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

机译:通过结合卫星和再分析土壤湿度数据来估算灌溉用水使用邻近的美国

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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-resolut
机译:有效的农业水管理需要准确,及时的信息有关灌溉水的可用性和使用信息。然而,大多数有关灌溉用水的信息(IWU)缺乏运营水管理所需的客观性和时空代表性,以及土地气候相互作用的有意义表征。虽然光学遥感已被用于映射受灌溉影响的区域,但它没有物理允许估计所施加的灌溉水的实际量。另一方面,顶层土壤层中的水分含量的微波观察直接受农业灌溉实践的影响,因此可能允许对IWU进行定量估计。在这项研究中,我们将表面土壤水分(SM)检索与来自Merra-2再分析的Merra-2 Reany分析的模拟土壤水分相结合,以获得2013年期间连续的美国(Conus)的每月IWU动力学 - 2016年。该方法是通过假设Merra-2模型的水文制剂不考虑灌溉的方法,而远程感测的土壤水分检索确实含有灌溉信号。对于许多康群灌溉热点,估计的空间灌溉模式与灌溉区域的参考数据显示良好。此外,在集中灌溉区域中,观察到的IWU的时间动态对于局部灌溉实践的辅助数据有意义。国家聚合的平均IWU体积来自SmaP和Merra-2土壤水分组合的源自良好的相关性与统计报告的状态级灌溉戒烟(ICN),但系统地低估它们。我们认为,这种差异主要归因于采用卫星土壤水分检索的粗糙空间分辨率,这未能解决局部灌溉实践。因此,更高的腐败

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