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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10508 - Physical geography

Projekt

<a href="/cs/project/LO1506" target="_blank" >LO1506: Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnost</a><br>

Návaznosti

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

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název periodika

HYDROGEOLOGY JOURNAL

ISSN

1431-2174

e-ISSN

—

Svazek periodika

28

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

17

Strana od-do

1809-1825

Kód UT WoS článku

000530990300002

EID výsledku v databázi Scopus

2-s2.0-85084303485