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Agricultural water and land, which are intricately related, are the two most critical resources for food production. However, the sustainability of agricultural water and land resources is faced with challenges due to intensive human activities and climate change. This paper builds crop water footprint model under uncertainty, and evaluates regional crop (rice, maize and soybean) blue and green waterfootprint under different probability. On this basis, the water footprint characteristics and differences of crops were analyzed. Then, an optimization model of crop planting structure with the objectives of minimum blue water footprint and the maximum agricultural net benefit was constructed and Monte Carlo simulation method was used to solve the model. The model can take into account the crop water footprint at different probabilities, enabling decision makers to combine years of information to make better decisions. Then, the model was applied to the Hulan River Irrigation District, and three scenarios were designed to analyze the optimal planting structure under different conditions. Under different scenarios, the optimization results have certain differences, but overall, increasing the area of crop cultivation, especially rice, has a good role in promoting regional agricultural development. Due to the optimization of the planting structure, the net benefit of the irrigation area increased by 7%, 15% and 5% in each of the three scenarios. Solutions are valuable for producing scientific alternatives that help decision makers determine the water and soil relationship management policies they need. (C) 2018 Elsevier Ltd. All rights reserved.