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Cosmic Ray Neutron Soil Moisture Estimation Using Physically Based Site-Specific Conversion Functions

机译：宇宙雷中子土壤水分估计使用物理基地特定的转换功能

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In order to advance the use of the cosmic ray neutrons (CRNs) to map soil moisture in heterogeneous landscapes, we need to develop a methodology that reliably estimates soil moisture without having to collect 100+ soil samples for each point along the survey route. In this study, such an approach is developed using physically based modeling with the numerical MCNP neutron transport code. The objective is to determine site-specific conversion functions to estimate soil moisture from CRNs for the dominant land covers. Here, we assess this methodology at three field sites with similar mineral soil composition, but different land covers. First, we ensure that the developed models capture the most important differences in neutron transport behavior across sites. For this, we use measured time series and height profiles of thermal and epithermal neutrons. Then, we compare the estimates obtained from the site-specific conversion functions with the standard N-0-calibration function. Finally, we compare the CRN soil moisture estimates with independent soil moisture estimates. Overall, the site-specific models are in agreement with the observed trends in neutron intensities. The site-specific soil moisture is similar to the N-0-estimated soil moisture, which results in comparable statistical measures. We show that various land covers have a significant impact on the amount and soil moisture sensitivity of epithermal neutrons, while the thermal neutrons are affected to a less degree. Thereby, thermal-to-epithermal neutron ratios can be used to identify the land cover type and thereby the appropriate conversion function for soil moisture estimation for each point along the survey route.
机译：为了推进宇宙射线中子（CRNS）以在异质景观中映射土壤水分，我们需要开发一种方法，可靠地估计土壤水分，而无需为沿着调查路线收集100多个土壤样品。在本研究中，使用与数值MCNP中子传输代码的物理学建模开发这种方法。目的是确定特定于现场的转换作用，以估算来自CRN的土壤水分为主要陆地覆盖。在这里，我们在具有相似矿物土壤组成的三个田间地点评估该方法，但不同的陆地覆盖物。首先，我们确保开发的模型捕获跨地站点中子传输行为最重要的差异。为此，我们使用测量的热和骨头中子的时间序列和高度轮廓。然后，我们将从站点特定的转换函数获得的估计进行比较，使用标准的N-0校准函数。最后，我们将CRN土壤水分估算与独立的土壤水分估算进行比较。总的来说，特定于网站的模型与观察到的中子强度趋势一致。特异性土壤水分类似于N-0估计的土壤水分，这导致了可比的统计措施。我们表明，各种陆地覆盖物对膜状中子的数量和土壤湿度敏感性有重大影响，而热中子受到较少程度的影响。由此，可以使用热对膜中子比来识别陆地覆盖型，从而适当转化函数用于沿着调查路线的每个点的土壤水分估计。

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