Abstract

This work is a climatological evaluation of terrestrial water storage anomalies (TWSAs), which act as driving forces for sustainable development, in one of the most populous countries of the world. The objective of this work is to evaluate RL06 mascon data from the GRACE and GRACE-FO satellite missions over India to explore seasonal and interannual changes in terrestrial water storage, encompassing an area of ~3.29 million km2 with 285 grid points, from 2002 through to 2020. Several statistical tests are performed to check the homogeneity (i.e., Pettitt’s test, the BRT, the SNHT, and the VNRT). Most of the homogeneous data are found in winter, pre-monsoon, and post-monsoon, approximately above 42% to 47%, and the least are found in monsoons and annual with only 33%, at a 95% significance level. According to Pettitt’s test, the majority of the breakpoints are present in 2014 for winter, 2012 for pre-monsoon, 2011 for monsoons and post-monsoon, and 2008 as well as 2011 for annual. Furthermore, to detect trends and magnitudes we employed the nonparametric MK test, the MMK test, Sen’s slope estimator, and the parametric SLR test. According to the MK and MMK tests, the most significant negative and positive trends indicate the chances of droughts and floods, respectively. The Indo–Gangetic region shows the highest declination. According to Sen’s slope and the SLR test, the most declining magnitude is found in Delhi, Panjab, Uttrakhand, the northern part of Rajasthan, and Uttar Pradesh. Based on our findings, the average declining rate of yearly terrestrial water storage data from the MK, MMK, and SLR tests is −0.0075 m (−0.75 cm/year) from 2002 to 2020. Koppen–Geiger climate zones are also used to depict the seasonal and interannual descriptive statistics of TWSA trends. Interestingly, the annual means of arid desert cold (−0.1788 cm/year) and tropical savanna (−0.1936 cm/year) have the smallest declining trends when compared to other climatic zones. Northern Indian regions’ temperate dry winter, hot/warm summer, and dry arid steppe hot regions show the maximum declining future trend. This study could be useful in planning and managing water resources, agriculture, and the long-term growth of the country by using an intelligent water delivery system.

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