It is necessary to use different planning models, including decision support systems (DSSs), to allocate water resources. For this purpose, in this study, an irrigation decision support system (IDSS) was developed to improve irrigation management in the farming fields of Mahabad Plain located to the south‐east of Lake Urmia. Next, the compatibility of the IDSS with the conditions of the Mahabad irrigation and drainage network, water and soil resources, meteorological data and soil moisture (SM) were investigated. The statistical indices of coefficient of determination (R2), root mean square error (RMSE), normalized root mean square error (NRMSE), Nash–Sutcliffe efficiency (EF) and Wilmot agreement (d) were used to evaluate the adaptability of the IDSS. The results showed that the IDSS has reasonable compatibility with soil and water resources, crop yield and meteorological data. Irrigation scheduling provided by the IDSS led to a 13.9% reduction in water consumption and a 6.7% increase in crop yield. The IDSS estimated minimum and maximum temperature and sunshine hours to a satisfactory degree and relative humidity with an acceptable degree (NRMSE = 0.72–0.77) compared to regional synoptic station data. The performance of the IDSS in simulating SM is ranked from good to well (NRMSE = 0.75–0.83). The results indicate that the IDSS has a sufficient performance in estimating meteorological and soil moisture data with R2 = 0.90, RMSE = 4.65, NRMSE = 0.78, EF = 0.76 and d = 0.80. In addition, the IDSS provides the optimal irrigation schedule by considering the ability to deliver water from the irrigation and drainage network to the third‐grade canal and agricultural fields as the upstream condition.