Journal
MODELING EARTH SYSTEMS AND ENVIRONMENT
Volume 6, Issue 4, Pages 2263-2289Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s40808-020-00807-9
Keywords
Flash floods; Watershed; Morphometric; Remote sensing; GIS; DSM
Categories
Funding
- University Grant Commission, Govt. of India [3146/(NET-JUNE 2014)]
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Flash floods pose significant threats to the socio-economic development of the Jalpaiguri and Darjeeling Districts. These districts situated in the piedmont zone of Sikkim-Darjeeling and Bhutanese Himalayas suffer from the flash floods, and those cause tremendous loss of life and property more or less every year. This study assessed flash flood risk of watersheds of the Himalayan foreland of Jalpaiguri and Darjeeling Districts in support of mitigation planning. Different hydro-geomorphological setup controls the magnitude, frequency and distribution of flash flood like topography, geomorphology, geology and climatology of the area under study. Land use/land cover and soils also have an integral relationship with run-off generation in the watersheds. Thus, we adopted holistic approach considering the topographic, hydrological, climatological, geological, soil and land use/land cover factors to assess the relative susceptibility to flash floods of the watersheds of Himalayan foreland of Jalpaiguri and Darjeeling Districts. Jaxa 30m DSM, Landsat8 OLI/TIRS and Sentinel 2A satellite images, digitized drainage network, geological, rainfall, soil and geomorphological map were analysed in GIS environment to infer lithology, land use, hydrological soil type and watershed morphometrics. The morphometric parameters were used to assign the relative susceptibility of the watersheds to flash flood, applying the weighted sum average method. Soil Conservation Service rainfall-runoff model of USDA and synthetic unit hydrograph were used to infer the hydrological response of the basin including curve number, runoff depth, time of concentration, lag time, peak discharge, etc. Final flash flood risk map was achieved by the integration of both the susceptibility maps. Higher weightage was given to the susceptibility map produced from run-off modelling and synthetic hydrograph parameters. The result shows that 63% of basins are fall in the high to very high categories of flash flood risk, 28% under medium and only 9% in the low categories of flash flood risk. Accuracy of the model was assessed using the flood inventory coupled with field diagnosis of past flood damages and available records. The resulting flash flood risk map could be used by the planners to adopt mitigation strategies to reduce the severity of the flash flood hazard.
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