High‐Resolution Soil Moisture Data Reveal Complex Multi‐Scale Spatial Variability Across the United States
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...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-08-01
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| Series: | Geophysical Research Letters |
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| Online Access: | https://doi.org/10.1029/2022GL098586 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Noemi Vergopolan |
| collection | DOAJ |
| description | 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 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). |
| format | Article |
| id | doaj-art-0440addfdc2c4b988a4b03df5603b2b6 |
| institution | DOAJ |
| issn | 0094-8276 1944-8007 |
| language | English |
| publishDate | 2022-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geophysical Research Letters |
| spelling | doaj-art-0440addfdc2c4b988a4b03df5603b2b62025-08-20T03:10:20ZengWileyGeophysical Research Letters0094-82761944-80072022-08-014915n/an/a10.1029/2022GL098586High‐Resolution Soil Moisture Data Reveal Complex Multi‐Scale Spatial Variability Across the United StatesNoemi Vergopolan0Justin Sheffield1Nathaniel W. Chaney2Ming Pan3Hylke E. Beck4Craig R. Ferguson5Laura Torres‐Rojas6Felix Eigenbrod7Wade Crow8Eric F. Wood9Department of Civil and Environmental Engineering Princeton University Princeton NJ USASchool of Geography and Environmental Sciences University of Southampton Southampton UKDepartment of Civil and Environmental Engineering Duke University Durham NC USACenter for Western Weather and Water Extremes Scripps Institution of Oceanography University of California San Diego CA USAEuropean Commission Joint Research Centre (JRC) Ispra ItalyAtmospheric Sciences Research Center University at Albany State University of New York Albany NY USADepartment of Civil and Environmental Engineering Duke University Durham NC USASchool of Geography and Environmental Sciences University of Southampton Southampton UKUSDA Hydrology and Remote Sensing Laboratory Beltsville MD USADepartment of Civil and Environmental Engineering Princeton University Princeton NJ USAAbstract 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).https://doi.org/10.1029/2022GL098586soil moisturelandscapeheterogeneityscalingspatial variabilityhyper‐resolution |
| spellingShingle | 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 High‐Resolution Soil Moisture Data Reveal Complex Multi‐Scale Spatial Variability Across the United States Geophysical Research Letters soil moisture landscape heterogeneity scaling spatial variability hyper‐resolution |
| title | High‐Resolution Soil Moisture Data Reveal Complex Multi‐Scale Spatial Variability Across the United States |
| title_full | High‐Resolution Soil Moisture Data Reveal Complex Multi‐Scale Spatial Variability Across the United States |
| title_fullStr | High‐Resolution Soil Moisture Data Reveal Complex Multi‐Scale Spatial Variability Across the United States |
| title_full_unstemmed | High‐Resolution Soil Moisture Data Reveal Complex Multi‐Scale Spatial Variability Across the United States |
| title_short | High‐Resolution Soil Moisture Data Reveal Complex Multi‐Scale Spatial Variability Across the United States |
| title_sort | high resolution soil moisture data reveal complex multi scale spatial variability across the united states |
| topic | soil moisture landscape heterogeneity scaling spatial variability hyper‐resolution |
| url | https://doi.org/10.1029/2022GL098586 |
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