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  • 标题:A measurement, quantitative identification and estimation method(QINRW) of non-rainfall water component by lysimeter
  • 本地全文:下载
  • 作者:Qiang Zhang ; Sheng Wang ; Ping Yue
  • 期刊名称:MethodsX
  • 印刷版ISSN:2215-0161
  • 电子版ISSN:2215-0161
  • 出版年度:2019
  • 卷号:6
  • 页码:2873-2881
  • DOI:10.1016/j.mex.2019.11.012
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Graphical abstractDisplay OmittedAbstractNon-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.
  • 关键词:Non-rainfall water(NRW);QINRW(quantitative identification method for NRW);Lysimeter;Land surface water (LSW) balance;Dew;Water vapor adsorption(WVA);Fog
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