Rainfall-runoff models are highly useful for water resources planning, development and flood mitigation. Rainfall-runoff analysis is quite difficult due to presence of complex nonlinear relationship in the transformation of rainfall to run-off however runoff analysis is very important for the predication of natural calamities like floods and drought. A rainfall-runoff model is a mathematical model describing the rainfall-runoff relations of a catchment area, drainage basin or washed. In the model calculates the rainfall into runoff. In rainfall-runoff modelling SCS-CN (Soil Conservation Service ? Curve Number) method uses the soil information, rainfall, storm duration, soil texture, type & extent of vegetative cover and conservation practices are considered. A new dimension has been added to the modelling approach through the adoption of the ANN (Artificial Neural Network) technique as these models possess desirable attributes of universal approximation, and the ability to learn from examples. The ANN is well known as a flexible mathematical tool and has the ability to generalize patterns in precise and ambiguous input and output data sets without attempting to reach understanding as to the nature of the phenomena. In the present study a feed forward back propagation algorithm of ANN model is used for Perumal tank, Uppanar sub basin in Kurinjipadi Taluk of Cuddalore District.
Rainfall, Runoff, Soil Conservation Service, Curve Number, Artificial Neural Network
IRE Journals:
Dr. S. Sivaprakasam , Dr. N. Nagarajan , Dr. K. Karthikeyan
"Rainfall - Runoff Modeling Using Artificial Neural Network Of Perumal Tank, Cuddalore District, Tamil Nadu, India" Iconic Research And Engineering Journals Volume 2 Issue 6 2018 Page 103-108
IEEE:
Dr. S. Sivaprakasam , Dr. N. Nagarajan , Dr. K. Karthikeyan
"Rainfall - Runoff Modeling Using Artificial Neural Network Of Perumal Tank, Cuddalore District, Tamil Nadu, India" Iconic Research And Engineering Journals, 2(6)