Estimation of root zone soil moisture at point scale based on soil water measurements from cosmic-ray neutron sensing in a karst catchment
Estimation of root zone soil moisture at point scale based on soil water measurements from cosmic-ray neutron sensing in a karst catchment
复制标题
基于宇宙射线中子传感土壤水分测量的喀斯特流域根区土壤水分点尺度估算
DOI：
10.1016/j.agwat.2023.108511
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发表时间：
2023-11
影响因子：
6.7
通讯作者：
Xuezhang Li;Xianli Xu;Kelin Wang;Xiaohan Li
中科院分区：
文献类型：
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作者：
Xuezhang Li;Xianli Xu;Kelin Wang;Xiaohan Li
宇宙射线中子传感（CRNS）是一种新兴的中等尺度土壤水分连续监测方法。然而，当其足迹内存在多个水文单元时，CRNS在水资源管理中的潜在应用受到限制。在此，我们提出了一种新的战略，预测点尺度SWC根区建立基于CRNS的土壤水分和改进的相对差异法。利用CRNS和EC-TM传感器分别在中尺度和点尺度上采集了喀斯特流域768 d的土壤水分数据。原始和改进的平均相对差方法预测点尺度SWCs内和有效测量深度，分别。有效测量深度10.13 ~ 19.23 cm，平均13.16 cm。土地利用类型和土壤结构对土壤剖面点尺度土壤含水量起着重要的调节作用。根据CRNS系统的SWC数据可以准确地预测根区的点尺度SWC（P< 0.001）。增加土壤湿度值的平均时间可以提高点尺度土壤含水量的预测精度。我们的研究结果表明，所提出的策略是可靠的CRNS预测SWC超过有效的测量深度。该研究为复杂水文过程地区水资源的有效管理提供了良好的前景。
The cosmic-ray neutron sensing (CRNS) is an emerging method for continuously monitoring soil water content (SWC) at an intermediate scale. However, when multiple hydrologic units are present within its footprint, the potential application of CRNS in water resources management is restricted. Here we propose a new strategy to predict point-scale SWC in root zone established on CRNS-based soil moisture and improved relative difference method. A total of 768 days of soil moisture data were collected by CRNS at the intermediate scale and EC-TM sensors at the point scale in a karst catchment. The original and improved mean relative difference methods predicted point-scale SWCs within and without the effective measuring depth, respectively. The mean effective measuring depth was 13.16 cm, ranging from 10.13 to 19.23 cm. Both land use type and soil structure played essential roles in regulating point scale SWC in the soil profile. Point-scale SWC in root zone can be predicted accurately (P< 0.001) based on SWC data derived from the CRNS system. The prediction accuracy of point scale SWC can be improved by increasing the averaging time of the soil moisture values. Our results demonstrated that the proposed strategy was reliable for CRNS to predict SWC beyond the effective measurement depth. This study provides a good perspective for effectively managing of water resources in areas with complex hydrological processes.