Estimation of crop water requirement (CWR) is key to the rational water use and agricultural water conservation in arid regions. Using remote sensing data to obtain long-term CWR over large areas helps water resources management in water-scarce areas. This study, taking the Kaidu-Kongqi River basin in arid northwest China as the study area, investigated the feasibility of synergistically using phenological characteristics, Savitzky-Golay filter, harmonic analysis and decision tree to extract crop planting structures (CPS) from MODIS EVI, and meanwhile analyzed the spatiotemporal variation in the estimated CWR. The results show that the integrated method for CPS identification and extraction is feasible and reliable with the classification accuracy over 80%. The mid-season stage requires the most water and cash crops need more water than cereal crops. Summer accounts for 69% the total growing season water use. The significant increase in the area of high water demand crops such as cotton raised the total CWR of the basin surging from 14.91× 10⁸m³ in 2000 to 34.92×10⁸m³ in 2017. The spatial distribution of CWR was more related to crop types and area than to climatic conditions. Controlling the expansion of arable land and optimizing the agricultural planting structure remain important tasks for the sustainable management of water resources in the basin.

估算作物需水量（CWR）是干旱地区合理用水和农业节水的关键。利用遥感数据获得大面积地区的长期CWR，有助于缺水地区的水资源管理。这项研究以西北干旱地区的开都-孔奇河流域为研究区域，研究了利用物候特征，Savitzky-Golay滤波器，谐波分析和决策树协同从MODIS EVI中提取农作物种植结构（CPS）的可行性，同时分析了估计的CWR的时空变化。结果表明，集成化的CPS识别与提取方法可行，可靠，分类准确率达80％以上。旺季需要最多的水，经济作物比谷物作物需要更多的水。夏季占生长期用水总量的69％。棉花等高需水农作物面积的显着增加使流域的总CWR从14.91×10激增至⁸米³在2000至34.92×10 ⁸米³在2017年CWR的空间分布是更相关的作物种类和面积比的气候条件。控制耕地面积的扩大和优化农业种植结构仍然是流域水资源可持续管理的重要任务。