Identifying reliable in situ reference measurements for satellite root-zone soil moisture validation from the International Soil Moisture Network

Root-zone soil moisture (RZSM) represents water available for plant uptake and evaporation, making it a key variable for agricultural applications and drought monitoring. While satellite observations are restricted to near-surface soil moisture, modeling approaches exist that can approximate soil moisture conditions in deeper layers. The validation of such deeper-layer products requires reliable ground reference measurements at corresponding depths. However, existing soil moisture monitoring networks, such as those available from the International Soil Moisture Network (ISMN), are highly inconsistent in sensor depth placement and vertical coverage. 

In this study, we first investigate the spatial and vertical distribution of in situ sensors available within the ISMN. We then propose a best practice method for identifying Fiducial Reference Measurements (FRMs) for RZSM dynamics, which can be used to validate RZSM products for any assumed soil layer depth. Finally, we compare these RZSM FRMs against existing satellite-derived and modeled RZSM products from the ESA Climate Change Initiative Soil Moisture (CCI SM) dataset and the GLDAS-NOAH land surface model.

Results reveal substantial gaps and inconsistencies in spatial coverage and sampling depth among ISMN networks, with a bias towards agriculturally dominated regions in temperate and cold climate zones, where most stations measure only within the top 10 cm. Out of almost 3000 ISMN stations, a small subset of less than 300 FRM-labeled stations provides sufficiently consistent and deep vertical sampling within the root-zone , assumed as top 1 m soil layer. Those stations are selected to determine an optimal vertical sampling design for the reliable monitoring of specific soil layers. RZSM FRMs are derived for four different soil layers (0-0.1 m, 0.1-0.4 m, 0.4-1 m, and 0-1 m) and used to validate ESA CCI SM and GLDAS-NOAH RZSM estimates for the same layers.