The present study investigates different operating systems' potential to be selected as a reliable alternative in the modernization of agricultural water distribution using a set of indices representing the sustainable development goals (SDGs). These indices include economic perspectives ("the implementation cost of the operating system"; "economic value of water"; "The opportunity cost" indices), environmental aspects ("water withdrawal from the aquifer"; "carbon dioxide emissions" indices), social viewpoint ("vandalism probability of on-site equipment"; "equity of agricultural water distribution" indices), and technical considerations (such as "efficiency of water distribution" index). The hydrodynamic simulation model was developed and calibrated to simulate water distribution in Qazvin Irrigation District, central Iran, in the status quo.Five practical systems-including manual operation (A1, A2), Hydro-mechanical gates (A3), and automatic operation (A4, A5)-were developed in MATLAB and integrated the hydrodynamic model. Agricultural water distribution practices are conducted for individual alternatives A1-A5, and the SDGs indices were determined quantitatively.The multi-criteria decision-making method was used to rank the indices based on their compliance with the SDGs indices. TOPSIS method was employed in non-fuzzy status and fuzzy state to prioritize the modernization alternatives A1-A5. The relative weights of the indices were determined in a fuzzy state by the opinion of 30 experts, and that of the non-fuzzy state was specified by the Shannon-Entropy method. The results show that using the Shannon-Entropy method, the "aquifer harvest index" with the weight of 0.16 is the most influential factor to meet the SDGs and the "vandalism probability of on-site equipment" index with 0.028 weight is the least active index. The final results indicate that the modernization alternatives A1-A5 are scored 0.35, 0.33, 0.30, 0.68, and 0.70, respectively, in the TOPSIS technique, and 0.29, 0.18, 0.14, 0.40, 0.74 using the fuzzy TOPSIS technique.