Depth-dependent seismic sensing of groundwater recovery from the atmospheric-river storms of 2023

• 成果类型: Article
• 署名作者: Mao, Shujuan; Ellsworth, William L.; Zheng, Yujie; Beroza, Gregory C.
• 署名单位: Stanford University; University of Texas System; University of Texas Austin; University of Texas System; University of Texas Dallas
• 刊物名称: SCIENCE
• ISSN/ISSBN: 0036-10726
• DOI: 10.1126/science.adr6139
• 发表日期: 2025-02-14
• 页码: 758-763
• 关键词: los-angeles; valley; drought; storage; deformation; colorado; index; FAULT

摘要

In early 2023, a series of intense atmospheric-river storms eased California's historic drought, yet the spatiotemporal extent of groundwater recovery remains poorly understood. We tracked two-decadal changes in groundwater in Greater Los Angeles using seismic ambient-field interferometry. The derived seismic hydrographs reveal distinct expressions of groundwater and surficial water droughts: Whereas surface and near-surface water storage nearly fully recovered in the epic wet season of 2023, only about 25% of the groundwater lost since 2006 was restored. On a decadal scale, we find substantial depletion in aquifers below 50-meter depth, with only limited storm-related recovery. Our analysis underscores the need to monitor deep aquifers for a more complete assessment of total water deficits, using high-resolution tools such as seismic sensing.