Irrigated agricultural expansion is one of the main reasons for water scarcity in the Lake Urmia basin. Although previous studies have analyzed the impact of cropland expansion on the Lake Urmia Shrinkage, there is a lack of comprehensive annual assessment of historical irrigation expansion in the Lake Urmia basin and its impact on water resources of this region. In this study, we developed an automatic and efficient workflow using Landsat and Gravity Recovery and Climate Experiment (GRACE) data, GRACE Follow-On (GRACE-FO) data, and a sample migration technique within the Google Earth Engine cloud computing platform to comprehensively investigate the impact of irrigated agricultural expansion on the shrinkage of Lake Urmia, as one of the most severe environmental crisis in the world. Additionally, using the global surface water data, we proposed a fully automatic procedure to obtain reference samples from water bodies. The Lake Urmia basin was first classified into the water, irrigated, and Non-Water/Irrigated classes using the random forest algorithm. The average overall accuracy of the produced annual land cover maps during 1987–2020 was 92.2%, representing the great potential of the developed method for land cover mapping. We found that the irrigated lands expanded by nearly 890 km² during the study period. Coincident with this change, although the area of water bodies in Lake Urmia partially recovered after 2015 (reached from 1,050 km² in 2015 to 3,370 km² in 2020), it is currently far beyond its original condition (i.e., ∼5,400 km², average record during 1987–2000). Moreover, the information of the Terrestrial Water Storage (TWS) from the GRACE and GRACE-FO data between 2003 and 2020 showed a dramatic decrease in TWS level (∼−11.5 cm). The findings of this research will assist the local stakeholders and authorities to better understanding the environmental costs of irrigation expansion in the Lake Urmia basin.

灌溉农业扩张是造成乌尔米亚湖流域缺水的主要原因之一。虽然之前的研究分析了耕地扩张对乌尔米亚湖收缩的影响，但缺乏对乌尔米亚湖流域历史灌溉扩张及其对该地区水资源影响的年度综合评估。在本研究中，我们使用 Landsat 和重力恢复与气候实验 (GRACE) 数据、GRACE Follow-On (GRACE-FO) 数据以及 Google Earth Engine 云计算平台内的样本迁移技术开发了一种自动高效的工作流程，以全面调查灌溉农业扩张对乌尔米亚湖萎缩的影响，这是世界上最严重的环境危机之一。此外，利用全球地表水数据，我们提出了一种从水体中获取参考样本的全自动程序。首先使用随机森林算法将乌尔米亚湖流域分为水类、灌溉类和非水/灌溉类。1987-2020 年期间制作的年度土地覆盖图的平均整体精度为 92.2%，表明所开发的土地覆盖制图方法潜力巨大。我们发现灌溉地扩大了近 890 公里²在学习期间。与这一变化同时发生，虽然乌尔米亚湖水体面积在2015年后部分恢复（从2015年的1,050 km ²到2020年的3,370 km ²），但目前已远远超出其原始状态（即~5,400 km ²， 1987-2000 年的平均记录）。此外，来自 2003 年至 2020 年 GRACE 和 GRACE-FO 数据的陆地蓄水量（TWS）信息显示 TWS 水平急剧下降（~-11.5 cm）。这项研究的结果将有助于当地利益相关者和当局更好地了解乌尔米亚湖流域灌溉扩张的环境成本。