Title :
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
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;
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
DOI :
10.1109/ARTCom.2009.202
