Abstract

Soil water content (SWC) is a key variable in various environmental processes, such as atmospheric interaction, infiltration, groundwater recharge, and stream water fluxes. An assessment and the prediction of these highly relevant processes demand quantification about SWC on the field scale (100 m to kilometers). To date, large-scale SWC has been either measured remotely by satellite systems or computed numerically by hydrological models. Both approaches contain a range of disadvantages, extensively discussed in the recent literature, such as the lack of the desired resolution, of detailed soil information, or the very shallow integral depth from satellite products. Cosmic-ray neutron sensing (CRNS) has become a popular method for noninvasive SWC measurements within the last decade. Particularly the hectare-scale lateral footprint and its integral depth of several decimeter bridged the instrumentation gap between point-scale SWC measurements and the remote-sensing products. CRNS could provide more representative SWC measurements than satellite products and thus has the potential to support model calibration. However, to reach a quantity of CRNS-based SWC measurements that cover large-scale areas as needed to match the dimensions of satellite and modeled SWC products, stationary and conventional car-bourne CRNS roving are not sufficient. In this study, we introduce the concept of large-scale SWC measurements by multiple mobile Rail-CRNS systems installed on cargo trains as a vision for the calibration of existing SWC products and to support model development. Up to five Rail-CRNS systems run almost daily along several hundreds of kilometers across Germany, recording near real-time SWC values along the tracks. However, as the CRNS signal is not solely affected by SWC, other hydrogen pools (e.g. biomass, vegetation, surface water), topography and anthropogenic constructions along the railway can influence the recordings. To convert the CRNS signal into reliable SWC values, signal corrections and interpretations are still part of ongoing investigations. Moreover, while the amount of measured SWC data increases, also the complexity of data processing and quality control rises and demand further consideration. Finally, the question of data accessibility and formatting needs to be addressed in the future to serve the needs of end users, such as the remote sensing and hydrological modelling communities or land use managers and local authorities. 

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