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dc.contributor.authorYin, Wenjie
dc.contributor.authorLi, Tongqing
dc.contributor.authorZheng, Wei
dc.contributor.authorHu, Litang
dc.contributor.authorHan, Shin-Chan
dc.contributor.authorTangdamrongsub, Natthachet
dc.contributor.authorŠprlák, Michal
dc.contributor.authorHuang, Zhiyong
dc.date.accessioned2020-10-26T11:00:16Z-
dc.date.available2020-10-26T11:00:16Z-
dc.date.issued2020
dc.identifier.citationYIN, W. ., LI, T. ., ZHENG, W. ., HU, L. ., HAN, S. ., TANGDAMRONGSUB, N. ., ŠPRLÁK, M. ., HUANG, Z. . Improving regional groundwater storage estimates from GRACE and global hydrological models over Tasmania, Australia. HYDROGEOLOGY JOURNAL, 2020, roč. 28, č. 5, s. 1809-1825. ISSN: 1431-2174en
dc.identifier.issn1431-2174
dc.identifier.uri2-s2.0-85084303485
dc.identifier.urihttp://hdl.handle.net/11025/39846
dc.format17 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherSpringeren
dc.relation.ispartofseriesHydrogeology Journalen
dc.rightsPlný text je přístupný v rámci univerzity přihlášeným uživatelům.cs
dc.rights© Springeren
dc.titleImproving regional groundwater storage estimates from GRACE and global hydrological models over Tasmania, Australiaen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessrestrictedAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedAccuracy of groundwater storage (GWS) estimates from the Gravity Recovery and Climate Experiment (GRACE) mission usually has certain relations with hydrological models. This study develops a statistical selection approach to optimally estimate GWS from GRACE using two hydrological models: the Global Land Data Assimilation System (GLDAS) and the WaterGAP Global Hydrology Model (WGHM), over Tasmania, Australia. This approach involves three variables: the long-term trend, Pearson correlation coefficient (PR), and root mean square error (RMSE). The results show that in-situ observations are highly correlated with GRACE-GLDAS (PR from 0.64 to 0.85) and GRACE-WGHM (PR from 0.69 to 0.88) in eastern and northern regions of Tasmania, respectively. The interannual trends of GRACE-GLDAS estimates are generally ~1.8 times larger than those from GRACE-WGHM solutions. With regard to the standard method, the statistical selection approach can effectively improve the PR and Nash-Sutcliffe efficiency index (NSE) by 3.80 and 1.38%, respectively, over the northern region, while it decreases the RMSE by 1.07%. Similar improvements can also be detected in the eastern region. In terms of spatial distribution, the statistical approach benefits from advantages of the different models, especially to preserve the characteristics of Central Highland. Overall, according to the models, Tasmania experienced a pronounced GWS decline during the Millennium Drought (2003–2010), at a depletion rate of –2.57 mm/year, mainly due to decreasing precipitation. The increasing precipitation infiltration after 2010 lead to the GWS recovery by 3.94 mm/year. The limitation of the method is that it depends on the availability of in-situ groundwater level data.en
dc.subject.translatedgroundwater storageen
dc.subject.translatedGRACEen
dc.subject.translatedhydrological modelsen
dc.subject.translatedTasmaniaen
dc.identifier.doi10.1007/s10040-020-02157-3
dc.type.statusPeer-revieweden
dc.identifier.document-number530990300002
dc.identifier.obd43929589
dc.project.IDLO1506/PUNTIS - Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnostcs
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