Abstract
This paper presents a comprehensive study of flood forecasting, analysis, and prediction using geographical information system (GIS) and wireless ad hoc sensor networks. The role of science and technology has moved the research towards new horizon, where scientists and engineers from all over the world are using GIS-based techniques for flood prediction and hydrological risk analysis. The radar satellite images are also most frequently used for identifying the flood catchment areas in specific disaster zone. The GIS domain also proves to be very helpful for us in geographical survey and to identify the tsunamis causing vast potential and economical damage. The input parameters for flood forecasting are also used for modeling GIS, depending on the environmental conditions and climatic parameters such as soil moisture, air pressure, direction of wind, humidity, and rain fall. The core objective of this research is to study various GIS based flood forecasting techniques. In this research study we have proposed a GIS-based flood forecasting model using neural network-based approach. Our proposed model is helpful for the researchers in predicting the upcoming disasters and to take necessary actions by the rescue authorities to save the life of thousands of people to be suffered from this critical circumstance.