Monitoring Terrestrial Water Storage Using GRACE/GRACE-FO Data over India: A Review

被引：0
作者：
Maniranjan Kumar [1 ]
Pramod Soni [2 ]
Debshri Swargiary [1 ]
机构：
[1] Department of Civil Engineering, National Institute of Technology Jamshedpur, Jharkhand
[2] Department of Civil Engineering, Indian Institute of Technology (BHU), Uttar Pradesh, Varanasi
来源：
Iranian Journal of Science and Technology, Transactions of Civil Engineering | 2025年 / 49卷 / 3期
关键词：
GRACE; GRACE-FO; Gravity; Groundwater; India; Terrestrial water storage;
D O I：
10.1007/s40996-024-01623-2
中图分类号：
学科分类号：
摘要：
The gravity recovery and climate experiment (GRACE) satellite mission, which was active between March 2002 and June 2017 and its successor, the GRACE follow-on (GRACE-FO), which has been in operation since May 2018, marked the pioneering remote sensing missions to track changes in terrestrial water storage (TWS) across time. TWS encompasses the cumulative water masses found in the Earth’s soil column, including elements like surface water, soil moisture, snow water equivalent and groundwater (GW). Over the course of the last 20 years, there has been extensive research conducted on fluctuations in the mass of different Elements of the Earth's system, such as the hydrosphere, seas, cryosphere, and solid Earth, utilizing time-varying gravity measurements from the GRACE/GRACE-FO missions. This technology can be utilised to improve monitoring results of large-scale spatial and temporal variations in the water cycle patterns. A review of recent GRACE data used for monitoring terrestrial hydrology over India is provided in this work. The primary applications of GRACE data in the context of large-scale terrestrial hydrological monitoring, such as assessing alterations in terrestrial water storage, involve: retrieving the hydrological components of GW, analysing droughts, floods, land subsidence and determining how glaciers are responding to climate change, have recently been described. India has the tenth position globally in the utilization of GRACE data. Therefore, more investigation is required to completely understand the potential of GRACE data. It was found through a review of the literature that several hydrological models have not yet been thoroughly examined with GRACE data. Furthermore, small river basins can be analysed at a fine scale with downscale GRACE data using machine learning/artificial intelligence. In the Indian context, no research has been conducted to estimate river discharge by using GRACE data. © The Author(s), under exclusive licence to Shiraz University 2024.
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页码：2225 / 2239
页数：14
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