichfinally are come up with a single value of Vulnerability Index.Table 2-4: Unique Index Assigned for Combined or Averaged Depth-Duration Index Combined or Averaged Unique Index Depth-Duration Index Assigned 0 – 0.49 0 0.5 – 1.49 1 1.5 – 2.49 2 2.5 – 3.49 2 3.5 – 4.49 4 4.5 – 5.49 5 5.5 – 6 62.3.3 PROBABILISTIC VULNERABILITY INDEX MAPAfter completing the generation of Yearly Vulnerability Index Maps for 30 years where index are assigned as 0, 1, 2 to 6, againa recurrence analysis for each and every index are performed for those maps. Like how many years out of 30 years everyraster grid or cell covering the whole study area is found of a particular index value. And then analysis is limited to twoprobability of flooding scenario; 75% and 50% probability. 75% Probabilistic Vulnerability Index Map show the Index for eachcell which has been found at least 22 years out of 30 years. The same is for 50% Probabilistic Index Map where it accounts 15years out of total 30 years. Thus two Probabilistic Vulnerability Index Maps are produced. Recurrence analysis has been doneusing spatial analyst utility of ESRI ArcGIS.2.4 DATA AND INFORMATION USEDThe basic data required for the development of the Hydrodynamic Model has described as following:2.4.1 FOR RAINFALL-RUNOFF MODEL DEVELOPMENT • Catchment information (area, physical characteristics, different surface, sub-surface, ground water, irrigation parame- ter values); • Time series rainfall, actual evaporation (evapotranspiration, ET0), irrigation abstraction data.2.4.2 FOR HYDRODYNAMIC MODEL DEVELOPMENT • Surveyed cross-section data for main rivers as well floodplain channels; • Floodplain information (physical features, flood cell, area-elevation data, etc.); • Information on river dikes or embankment, control structures, culverts and bridges; • Time series measured or estimated boundary data (discharge for upstream boundary and water level for downstream boundary); • Output of Rainfall-Runoff Model (time series catchment runoff data) which are distributed along the river and flood- plain channels and also in some cases as a point sources for certain location of a main model river; • Roughness and vegetation characteristics of the river and floodplain system;
  • 25. 20 Methodology • Measured water level data at the regular measurement stations inside the project area to calibrate the model. 2.4.3 FOR FLOOD MAP GENERATION • Digital Elevation Model (DEM) of the project area. DEM of smaller resolution (e.g. 50m X 50 m or 100m X 100m) would be preferable; • Satellite flood images for the verification of flood water extension or spreading over the floodplain area as well as on other land type during high flood scenario; • Measured water level data at the regular and /or newly installed measurement points on the flood-plain area to cali- brate the flood map (flood depth and duration verification).
  • 26. 3 DEVELOPMENT OF FLOOD HAZARD MODEL3.1 INTRODUCTIONAs it has been mentioned before, the present study aims to produce daily flood inundation maps/ data for Sirajganj Districtduring flood season (June to October) over the period of 1978 to 2007. As such, a dedicated one-dimensional hydrodynamicmodel for the project area is developed. The developed dedicated one-dimensional model incorporates more and detailinformation on physical settings of the hydrology (rainfall, evaporation, incoming and outgoing discharge to the system) andhydrometric network (river, floodplain, water and other types of infrastructures, etc.) of selected model domain area.Existing FFWC Super Model is taken as the base model for dedicated Sirajganj Flood Hazard Model development. Basically,the dedicated model is a cut model of Super Model, therefore the hydrological model setup (catchment size and characteristics,rainfall and evapotranspiration distribution, land cover and soil characteristics, soil moisture content and abstraction, etc.) aswell as the basic hydrodynamic model setup remain same. However, flood propagation route through floodplain and itsconnectivity /disconnectivity to the main channels, perennial or non perennial water storage, and flood cells are included in thededicated model to represent the geo-physical settings of river-floodplain interaction and flooding scenario of the project in abetter way. Boundary data for cut or dedicated model are generated from FFWC Super model results simulated for 30consecutive years (from 1978 to 2007). The present chapter presents a description of existing Super Model setup first. Then itdescribes the activities done regarding the development of Sirajganj dedicated or cut model. To note that, dedicated or cutmodel is mentioned as Sirajganj Flood Hazard Model afterwards.
  • 27. 22 Model Development Figure 3-1: River network of FFWC Super Model 3.2 EXISTING SUPER MODEL The Flood Forecasting and Warning Center (FFWC) of Bangladesh Water Development Board (BWDB) operates a real time numerical model based on one dimensional fully hydrodynamic model (MIKE 11 HD) incorporating all major rivers and floodplains of the country. The hydrodynamic model is linked to a lumped conceptual rainfall-runoff model (MIKE 11 RR) which generates inflows from catchments within the country. FFWC usually collects real time hydro-meteorological data and simulate the numerical model routinely throughout the monsoon season FFWC also takes account of the satellite images & information as well as rainfall and water level data from Ganges-Brahmaputra-Meghna (GBM) basins outside the country for boundary estimation. The model covers most of the flood prone areas of the country and is now used to provide 24, 48 & 72 hours forecasts to a total of 69 stations. The flood warning is developed and disseminated to a wide range of user including Government and non-government sectors. The river network of FFWC Model is shown in Figure 4. The FFWC super model is updated based on topographic and infrastructure information of 2007 or earlier. The present status of the super model has been described in the following sections. The FFWC super model is updated based on topographic and infrastructure information of 2007 or earlier. The present status of the super model has been described in the following sections. 3.2.1 HYDRO-METEOROLOGICAL DATA INPUT For real time flood forecasting purposes hydro-meteorological data is required for inside as well as outside the country. FFWC collects data from three sources: BWDB gauge data, additional gauge data and remote sensing data which are incorporated in the FFWC super model for routine operation of flood forecasting. BWDB gauge data includes 82 (presently 73) water level and 58 rainfall stations (presently 56) data which are measured manually and transmitted by either radio or mobile phone to FFWC daily morning. Additional data includes Indian and Nepalese data through the Joint River Commission (JRC), Bangladesh. The JRC provides water level data at 13 stations within India and 4 stations within Nepal (IWM, 2009, SMReport). Remote Sensing Data includes Satellite images and RADAR images. Satellite data are captured through internet from a variety of secondary sources. Rainfall radar images are provided by BMD via microwave link to FFWC from each of the country’s radar sites at Dhaka, Khepupara, Cox’s Bazar and Rangpur.
