High-resolution soil moisture data reveal complex multi-scale spatial variability across the United States

Noemi Vergopolan, Justin Sheffield, Nathaniel W. Chaney, Ming Pan, Hylke E. Beck, Craig R. Ferguson, Laura Torres-Rojas, Felix Eigenbrod, Wade Crow, Eric F. Wood

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Soil moisture (SM) spatiotemporal variability critically influences water resources, agriculture, and climate. However, besides site-specific studies, little is known about how SM varies locally (1–100-m scale). Consequently, quantifying the SM variability and its impact on the Earth system remains a long-standing challenge in hydrology. We reveal the striking variability of local-scale SM across the United States using SMAP-HydroBlocks — a novel satellite-based surface SM dataset at 30-m resolution. Results show how the complex interplay of SM with landscape characteristics and hydroclimate is primarily driven by local variations in soil properties. This local-scale complexity yields a remarkable and unique multi-scale behavior at each location. However, very little of this complexity persists across spatial scales. Experiments reveal that on average 48% and up to 80% of the SM spatial information is lost at the 1-km resolution, with complete loss expected at the scale of current state-of-the-art SM monitoring and modeling systems (1–25 km).
Original languageEnglish (US)
JournalGeophysical Research Letters
DOIs
StatePublished - Aug 4 2022
Externally publishedYes

ASJC Scopus subject areas

  • Geophysics
  • General Earth and Planetary Sciences

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