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

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 (S-NS) dynamics at the catchment scale and its value in semi-distributed rainfall-runoff modelling calibration. For a humid mixedagricultural catchment (similar to 10 km(2)) in Scotland, we combined similar to 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 S-NS dynamics 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 SNS dynamics 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 organicrich soils and wetter environments, although testing in different environments would be required to evaluate the wider applicability.

Automated summary

SWC is a key variable in land surface processes and can be studied using CRNS technology. This study presents a new methodology for exploring SWC dynamics in humid environments at the catchment scale and its value in rainfall-runoff modeling calibration. The study combines static CRNS data with snapshots at key soil-land use units to generate SWC time series and examines the suitability of CRNS calibration in different soil types.