  • 28. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 23Topographic Data Topographic data used in the model are river bathymetry, infrastructure (roads, bridges, land fills, etc), interventions (embankments, control structures, etc) and land terrain. Bathymetry data used in the super model is mainly of 2007 or older except some important rivers in the southwest region where river bathymetries of 1998 are incorporated. Other topographic information is also of 1998 or earlier (IWM, 2009). 3.2.2 RAINFALL-RUNOFF MODEL The rainfall runoff model of the FFWC Super Model comprises 157 sub-catchments having a total area of 122437 sq. km. All properties of the sub-catchments are used unchanged and same as that included in the existing six regional models. The Rainfall Runoff model receives precipitation from 40 stations within the country where real time measurements are available. Evaporation is taken as 4 mm/day throughout the season. Abstraction data processed by WARPO based on NMIDP census is usually used in the NAM model. 3.2.3 HYDRODYNAMIC MODEL The hydrodynamic model component of the super model includes 217 regular rivers/khals having a total length of 10235 km. The model also includes floodplain link channels of substantial length for representing floodplain flow in the flood-prone areas. Bathymetries of most of theFigure 3-2: The updated and non updated river reaches in Super rivers are as old as 1998 or earlier. Bathymetries ofModel floodplain routing channels are taken from national land terrain model developed in FAP 19. Geometries of linkchannels are computed based on topography, infrastructure and intervention. The model comprises 72 boundaries out of which15 points are water level boundary and the rest are inflow boundary. Out of 15 water level boundaries, 8 are upstreamboundary and 7 are downstream boundary. Four out of 8 upstream water level boundaries are located on major rivers whichare very important for model performance. Out of 7 downstream water level boundaries, 5 are tidal where forecasted waterlevels are generated using tidal parameters of each station and tidal chart of BIWTA.3.2.4 BOUNDARY GENERATIONThe simulation of the flood forecasting model needs forecasted rainfall and water level or flows at the boundary locations forgenerating flood forecasts. In FFWC, the forecaster relies on satellite and radar imagery and qualitative forecast of both BMDand IMD for rainfall estimate. Tidal water levels at the downstream boundaries of the model are generated from published tidetable data and adjusted based on an analysis of the previous 24 hours of measurements. Upstream water level boundaries aremuch more difficult to predict, and represent the main weakness of present flood forecasting model. Water level estimates arerequired at 17 boundary locations at the periphery of the country, of which the most important are the Ganges andBrahmaputra, as these have a widespread affect on flood levels within the country.The boundary estimates of Brahmaputra are aided to a degree by water level measurements upstream made available throughthe JRC. The furthest upstream station for which information is received is Pandu, located approximately 24 hours (in terms of
  • 29. 24 Model Development wave travel time) upstream of model boundary at Noonkhawa. Using the limited data made available through the JRC, FFWC have developed correlations between the measured Pandu level and the level at Noonkhawa 24 hours later. This correlation is only possible when the Pandu data is supplied (when water level is above danger level). It is not possible to produce correlations for 48 or 72 hour water level estimates as these would require gauge data from India further upstream. Hence these estimates are still based on experience and judgment of the forecaster. Water level estimates for the Ganges are based on measurements at Farakka, located just 32 km upstream of the model boundary at Pankha. Due to close proximity of this gauge, the Farakka data is of limited use, as the wave travel time is only approximately 5 hours. Consequently, the estimate of water level at Pankha also takes into account observed and forecasted rainfall data in the Ganges catchment. Water level estimation for the remaining 15 minor inflow boundary locations are based mainly on experience, available Indian data and an assessment of forecast rainfall in the particular catchment. 3.2.5 PERFORMANCE OF THE SUPER MODEL The hydrodynamic model has been validated against water level and discharge using the data for the period of 2007. Similar to calibration, overall, comparison of discharge and water levels at many stations show fairly good agreement. Model generated water level cannot follow the measured data at few stations. The present model is fairly good for flood forecasting in North- West, North-East, North-Central and South-West part of Bangladesh. Model performance has also been analyzed at monitoring stations of FFWC in terms of Co-efficient of Determination (R2), Nash-Sutcliffe efficiency (NSE) and Mean Squared Error (MSE). Good performance have been achieved at around 30 stations where as average performance is observed at about 20 stations during monsoon in 2007-08 hydrological year. Performance at rest of the monitoring stations could not be analyzed due to unavailability of measured data. The performance category scales: good, average, below average, poor and very poor have been described in Appendix-B including scientific background of three performance indicator R2, NSE and MSE. The performance of different stations has been shown in Figure 3-3. Sample comparison plots of simulated water level of Jamuna, Ganges and Meghna have been presented in Figure 7 at Sirajganj, Rajshahi, and Bhairab Bazar respectively.
  • 30. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 25Figure 3-3: Evaluation of FFWC Model performance at Figure 3-4: Comparison of simulated water level of Brahmaputra at Siraj-different stations ganj (top) Ganges at Rajshahi (middle) and and Meghna at Bhairab Bazar (bottom)3.3 SIRAJGANJ FLOOD HAZARD MODELThe base of Sirajganj Flood Hazard Model is the FFWC Super Model. This dedicated model is a cut model of Super Model,therefore the hydrological model setup (catchment size and characteristics, rainfall and evapotranspiration distribution, landcover and soil characteristics, soil moisture content and abstraction, etc.) as well as the basic hydrodynamic model setupremain same. However, to incorporate the detail geo-physical settings of the Sirajganj District including the flood propagationroute through the floodplain and its connectivity /disconnectivity to the main channel, perennial or non perennial water storage,detailed topographic information have been incorporated in the dedicated model. To do so, identification of floodplain channelthat were not in FFWC Super Model setup, extraction or generation of cross-section data for those floodplain channels andmost importantly re-distribution of catchment connection to those floodplain channels have been carried out. The followingsections of this chapter will describe the overall activities regarding this dedicated model development, its re-calibration andvalidation been achieved so far and the model performance in terms of comparability between simulating river and floodplainwater level and available observed data.3.3.1 INCORPORATION OF FLOODPLAIN CHANNEL & CROSS-SECTIONThe base hydrodynamic model setup for Flood Hazard Model for Sirajganj District includes regular rivers /khals, few floodplainrouting channel & link channel as it has been already in FFWC Super Model river network. Additional floodplain channels, theirconnectivity and disconnectivity to the major rivers, perennial or non perennial water storage, and flood cells are incorporated inthe customized Hazard Model setup. The idea of such customization is to represent physical settings of hydrological and
  • 31. 26 Model Development hydrometric features of Sirajganj district in a better way. Figure 3-5 shows the river and floodplain network for Sirajganj Flood Hazard Model. Identification of floodplain channels, water storage area or flood cells was the big challenging part at this stage. Ideally a detail field survey comprising floodplain survey is required for such identification. But due to time and resource constraint this type of detail floodplain survey was not done. However, the recent cross-sections of the significant flood routes are incorporated in the customized dedicated model. On the other hand, identification as well as digitization of floodplain channels, flood storage area is done using the available most recent satellite and google earth images (see Figure 3-6). The GIS based satellite and google earth image give a detail view of the remotely sensed topographic features, vegetation condition, land use pattern and homestead. On the basis of those available images, floodplain areas adjacent to any small channels /link channels are identified and added to the existing hydrodynamic river network setup. The cross-sections of those additional channels are generated from DEM (Digital Elevation Model) having resolution of 300 meter. Land coverage, homesteads, depression area adjacent to those floodplain channels are also identified from satellite images and cross-sections are Figure 3-5: Sirajganj Flood Hazard Model river network generated for comparatively low land depressed areas. Figure 3-6: Floodplain channels incorporated in the dedicated Sirajganj Model
  • 32. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 27Well representation of flood water propagation, storage or flood cells involved in water physical system of the area is requiredto be incorporated in the model so that it can produce as many as simulated data in extended model grid points covering thewhole project area (see Figure 3-7 and Figure 3-8). It also enables to produce local flooding scenario either occurred from overflow of peripheral main river system or due to local rainfallFigure 3-7: Existing river network in Super Model covering the project area (left) and customized river and floodplain network in Si-rajganj Flood Hazard Model (right).
