IRRIGATION OPTIMIZATION BY THE USE OF FUZZY LOGIC TECHNOLOGY

Abstract

The aim of this study was to develop a Fuzzy Inference System (FIS) to optimize the water requirements as per standards for irrigation purposes. There are three major inputs in FIS including water quality, field capacity and water quantity while one output named as optimized irrigation. Firstly water quality FIS was developed by using three important such as electrical conductivity (EC), pH and sodium absorption ratio (SAR) with excellent, good, permissible and harmful membership functions for inputs and same for output. To create fuzzy inference system for water quantity, five membership functions were developed as very low, low, middle, high and very high considering the discharge of water available in the Sakarya River, Turkey and low, medium and high as fuzzy membership functions for field capacity were also developed. To complete the FIS of the study, very low, low, medium, high and very high fuzzy membership functions were developed for a fuzzy optimized irrigation as the output of the system and the main finding of the study. In this study a practical solution based on FIS is presented for Sakarya River Basin in Turkey to meet irrigation objectives locally. The findings clearly indicate that fuzzy logic method may successfully interpret complex conditionsto classify the optimized irrigation with respect to water quality, water quantity discharge and soil filed capacity. The developed fuzzy model was validated by using data collected from Pamukova, Dogancay and Adatepe three monitoring stations of Sakarya River during 1993-2013.