Abstract:
Flood is one of the most common hydrologic experienced by our country. The flood problem faced by India is unique in several respects due to varied climate and rainfall patterns in different parts of the country. Generally it is found that when part of the country is experiencing floods while another is in the grip of a severe drought. Heavy and intense rainfall is one of the important factors contributing the floods. The floods may also be caused due to many other factors which include failure of the flood control structures, drainage congestions, sudden release of water due to removal of ice jams or land slides in the mountainous streams and coastal flooding due to high tides etc. In spite of various short term and long term measures adopted to prevent and mitigate the consequences of floods, there have been considerable damages and losses due to greater interference by man in natural processes and encroachment of flood plain zones and even riverbeds by human beings. Flood forecasting is used to provide warning to people residing in flood plains and can alleviate a lot of distress and damage. Recently, there has been a growing interest in soft computing techniques viz. Artificial Neural Networks (ANN) and fuzzy logic in hydrologic modelling and forecasting. These models are capable of adopting the non-linear relationship between rainfall and runoff. This paper highlights the applications of soft computing based techniques in flood forecasting. Further, flood forecasting using ANN and Fuzzy inference system based techniques have been demonstrated in Mahanadi river system.
