Modeling of Mamdani Fuzzy Inference System for the Prediction of Groundwater Level of a Watershed

Abstract

In the recent past, soft computing techniques have been used increasingly in various fields of science and technology for prediction purposes. In particular, Fuzzy has been found useful in the area of groundwater modeling. Since many uncertainties occur in groundwater studies. Fuzzy systems are suitable for uncertain or approximate reasoning, especially for the system with a mathematical model that is difficult to derive. Fuzzy logic allows decision-making with estimated values under incomplete or uncertain information. A major contribution of fuzzy set theory is its capability of representing vague data. As a methodology, fuzzy set theory incorporates imprecision and subjectivity into the model formulation and solution process. In the present study Mamdani Fuzzy Inference systems (MFIS) is used to predict the groundwater levels in Thurinjapuram watershed, Tamilnadu. For performance evaluation, the model predicted output was compared with the actual water level data. Simulation results reveal that fuzzy logic is an efficient and promising tool in hydrology.