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


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
StatePublished - Aug 4 2022
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2022-09-14
Acknowledged KAUST grant number(s): OSR-2017-CRG6
Acknowledgements: This work was supported by the “Modernizing Observation Operator and Error Assessment for Assimilating In-situ and Remotely Sensed Snow/Soil Moisture Measurements into NWM” project from NOAA (grant number NA19OAR4590199), the ”Understanding Changes in High Mountain Asia project” project from NASA (grant number NNH19ZDA001N-HMA), the NASA-NOAA Interagency Agreement through the High Mountain Asia program (grant number 80HQTR21T0015), the ”A new paradigm in precision agriculture: assimilation of ultra-fine resolution data into a crop-yield forecasting model” project from the King Abdullah University of Science and Technology (grant number OSR-2017-CRG6), and the ”Building REsearch Capacity for sustainable water and food security In drylands of sub-saharan Africa (BREC-cIA)” project from the UK Research and Innovation as part of the Global Challenges Research Fund (grant number NE/P021093/1).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

ASJC Scopus subject areas

  • Geophysics
  • General Earth and Planetary Sciences


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