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 N₀‐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 N₀‐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.

中文翻译：

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基于物理的站点特定转换函数估算宇宙射线中子的土壤湿度

为了促进使用宇宙射线中子（CRN）绘制异质景观中的土壤水分，我们需要开发一种方法，该方法可以可靠地估算土壤水分，而不必沿调查路线的每个点收集100多个土壤样品。在这项研究中，这种方法是使用具有物理数字的MCNP中子输运代码的物理建模方法开发的。目的是确定特定地点的转换函数，以便从CRN中估算主要土地覆盖层的土壤水分。在这里，我们在三个具有相似矿物土壤组成但土地覆盖不同的田间地点评估了该方法。首先，我们确保所开发的模型捕获跨站点的中子传输行为中最重要的差异。为了这，我们使用测得的热中子和超中子的时间序列和高度剖面。然后，我们将从网站特定转换函数获得的估算值与标准N ₀校准功能。最后，我们将CRN土壤湿度估算值与独立的土壤湿度估算值进行比较。总体而言，针对具体地点的模型与观察到的中子强度趋势一致。特定地点的土壤水分与N ₀估算的土壤水分相似，这导致可比较的统计量。我们表明，各种土地覆盖对超热中子的数量和土壤湿度敏感性有显着影响，而热中子的影响程度较小。因此，可以使用热中-上中子比率来识别土地覆盖类型，从而确定沿调查路线上每个点的土壤湿度估算的适当转换函数。