干涉合成孔径雷达
地质学
地下水
大地基准
含水层
合成孔径雷达
全球导航卫星系统应用
反演(地质)
孔力学
遥感
大地测量学
卫星
地震学
构造学
岩土工程
工程类
多孔介质
航空航天工程
多孔性
作者
Grace Carlson,Susanna Werth,Manoochehr Shirzaei
标识
DOI:10.1016/j.rse.2024.114303
摘要
Water years 2020 and 2021 in California were two of the driest on record and the most recent series of dry years during a two-decade-long mega-drought. The 2020–2021 drought period, characterized by low precipitation and high temperatures, had devastating effects, including an increase in ongoing groundwater overdraft, manifesting in rapid subsidence in California's Central Valley. Here, we present a unified hybrid physics-based stochastic model incorporating measurements from three geodetic sensors to produce a high-resolution map of terrestrial water storage change (∆TWS) across California during the 2020–2021 dry years. The novel joint inversion framework combines Global Navigation Satellite System (GNSS) elastic vertical displacements, ∆TWS from the Gravity Recovery and Climate Experiment Satellites (GRACE and the follow-on mission, GRACE-FO) and Interferometric Synthetic Aperture Radar (InSAR) measurements of poroelastic deformation through a model comprising elastic loading and poroelastic Green's functions. This framework yields a high-resolution and more realistic estimate of ∆TWS within the Central Valley and the surrounding mountain ranges by accounting for poroelastic aquifer deformation. Besides the total ∆TWS, our novel inversion framework simultaneously solves the change in groundwater storage and is used to produce a high-resolution map of groundwater storage loss across the Central Valley. We calculate a groundwater volume loss of 20.4+/− 2.6 km3 in the semi-confined to confined portion of the aquifer-system, with the largest groundwater volume loss in the southern Central Valley over the two dry years. We show that groundwater loss estimates found using our joint inversion framework agree with results from a conventional approach for GRACE-FO-derived groundwater loss estimates when considering underlying processes and uncertainties. Finally, we compare shallow groundwater storage change estimates with those derived from in-situ groundwater level measurements in the Sacramento Valley.
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