- Fatih Üneş
Department of Civil Engineering, Iskenderun Technical University, Turkey
- Levent Keskin
Department of Civil Engineering, Iskenderun Technical University, Turkey
- Mustafa Demirci
Department of Civil Engineering, Iskenderun Technical University, Turkey
Volume 4 - No: 3
Artificial Neural Networks Method for Prediction of Rainfall-Runoff Relation: Regional Practice
Keywords: Rainfall, Runoff, Artificial Intelligence, Multi Linear Regressions, Artificial Neural Networks.
Abstract
Rainfall and runoff relation is very important on efficient use of water resources and prevention of disasters. Nowadays, different methods of artificial intelligent techniques are applied to determine the rainfall-runoff relations. Artificial Neural Networks (ANN) is used for the present study. Also, Classical methods such as Multiple Linear Regression (MLR) are used. In this study, the data obtained from USA Waltham Massachusetts Stony Brook Reservoir basin was taken. 731 daily data of rainfall, runoff, and temperature were used to generate input data in the Multi Linear Regression and Feed-Forward Back-Propagation Artificial Neural Network models. The results obtained were compared with the actual results.