Soft Computing Approach for Rainfall-runoff Modelling: A Review

Enormous cost and manpower utilization encountered in constructing a water resource project demands a great deal of attention in devising precise Rainfall-Runoff models for its successful performance. These models are dependent on the physiographic, climatic and biotic characteristics of the basin. These factors sometimes induce either a linear, non-linear or highly complex behaviour among the rainfall and runoff parameters. The unstructured nature of Rainfall-Runoff relations has diverted the attention of researchers towards Soft Computing tools which, harnesses reasoning, intuition, consciousness and wisdom possessed by human beings. Soft Computing being a multi-disciplinary field uses a variety of statistical, probabilistic and optimization tools which complement each other to produce its three main branches viz., Neural Networks, Genetic Algorithms and Fuzzy Logic. These techniques, whether complementing each other or working on their own, are able to model complex or unknown relationships which are either nonlinear or noisy. The review paper presents an introduction to these techniques and discusses their applications in modelling Rainfall-Runoff relations which to some extent have replaced time consuming conventional mathematical techniques with wiser and time saving computing tools.