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• W2991574996 abstract "Non-rainfall water (NRW) has an important impact on the ecosystem, especially in arid and semi-arid areas. It is also an important component in the surface water cycle. Currently, there is not any instrument that can directly measure NRW and it can only be estimated by observation data. Presently, there is no standard method available to estimate each constituents of NRW. With some research not distinguishing each component of NRW, this inaccurate methodology will consequently lead to a greater scope for statistical error. Naturally, this compounds the difficulty in evaluating the role of NRW on the ecosystem and land surface water cycle. Therefore, this paper proposes a new methodology for separating NRW components, which is called QINRW(A Quantitative Identification method for NRW). Based on lysimeter data and combined with meteorological data, this method distinguishes the physical properties of each component of NRW. Consequently, the amount of NRW can be obtained. It is also suitable for microlysimeter data to be applied in QINRW.The advantages of QINRW are three points:•It is more accurate for excluding the precipitation and dry deposition information from lysimeter data, which was not mentioned in previous studies;•It can obtain each component of NRW;•The identification process is more rigorous and clear in theory so far." @default.
• W2991574996 created "2019-12-05" @default.
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• W2991574996 date "2019-01-01" @default.
• W2991574996 modified "2023-10-16" @default.
• W2991574996 title "A measurement, quantitative identification and estimation method(QINRW) of non-rainfall water component by lysimeter" @default.
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• W2991574996 doi "https://doi.org/10.1016/j.mex.2019.11.012" @default.
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