Discharge Structure for Hazard and Vulnerability Analysis using GIS and Real Time Flood Data

Abstract

From pandemics to man-made disasters, all have impacted hundreds of thousands of humans worldwide. India is ranked as the 14th vulnerable country in the global because of severe weather-associated events. Out of thirty-six States and Union Territories in India, twenty-seven are disaster-prone. With GIS interactive maps, Government view essential statistics in layers and make knowledgeable decisions. GIS based information providing to the general public, how much area has to be evacuated, what are the alternative places for accommodation, food and medicine supply is important. This app is developed for the state of Andhra Pradesh as suggested by Andhra Pradesh Disaster Management Authority (APSDMA) which predicts the floods based on the runoff value given and identifies the disaster prone areas according to the runoff parameter. This web application also provides methods for flood change detection using image processing. The technology which is used here is ArcGIS. The database used for storing the runoff data is MongoDB. The accuracy of the Convolutional Neural Network (CNN) model that was built is 98.4%.