美国大陆长序列高时空分辨率（逐月1km）灌溉用水量数据（2000-2020）

全球约70%的取水用于农业，而灌溉用水占总耗水的90%以上。受灌溉水源、灌溉设施、作物种植类型等影响，灌溉用水量空间异质性大。灌溉水可通过蒸散消耗，或形成土壤水储存在根区土壤层中，而超过饱和带的部分将补给地下水。以上灌溉过程的复杂性导致灌溉用水量估算难度极大、充满挑战。
基于灌溉条件下的土壤水量平衡，考虑灌溉用水量的多重构成，本研究系统推导了灌溉用水量计算公式，提出了利用遥感反演的实际蒸散和模型模拟的实际蒸散及土壤水分，估算灌溉用水量的新方法，并生成了美国大陆2000–2020年高时空分辨率（1 km，逐月）灌溉用水量数据集。经美国州、县尺度灌溉取用水统计值及与以往研究对比验证，结果表明本研究提出的方法具备刻画灌溉多过程的物理基础，且能够获得高时空分辨率且精度更高的灌溉用水量数据。

Approximately 70% of global water withdrawals are used for agriculture, and irrigation water accounts for over 90% of total water consumption. Irrigation water use exhibits strong spatial heterogeneity, which is influenced by factors such as irrigation water sources, irrigation infrastructure, and crop planting types. Irrigation water can be consumed via evapotranspiration, or form soil water stored in the root zone soil layer. The portion exceeding the saturation zone will recharge groundwater. The complexity of the aforementioned irrigation processes makes irrigation water use estimation extremely difficult and challenging. Based on the soil water balance under irrigation conditions and considering the multiple components of irrigation water use, this study systematically derived the formula for irrigation water use calculation, proposed a novel method for estimating irrigation water use by utilizing remotely sensed retrieved actual evapotranspiration, model-simulated actual evapotranspiration, and soil moisture, and generated a high spatiotemporal resolution (1 km, monthly) irrigation water use dataset for the Contiguous United States from 2000 to 2020. Verified by irrigation water withdrawal and consumption statistics at the state and county scales in the United States and comparisons with previous studies, the results show that the method proposed in this study has a physical basis for characterizing multiple irrigation processes, and can obtain irrigation water use data with high spatiotemporal resolution and higher accuracy.

搜集汇总

背景与挑战

背景概述

该数据集提供了美国大陆2000-2020年高时空分辨率（逐月1km）的灌溉用水量数据，采用遥感反演和模型模拟方法生成，适用于区域尺度的水资源管理研究。数据以tif格式存储，便于使用GIS或MATLAB等工具进行空间分析。