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Sarkar, Tandrila, Karunakalage, Anuradha, Kannaujiya, Suresh, and Chaganti, Charan, 2022. Quantification of groundwater storage variation in Himalayan & Peninsular River basins correlating with land deformation effects observed at different Indian cities. Contributions to Geophysics and Geodesy, 52(1):1–56, doi:10.31577/congeo.2022.52.1.1.
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@ARTICLE{2022CoGG...52....1S,
author = {{Sarkar}, Tandrila and {Karunakalage}, Anuradha and {Kannaujiya}, Suresh and {Chaganti}, Charan},
title = "{Quantification of groundwater storage variation in Himalayan \& Peninsular River basins correlating with land deformation effects observed at different Indian cities}",
journal = {Contributions to Geophysics and Geodesy},
year = 2022,
month = apr,
volume = {52},
number = {1},
pages = {1-56},
abstract = "{Groundwater is a significant resource that supports almost one-fifth
population globally, but has been is diminishing at an alarming
rate in recent years. To delve into this objective more
thoroughly, we calculated interannual (2002{\textendash}2020)
GWS (per grid) distribution using GRACE \& GRACE-FO (CSR-M,
JPL-M and SH) Level 3 RL06 datasets in seven Indian river basins
and found comparatively higher negative trends
({\ensuremath{-}}20.10 {\ensuremath{\pm}} 1.81 to
{\ensuremath{-}}8.60 {\ensuremath{\pm}} 1.52 mm/yr) in Basin
1{\textendash}4 than in Basin 5{\textendash}7
({\ensuremath{-}}7.11 {\ensuremath{\pm}} 0.64 to
{\ensuremath{-}}0.76 {\ensuremath{\pm}} 0.47 mm/yr). After
comparing the Groundwater Storage (GWS) results with the CHIRPS
(Climate Hazards Group Infrared Precipitation with Stations)
derived SPI (Standardized Precipitation Index) drought index, we
found that GWS exhausts analogously in the same period
(2005{\textendash}2020) when SPI values show improvement
({\ensuremath{\sim}}1.89{\textendash}2), indicating towards wet
condition. Subsequently, the GWSA time series is decomposed
using the STL (Seasonal Trend Decomposition) (LOESS Regression)
approach to monitor long-term groundwater fluctuation. The long
term GWS rate (mm/yr) derived from three GRACE \& GRACE-FO
solutions vary from {\ensuremath{-}}20.3 {\ensuremath{\pm}} 5.52
to {\ensuremath{-}}13.19 {\ensuremath{\pm}} 3.28 and the GWS
mass rate (km3/yr) lie in range of {\ensuremath{-}}15.17
{\ensuremath{\pm}} 4.18 to {\ensuremath{-}}1.67
{\ensuremath{\pm}} 0.49 for basins 1{\textendash}3.
Simultaneously, in basin 4{\textendash}7 the GWS rate observed
is {\ensuremath{-}}8.56 {\ensuremath{\pm}} 8.03 to
{\ensuremath{-}}0.58 {\ensuremath{\pm}} 7.04 mm/yr, and the GWS
mass rate differs by {\ensuremath{-}}1.71 {\ensuremath{\pm}}
0.64\$ to {\ensuremath{-}}0.26 {\ensuremath{\pm}} 3.19 km3/yr.
The deseasonalized GWS estimation (2002{\textendash}2020) states
that Himalayan River basins 1,2,3 exhibit high GWS mass loss
({\ensuremath{-}}260 to {\ensuremath{-}}35.12 km3), with Basin 2
being the highest ({\ensuremath{-}}260 km3). Whereas the
Peninsular River basin 4,6,7 gives moderate mass loss value from
{\ensuremath{-}}26.72 to {\ensuremath{-}}23.58 km3. And in River
basin 5, the GWS mass loss observed is the lowest, with a value
of {\ensuremath{-}}8 km3.}",
doi = {10.31577/congeo.2022.52.1.1},
adsurl = {https://ui.adsabs.harvard.edu/abs/2022CoGG...52....1S},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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