Conventional application of nitrogen fertilizers via irrigation is likely to be responsible for the increased nitrate in groundwater of the irrigated agricultures. Thus, appropriating water and nutrient management is necessary to minimize groundwater pollution and to maximize nutrient use's efficiency as well as crop production. To fulfill these requirements, drip fertigation is an important alternative. Designing and operation of drip fertigation system requires understanding of nutrient leaching behavior in cases of shallow rooted crops such as potatoes, which cannot extract nutrient from lower soil depth. In first part of the present studies HYDRUS-2D package was applied to model and simulate nitrate leaching from tape irrigation for varying emitter discharge rates and various amounts of fertilizer doses. In the second part of the present study the capability of Mamdani fuzzy inference system (MFIS) and an adaptive network-based fuzzy inference system (ANFIS) were investigated with regard to prediction of nitrate leaching, obtained from HYDRUS simulation. The correlation coefficient, normalized root mean square error, and relative mean absolute eroror percentage between the data obtained by HYDRUS-2D and the estimated values using ANFIS and MFIS modeles were 0.99, 0.023, 0.66, 0.99, 0.086 and 2.38 respectively. ANFIS model was more accurate than the MFIS model. Key Words Nitrate leaching, HYDRUS-2D, ANFIS, Fuzzy inference system, Genetic algorithms, Potato.
