TY - JOUR
T1 - High-resolution soil moisture data reveal complex multi-scale spatial variability across the United States
AU - Vergopolan, Noemi
AU - Sheffield, Justin
AU - Chaney, Nathaniel W.
AU - Pan, Ming
AU - Beck, Hylke E.
AU - Ferguson, Craig R.
AU - Torres-Rojas, Laura
AU - Eigenbrod, Felix
AU - Crow, Wade
AU - Wood, Eric F.
N1 - 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.
PY - 2022/8/4
Y1 - 2022/8/4
N2 - 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).
AB - 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).
UR - http://hdl.handle.net/10754/680190
UR - https://onlinelibrary.wiley.com/doi/10.1029/2022GL098586
U2 - 10.1029/2022gl098586
DO - 10.1029/2022gl098586
M3 - Article
SN - 0094-8276
JO - Geophysical Research Letters
JF - Geophysical Research Letters
ER -