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Statistical Downscaling of GRACE‐Derived Groundwater Storage Using ET Data in the North China Plain
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 anom...
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Published in: | Journal of geophysical research. Atmospheres 2018-06, Vol.123 (11), p.5973-5987 |
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creator | Yin, Wenjie Hu, Litang Zhang, Menglin Wang, Jingrui Han, Shin‐Chan |
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.
Key Points
An innovative downscaling approach is developed to improve the spatial resolution of GRACE‐derived GWS anomalies using ET data
Validations with observation data in the Beijing Plain show downscaled GWS data generally capture subgrid heterogeneity in changes to groundwater storage
The method can be applicable only when the GWS data have a strong relationship with ET over the study area |
doi_str_mv | 10.1029/2017JD027468 |
format | article |
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Key Points
An innovative downscaling approach is developed to improve the spatial resolution of GRACE‐derived GWS anomalies using ET data
Validations with observation data in the Beijing Plain show downscaled GWS data generally capture subgrid heterogeneity in changes to groundwater storage
The method can be applicable only when the GWS data have a strong relationship with ET over the study area</description><identifier>ISSN: 2169-897X</identifier><identifier>EISSN: 2169-8996</identifier><identifier>DOI: 10.1029/2017JD027468</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Anomalies ; Aquifers ; Climate ; Coefficients ; Correlation coefficient ; Correlation coefficients ; Data ; Data processing ; Data recovery ; Evapotranspiration ; Geophysics ; GRACE ; GRACE (experiment) ; Gravitation ; Gravity ; Groundwater ; Groundwater data ; Groundwater levels ; Groundwater management ; Groundwater resources ; Groundwater storage ; GWS ; Heterogeneity ; Observation wells ; Recovery ; Resolution ; Resource management ; Spatial discrimination ; Spatial resolution ; statistical downscaling method ; Statistical methods ; Statistics ; the Beijing Plain ; Water resources ; Water resources planning</subject><ispartof>Journal of geophysical research. Atmospheres, 2018-06, Vol.123 (11), p.5973-5987</ispartof><rights>2018. American Geophysical Union. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a3688-25208f5bf92d8adca7567a62b4eb3baee1a64735efc6fa73f717c039df1cecd33</citedby><cites>FETCH-LOGICAL-a3688-25208f5bf92d8adca7567a62b4eb3baee1a64735efc6fa73f717c039df1cecd33</cites><orcidid>0000-0003-1810-1670 ; 0000-0002-3888-6324</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Yin, Wenjie</creatorcontrib><creatorcontrib>Hu, Litang</creatorcontrib><creatorcontrib>Zhang, Menglin</creatorcontrib><creatorcontrib>Wang, Jingrui</creatorcontrib><creatorcontrib>Han, Shin‐Chan</creatorcontrib><title>Statistical Downscaling of GRACE‐Derived Groundwater Storage Using ET Data in the North China Plain</title><title>Journal of geophysical research. Atmospheres</title><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.
Key Points
An innovative downscaling approach is developed to improve the spatial resolution of GRACE‐derived GWS anomalies using ET data
Validations with observation data in the Beijing Plain show downscaled GWS data generally capture subgrid heterogeneity in changes to groundwater storage
The method can be applicable only when the GWS data have a strong relationship with ET over the study area</description><subject>Anomalies</subject><subject>Aquifers</subject><subject>Climate</subject><subject>Coefficients</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Data</subject><subject>Data processing</subject><subject>Data recovery</subject><subject>Evapotranspiration</subject><subject>Geophysics</subject><subject>GRACE</subject><subject>GRACE (experiment)</subject><subject>Gravitation</subject><subject>Gravity</subject><subject>Groundwater</subject><subject>Groundwater data</subject><subject>Groundwater levels</subject><subject>Groundwater management</subject><subject>Groundwater resources</subject><subject>Groundwater storage</subject><subject>GWS</subject><subject>Heterogeneity</subject><subject>Observation wells</subject><subject>Recovery</subject><subject>Resolution</subject><subject>Resource management</subject><subject>Spatial discrimination</subject><subject>Spatial resolution</subject><subject>statistical downscaling method</subject><subject>Statistical methods</subject><subject>Statistics</subject><subject>the Beijing Plain</subject><subject>Water resources</subject><subject>Water resources