JFET_V5_N4_A1 C. Gajendran P. Thamarai C. Mahendran Journal on Future Engineering and Technology 2230 – 7184 5 4 1 6 ANN, GIS, Statistical Study, Regression Analysis, Fuzzy logic, Water Resources Engineering Water is vital for all aspects of human and ecosystem survival and health. Lack of water resources and optimum management has been two recent challenges of water resources engineering. Population growth, decrease of usable water resources, improvements in lifestyle, growing rate of consumption, climate change and several other parameters have caused useable water to be a significant problem for the future. American Society of Civil Engineers (ASCE) research committee reported that Artificial Neural Network (ANN) is able to simulate many of complicated nonlinear processes. Over the last few years, the use of Artificial Neural Networks (ANNs) has increased in many areas of Engineering. In particular, ANNs are being applied to many water resources engineering problems and have demonstrated some degree of success. A review of literature reveals that ANNs have been used successfully in water for quality and quantity prediction, modelling of water pollution and so on. The objective of this paper is to provide a general review of some ANN applications for solving some types of water resources engineering problems. It is not intended to describe the issue of ANNs modelling in water resources engineering and not covering every single application or scientific paper that is found in literature. However, some important works are selected to be described in some detail, while others are acknowledged for reference purposes. The paper then discusses the strengths and limitations of ANNs compared with the other modelling approaches. May - July 2010 Copyright © 2010 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=1191