- Title
- Statistical downscaling of GRACE-derived groundwater storage using ET data in the North China Plain
- Creator
- Yin, Wenjie; Hu, Litang; Zhang, Menglin; Wang, Jingrui; Han, Shin-Chan
- Relation
- Journal of Geophysical Research: Atmospheres Vol. 123, Issue 11, p. 5973-5987
- Publisher Link
- http://dx.doi.org/10.1029/2017JD027468
- Publisher
- Wiley-Blackwell
- Resource Type
- journal article
- Date
- 2018
- Description
- Due to coarse spatial resolution, the application of Gravity Recovery and Climate Experiment (GRACE) data in local groundwater resource management has been limited. To overcome this issue, a downscaling approach is presented to improve the spatial resolution of GRACE‐derived groundwater storage anomalies using evapotranspiration (ET) data. The statistical downscaling method is only applied in areas where there is a strong relationship between GRACE‐derived groundwater storage (GWS) and ET, and the relationship can be established under different spatial resolutions. In this study, GWS anomalies are downscaled from 110 km to 2 km in the North China Plain, capturing subgrid heterogeneity in groundwater storage changes. The downscaled results are further validated using data from 111 observation wells from 2003 to 2014 in the Beijing Plain. The results show that the in situ groundwater levels agree with the Gravity Recovery and Climate Experiment (GRACE) downscaled results for the Beijing Plain in both interannual and monthly scales, with the correlation coefficient of 0.94 and 0.80, respectively. The correlation coefficients vary from 0.63 to 0.78, in 10 of the 13 Beijing Plain administrative regions. The regional downscaling approach employed in this study may be readily integrated into local water resources planning activities.
- Subject
- statistical downscaling method; GRACE; ET; GWS; Beijing Plain
- Identifier
- http://hdl.handle.net/1959.13/1405712
- Identifier
- uon:35538
- Identifier
- ISSN:0148-0227
- Rights
- Copyright 2018 American Geophysical Union.
- Language
- eng
- Full Text
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