Water Level Forecasting in the Vembanad Water System Using Artificial Neural Networks

Author

Gopakumar, R. ; Takara, K.

Author_Institution

Centre for Water Resources Dev. & Manage. (CWRDM), Kozhikode, India

fYear

2009

fDate

27-28 Oct. 2009

Firstpage

948

Lastpage

953

Abstract

Nonlinear modeling of water level variations in the complex water system of Vembanad wetland of Kerala State is studied using Artificial Neural Networks (ANNs). Multi-site ANN models are developed for forecasting of 1-day ahead water levels at three selected stations using the limited data on water levels, rainfall and river discharges. Performances of the models are presented in terms of selected numerical indices. Promises and limitations of neural network approach for water level forecasting in the wetland are discussed.

Keywords

artificial intelligence; environmental science computing; forecasting theory; neural nets; water supply; Kerala State; Vembanad water system; Vembanad wetland; artificial neural networks; multisite ANN model; nonlinear modeling; numerical indices; rainfall; river discharges; water level forecasting; Artificial neural networks; Electronic mail; Floods; Hydrogen; Lakes; Neural networks; Predictive models; Protection; Rivers; Water resources; Vembanad wetland; complex system; flood; forecasting; neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Advances in Recent Technologies in Communication and Computing, 2009. ARTCom '09. International Conference on

Conference_Location

Kottayam, Kerala

Print_ISBN

978-1-4244-5104-3

Electronic_ISBN

978-0-7695-3845-7

Type

conf

DOI

10.1109/ARTCom.2009.202

Filename

5328654