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Author Ray Singh, Meena
Researcher Ray Singh, Meena
Source NIT Rourkela-Thesis
Content type Text
Educational Degree Master of Technology (M.Tech.)
File Format PDF
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Hydraulic engineering
Subject Keyword Water Resources Engineering
Abstract Floods are probably the most recurring, widespread, disastrous and frequent natural hazards of the world. India is one of the worst flood-affected countries. In India the Himalayan Rivers account for maximum flood damage in the country. The problem of flood in the state of Bihar is well known and every year it becomes a recurring problem to the entire region. The plains of north Bihar are some of the most susceptible areas in India, prone to flooding. Flood forecasting & flood warning, flood hazard mapping and flood risk zoning are quite effective non-structural procedures in managing floods that decreases the risks and disasters floods may cause. In view of this an attempt has been made in the present work to simulate runoff and flood inundation for Kosi River Basin in Bihar, India. This study introduces about the parameterization of hydrologic and hydraulic modelling for simulation of runoff and flood inundated area mapping. Time series analysis of hydrological data has been done to look for the rainfall and runoff behaviour in Kosi Basin and their cross-correlation. SRTM-DEM of 90m resolution is used to generate the various maps (DEM) of Kosi Basin. Hydrological and hydraulic models HEC-HMS, HEC-RAS, SCS-CN in addition to ANN models are used for runoff and floodplain inundation modelling. Results indicated that for Kosi catchment, the empirical runoff prediction approach (ANN technique), in spite of requiring much less data, predicted daily runoff values more accurately than semi-distributed conceptual runoff prediction approach (SCS-CN method). The flood inundation simulation for the Kosi River floodplain is carried out using HEC-RAS 1-D hydrodynamic model indicates promising results. Further, linear/non- linear regression models were developed to estimate the flood inundation area provides best results.
Education Level UG and PG
Learning Resource Type Thesis
Publisher Date 2012-01-01