Combining static and portable Cosmic ray neutron sensor data to assess catchment scale heterogeneity in soil water storage and their integrated role in catchment runoff response
Combining static and portable Cosmic ray neutron sensor data to assess catchment scale heterogeneity in soil water storage and their integrated role in catchment runoff response
复制标题
DOI：
10.1016/j.jhydrol.2021.126659
复制
发表时间：
2021-10
影响因子：
6.4
通讯作者：
Katya Dimitrova-Petrova;R. Rosolem;C. Soulsby;M. Wilkinson;A. Lilly;J. Geris
中科院分区：
文献类型：
--
作者：
Katya Dimitrova-Petrova;R. Rosolem;C. Soulsby;M. Wilkinson;A. Lilly;J. Geris
土壤含水量（SWC）是许多地表过程（如径流生成）的关键变量，因此了解其在流域尺度上的时空动态可以用于约束和评估水文模型。宇宙射线中子传感器（CRNS）技术提供公顷尺度的SWC数据，随着移动CRNS的最新进展，这种信息价值可以扩展到集水区尺度，尽管在校准方面仍然存在挑战，特别是在潮湿环境中。本研究提出了一种适用于湿润环境的新方法，用于探索集水区尺度下近地表土壤水储存（SNS）动态的时空变化及其在半分布式降雨径流模型校准中的价值。对于苏格兰一个湿润的混合农业集水区（~10 km2），我们将具有景观代表性位置的静态CRNS约4年的SWC数据与四个关键土壤-土地利用（SLU）单元的“快照”相结合，生成了每个单元的SWC时间序列。SLU单元包括自由排水的矿物质和不排水的富含有机物的土壤的混合物，分别支持作物和牲畜养殖和沼地。我们还探讨了标准CRNS校准方法在SLU单元中的适用性，并发现富有机质土壤需要适应SWC的参数校准。沼地SLU单元与其他农业SLU单元的SWC动态差异最大。为了探索联合CRNS方法产生的附加信息，我们通过在单个SLU单元中使用SNSdynamics来校准半分布式降雨-径流模型（HBV-light）。与集总方法相比，半分布式SWC信息和模型结构有助于产生更好的约束流，并进一步改善流域内部存储动态的表示。最终，降雨径流模型中不同SLU单位的SWC时间序列的值将取决于模型结构和景观内sns动态变化的程度。该研究表明，在解决与富有机质土壤和潮湿环境相关的各种挑战的同时，使用便携式CRNS调查扩大永久安装CRNS传感器的信息价值的潜力，尽管需要在不同的环境中进行测试以评估更广泛的适用性。
Soil water content (SWC) is a key variable in many land surface processes, such as runoff generation, thus knowledge about its spatiotemporal dynamics at the catchment scale can be useful for constraining and evaluating hydrological models. Cosmic ray neutron sensor (CRNS) technology provides hectare scale SWC data, and with recent advances in mobile CRNS such information value can be extended to the catchment scale, although challenges in calibration remain, especially in wet environments. This study presents a new methodology suited for humid environments to explore spatio-temporal variability in near-surface soil water storage (SNS) dynamics at the catchment scale and its value in semi-distributed rainfall-runoff modelling calibration. For a humid mixed-agricultural catchment (~10 km2) in Scotland, we combined ~ 4-years of SWC data from a static CRNS at a landscape-representative location with “snapshots” at four key soil-land use (SLU) units to produce SWC timeseries for each one of those units. The SLU units involved a mixture of freely draining mineral and poorly draining organic-rich soils, supporting crop and livestock farming and moorland, respectively. We also explored the suitability of the standard CRNS calibration approach in the SLU units and found that the organic-rich soils required an adapted parameter calibration for SWC. The moorland SLU unit had the greatest difference in SWC dynamics from the other agricultural SLU units. To explore the additional information generated by the combined CRNS approach, we calibrated a semi-distributed rainfall-runoff model (HBV-light) by using SNSdynamics in individual SLU units in addition to streamflow. Compared to a lumped approach, the semi-distributed SWC information and model structure helped produce better constrained stream flows and further improved the representation of catchment internal storage dynamics. Ultimately, the value of the SWC time series for different SLU units in rainfall-runoff modelling will depend on model structure and the degree to which SNSdynamics vary within the landscape. This study showed the potential of expanding the information value of permanently installed CRNS sensors using portable CRNS surveys while addressing the various challenges related to organic-rich soils and wetter environments, although testing in different environments would be required to evaluate the wider applicability.