  • 33. 28 Model Development Figure 3-8: Water level grid (model h-points) of existing Super Model setup (left) and increased model grid points for customized Sirajganj Flood Hazard Model (right) 3.3.2 WATERSHED /CATCHMENT RUNOFF DISTRIBUTION TO RIVER NETWORK Catchment delineation is one of the important works before computation of runoff generated from rainfall. It is done on the basis of existing topographic map of SoB (Survey of Bangladesh), existing DEM and Satellite Image. Super model network is used for this project with addition of some channels digitized on the basis of topographic map and existing satellite image and it is described in previous section. The runoff generated from NAM module is connected with the HD module by distributing catchment runoff to the rivers and floodplain channels. Runoff distribution is done by connecting a particular catchment to river(s) and floodplain(s) which are found to be contributed from that particular catchment. Now as the additional channels are added to the river network of the customized model setup, re-distribution of the catchment runoff contribution is required to be carried out. There are two options that can be applied for catchment runoff distribution in hydrodynamic model. One is to re-delineate the sub-catchments for the newly developed river network. Another is to re-distribute the runoff to the rivers with additional included channels. The second option is adopted for this present model development. Though the catchments are not re-delineated (e.g. same catchments are used as they are in Super Model Rainfall-Runoff Model setup), re-distribution of catchment runoff is done in hydrodynamic setup (see Table A-2 in Annex-A) on the basis of judgment against DEM, channel networks, satellite Images and above all close observation of field condition. In newly developed network, the additional channel is connected with the main river. Ultimately these channels receive water from adjacent floodplain area in early and late monsoon, particularly when the main river stage remains under the floodplain level. During the period of high and continuous rainfall with higher incoming flow from upstream, major rivers are experienced of bankfull stage or even water spills to the surrounding floodplain area. In such case, secondary or tertiary channel and also the floodplain channels receive water from those main channels with a continuous contribution of catchment runoff. In other words, accumulation of water in floodplain areas is happened in both ways; spilled and sometimes embankment breached water comes from major river and from catchment runoff. As par re-distribution of catchments area to the overall newly developed network is concerned, judgment is applied based on land use pattern and existing human interventions explored from satellite
  • 34. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 29image and also on existing topographic map, fields observation, etc. Finally within a particular sub-catchment, catchment areais re-distributed to adopt catchment influence for additional channel(s) by means of fractionalize the total area for that particularcatchment which lowering the influenced area for main river(s). As a whole, the areal sum of all fractionalized catchment areafor a single catchment is maintained same as it is distributed mainly to major river(s) in coarse model setup (like in Super Modelsetup). The following figures (Figure 3-9) depicts the approach been applied for catchment runoff re-distribution.Figure 3-9: Thematic presentation of catchment runoff distribution approach. Main channel and corresponding catchment area (leftfigure), main channel including additional channels (middle figure) and re-distribution of catchment area to main and additionalchannels (right figure)3.3.3 BOUNDARY GENERATION FOR SIRAJGANJ FLOOD HAZARD MODELBoundary generation is very important part of any model development. Without reliable or realistic boundary data observation/generation /estimation both at upstream and downstream, one cannot expect the model would give good simulation data. Infact, quality and /or realistic boundary data dictate the model largely on how good calibration and validation of the model can beachieved. The dedicated Sirajganj Model is a cut model of FFWC Super Model with necessary customization, detailing andadaptation according to the project purposes. Both upstream and downstream boundaries of this dedicated model are takenfrom the simulated data of FFWC Super Model. The FFWC Super Model is reasonably well calibrated model for most of themajor rivers system covered in the model setup (IWM, 2009), in North-West Region.
  • 35. 30 Model Development The dedicated model of project area, here it is referred as Sirajganj Flood Hazard Model, a thorough attempt has been taken to calibrate and validate the model. The calibration and validation of the newly developed model is described in chapter following this one. The simulation of flood Hazard model needs water level or discharge data at the boundary locations to simulate continuously. To get boundary data for Sirajganj Flood Hazard Model, Super Model has been simulated first for 30 years of simulation period (year 1978- 2007) and extracted boundary data from those simulation results. It might have a relevance to give a graphical and tabular description on the upstream and dowunstream boundary of North-West Region of Bangladesh as these data has already been shared with CIRM, India. Figure 13 shows the upstream boundary location for North-West Region while Table 4 shows the data type and availability for those stations. Figure 3-10: Boundary location of North West Region of Super Model Out of total 34 boundary positions of Sirajganj Hazard Model, discharge data for 25 locations and water level data for 9 locations have been extracted from 30 years (period 1978 – 2007) simulated results of Super Model. Ideally discharge data is assigned at upstream boundary of hydrodynamic model, while water level data at downstream boundary. This convention is maintained here also. Figure 3-10 and Table 3-1 show the position of upstream and downstream boundary used in present Hazard Model setup. Table 3-1: Boundary data type and availability status for Northwest Region of Super Model River /Khal Name Boundary Boundary Type Data Availability (Year to Year) Remarks Station Name WL Q (see below of table) Jamuna / Brahma- Noonkhawa Rated Discharge 1962 - 2008 1962 - 2008 Remark No. 1 putra Dudhkumar Poteswari Rated Discharge 1962 - 2008 1968 - 2008 - Dharla Taluk Simul- Rated Discharge 1965 - 2008 1968 - 2008 - bari Teesta Kaunia Rated Discharge 1945 - 2008 1959 - 2007 - Ghaghot Islampur Rated Discharge 1946 - 2008 1964 - 1980 Remark No. 2 Atrai Mohadevpur Rated Discharge 1959 - 2008 1973 - 2008 Mohananda Mokarrampur Rated Discharge 1950 - 2008 1966 - 2008 Remark No. 3 Ganges Godagari Rated Discharge 1910 - 2008 1934 - 2008 Remark No. 4 Gorai Gorai RB Rated Discharge 1946 - 2008 1964 - 2008 CJamuneswari Boragari Rated Discharge 1960 - 2008 - Remark No. 5 Akhira, Kharkharia Close Boundary - - -
  • 36. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 31 Ich-Jamuna Monohorganga Ghaelgulhari Rasulpur Kamargaon Khari Boro Khari Joal Khari Bulai Khal B-Chikly Ghaogot-At Jamuna / Brahma- Aricha Measured WL 1964 - 2008 1964 - 2008 - putraRemark No. 1: Generated (Rated) discharge for Bahadurabad is used with 5% reduction plus 6 hours lead time.Remark No. 2: Discharge for Jafragang station is available for mentioned period (see Q availability column) which is 20 km upstream of Is-lampur Station. On the other hand, water level for Islampur station is available for mentioned period (see WL availability column). Therefore,co-related discharge for Islampur Station could be generated from the available discharge data at Jafraganj station.Remark No. 3: Discharge data for Rohanpur station is available for mentioned period (see Q availability column), which is 4 km upstream ofMokarrampur station. Therefore, co-related discharge data for Mokarrampur station could be generated from the available discharge data atRohanpur station.Remark No. 4: Generated (Rated) discharge for Hardinge Bridge is used with 5% reduction plus 2.5 hours lead time.Remark No. 5: Rated discharge for 2006 is available. Therefore if it is decided, the same rating equation could be used for generating dis-charge from the available water level for mentioned period.Table 3-2: Boundary position of Sirajganj Flood Hazard Model with river name and chainage corresponds to FFWC Super Modelgrid points used Boundary Type River Name Chainage (m) Boundary Type River Name Chainage (m) Inflow Futikjani 2000 Inflow Ichamati-nw-LFP6 0 Inflow Louhajang 6500 Inflow Ichamati-nw-LFP4 0 Inflow Pungli_RB 5000 Inflow Baral-RF1 20200 Inflow Kara_R095 10000 Inflow Baral-RF2 11300 Inflow Lkaratoya 400 Inflow Bangali-LFP9 0 Inflow Lnagor 2500 Inflow Bangali-LFP8 0 Inflow Ljam_L022 9800 Inflow Baral-RF4 2360 Inflow Atrai 57144 Inflow Ichamati-NW-LFP5 0 Inflow Polc_Art 25600 Inflow Ichamati-NW-LFP2 0 Inflow Sib-barnai 120700 Water Level Dhaleswari 20700 Inflow Godai 7250 Water Level Dhales_RB 20000 Inflow Narod 29700 Water Level Ghior_K 4100 Inflow Nandakuja 57550 Water Level Louhajang_RB 10000 Inflow Bangali 89080 Water Level Pungli 7100 Inflow Chatal_S 11651 Water Level Dhales_L009 3450 Inflow Jamuna 135375 Water Level Jamuna 219200 Inflow Louha_R009 1140 Water Level Elangjani 8000 Inflow Dhales_R036 5625 Water Level Elangjani_RB 5500 Inflow Bangali-LFP7 0
