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Estimating irrigation water use over the contiguous United States by combining satellite and reanalysis soil moisture data

机译:通过结合卫星和重新分析的土壤水分数据估算美国连续的灌溉用水

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摘要

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 spatiotemporal representativeness needed for operational water management and meaningful characterization 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 (SM) retrievals from the spaceborne SMAP, AMSR2 and ASCAT microwave sensors with modeled 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 (IWW) 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.
机译:有效的农业用水管理需要及时,准确地提供灌溉用水的信息。但是,有关灌溉用水的大多数现有信息(IWU)缺乏运营用水管理和有意义的土地-气候相互作用特征所需的客观性和时空代表性。尽管光学遥感已用于绘制受灌溉影响区域的地图,但它在物理上无法估算实际灌溉水量。另一方面,对土壤表层水分含量的微波观测直接受到农业灌溉实践的影响,因此潜在地允许对IWU进行定量估算。在这项研究中,我们结合了从星载SMAP,AMSR2和ASCAT微波传感器中获取的地表土壤水分(SM)与来自MERRA-2再分析的模型化土壤水分,以得出2013年以来美国(CONUS)连续月的IWU动态2016。该方法基于以下假设:MERRA-2模型的水文公式不考虑灌溉,而遥感土壤水分反演确实包含灌溉信号。对于许多CONUS灌溉热点,估计的空间灌溉模式与灌溉区域的参考数据集显示出很好的一致性。此外,在集约灌溉地区,观察到的IWU的时间动态对于当地灌溉实践的辅助数据是有意义的。从SMAP和MERRA-2土壤湿度的组合得出的州汇总平均IWU量与统计报告的州一级灌溉用水量(IWW)表现出很好的相关性,但系统地低估了它们。我们认为,这种差异主要归因于所用卫星土壤水分取回的粗糙空间分辨率,这无法解决当地的灌溉习惯。因此,需要更高分辨率的土壤水分数据来进一步提高IWU测绘的准确性。

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