Estimating irrigation water use over the contiguous United States by combining satellite and reanalysis soil moisture data
Estimating irrigation water use over the contiguous United States by combining satellite and reanalysis soil moisture data
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DOI：
10.5194/hess-2018-388
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发表时间：
2018-08
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通讯作者：
Felix Zaussinger;W. Dorigo;A. Gruber;A. Tarpanelli;Paolo Filippucci;L. Brocca
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作者：
Felix Zaussinger;W. Dorigo;A. Gruber;A. Tarpanelli;Paolo Filippucci;L. Brocca
抽象的。有效的农业用水管理需要关于灌溉用水的供应和使用的准确和及时的信息。然而，大多数现有的信息灌溉用水（IWU）缺乏客观性和时空的代表性需要业务水管理和有意义的表征土地-气候相互作用。虽然光学遥感已被用于绘制受灌溉影响的地区的地图，但它实际上并不允许对实际灌溉水量进行估计。另一方面，微波观测的土壤表层中的水分含量的直接影响农业灌溉的做法，从而有可能允许的IWU的定量估计。在本研究中，我们将来自星载SMAP、AMSR 2和ASCAT微波传感器的联合收割机表层土壤水分反演与来自MERRA-2再分析的模拟土壤水分结合起来，以推导出2013年至2016年期间美国本土（CONUS）的每月IWU动态。该方法是由假设的水文制定的MERRA-2模型不考虑灌溉，而遥感土壤水分反演包含灌溉信号。对于许多CONUS灌溉热点，估计的空间灌溉模式显示出良好的协议与参考数据集的灌溉面积。此外，在集中灌溉地区，观测到的IWU的时间动态是有意义的辅助数据对当地的灌溉做法。来自SMAP和MERRA-2土壤水分组合的国家汇总平均IWU卷显示出良好的相关性与统计报告的国家级灌溉取水量，但系统地低估了他们。我们认为，这种差异可以主要归因于粗糙的空间分辨率的卫星土壤水分反演，未能解决当地的灌溉做法。因此，需要更高分辨率的土壤水分数据，以进一步提高IWU制图的精度。
Abstract. Effective agricultural water management requires accurate and timely information on the availability and use of irrigation water. However, most existing information on irrigation water use (IWU) lacks the objectivity and spatio-temporal representativeness needed for operational water management and meaningful characterisation of land-climate interactions. Although optical remote sensing has been used to map the area affected by irrigation, it does not physically allow for the estimation of the actual amount of irrigation water applied. On the other hand, microwave observations of the moisture content in the top soil layer are directly influenced by agricultural irrigation practices, and thus potentially allow for the quantitative estimation of IWU. In this study, we combine surface soil moisture retrievals from the spaceborne SMAP, AMSR2, and ASCAT microwave sensors with modelled soil moisture from MERRA-2 reanalysis to derive monthly IWU dynamics over the contiguous United States (CONUS) for the period 2013–2016. The methodology is driven by the assumption that the hydrology formulation of the MERRA-2 model does not account for irrigation, while the remotely sensed soil moisture retrievals do contain an irrigation signal. For many CONUS irrigation hot spots, the estimated spatial irrigation patterns show good agreement with a reference data set on irrigated areas. Moreover, in intensively irrigated areas, the temporal dynamics of observed IWU is meaningful with respect to ancillary data on local irrigation practices. State-aggregated mean IWU volumes derived from the combination of SMAP and MERRA-2 soil moisture show a good correlation with statistically reported state-level irrigation water withdrawals but systematically underestimate them. We argue that this discrepancy can be mainly attributed to the coarse spatial resolution of the employed satellite soil moisture retrievals, which fails to resolve local irrigation practices. Consequently, higher resolution soil moisture data are needed to further enhance the accuracy of IWU mapping.