  • 37. 32 Model Development 3.3.4 CALIBRATION AND VALIDATION OF SIRAJGANJ MODEL The hydrodynamic model has been calibrated first against the water level data recorded at BWDB regular monitoring stations for monsoon 2007 period. After successful calibration of the model, validation is done for year 2004 and 1998 flood years without changing any parameters’ value or hydrometric data (e.g. cross-section, floodplain topography, etc.). The point should be kept in mind that no Brahmaputra Right Embankment (BRE) breach condition is considered either in the base year (2007) or in any other flooding scenario from 1978 to 2007 at first stage. Though in later stage, three different model setups for past three major floods like flood in 1998, 2004 and 2007 have been developed incorporating the required information of BRE breach occurred in those years. Reporting on those three separate model development is given in Section 3.3. Figure 3-11: Water level comparison points for calibration and validation of the model Nevertheless, calibration and validation of model for the respective year against available water level data at monitoring locations in and near outside of the study area (see Figure 3-11) show fairly good resemble. Other than graphical comparison, some statistical analyses usually applied for evaluation of model performance have been also done. This statistical analysis includes calculating Maximum Positive Error, Mean Absolute Error (MAE), Peak Error, Mean Square Error (MSE), Root Mean Square Error (RMSE), Co-relation Co-efficient (R2), Nash–Sutcliffe Efficiency Co-efficient (NSE) between observed and simulated water level data. In addition, using a combined scale calculated from R2, NSE and MSE for each and every station, performance of the model has been categorized as good, average, below average, poor and very poor. The performance category scales: good, average, below average, poor and very poor have been described in Appendix-B including scientific background of three performance indicator R2, NSE and MSE. The performance of different stations has been shown in Figure 3-12 to Figure 3-28 and Table 3-3 to Table 3-4. Calibration for all points shown in Figure 3-11 could not be possible due to non-availability of measured data. This has been the case for other two comparison years also. As such, comparisons are shown here only for those stations only where water level data are available for particular year. Table 3-3: Statistical parameter values for model performance (Year 2007) Parameters Values for different stations Ullapara Sirajganj Chanchakair Baral Bhaghabari Max. Positive Error 0.35 0.51 1.33 0.64 0.91 Max. Negative Error -1.99 -0.47 -0.99 -0.59 -0.66 Peak Observed Value 13.66 14.95 11.57 11.98 11.58 Peak Modelled Value 12.39 15.36 12.52 12.34 12.25 Peak Error 1.27 -0.41 -0.95 -0.36 -0.67
  • 38. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 33 Mean Absoulute Error (MAE) 0.94 0.19 0.27 0.21 0.38 Mean Square Error (MSE) 1040.73 1.83 40.92 3.99 28.70 Root Mean Square Error 32.26 1.35 6.40 2.00 5.36 (RMSE) Nash–Sutcliffe Efficiency (NSE) 0.47 0.96 1.00 0.96 0.89 Correlation Co-efficient (R2) 0.91 0.99 0.69 0.96 0.91Table 3-4: Statistical parameter values for model performance (Year 2004). Parameters Values for different stations Ullapara Sirajganj Gumani Chanchakair Baral Atrai Baghabari RB Max. Positive Error 0.41 1.02 2.74 1.22 0.78 1.71 0.94 Max. Negative Error -1.51 -0.69 0.00 -0.94 -1.33 -0.79 -0.46 Peak Observed Value 13.06 14.81 9.50 12.61 12.23 13.68 11.86 Peak Modelled Value 12.58 15.53 10.09 12.59 12.40 13.62 12.30 Peak Error 0.48 -0.72 -0.59 0.02 -0.17 0.06 -0.44 Mean Absoulute Error (MAE) 0.52 0.39 0.24 0.43 0.40 0.44 0.23 Mean Square Error (MSE) 100.73 28.27 57.60 59.10 39.62 54.98 6.24 Root Mean Square Error 10.04 5.32 7.59 7.69 6.29 7.42 2.50 (RMSE) Nash–Sutcliffe Efficiency (NSE) 0.76 0.81 0.99 0.75 0.82 0.60 0.93 Correlation Co-efficient (R2) 0.86 0.91 0.97 0.76 0.91 0.61 0.96Selection of 2007 flooding year as for the calibration year of the model is easily understood as the present dedicated SirjaganjModel or in other words Sirajganj Flood Hazard Model is developed with necessary customization of FFWC Super Model 2007.But selection of 1998 and 2004 as for validating the model is purely derived from the concept of whether the developed modelcould simulate the flooding condition of the study area with a greater degree of reliability as the present study aims to simulatethe flood hazards occurred from flood at least for the period of 30 years.Figure 3-12 to Figure 3-16 show comparison of model simulated water level with observed water level for calibration offlood year, 2007Figure 3-12: Comparaison at Aricha (JAMUNA 219200 m) Figure 3-13:Comparison at Sirajganj (JAMUNA 16250 m)
  • 39. 34 Model Development Figure 3-14: Comparaison at Atrai RB (ATRAI 58600 m) Figure 3-15: Comparison at Baghabari (ATRAI 167170 m) Figure 3-16: Comparison at Baral RB (BARAL 10700 m) Figure 3-17 to Figure 3-22 show comparison of model simulated water level with observed water level for validation of flood year, 2004. Figure 3-17: Comparison at Aricha (JAMUNA 219200 m) Figure 3-18: Comparison at Sirajganj (JAMUNA 16250 m)
  • 40. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 35Figure 3-19: Comparison at Atrai RB (ATRAI 58600 m) Figure 3-20:Comparison at Baghabari (ATRAI 167170 m)Figure 3-21: Comparison at Baral RB (BARAL 10700 m) Figure 3-22: Comparison at Astomanisha (ATRAI 125126 m)Figure 3-23 to Figure 3-28 show comparison of model simulated water level with observed water level for validation offlood year, 1998
  • 41. 36 Model Development Figure 3-23: Comparison at Aricha (JAMUNA 219200 m) Figure 3-24: Comparison at Sirajganj (JAMUNA 16250 m) Figure 3-25: Comparison at Atrai RB (ATRAI 58600 m) Figure 3-26: Comparison at Baghabari (ATRAI 167170 m) Figure 3-27: Comparison at Baral RB (BARAL 10700 m) Figure 3-28: Comparison at Astomanisha (ATRAI 125126 m) However, even the developed model could simulate flooding condition of 5 to 10 years back with a greater margin of reliability, the static hydro-geological, land use pattern for rainfall-runoff model development and hydrometric, topographic, floodplain data for hydrodynamic model development postulate a big limitation of such flood hazard modeling. It is expected that lots of changes have been happened in land use patterns, infrastructural development, morphologic and topographic features; above all the whole geo-physical settings of the study area. But these changes cannot be represented in single set of model setup unless and otherwise we have enough data and information for each and every year. This is in fact the main reason why no breach information is included in Sirajganj Hazard Model which is used to generate river stage and flow data for 30 years of selected period. Brahmaputra Right Embankment (BRE) breaching is not a regular phenomenon as it is one of the highly protected and monitored embankments in the country. Even though couple of locations has been under severe threat to be breached against the huge thrust of high flood water of Brahmaputra River over the last major floods like in 1988, 1998, 2004 and 2007. In those years, few of the most vulnerable points of BRE were breached actually and affected the area severely.
