期刊
GEOPHYSICAL RESEARCH LETTERS
卷 49, 期 15, 页码 -出版社
AMER GEOPHYSICAL UNION
DOI: 10.1029/2022GL098586
关键词
soil moisture; landscape; heterogeneity; scaling; spatial variability; hyper-resolution
资金
- Modernizing Observation Operator and Error Assessment for Assimilating In-situ and Remotely Sensed Snow/Soil Moisture Measurements into NWM project from NOAA [NA19OAR4590199]
- NASA [NNH19ZDA001N-HMA]
- NASA-NOAA [80HQTR21T0015]
- King Abdullah University of Science and Technology [OSR-2017-CRG6]
- UK Research and Innovation, Global Challenges Research Fund [NE/P021093/1]
Soil moisture shows significant spatiotemporal variability at local scale, primarily driven by local variations in soil properties. This local-scale complexity yields multi-scale behavior at different locations and is lost at larger spatial scales.
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 data set 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 resolution).
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