Abstract: Net irrigation requirement is the major component of agricultural water use. In this study, the regional net irrigation requirement of agricultural area in Shiyang river basin in semi-arid region of Northwest China was analyzed. Based on the zones of local agricultural water use, the key factors are chosen by driving factor analysis (1959-2005), and then regional net irrigation requirement was simulated using multiple-linear regression (MLR), artificial neural network (ANN) and Ensemble ANN models. Then discrimination time-series Monte-Carlo (MC) simulation is used for inputs uncertainty analysis of these models. Results suggest that compared with MLR and ANN, the Ensemble ANN model show better ability in the simulation of regional net irrigation requirement with smallest error and lowest uncertainty index.