Agriculture and crop production is the sector with the highest water demand, and because of water shortages and an unbalanced distribution of natural resources in China, improving the efficiency of agricultural water use is essential. In this study, we quantified the total water footprint (WF) of major crop products in Northwest China using the Penman–Monteith formula. The logarithmic mean divisor index (LMDI) was used to explain the four factors driving the spatial and temporal differences in the WFs of the major crops in five provinces and regions in Northwest China. The results showed that from 2006 to 2015, the total WF of the major crops was increasing overall. From a temporal perspective, the crop area and yield effects, which were the factors driving the overall increase in the WF, positively impacted the overall change in the WF of the major crops in Northwest China. The effects of the virtual water content (VWC) and crop structure were both volatile. The effect of the crop structure made a relatively small contribution, while the effect of the VWC played a significant role in changing the overall WF. From a spatial perspective, the changes in the VWC and crop structure negatively inhibited the increase of the WF, widening the difference between these provinces and regions and Shanxi. The increased yields in Xinjiang most clearly increased the WF, followed by those in Ningxia, Qinghai, and Gansu. In comparison with Shanxi, in all the provinces and regions except Xinjiang, the change in cultivated area was less effective in promoting the WF. Therefore, scientific planting plans should be developed for adapting to climate change, considering the differences in natural features among various provinces and regions. Water conservation and advanced agricultural technology should be promoted to enhance the sustainability of agricultural development.

The intelligent information retrieval model discussed in this paper is constructed by multi-agent. Currently, BDI cognitive theory is accepted widely by the scholars of this field, but the related researches mainly focus on the theoretical derivation and presentation of symbols, lack of model facing practical application. In this article, a dynamic rule-based reasoning model is proposed. The model based on BDI theory is an expression of agent intelligence. The basic logical reasoning of the BDI theory is extended in this article. The author not only introduces several functions to study the dynamic changes of agents' mental state, but also give a detailed description of how to use the theory of production rules to express BDI-based reasoning. This article also studies and designs the agent communication mechanism in MAS. Finally, the intelligent information retrieval system is designed and implemented with the idea of AOP.