A Comparative Evaluation of the Use of Artificial Neural Networks for Modeling the Rainfall-Runoff Relationship in Water Resources Management

Turhan, Evren

doi:10.12911/22998993/135775

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Tytuł artykułu

A Comparative Evaluation of the Use of Artificial Neural Networks for Modeling the Rainfall-Runoff Relationship in Water Resources Management

Autorzy

Turhan Evren

Treść / Zawartość

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DOI

10.12911/22998993/135775

Warianty tytułu

Języki publikacji

Abstrakty

Recently, Artificial Neural Network (ANN) methods, which have been successfully applied in many fields, have been considered for a large number of reliable streamflow estimation and modeling studies for the design and project planning of hydraulic structures. The present study aimed to model the rainfall-runoff relationship using different ANN methods. The Nergizlik Dam, located in the Seyhan sub-basin and one of the important basins in Turkey, was chosen as the study area. Analyses were carried out based on streamflow estimation with the help of observed precipitation and runoff data at certain time intervals. Feed Forward Backpropagation Neural Network (FFBPNN) and Generalized Regression Neural Network (GRNN) methods were adopted, and obtained results were compared with Multiple Linear Regression (MLR) method, which is accepted as the traditional method. Also, the models were performed using three different transfer functions to create optimum ANN modeling. As a result of the study, it was seen that ANN methods showed statistically good results in rainfall-runoff modeling, and the developed models can be successfully applied in the estimation of average monthly flows.

Słowa kluczowe

rainfall-runoff model artificial neural networks MLR Nergizlik Dam

Wydawca

Polskie Towarzystwo Inżynierii Ekologicznej
Lublin University of Technology

Czasopismo

Journal of Ecological Engineering

Rocznik

2021

Tom

Vol. 22, nr 5

Strony

166--178

Opis fizyczny

Bibliogr. 77 poz., rys., tab.

Twórcy

autor

Turhan Evren

eturhan@atu.edu.tr

Department of Civil Engineering, Adana Alparslan Türkeş Science and Technology University, Turkey

https://orcid.org/0000-0002-0742-4848

Bibliografia

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Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).

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