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Results from groundwater pumping-induced subsidence model, San Joaquin Valley (Dataset)
| Content Provider | Dryad |
|---|---|
| Author | Smith, Ryan |
| Abstract | The San Joaquin Valley, California has experienced dramatic subsidence over the past 100 years, but the regions with the most subsidence have shifted dramatically over this time period, from west (Kettleman City/Los Banos) to south (Tulare/Pixley/Corcoran). To date, no study has done an in-depth analysis of the mechanisms driving this shift in subsidence. We analyze head records, utilizing a novel approach that assimilates change in head data from multiple overlapping time periods, to produce an 80-year record of change in head over both the historical and modern regions of greatest subsidence. We then calibrate a deformation model to fit both historical (measured with leveling surveys) and modern (measured with Interferometric Synthetic Aperture Radar, or InSAR) datasets. We find that the stress history of the Kettleman City/Los Banos region with historically high subsidence plays a large role in reducing modern subsidence in that region, while declining heads in both regions are likely to result in major subsidence over the next several decades. This study highlights the need for active groundwater management to mitigate ongoing and future subsidence. One key dataset needed in this effort is accurate long-term head histories to reconstruct the stress history of aquifers for accurate deformation modeling. |
| File Size | 777913 |
| File Format | HTM / HTML |
| ISSN | 19447973 |
| DOI | 10.5061/dryad.79cnp5j1p |
| Alternate Webpage(s) | https://datadryad.org/stash/downloads/file_stream/2762436 |
| Alternate Webpage(s) | https://datadryad.org/stash/downloads/file_stream/2762440 |
| Alternate Webpage(s) | https://datadryad.org/stash/downloads/file_stream/2762437 |
| Language | English |
| Publisher Date | 2023-12-12 |
| Access Restriction | Open |
| Subject Keyword | Subsidence Groundwater Subsidence Modeling Water Science and Technology |
| Content Type | Text |
| Resource Type | Data Set |
| Subject | Water Science and Technology |
