Work

Artificial Neural Networks Method for Prediction of Rainfall-Runoff Relation: Regional Practice

Year: 2019

Type: article

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.

Source: Natural and Engineering Sciences

DOI: 10.28978/nesciences.646198

Authors: Fatih ÜNEŞ, Levent KESKİN, Mustafa DEMİRCİ

Institution: İskenderun Technical University

Language: English

Topic: Hydrological Forecasting Using AI

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDG: Clean water and sanitation

Open Access status: diamond

Funder: U.S. Geological Survey