ESTIMATION OF TOTAL DISSOLVED SALTS OF IRRIGATION WATER USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM

Abstract

There are numerical indicators indicating the suitability of water for agriculture irrigation. These indicators focus on total dissolved salts (TDS) as the crops can be grown are dependent on such indicator. However, it has impact on crop productivity. The laboratory analysis is usually used in TDS determenation or TDS can be determined through empirical equations by measuring the electrical conductivity of the irrigation water. On the other hand, the empirical equations did not reflect the actual situation of the used water. So, in this study, an Adaptive Neuro Fuzzy Inference System (ANFIS) was employed to estimate the concentration of total dissolved salts of irrigation water. Howevere, the water samples were collected from wells located in Huraimla Governorate, Saudi Arabia. ANFIS Sugeno model was used to formulate the system. The inputs to the ANFIS were pH, calcium, magnesium, nitrate and iron concentrations and the output was TDS concentration. The possibility of the developed system to estimate the concentration of TDS was proven through comparing with results from multiple linear regression model. The mean relative error between actual TDS and estimated TDS was 2.972% for testing data set when using ANFIS in prediction. While, by using multiple linear regression model in prediction of TDS, the mean relative error was -15.782% for testing data set between actual TDS and estimated TDS. Thus it is possible to use ANFIS to estimate the concentration of total dissolved salts and it can be used as a management tool for water irrigation purposes.