TY - JOUR
T1 - SOIL-WATERGRIDS, mapping dynamic changes in soil moisture and depth of water table from 1970 to 2014
AU - Guglielmo, Magda
AU - Tang, Fiona H.M.
AU - Pasut, Chiara
AU - Maggi, Federico
N1 - Funding Information:
We thank the Editorial Board and two anonymous Reviewers for the suggestions and recommendations to the earlier submissions of this paper. Magda Guglielmo and Fiona Tang are supported by the SREI2020 of the University of Sydney. Magda Guglielmo is also supported by the W H Gladstones Population and Environment Fund of the Australian Academy of Science awarded to Fiona Tang. Chiara Pasut is supported by the The University of Sydney Postgraduate Scholarship Award “Contaminant Hydrology”. The authors acknowledge the Sydney Informatics Hub and the University of Sydney’s high-performance computing cluster Artemis for providing the high-performance computing resources that have contributed to the results reported within this work. The authors acknowledge the use of the National Computational Infrastructure (NCI) which is supported by the Australian Government, and accessed through the NCMAS allocation scheme award to Maggi, 2020, “Global soil and water resource in a changing climate”, and the Sydney Informatics Hub HPC Allocation Scheme, which is supported by the Deputy Vice-Chancellor (Research), University of Sydney and the ARC-LIEF, 2019: Smith, Muller, Thornber et al., Sustaining and strengthening merit-based access to National Computational 613 Infrastructure (LE190100021).
Publisher Copyright:
© 2021, The Author(s).
PY - 2021/10/6
Y1 - 2021/10/6
N2 - We introduce here SOIL-WATERGRIDS, a new dataset of dynamic changes in soil moisture and depth of water table over 45 years from 1970 to 2014 globally resolved at 0.25 × 0.25 degree resolution (about 30 × 30 km at the equator) along a 56 m deep soil profile. SOIL-WATERGRIDS estimates were obtained using the BRTSim model instructed with globally gridded soil physical and hydraulic properties, land cover and use characteristics, and hydrometeorological variables to account for precipitation, ecosystem-specific evapotranspiration, snowmelt, surface runoff, and irrigation. We validate our estimates against independent observations and re-analyses of the soil moisture, water table depth, wetland occurrence, and runoff. SOIL-WATERGRIDS brings into a single product the monthly mean water saturation at three depths in the root zone and the depth of the highest and lowest water tables throughout the reference period, their long-term monthly averages, and data quality. SOIL-WATERGRIDS can therefore be used to analyse trends in water availability for agricultural abstraction, assess the water balance under historical weather patterns, and identify water stress in sensitive managed and unmanaged ecosystems.
AB - We introduce here SOIL-WATERGRIDS, a new dataset of dynamic changes in soil moisture and depth of water table over 45 years from 1970 to 2014 globally resolved at 0.25 × 0.25 degree resolution (about 30 × 30 km at the equator) along a 56 m deep soil profile. SOIL-WATERGRIDS estimates were obtained using the BRTSim model instructed with globally gridded soil physical and hydraulic properties, land cover and use characteristics, and hydrometeorological variables to account for precipitation, ecosystem-specific evapotranspiration, snowmelt, surface runoff, and irrigation. We validate our estimates against independent observations and re-analyses of the soil moisture, water table depth, wetland occurrence, and runoff. SOIL-WATERGRIDS brings into a single product the monthly mean water saturation at three depths in the root zone and the depth of the highest and lowest water tables throughout the reference period, their long-term monthly averages, and data quality. SOIL-WATERGRIDS can therefore be used to analyse trends in water availability for agricultural abstraction, assess the water balance under historical weather patterns, and identify water stress in sensitive managed and unmanaged ecosystems.
UR - http://www.scopus.com/inward/record.url?scp=85116505761&partnerID=8YFLogxK
U2 - 10.1038/s41597-021-01032-4
DO - 10.1038/s41597-021-01032-4
M3 - Article
C2 - 34615885
AN - SCOPUS:85116505761
SN - 2052-4463
VL - 8
JO - Scientific Data
JF - Scientific Data
IS - 1
M1 - 263
ER -