  • 42. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 37Anyway, team members of the current study have decided to develop three different models for the last three major floods;flood in 1998, 2004 and 2007 where available breach information would be considered and that has been done successfully.Nevertheless, calibration and validation of Hazard Model with static geo-hydrological and hydrometric, topographic data andinformation have been achieved so far. For hydrodynamic model, channel and floodplain roughness (parameter Manning’s M)is the key parameter to be properly adjusted during calibration with consideration of geo-morphological features of the rivers/channels /floodplains. Values of Manning’s M to characterize roughness for rivers are set as 40 to 50; whereas for floodplainthe value ranges from 30 to 35. During the simulation of model for validating purpose, parameter of channel roughness alongwith all other parameters values are kept as same as they are in the calibrated model.As far as floodplain water level or flood depth validation is concerned, this has not been done so far due to non-availability ofmeasured water level data in any floodplain area. BWDB maintains some regular water measurement stations as it ismentioned earlier, but all those gauges are stationed at the river bank side to measure the river stages.3.3.5 FLOOD INUNDATION MAPS/ DATA GENERATIONAfter successful calibration and validation of model, flood inundation maps /data are produced using MIKE 11 GIS tool. TheMIKE 11 GIS system integrates the MIKE 11 river and floodplain modeling technologies with the spatial analysis capabilities ofthe ArcView Geographic Information System (GIS). Based on the discrete information from MIKE 11, MIKE 11 GIS constructs agrid based water surface and compares this data with the already available or updated DEM to produce flood depth andduration mapped surfaces.At its most basic level, MIKE 11 GIS requires information from a MIKE 11 model (river network), MIKE 11 flood simulations anda Digital Elevation Model (DEM). Other useful inputs are maps of rivers, infrastructure, property type, land use, satellite imageryand other more study specific data.Furthermore, it is recommended that some or all of the additional data such as GIS themes characterizing property types, landuse, etc and, if available, satellite images or aerial photographs included to improve the quality of analysis and presentation.The GIS themes mentioned above are used to highlight floodplain features. They are recommended to assist with thedevelopment and quality checking of the generated DEM. Examples of such additional data features is contour lines and/orspot levels and themes accurately describing the location of rivers, roads, embankments, villages and lakes etc. A DigitalElevation Model, or DEM, in the context used here, is a square grid-based ground surface elevation model. It consists of a gridof elevation points defined by X, Y and Z (elevation) co-ordinates. For the purposes of flood mapping it is essential that theDEM represents accurately all the important topographical features of the floodplain (DHI, 2008). The elevation accuracy of thefloodplain DEM is also of importance. The accuracy of any generated floodmap will only be as good as the accuracy of thebase DEM data assuming that MIKE one-dimensional model could produce reliable river and floodplain stage for study area.However in the present study, generating flood inundation maps or flood maps /data is completely relied on already availableDEM data; land level of which is first surveyed during 60’s of last century and later updated in mid 80’s. In other words, moreemphasis is given on developing a well calibrated and validated one-dimensional model rather than to improve the quality ofexisting DEM under the present study. Improvement of DEM data, whether it is to minimize the resolution or to attain theaccuracy of land level and incorporating present landuse, infrastructural, other physical or non-physical setup of the study arearequires large scale of survey and data analysis (e.g. satellite image analysis) activities. Meanwhile, there was no option andopportunity to go for such detail survey and data analysis works under the present study. Therefore, there remains a biguncertainty about the quality of produced floodmaps or data; though this has been so far the best available techniques widelybeing acclaimed in and outside of the country to generate flood depth data.Triangular Irregular Network (TIN) surface generating techniques has been used to interpolate the water level data of modelgrid points. Another important aspect of flood water surface generating is to provide correct and accurate description ofembankment /levee elevation and alignment in MIKE 11 GIS setup. Brahmaputra Right Embankment (BRE) and other
  • 43. 38 Model Development supposedly non-submergible embankment alignments are considered during floodmap generation (see Figure X). To do so, Floodmap with dynamic and user defined Channel Boundary Lines (CBL) method has been used here leads to the most realistic floodmap, because it takes into account natural or artificial obstacles, which may prevent areas from being flooded. This also means that water levels are not extrapolated across obstacles unless the water level is higher than the feature. If the DEM is detailed enough, obstacles such as railway embankments or dykes are usually incorporated into it. These obstacles form so-called Dynamic Channel Boundary lines. But if the lines are not incorporated in the DEM, the user can define them manually, using the fault line called User Defined Channel Boundary Lines. BRE and other non-submergible embankments are defined as user defined fault line in MIKE 11 setup so that it can be taken into account during the extrapolation of model grid point’s data. For more information please see the scientific background of MIKE 11 GIS reported in Annex-C. 3.4 BREACH MODEL Jamuna River is one of the widest river and carrying major runoff through our country. It is a braided river where each of channel having most of meandering characteristics. Severe bank erosion, bed aggradations – degradation, annual flood due to the lowering channel carrying capacity, variation of upcoming wash load due to the change of land use pattern, bed scouring and sedimentation based on seasonal flow variation & sediment carrying capacity, lateral instability causing meandering activities, local scour due to the existing structural intervention are the most common scenario of this river on location and topography basis. As sediment load is proportional to the discharge passing through the channel. Due to the insufficient supply of sediment to the channel, it mostly covers the residual amount of sediment pick up rather from Figure 3-29: Location of BRE breach position during past major floods. river bed or from river bank. Thus river bank erosion is the most common phenomenon for Jamuna and as subsequent triggering to the lateral shifting of the river. And finally it attracts to the constructed embankment especially on Brahmaputra right embankment (BRE). And there are so many evidence of breaching of embankment during severe flood year of 1988, 1998, 2004 and 2007. A cut model concept is adopted for the preparation of flood inundation grid data on Sirajganj district from North-West regional model. Comparison of simulated data with the observed data sets in specific location is one of the model calibration technique whether incorporation of all different type of field situation (existing controlling structures, major embankment breach in specific location) must be the essential thing to represent the flood scenario, flow type, flow pattern, flow network in a reliable and realistic manner. For this an effective field trip was arranged to the Siraganj district to gather the information about breach in different flood year. And finally it is possible to collect the information from a day long discussion with BWDB professionals and over all with the discussion with local people. The outcome of the discussion is presented in Table 3-5 and also a schematic presentation is Figure 3-29.
