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Bhunia, Partha Sarathi and Patra, Kanhu Charan, 2024. Evaluating dynamics of land water storage and its response to climate variation in the Deccan Plateau, India. Catena, 237:107783, doi:10.1016/j.catena.2023.107783.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2024Caten.23707783B,
author = {{Bhunia}, Partha Sarathi and {Patra}, Kanhu Charan},
title = "{Evaluating dynamics of land water storage and its response to climate variation in the Deccan Plateau, India}",
journal = {Catena},
keywords = {GRACE, GLDAS Noah model, Terrestrial water storage, Deccan plateau, Rainshadow region},
year = 2024,
month = mar,
volume = {237},
eid = {107783},
pages = {107783},
doi = {10.1016/j.catena.2023.107783},
adsurl = {https://ui.adsabs.harvard.edu/abs/2024Caten.23707783B},
adsnote = {Provided by the SAO/NASA Astrophysics Data System},
abstract = {Inter-state river water disputes are frequent over the rain shadow (RS) region of the Western Ghats (WG), where the annual rainfall is much lower (75.2 cm) than that of overall India (118 cm). This study investigated the TWS (Terrestrial Water Storage) dynamics of the entire Deccan plateau (DP) and RS regions, located at the leeward side of the WG mountain range, with the help of Gravity Recovery and Climate Experiment (GRACE) based TWS anomalies (TWSA) data. Here, the latest TRMM (Tropical Rainfall Measuring Mission) rainfall product was evaluated at different time scales against gauge-based measurements to check its applicability as an alternative to gauge-based observed data. Trends in climate variables and TWSA were estimated to understand their variations during 2003–2016 in both regions. The response of GRACE-based TWSA and its constituent components to rainfall was determined using time-lagged correlation analysis. The contribution of constituent variables to TWSA was estimated using the component contribution ratio (CCR) method. It was observed that the TRMM-3B43 data captured the rainfall pattern over the entire DP with great accuracy. Results showed that the increasing trend of TWS in 2003–2009 had reversed in 2010–2016 due to the reduction of climate moistening in both regions. The warming trend of climate is more than twice in the RS region than that found in the DP, leading to a higher decreasing rate of TWS in this region than in DP. For both DP and RS regions, the time lags of groundwater storage anomalies (GWSA), total runoff anomalies (RA), canopy water storage anomalies (CWSA), and soil moisture storage anomalies (SMSA) to rainfall can be arranged as CWSA ≤ RA ≤ SMSA ≤ GWSA. SMSA and GWSA are the main contributors to the TWSA in both areas. However, SWSA also played a vital role in TWS variability, particularly in the RS region.}
}
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