Potato is one of the most important crops for meeting food needs worldwide.The water requirement of this crop is high, and its yield is sensitive to the amount of irrigation water. Studying different amounts of irrigation water in irrigation methods is not only expensive but also time-consuming, so it is necessary to use water-driven crop models such as AquaCrop. This research aims to evaluate the accuracy of AquaCrop for simulating potato yield and biomass in Iran at three irrigation levels (full irrigation [FI] stands for 100%, I 80 for 80% and I 65 for 65% of the crop water requirement) via two irrigation methods (furrow irrigation and drip irrigation). For furrow irrigation, the normalized root mean square error values in the FI, I 80 and I 65 treatments varied between 17% and 28% for yield and 12% and 17% for biomass. These results for drip irrigation were 17%-22% (yield) and 9%-18% (biomass). For furrow irrigation, the average root mean square error values for potato biomass and yield were 0.89 and 0.68 t ha À1 , respectively. The corresponding results for drip irrigation were 0.79 and 0.64 t ha À1 , respectively. Based on all the results, the accuracy of AquaCrop was good for both irrigation methods, even though its accuracy under severe water stress conditions (I 65 ) for the drip irrigation method was better than that for furrow irrigation.