  • 44. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 39Table 3-5: Breach information on BRE in different flood year.Flood Year Location Name Tentative time of breach Final length of Final depth of occurring breach (m) breach (m)1998 Khokshabari August - -2004 D/S of Sailabari Groyne July 27 140 302007 Songachha August 400 122007 Kholishakura August 650 142007 Khokshabari August 700 18
  • 45. 4 OUTPUT, RESULTS AND DATA SHARING4.1 OUTPUTMain objective and output of this study, as it is mentioned earlier can be summarized as the development of a Flood HazardModel for the Sirajganj District which is able to produce daily monsoon flooding scenario at least for 30 years at raster gridlevel. This Hazard Model and its output then would be used for the development of a Flood Loss Model for the study area toestimate the loss of property and income to people, households, infrastructures, enterprises and so. After effective lossestimation, Index Based Flood Insurance Products or System can be developed. Data sharing is another important aspect ofthis study; not only sharing current study output but also some other data and information which are very much essential todevelop Flood Loss Model. Landuse and settlement data are among those. Also for a better understanding of overall hydrologyof North-West Region of Bangladesh, hydro-meteorology and hydrologic data like rainfall, discharge, water level data at someimportant locations has been shared with partner of this study, Centre for Insurance and Risk Management (CIRM). Resultanalysis of Sirajganj Flood Hazard Model and produced yearly as well as probabilistic Vulnerability Index considering 30 sets ofyearly Vulnerability Index have been presented and discussed.The present chapter describes the overall outputs, results including vulnerability indexing been produced and data sharingbeen done so far under this present study.4.1.1 OUTPUT OF FLOOD HAZARD MODEL
  • 46. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 41Figure 4-1: Area of XYZ value extraction After successful development of Sirajganj Flood HazardModel, historic daily flood depth data /maps during monsoon season (June to October) for the period of 1978 to 2007 havebeen produced. Figure 34 to Figure 35 show some sample floodmaps during monsoon 2007. A total of 152 nos. floodmapshave been produced for each monsoon season; as a whole the total number stands on 4560 floodmaps for study area. Modelperformance regarding simulating representative flooding scenario at major river stations is analyzed and discussed in previouschapter, proper performance evaluation could not be done for floodplain level due to non-availability of observed data infloodplain. However, water surface extension has been checked with available satellite images during extreme floodingcondition, and it shows almost similar water surface extension.It would be worthy to mention that 300m X 300m grid based daily flood depth data are produced initially in BangladeshTransverse Mercator (BTM) co-ordinate projection system and then converted to World Geographic 1984 (WGS84) projectionsystem. Unique conversion parameters are already established and being used for such projection conversion for many yearsnow in Bangladesh. After transforming projection system of daily flood depth data /maps from BTM to WGS84 Longitude (X),Latitude (Y) Flood Depth (Z) values for all raster grid points are extracted using the utility tools of ArcGIS software. Overallspatial extension of data extraction includes whole Sirajganj District, administrative boundary of which falls at both side of theJamuna River. Also consideration was there to include full width of Jamuna River adjacent to Sirajganj District, part of Jamalpurand Tangail District are included in the spatial extension of data extraction. Figure 4-1 shows the total area of data extractionwith their standard identification code. As for 300m X 300m cell size, the mentioned area includes as many as 40243 points.Figure 4-2 andFigure 4-3 show flood maps of six different dates of 2007. First figure represents the dry condition for the study area, whileremaining five flood maps are produced on the basis of approximately 1m increase in river stage during 2007 monsoon.Figure 4-2: 2007 Flood depth in and around of Sirajganj District; June 07 (left), July 12 (middle) and July 18 (right)
  • 47. 42 Conclusion Figure 4-3: 2007 Flood depth in and around of Sirajganj District; July 25 (left), July 29 (middle) and August 03 (right) Table 4-1 shows sample output of X,Y and flood depth value (Z value) during June 13 to 19, 2007 for few points only. Table 4-1: Sample output of X,Y and flood depth value (Z) extracted from flood maps Area Longitudes Latitude fm013_0613 fm014_0614 fm015_0615 fm016_0616 fm017_0617 fm018_0618 fm019_0619 Code (X) (Y) 88 89.5709 24.2501 0 0 0 0 0 0 0 88 89.5737 24.2501 0 0 0 0 0 0 0 88 89.5765 24.2501 0 0 0 0 0 0 0 88 89.5793 24.2501 0 0 0 0 0 0 0 88 89.5821 24.2501 0 0 0 0 0 0 0 88 89.5849 24.2501 0 0 0 0 81 49 49 88 89.5877 24.2501 0 69 117 120 141 103 103 88 89.5905 24.2501 0 99 160 164 165 127 127 88 89.5933 24.2501 0 100 162 166 167 128 128 88 89.5961 24.2501 0 88 150 154 154 116 115 88 89.5989 24.2501 0 34 59 61 63 61 60 88 89.6017 24.2501 0 1 2 43 44 34 33 88 89.6045 24.2501 0 29 57 100 100 63 62 88 89.6073 24.2501 0 33 66 71 71 50 50 88 89.6101 24.2501 7 1 14 17 19 17 19 88 89.6129 24.2501 42 0 53 61 67 65 70 88 89.6157 24.2501 70 0 75 83 91 92 99 88 89.6185 24.2501 14 0 16 23 29 30 36 88 89.6213 24.2501 0 0 0 0 0 0 0 88 89.6241 24.2501 0 0 0 0 0 0 0 100 89.7025 24.2501 216 211 211 218 229 246 262
  • 48. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 43 100 89.7053 24.2501 378 370 369 380 398 424 449 100 89.7081 24.2501 423 415 413 424 442 469 494 100 89.7109 24.2501 379 371 369 380 398 425 451 100 89.7137 24.2501 231 223 222 232 251 279 305 100 89.7165 24.2501 74 69 68 74 86 103 1194.2 YEARLY FLOOD VULNERABILITY INDEX MAPAccording to the methodology described earlier, Yearly Flood Vulnerability Index Maps are produced for 30 years of period(1978 to 2007). Some of those Index Maps are shown in below under different flood category. It should be kept in mind thatwhenever it is referred as Vulnerability Index Map, it should have related with the scale of loss to property and income ofpeople, homestead and other infrastructural damages been occurred due to flood. In this regard, Vulnerability Index Mapshould have to be an object oriented classification; object can be classified as loss of income and property to people,homesteads, infrastructures and other enterprises and so. The Vulnerability Index Maps what have been produced under thisstudy only represent the degree of flooding scenario for a particular year in which combined effect of Depth and Duration areonly summed up by averaging two corresponding scales. This has been described in detail in Section 2.3.2. However, anattempt was there to indentify the basic loss criteria for agriculture and homestead and these two are represented by Index 1and Index 2, respectively. The idea is that for agricultural loss, more than 30 cm of flood depth with duration of more than 3days is considered to be enough for loss of agricultural products and that is represented by Index 1. On the other hand, morethan 50 cm of flood depth with duration of 7 to 20 days are considered to be havoc for homestead loss and that is representedby Index 1 and 2.Other than this simple criteria, vulnerability in broader scale cannot be understood from these Maps. The importance of theseVulnerability Index Maps though remains on a better and reasonable understanding of degree of flooding scenario affected indifferent area of the study area. These maps could have of importance to estimate the various categories of losses due tofloods. Furthermore, these maps or methodology to produce these maps can be further utilized to come up with a objectoriented Flood Vulnerability Index Map4.2.1 INDEX FOR MAJOR FLOOD1988, 1998, 2004 and 2007 flood year are very much known to large or major floods for not only Sirajganj District but also forwhole Bangladesh. Out of those years, 1988 and 1998 are regarded as 1 in 75 to 100 flood year depending on the regionalflood scale, while 2004 and 2007 flood are considered as 1 in 50 year flood year. Though interesting enough to let it inform that2004 flood is found 1 in 100 year flood for North East Region. Meanwhile, Figure 4-4 and Figure 4-5 show Flood VulnerabilityIndex Map for two of most severely affected flood in the study are in recent past.
