TY - JOUR
T1 - SMAP-HydroBlocks, a 30-m satellite-based soil moisture dataset for the conterminous US
AU - Vergopolan, Noemi
AU - Chaney, Nathaniel W.
AU - Pan, Ming
AU - Sheffield, Justin
AU - Beck, Hylke E.
AU - Ferguson, Craig R.
AU - Torres-Rojas, Laura
AU - Sadri, Sara
AU - Wood, Eric F.
N1 - Generated from Scopus record by KAUST IRTS on 2023-02-14
PY - 2021/12/1
Y1 - 2021/12/1
N2 - Soil moisture plays a key role in controlling land-atmosphere interactions, with implications for water resources, agriculture, climate, and ecosystem dynamics. Although soil moisture varies strongly across the landscape, current monitoring capabilities are limited to coarse-scale satellite retrievals and a few regional in-situ networks. Here, we introduce SMAP-HydroBlocks (SMAP-HB), a high-resolution satellite-based surface soil moisture dataset at an unprecedented 30-m resolution (2015–2019) across the conterminous United States. SMAP-HB was produced by using a scalable cluster-based merging scheme that combines high-resolution land surface modeling, radiative transfer modeling, machine learning, SMAP satellite microwave data, and in-situ observations. We evaluated the resulting dataset over 1,192 observational sites. SMAP-HB performed substantially better than the current state-of-the-art SMAP products, showing a median temporal correlation of 0.73 ± 0.13 and a median Kling-Gupta Efficiency of 0.52 ± 0.20. The largest benefit of SMAP-HB is, however, the high spatial detail and improved representation of the soil moisture spatial variability and spatial accuracy with respect to SMAP products. The SMAP-HB dataset is available via zenodo and at https://waterai.earth/smaphb.
AB - Soil moisture plays a key role in controlling land-atmosphere interactions, with implications for water resources, agriculture, climate, and ecosystem dynamics. Although soil moisture varies strongly across the landscape, current monitoring capabilities are limited to coarse-scale satellite retrievals and a few regional in-situ networks. Here, we introduce SMAP-HydroBlocks (SMAP-HB), a high-resolution satellite-based surface soil moisture dataset at an unprecedented 30-m resolution (2015–2019) across the conterminous United States. SMAP-HB was produced by using a scalable cluster-based merging scheme that combines high-resolution land surface modeling, radiative transfer modeling, machine learning, SMAP satellite microwave data, and in-situ observations. We evaluated the resulting dataset over 1,192 observational sites. SMAP-HB performed substantially better than the current state-of-the-art SMAP products, showing a median temporal correlation of 0.73 ± 0.13 and a median Kling-Gupta Efficiency of 0.52 ± 0.20. The largest benefit of SMAP-HB is, however, the high spatial detail and improved representation of the soil moisture spatial variability and spatial accuracy with respect to SMAP products. The SMAP-HB dataset is available via zenodo and at https://waterai.earth/smaphb.
UR - https://www.nature.com/articles/s41597-021-01050-2
UR - http://www.scopus.com/inward/record.url?scp=85116829476&partnerID=8YFLogxK
U2 - 10.1038/s41597-021-01050-2
DO - 10.1038/s41597-021-01050-2
M3 - Article
SN - 2052-4463
VL - 8
JO - Scientific data
JF - Scientific data
IS - 1
ER -
