Hydrogeodesy - Going deep: combining CRNS with other non-invasive soil moisture measurements with varying integration depths

水文大地测量学 - 深入研究：将 CRNS 与其他具有不同集成深度的非侵入性土壤湿度测量相结合

• 批准号: 414048032
• 负责人: Dr. Theresa Blume
• 金额: --
• 依托单位: Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum (GFZ)
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/414048032?language=en
• 关键词: Hydrogeodesy; Going; deep; combining; CRNS

The main goal of the module Hydrogeodesy (HG) within the RU Cosmic Sense is to extrapolate the CRNS (Cosmic Ray Neutron Sensing) soil moisture beyond its near-surface sensing depth to the entire unsaturated zone. A unique data set of depth-resolved soil moisture at the CRNS footprint and at the catchment scale will be generated to develop and test depth-scaling approaches, assuming that CRNS observations provide valuable information for assessing the water content in the deeper vadose zone. We combine CRNS with two other non-invasive monitoring techniques with a similar horizontal footprint as CRNS (in the order of 100 m) but with different vertical integration depths: GNSS reflectometry (GNSS-R) with a depth of a few centimeters, and terrestrial gravimetry which integrates over the entire vadose zone. At field sites with collocated sensors of the three techniques (CNRS, GNSS-R and gravimeters) and with in-situ sensor profiles and/or lysimeters, we will merge the observations and derive time-variable functional relationships between the soil moisture variations at different depths. Main objectives of this project include: 1) Increasing the CRNS observational window by vertical extrapolation at the local footprint and at the regional scale based on depth-scaling approaches. The application and evaluation of the depth-scaling approaches at the regional scale will be enabled by the campaign-based combination of stationary and roving CRNS with gravimetry on a spatially distributed network of support points (during RU joint field campaigns). This will also facilitate extrapolating remotely sensed soil moisture to greater depths.2) Comparing and correlating soil moisture dynamics of the different monitoring techniques from a twofold perspective: a) understanding in which way the respective time series are related to each other with regard to correlation, time lags and signal damping between observations of different integration depths and b) assessing the respective data quality and uncertainties. 3) Advancing terrestrial gravimetry as a complementary technique to CRNS, adding information on water storage dynamics at larger depths. 4) Advancing the CRNS method by investigating the CRNS signal response to horizontal and vertical soil moisture heterogeneities within the footprint. This includes a comparative response analysis of neutrons with different energy levels at sites with either a natural or artificially induced pronounced heterogeneity in moisture conditions, and exploring the value of both CRNS and gravimeter observations at different positions below ground for better resolving soil moisture heterogeneity with depth.This work will ultimately contribute to a better understanding of water fluxes between atmosphere, soil and groundwater as a function of soil water content, and to quantifying water balances beyond the point or profile scale, including deeper storage variations.

RU Cosmic Sense中水文测地学（HG）模块的主要目标是将CRNS（宇宙射线中子传感）土壤水分外推到其近地表传感深度以外的整个非饱和带。 一个独特的数据集的深度分辨土壤水分在CRNS足迹和在集水区规模将产生开发和测试深度缩放的方法，假设CRNS观测提供有价值的信息，用于评估在更深的包气带的水含量。我们结合联合收割机CRNS与其他两个非侵入性监测技术与类似的水平足迹CRNS（在100米的顺序），但具有不同的垂直集成深度：GNSS反射仪（GNSS-R）的深度为几厘米，和地面重力测量，集成在整个包气带。在实地与配置传感器的三种技术（CNRS，GNSS-R和重力仪），并与原位传感器配置文件和/或蒸渗仪，我们将合并的意见，并得出随时间变化的函数关系在不同深度的土壤水分变化。该项目的主要目标包括：1）通过基于深度缩放方法的本地足迹和区域尺度的垂直外推，增加CRNS观测窗口。将在空间分布的支持点网络上将固定和流动的CRNS与重力测量结合起来（在RU联合实地活动期间），从而能够在区域范围内应用和评价深度缩放方法。2）从两个角度比较和关联不同监测技术的土壤水分动态：a）了解不同时间序列在不同积分深度观测之间的相关性、时滞和信号衰减方面以何种方式相互关联，以及B）评估相应数据质量和不确定性。3)推进陆地重力测量作为CRNS的补充技术，增加更大深度的水储存动态信息。4)通过研究CRNS信号对足迹内水平和垂直土壤水分非均匀性的响应，推进CRNS方法。这包括在水分条件具有明显不均匀性的自然或人为引起的地点对不同能量水平的中子的比较响应分析，以及探索CRNS和重力仪在地下不同位置的观测值，以更好地解决土壤水分随深度的不均匀性。土壤和地下水作为土壤含水量的函数，并量化水平衡超过点或剖面尺度，包括更深的存储变化。