Name: Mousumi Ghosh
Department: Interdisciplinary Programme in Climate Studies
Program: Ph D. (4th year)
Name of supervisor: Prof. Subhankar Karmakar and Prof. Subimal Ghosh
The rapid escalation of various forms of natural disasters like floods, droughts, wildfires, heatwaves are testimonial to the fact the climate change is for real. Floods account for the most widespread, disastrous, frequent and recurring natural disaster in context of the Indian subcontinent. The urban population is at a greater risk to damages caused due to flood due to lack of proper drainage system, low permeable catchment, human induced land cover changes and presence of dense population in space-constrained regions. Therefore, it has become quintessential for the administration and researchers to solve the flood damage related problems though optimal planning and development of different scientific frameworks and technologies and solutions for efficient flood mitigation and management. The conventional implementation of structural measures such as the development of flood storage structures, reservoirs, etc. often becomes difficult in urban areas owing to space constraints and rapidly thriving populations. Therefore, it has become desirable to solve these flood damage-related problems through optimal planning and integration of non-structural measures along with the structural ones.
With this context, we propose a comprehensive hydrodynamic flood modelling framework in order to lessen the extent and impact of flooding due to extreme rainfall event.Various hydraulic scenarios which consist of different combinations of river cross sections such as rectangular and trapezoidal cross-section and lining materials such as gravel and concrete in addition to the original cross section and lining material along the river channel are incorporated in the flood modelling framework resulting in total number of 45 scenarios (Figure 1). Further, the scenario which maximises the reduction in flood extent is identified from the flood inundation and hazard maps derived from the modelling framework. Flood modelling is a non-structural technique of flood management in which different characteristics of flood like the water depth over land, its velocity, extent and duration during a heavy rainfall event are translated into flood inundation and hazard maps. These maps can be utilised by the civic bodies, urban planners as well as common public to categorize the likely areas of flood risk so that steps can be taken accordingly to implement various measures for flood management and mitigation thereby reducing the damages and losses. A combination of hydrologic and hydrodynamic modelling is widely implemented for assessment of flood hazard at a finer scale. The hydrologic models help us to quantify streamflow in a river channel while hydrodynamic models utilize laws of physics and mathematics to simulate the motion of fluid along the river channel and surrounding areas to replicate the proliferation of flood during and after a rainfall event. However, flood modelling has the requirement of huge data repository ranging from meteorological, topographical, hydrological to hydraulic data in order to obtain flood hazard at finer scale. Lack of these extensive data sets often form obstacle in flood modelling especially in developing and developed countries. Therefore, the current research attempts to implement alternate robust techniques to address the issue to data unavailability which can be adapted for similar data scarce catchments. The Mithi river catchment, a major flood prone area of Mumbai which is subjected to heavy rainfall almost every year during the monsoon months of June to September and results in massive economic losses and inconvenience to people has been used to demonstrate the proposed framework (Figure 2). Flood modelling over this catchment is further more complex due to factors such as lack of long-term reliable data sets, tidal influence along the coastline, rapid change in slope over a small area, unplanned expansion of urban areas and settlement of a large number of urban poor population along the Mithi river bank.
In this study, MIKE FLOOD platform has been used to develop a 3-way coupled flood model (Figure 3) for a data scarce urban area by considering various flood influencers like precipitation, channel flows, overland flow and tidal influences in which MIKE 11 model which accounts for river flow and storm water drains are coupled with MIKE 21 model which accounts for overland flow.
First, rainfall, streamflow and tidal data, the three major inputs required for hydrodynamic flood modelling are obtained for 10-, 50- and 200-year return periods. Due to the absence of dense rain gauge networks over the study area, the regionalization approach is adapted for one long-term observed time series of rainfall to estimate various return periods of rainfall. Following this, to account for the absence of long-term observed streamflow data, the hydrological model SWAT is set up to simulate streamflow which is provided as input to the flood model. Similarly, a synthetic time series for tidal elevation is utilized to determine the astronomical tide height for various return periods by fitting into a GEV model. Subsequently, the maps are derived for different return periods of design precipitation, tidal elevation and streamflow discharge values for the proposed hydraulic scenarios to identify the best one. The proposed framework efficiently determines that the scenarios having trapezoidal and rectangular river cross-sections with concrete lining material which corresponds to scenario II(E) and scenario III(E) respectively maximizes the decrease in spatial extent of flood in comparison to the other scenarios (Figure 4).
Further, the scenario II(E) performs the best amongst all the 45 scenarios, since the water carrying capacity of a trapezoidal cross-section is greater than the others due to increase storage area which results in higher storage of water in the river channel and lesser spilling of river water across the banks This user-friendly generic approach can be potentially executed as an effective flood mitigation option in thickly populated regions where lack of space limit the implementation of structural measures for flood management.