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Improving regional groundwater storage estimates from GRACE and global hydrological models over Tasmania, Australia

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F20%3A43958590" target="_blank" >RIV/49777513:23520/20:43958590 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1007/s10040-020-02157-3" target="_blank" >https://doi.org/10.1007/s10040-020-02157-3</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s10040-020-02157-3" target="_blank" >10.1007/s10040-020-02157-3</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Improving regional groundwater storage estimates from GRACE and global hydrological models over Tasmania, Australia

  • Original language description

    Accuracy 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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10508 - Physical geography

Result continuities

  • Project

    <a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    HYDROGEOLOGY JOURNAL

  • ISSN

    1431-2174

  • e-ISSN

  • Volume of the periodical

    28

  • Issue of the periodical within the volume

    5

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    17

  • Pages from-to

    1809-1825

  • UT code for WoS article

    000530990300002

  • EID of the result in the Scopus database

    2-s2.0-85084303485