Mapping field-scale soil moisture and its spatial variability across the United States using SMAP-HydroBlocks

Soil moisture (SM) varies widely in space and time. This variability influences agriculture, land-atmosphere interactions and triggers hazards, such as flooding, landslides, droughts, and wildfires. Yet, current observations are limited to a few regional in situ measurement networks or coarse-scale satellite retrievals (9–36-km resolution). As a result, besides site-specific studies, little is known on how SM varies locally (1–100-m resolution). Consequently, quantifying the impact of this variability remains a critical and long-standing challenge in hydrology. This presentation introduces SMAP-HydroBlocks – a novel 30-m resolution SM dataset (2015–2019) that combines hyper-resolution land surface modeling, satellite, and in-situ observations over the United States. Using this data, we reveal the striking variability of local-scale SM across the United States. By mapping the SM spatial variability and its persistence across spatial scales, we show the complex interplay between the landscape and hydroclimate and how this variability is highly scale-dependent. Results show that up to 80% of SM spatial variability information is lost at the 1-km scale, with further losses expected at the scale of current monitoring systems (5–25-km). This high degree of SM variability has a critical influence on freshwater and land ecosystem dynamics. By mapping its spatial variability locally, we provide a stepping-stone towards understanding SM-dependent hydrological, biogeochemical, and ecological processes at local (and so far unresolved) scales.