<p>This study evaluated an irrigation decision support system (DSS) for irrigation planning based on actual farm conditions and types of irrigation systems in eight farms and four villages in the Mahabad Plain irrigation and drainage network in the Urmia Lake basin with farmer participation in irrigation planning decision. This system allows farmers to determine the actual irrigation needs of each crop based on various factors such as soil texture type, crop growth stages, climatic conditions, weather forecast, farm or garden shape, landholding status, and the type of irrigation system available in the farm or garden for precise irrigation. Data were collected through field measurements and Participatory Rural Appraisal (PRA) techniques. The results showed that optimized irrigation with DSS resulted in significant agricultural water savings, 41% for drip systems and 14% for sprinkler systems compared to control plots. In drip systems, the greater savings were due to farmers’ concerns of over irrigation because of erratic water delivery. Water use, however, increased slightly in surface irrigation systems by 2.8% due to improve advancement in control mechanisms and better end irrigation timing. Furthermore, the productivity of water resources improved with the implementation of the DSS for all systems, 3.87% in drip, 7.20% in sprinkler, and 1.5% in surface irrigation systems. Proper and timely irrigation scheduling increases water productivity, as the study highlights. Regarding surface irrigation, the study recommends system optimizations, such as reducing plot lengths to enhance DSS efficiency. Collectively, the results emphasize the significant of employing innovative approaches and integrating advanced technologies like DSS for improving irrigation automation and efficiency. Active stakeholders contributed significantly to determining optimal design sustainability and performance improvements for the collaborative irrigation systems.</p>