  • 49. 44 Conclusion Figure 4-4: Flood Vulnerability Index Map for 2007 Figure 4-5: Flood Vulnerability Index Map for 1998 4.2.2 INDEX FOR NORMAL OR AVERAGE FLOOD YEAR Figure 4-6 and Figure 4-7 show Flood Vulnerability Index Map for two normal or average flood year in recent time. Figure 4-6: Flood Vulnerability Index Map for 2001 Figure 4-7: Flood Vulnerability Index Map for 1997 4.2.3 INDEX FOR BELOW THAN NORMAL FLOOD YEAR As it was in 2009, 2006 monsoon was also one of the lean or dry periods so far been experienced. The Index Map (see Figure 4-8) clearly shows that
  • 50. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 45 4.2.4 PROBABILISTIC INDEX MAP Figure 4-9 and Figure 4-10 show the 75% and 50% Probabilistic Flood Vulnerability Index Map for the study area, respectively. The map indicates the index which has been found at least 75% (22 years) and 50% (15 years) case out of total 30 Yearly Vulnerability Index Maps. Thana boundary and name (local administrative unit) are mentioned in those figures so that Thana wise vulnerability can be understood. Also in Table 4-2 shows Thana wise total area affected by different vulnerability indices for 75% probabilistic flooding scenario while Table 4-3 shows the same in percentage of total Thana area. Table 4-4 and Table 4-5 show same statistics for 50% probabilistic flooding scenario.Figure 4-8: Flood Vulnerability Index Map for 2006 Figure 4-9: 75% Probability Flood Index Map Table 4-2: Thana wise total area affected by different vulnerability indices for 75% probabilistic flooding scenario Thana Name with Area Under Six Flood Vulnerability Index Flood Index Belkuchi Chauhali Kamarkhanda Kazipur Royaganj Shahjadpur Sirajganj Sadar Tarash Ullah Para 0 12.8 1.3 0.7 9.0 22.9 49.0 56.4 36.9 48.6 1 86.4 27.3 93.9 122.7 223.1 103.6 162.2 205.2 311.0 2 11.4 1.6 0.1 3.0 2.2 51.6 7.2 11.4 12.6 3 1.9 0.3 1.2 6.9 6.4 30.4 6.3 36.9 36.9
  • 51. 46 Conclusion 4 2.5 0.2 0.0 0.2 1.4 12.1 10.0 6.7 6.4 5 0.0 0.4 0.0 0.0 0.0 0.0 15.6 0.0 0.0 6 0.0 0.0 0.0 0.0 0.0 0.0 8.1 0.0 0.0 Area within Jamuna River* 34.0 188.8 0.0 220.0 0.0 75.8 48.1 0.0 0.0 Total Area 148.9 219.8 96.2 361.8 255.5 322.6 313.9 297.5 415.3 Table 4-3: Thana wise percentage of area affected by different vulnerability indices for 75% probabilistic flooding scenario Thana Name with Percentage of Area Under Six Flood Vulnerability Index Flood Index Belkuchi Chauhali Kamarkhanda Kazipur Royaganj Shahjadpur Sirajganj Sadar Tarash Ullah Para 0 12.8 1.3 0.7 9.0 22.9 49.0 56.4 36.9 48.6 1 86.4 27.3 93.9 122.7 223.1 103.6 162.2 205.2 311.0 2 11.4 1.6 0.1 3.0 2.2 51.6 7.2 11.4 12.6 3 1.9 0.3 1.2 6.9 6.4 30.4 6.3 36.9 36.9 4 2.5 0.2 0.0 0.2 1.4 12.1 10.0 6.7 6.4 5 0.0 0.4 0.0 0.0 0.0 0.0 15.6 0.0 0.0 6 0.0 0.0 0.0 0.0 0.0 0.0 8.1 0.0 0.0 Area within Jamuna River* 34.0 188.8 0.0 220.0 0.0 75.8 48.1 0.0 0.0 Total Area 148.9 219.8 96.2 361.8 255.5 322.6 313.9 297.5 415.3 Figure 4-10: 50% Probability Flood Index Map Table 4-4: Thana wise total area affected by different vulnerability indices for 50% probabilistic flooding scenario Thana Name with Area Under Six Flood Vulnerability Index Flood Index Belkuchi Chauhali Kamarkhanda Kazipur Royaganj Shahjadpur Sirajganj Sadar Tarash Ullah Para 0 2.9 0.5 0.7 8.4 22.6 1.2 22.3 7.2 0.1 1 65.8 21.0 86.6 116.0 210.7 36.4 157.7 142.9 175.4 2 35.0 8.4 7.2 8.0 12.9 129.6 14.1 71.5 146.9 3 7.7 0.5 1.4 8.9 8.1 62.7 16.9 63.7 80.5
  • 52. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 47 4 3.4 0.2 0.0 0.4 1.6 16.8 20.2 11.7 12.7 5 0.0 0.4 0.0 0.0 0.0 0.1 24.9 0.0 0.0 6 0.0 0.0 0.0 0.0 0.0 0.0 9.7 0.0 0.0Area withinJamunaRiver* 34.0 188.8 0.0 220.0 0.0 75.8 48.1 0.0 0.0Total Area 148.9 219.8 96.2 361.8 255.5 322.6 313.9 297.5 415.3Table 4-5: Thana wise percentage of area affected by different vulnerability indices for 50% probabilistic flooding scenario Thana Name with Percentage of Area Under Six Flood Vulnerability Index Flood Index Belkuchi Chauhali Kamarkhanda Kazipur Royaganj Shahjadpur Sirajganj Sadar Tarash Ullah Para 0 2.0 0.2 0.7 2.3 8.8 0.4 7.1 2.4 0.0 1 44.2 9.6 90.0 32.1 82.5 11.3 50.2 48.0 42.2 2 23.5 3.8 7.4 2.2 5.0 40.2 4.5 24.0 35.4 3 5.2 0.2 1.5 2.5 3.2 19.4 5.4 21.4 19.4 4 2.3 0.1 0.0 0.1 0.6 5.2 6.4 3.9 3.1 5 0.0 0.2 0.0 0.0 0.0 0.0 7.9 0.0 0.0 6 0.0 0.0 0.0 0.0 0.0 0.0 3.1 0.0 0.0Area withinJamunaRiver* 22.9 85.9 0.0 60.8 0.0 23.5 15.3 0.0 0.0Total Area 100 100 100 100 100 100 100 100 100
  • 53. 48 Conclusion Figure 4-11: 75% Probabilistic flooding scenario in terms of percentage of total Thana area of Sirajganj District affected by six vulnerability indices Figure 4-12: 50% Probabilistic flooding scenario in terms of percentage of total Thana area of Sirajganj District affected by six vulnerability indices Note: Detail analysis will be presented in Final Report
  • 54. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 495 CONCLUSIONThe main aim of the present study is the development of Flood Hazard Model for Sirajganj District. A methodology as well asoutput of 300m X 300m grid based Flood Vulnerability Indexing for the study area has been produced. Al though, every studyhas some limitation regarding updated information and data, proper adaptation of methodology or so, and this study is notexcept in that. Those limitations are mentioned in this present chapter. However, the study utilized best available approach andmodeling tools for development of subsequent integrated Flood Hazard Model and Flood Vulnerability Index for the selectedstudy area.5.1 CONCLUSIONSThe following are the list of works those have been done to fulfill the objectives been set under the present study. • A literature review on floods in Bangladesh, its causes and impacts have been analyzed. • A methodology has been adopted to develop Sirajganj Flood Hazard Model. FFWC Super Model is considered as the Base Model for such dedicated Flood Hazard Model development for SIrajganj District. The Sirajganj Model is the Cut or Sub model of FFWC Super Model. Several customizations and detailing of this Sub Model have been carried out in the study area utilizing data and information from primary and secondary sources. • the customization and detailing includes incorporation of most recent measured cross-section for main rivers included in the Siragjang Flood Hazard Model river network, identification of floodplain channel from recent satellite image and incorporated in the model river network, extraction of newly added floodplain cross-section from available 300m X 300m Digital Elevation Data (DEM) of the area, re-distribution of catchment runoff to main rivers as well to added floodplain channels. As far modeling tool used for this modeling, MIKE