It is evident from the background given earlier that we need varying kinds of flood prediction capabilities depending on the nature of flooding along with the morphology of the river basin. The required process for creating the inputs or for modifying the freely available data into an acceptable form, particularly the terrain data, will be different depending on the scale of the problem as well as the morphology of the river basin. Chapter 2 provides a general description of the study sites that have been selected for the four empirical experiments. The main content of this thesis is presented in the form of four articles in Chapter 3 to 6. Chapter 3 has been already published. Chapter 4 is in the final stages of preparation before submission. Chapters 5 and 6 are under review in reputed international journals. Each manuscript addresses a combination of the major issues highlighted in the background section. Due to the article format of the thesis, there is some element of overlap between the chapters, especially in the description of study sites and field methods. My intention is to demonstrate the challenges of modelling streamflow in data sparse situations and the effect of scale and channel morphology on the success of the modelling process.
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The main focus of Chapter 3 is to develop a flood routing system in a regional scale using a 110 km reach in the middle course of the Damodar River as the study area. As the length of the river reach is too big for undertaking any computationally demanding and complex fully 2D hydraulic model, a simple and computationally efficient model is more suitable. Due to the large scale of this study only modifying the existing terrain data will be considered rather than creating a new one. In addition, this investigation will demonstrate how very limited ground survey can provide complementary terrain information for accurate routing of extremely high magnitude flood waves. The impact of uncertainty arising from inputs such as terrain, boundary conditions, channel configurations as well as modelling parameters like the selection of roughness coefficients will also be evaluated as part of this section of this thesis.
The issue of modelling inundation at the reach scale with limited data is addressed in Chapter 4. As mentioned earlier that a lot of flood-prone areas around the world are located in deltaic lowlands that are associated with numerous river bifurcations and channel islands. Chapter 4 tackles the challenge of simulating widespread floodplain inundation in anabranching channels without the access to a high resolution input terrain and SAR images for calibration and validation. The lower Damodar Basin has been chosen as the study area which is frequently flooded and associated with river bifurcations and river islands. Since the scale of this study is relatively small but with a complex morphology and high severity of hazards it demands more detailed treatment of both inputs as well as the physical process representation. Hence, I demonstrate a novel approach for creating an improved terrain data by combining elevation information extracted from low-cost stereo satellite imageries, modified SRTM DEM and limited surveyed cross-sections. The emphasis is on generating a hybrid terrain data that represent topographic features with greater influence on the inundation process such as channels, embankments and roads in finer details than the homogeneous farmlands. The other focus-point of this chapter will be evaluating how inundation models with varying levels of hydraulic process representation such as simple 1D-2D coupled LISFLOOD-FP or complex TELEMAC2D perform with the improved terrain data for simulating flood extents in an anabranching river system. The spatial distribution of inundated area in an anabranching river is often patchy and sometimes can be observed at considerable distance from the main channel. This is caused by the overtopping of the levees at the main channel as well as various smaller distributaries.
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This chapter argues that the performance of any hydrodynamic code in this kind of fluvial system primarily depends on its ability to divert high velocity flows in the smaller distributaries from the main channel. The level of process representation and the suitability of the code for a terrain data of varying details are likely to affect this ability.
Chapter 5 examines the issue of uncertainty arising in the study conducted in Chapter 4. Uncertainty estimation is carried out under the GLUE framework. The salient features of this chapter are 1) distributed uncertainty assessment of a complex and computationally demanding finite element inundation model such as TELEMAC2D at high resolution for a model domain of ~ 300 km2, 2) special emphasis on the spatial nature of uncertainty arising at the different stages of the considered flood event from the use of a terrain data with limited resolution and accuracy in a complex channel network, and 3) assessing the impact of incorporating the element of error in the observed flood extent map on the computation of uncertainty vis-a-vis the use of deterministic flood maps. In general, this chapter explores whether the element of uncertainty in the distributed observed records can make a significant impact in the overall uncertainty scenario when the inputs like inflow hydrograph and terrain have a high degree of uncertainty and the parameter space of the model has a higher dimension.
Chapter 6 investigates whether degrading land use/cover in steep hillslopes is intensifying the downstream flood risk. The event-scale rainfall-runoff modelling setup in this chapter is created primarily from a mitigation perspective. Mitigation measures such as remedial land use planning for reducing runoff coefficient of high runoff producing areas can be implemented only on local scale which generally corresponds with a sub-catchment of a river system. This chapter illustrates a systematic approach of investigating the causal relationship of sub-catchment-wise land-use change on the flood hydrograph at the basin outlet.
Chapter 7 is a general discussion chapter for the whole thesis. This chapter summarises the key findings of Chapter 3 to 6 and indicates where they fit into the broader perspective of predicting flooding at different scale and over varying physiography of land surface with limited data, typically available in the developing countries. Chapter 8
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provides the conclusion and the scope and potential of further research under the broad theme of this thesis.
The overall purpose of this thesis is to demonstrate how the existing datasets available in developing countries can be adapted and modified to model flooding with number of freely available hydrological and hydrodynamic models. This study addresses the challenge of predicting flooding and its causes with the sparse datasets at different scale. The aim of this research work is to illustrate a holistic approach that deals with the necessary prediction capability of flooding for providing early warning system, developing flood defences, creating flood risk maps, as well as planning remedial