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Due to heavy rainfall in the Himalayan and other watersheds of the North India, Haryana is endowed with extensive river system consisting of the Satluj, and its tributary. All the rivers in Haryana are flood prone, mainly because they receive heavy rainfall within a short duration. These rivers are in their earlier stage of maturity and are active agents of erosion. This region of India, which has about one third of the country’s total water resources potential, is however not enjoying the enormous water resources potential; instead suffering a lot due to the regular flood hazard. Need of improving flow forecasting capability for better management of Water Resources has also been emphasized by Sarma et. al (2007). Therefore, an attempt has been made to develop a flood forecasting model using ANN in this study. Flood forecasting undoubtedly is the most challenging and important task of operational hydrology. Conventional methods for establishing the relationship between rainfall and runoff need to understand the behavior of hydrological cycles. The temporal and spatial variability that characterizes a river system makes flow forecasting a demanding task. Flow forecasting is a crucial part of flow regulation and water resource management. It is well known that floods kill more people and cause more damage than any other natural disaster. Consequently there is a need for systems capable of efficiently forecasting discharge rates in rivers. Artificial Neural Networks provide a fast and flexible means for developing non-linear flow routine models. Flood Forecasting (FF) forms an important tool in reducing vulnerabilities and flood risk. Therefore, the attempt …