Rainfall-Runoff Model (MIKE NAM) and MIKE 11 HD (Hydrodynamic) modeling software been used. • Other modification of the model consists of re-calibration of the model for 2007 flood year and subsequent validation of the model for 2006, 2004, and 1998 flood year. The model results have been verified with observed data of past major flood events at BWDB gauge stations and the flood extent of 1998 flood was compared with the satellite image of same time and found satisfactory. In addition local flood inundation of 2007 produced by the model has been veri- fied through discussions with local people in the study area. • Flood inundation maps or Floodmaps are produced on daily basis for every monsoon (June to October) season for 30 years of period (1978 to 2007). In this account, 152 floodmaps have produced for every single year and the number of total floodmaps is thereby accounts as 4560 for 30 years. • Yearly as well as Probabilistic Vulnerability Index Maps has been produced for the study area. These maps are also raster grid based, as same as floodmaps and the cell or grid size is 300m X 300m. • Yearly Vulnerability Index Map takes in account 152 daily floodmaps. After reclassification on the basis of chosen depth and duration criteria and recurrence analysis for certain events, final Yearly Vulnerability Index Map have been developed. • Probabilistic Vulnerability Index Maps has been produced on the basis of probability analysis of occurrence of certain events over the period of 1978 to 2007. In this case, 30 Yearly Vulnerability Index Maps are considered and probabil- istic analysis considers Yearly Vulnerability Index for each and every cell covering the area as an event. • The Vulnerability Index Maps what have been produced under this study only represent the degree of flooding scena- rio for a particular year in which combined effect of Depth and Duration are only summed up by averaging two cor- responding scales. However, an attempt was there to indentify the basic loss criteria for agriculture and homestead and these two are represented by Index 1 and Index 2, respectively. Other than this simple criteria, vulnerability in broader scale cannot be understood from these Maps.
  • 55. 50 Conclusion • The importance of these Vulnerability Index Maps though remains on a better and reasonable understanding of de- gree of flooding scenario affected in different area of the study area. • These maps could have of importance to estimate the various categories of losses due to floods. Furthermore, these maps or methodology to produce these maps can be further utilized to come up with an object oriented Flood Vulne- rability Index Map. • Flood depth data has been extracted from floodmaps as X (longitude), Y (latitude) and Z (flood depth) table. • Extracted flood depth data (XYZ table); land use data such as Homestead, Water Body, Agricultural Land of different types and Agro-geological zone of the study area; discharge data for some important locations in North-West Region have been archived and preserved for further research work. • Finally all the data has been provided to CIRM specialists for the development of Flood Loss Model for flood insur- ance of the study area. The generated data would be accurate enough for analysis of the flooding of 300m X300 m grid area. The flood index maps will be very useful in identifying the flood risk areas of the Sirajganj District. • There have been found some bias in flood maps /data in terms of interpolating one-dimensional model grid points’ water level data for considerably small numbers of grid points. Only 108 grid points out of total 300m X 300m based 40243 grids show such inconsistency and this has been reported by specialist of CIRM. Therefore, this inconsistency will be checked and corrected as soon as possible and shared with CIRM. 5.2 LIMITATIONS The presented flood maps can be termed as coarse and should be used carefully knowing its limitations. The flood maps have the following limitations: • The Digital Elevation Model (DEM) is coarse having a resolution of 900 meter surveyed back in 60s of last century and re-defined it to 300-meter grid size during the period of early 1990s. After then, other than the specific project re- quirement, DEM of the country is not updated with recent survey. That reflects that the present DEM does not reflect the changes been occurred in topography, landuse, agricultural practice, urbanization and in many other infrastruc- tural development at least for the last 20-40 years. Hence the flood depth may contain some uncertainty /error, espe- cially in and around those areas where the topography has changed a lot. • Detail information of changes in physical infrastructure (for example, embankments, local roads etc.) and other artifi- cial interventions is not reflected in present DEM and flood situation, therefore in some cases might differ in actual field condition.  The model has provided results in 300X300 grid size which is comparatively large for describing condition of a specif- ic household which is important for devising flood insurance for residential/ commercial area, however the generated data would be suitable for big areas like agricultural land. • Breach information for the Brahmaputra Right Embankment (BRE) for major floods like 1998, 2004 and 2007 has not been considered for model based on which 30 years daily flood depth data is generated. • The generated Flood Vulnerability Index Map doesn’t represent fully the object oriented vulnerability of the area. It only indicates what depth and duration scenario for different parts of Sirajganj District both in Yearly and 30 years Probabilistic Vulnerability Index Maps. 5.3 RECOMMENDATIONS The following are the recommendations of the present study:  Further investigation should be carried out incorporating the historical breach information of Brahmputra Right Embnkment (BRE)
  • 56. Index Based Flood Insurance Products: Report on Flood Hazard Model for Sirajganj District 51 The model results should be updated utilizing updated ground levels (DEM) and other information of latest develop- ment. Data should be generated in a smaller grid size to get localized flood information. The developed model of Sirajganj seems to be suitable for generating local flood information; there is a scope to util- ize the developed model for generating community level flood warnings in Sirajganj area incorporating the real time flood forecasts of FFWC. Applying the methodology used in this study to produce Flood Vulnerability Index Map, fully object oriented Vulnera- bility Maps could be produced in future.
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