2021
DOI: 10.3390/cli9040056
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Monthly and Seasonal Drought Characterization Using GRACE-Based Groundwater Drought Index and Its Link to Teleconnections across South Indian River Basins

Abstract: Traditional drought monitoring is based on observed data from both meteorological and hydrological stations. Due to the scarcity of station observation data, it is difficult to obtain accurate drought distribution characteristics, and also tedious to replicate the large-scale information of drought. Thus, Gravity Recovery and Climate Experiment (GRACE) data are utilized in monitoring and characterizing regional droughts where ground station data is limited. In this study, we analyzed and assessed the drought c… Show more

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Cited by 23 publications
(17 citation statements)
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“…But for sub-basin, which shows significant negative trends for both CCDI and GRACE-DSI, conclude that sub-basin gets low or no rainfall due to which TWS continuously depleting. Further, GRACE-DSI characterized drought events in the sub-basins of Godavari, Krishna, Cauvery is also shown by GGDI during 2008–2010, 2003–2004 & 2015–2016, and 2015–2016 respectively 20 , which informs that groundwater table depletes during this period and leads to drought events. Krishna & Godavari river basins experienced drought during 2003–2004, 2003–2004 & 2008–2010, is also observed by Sinha et al 19 , which is also explained through GGDI and GRACE-DSI.…”
Section: Discussionmentioning
confidence: 75%
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“…But for sub-basin, which shows significant negative trends for both CCDI and GRACE-DSI, conclude that sub-basin gets low or no rainfall due to which TWS continuously depleting. Further, GRACE-DSI characterized drought events in the sub-basins of Godavari, Krishna, Cauvery is also shown by GGDI during 2008–2010, 2003–2004 & 2015–2016, and 2015–2016 respectively 20 , which informs that groundwater table depletes during this period and leads to drought events. Krishna & Godavari river basins experienced drought during 2003–2004, 2003–2004 & 2008–2010, is also observed by Sinha et al 19 , which is also explained through GGDI and GRACE-DSI.…”
Section: Discussionmentioning
confidence: 75%
“…Satish Kumar et al 20 use six drought indices and found that CCDI and GRACE-DSI effectively study drought characteristics. Overall, the CCDI and GRACE-DSI show promising results.…”
Section: Discussionmentioning
confidence: 99%
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“…To get rid of the uncertainty induced by the GRACE data processing errors, the modern Mascon solution data was applied instead, which is proven to be superior to the alternative spherical harmonics data (Aryal & Zhu, 2020). However, there are also uncertainties associated with the Mascon solutions on account of the used diverse background models as well as data processing approaches (Kumar et al, 2021). The other source of the uncertainties of the results is the simulation errors of the global models such as Noah and CLSM.…”
Section: Discussionmentioning
confidence: 99%