planning</subject><issn>2169-897X</issn><issn>2169-8996</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp90MtKAzEUBuAgCpbanQ8QcOtoJplcZlk6dbQUlV7A3XA6k7QpdaYmqaU7H8Fn9ElsqYgrz-b8i49z4EfoMiY3MaHpLSWxHGSEykSoE9SisUgjlabi9DfLl3PU8X5J9qMIS3jSQnocIFgfbAkrnDXb2u-Dree4MTgfdXv9r4_PTDv7riucu2ZTV1sI2uFxaBzMNZ76A-5PcAYBsK1xWGj82LiwwL2FrQE_r8DWF-jMwMrrzs9uo-ldf9K7j4ZP-UOvO4yACaUiyilRhs9MSisFVQmSCwmCzhI9YzPQOgaRSMa1KYUByYyMZUlYWpm41GXFWBtdHe-uXfO20T4Uy2bj6v3LghKuOE9pclDXR1W6xnunTbF29hXcrohJceiy-NvlnrMj39qV3v1ri0E-yngipGLf1nl17Q</recordid><startdate>20180616</startdate><enddate>20180616</enddate><creator>Yin, Wenjie</creator><creator>Hu, Litang</creator><creator>Zhang, Menglin</creator><creator>Wang, Jingrui</creator><creator>Han, Shin‐Chan</creator><general>Blackwell Publishing Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0003-1810-1670</orcidid><orcidid>https://orcid.org/0000-0002-3888-6324</orcidid></search><sort><creationdate>20180616</creationdate><title>Statistical Downscaling of GRACE‐Derived Groundwater Storage Using ET Data in the North China Plain</title><author>Yin, Wenjie ; Hu, Litang ; Zhang, Menglin ; Wang, Jingrui ; Han, Shin‐Chan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a3688-25208f5bf92d8adca7567a62b4eb3baee1a64735efc6fa73f717c039df1cecd33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Anomalies</topic><topic>Aquifers</topic><topic>Climate</topic><topic>Coefficients</topic><topic>Correlation coefficient</topic><topic>Correlation coefficients</topic><topic>Data</topic><topic>Data processing</topic><topic>Data recovery</topic><topic>Evapotranspiration</topic><topic>Geophysics</topic><topic>GRACE</topic><topic>GRACE (experiment)</topic><topic>Gravitation</topic><topic>Gravity</topic><topic>Groundwater</topic><topic>Groundwater data</topic><topic>Groundwater levels</topic><topic>Groundwater management</topic><topic>Groundwater resources</topic><topic>Groundwater storage</topic><topic>GWS</topic><topic>Heterogeneity</topic><topic>Observation wells</topic><topic>Recovery</topic><topic>Resolution</topic><topic>Resource management</topic><topic>Spatial discrimination</topic><topic>Spatial resolution</topic><topic>statistical downscaling method</topic><topic>Statistical methods</topic><topic>Statistics</topic><topic>the Beijing Plain</topic><topic>Water resources</topic><topic>Water resources planning</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yin, Wenjie</creatorcontrib><creatorcontrib>Hu, Litang</creatorcontrib><creatorcontrib>Zhang, Menglin</creatorcontrib><creatorcontrib>Wang, Jingrui</creatorcontrib><creatorcontrib>Han, Shin‐Chan</creatorcontrib><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Journal of geophysical research. Atmospheres</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yin, Wenjie</au><au>Hu, Litang</au><au>Zhang, Menglin</au><au>Wang, Jingrui</au><au>Han, Shin‐Chan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Statistical Downscaling of GRACE‐Derived Groundwater Storage Using ET Data in the North China Plain</atitle><jtitle>Journal of geophysical research. Atmospheres</jtitle><date>2018-06-16</date><risdate>2018</risdate><volume>123</volume><issue>11</issue><spage>5973</spage><epage>5987</epage><pages>5973-5987</pages><issn>2169-897X</issn><eissn>2169-8996</eissn><abstract>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.
Key Points
An innovative downscaling approach is developed to improve the spatial resolution of GRACE‐derived GWS anomalies using ET data
Validations with observation data in the Beijing Plain show downscaled GWS data generally capture subgrid heterogeneity in changes to groundwater storage
The method can be applicable only when the GWS data have a strong relationship with ET over the study area</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2017JD027468</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0003-1810-1670</orcidid><orcidid>https://orcid.org/0000-0002-3888-6324</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Anomalies Aquifers Climate Coefficients Correlation coefficient Correlation coefficients Data Data processing Data recovery Evapotranspiration Geophysics GRACE GRACE (experiment) Gravitation Gravity Groundwater Groundwater data Groundwater levels Groundwater management Groundwater resources Groundwater storage GWS Heterogeneity Observation wells Recovery Resolution Resource management Spatial discrimination Spatial resolution statistical downscaling method Statistical methods Statistics the Beijing Plain Water resources Water resources planning |
title | Statistical Downscaling of GRACE‐Derived Groundwater Storage Using ET Data in the North China Plain |
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