High rates of land subsidence, caused by groundwater overdraft, are resulting in millions of dollars of infrastructure damage in California's San Joaquin Valley (SJV). In recent years, the use of interferometric synthetic aperture radar (InSAR) has enabled us to substantially improve our understanding of this subsidence. However, only very occasionally have the InSAR data been integrated with a physical model of subsurface compaction. Here, we have used InSAR and other data to parameterize and calibrate a 1D compaction model. We applied our model to a study area in the SJV where we had access to the necessary information on hydraulic head to develop model inputs. Our model simulated subsidence in the three aquifer system layers over the period 1952–2017, and is the first 1D compaction model in the SJV to simulate multiple aquifer system layers from the 1950s to 2017. The results from our model suggest that previous studies have significantly underestimated the time constants governing the slow, residual compaction of subsurface clays. We suggest that residual compaction of clays is a process that continues for decades-to-centuries, indicating that to significantly reduce subsidence requires some recovery of head, not just a stabilization. We also show how compaction in the lower, confined aquifer has accounted for over 90% of subsidence in the past 20 years. Although our study area is small, our findings are likely representative of the subsiding regions of the SJV, and our methodology can be applied to unconsolidated aquifer systems exhibiting subsidence worldwide.
M. Lees et al., "Development and Application of a 1D Compaction Model to Understand 65 Years of Subsidence in the San Joaquin Valley," Water Resources Research, vol. 58, no. 6, article no. e2021WR031390, Wiley; American Geophysical Union, Jun 2022.
The definitive version is available at https://doi.org/10.1029/2021WR031390
Geosciences and Geological and Petroleum Engineering
Keywords and Phrases
groundwater hydrology; hydrogeophysics; numerical modeling; remote sensing; water management
International Standard Serial Number (ISSN)
Article - Journal
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01 Jun 2022