120-7 From Data to Decision: Predicting Future Subsidence Under Varying Management Strategies

Session: Land Surface Subsidence: Processes, Impacts, and Ongoing Challenges

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Land subsidence remains a persistent threat to infrastructure and groundwater sustainability in regions such as California’s Central Valley and parts of Illinois, where aquifer systems are stressed by intensive groundwater use. To better understand and forecast subsidence behavior under varying hydrologic conditions, we developed a suite of one-dimensional MODFLOW 6 models using the CSUB package, integrated with long-term observational datasets including leveling, InSAR, extensometers, and groundwater level records. This work emphasizes the important role of modeling in estimating the critical head—defined as the groundwater level below which permanent subsidence initiates—and in quantifying residual compaction due to delayed drainage of thick fine-grained interbeds.

Using ensemble-based data assimilation, we constrained model parameters across more than 50 benchmark sites and projected subsidence under a range of groundwater management scenarios. Results indicate that managing groundwater levels to historical lows or even to critical head values is insufficient to eliminate future subsidence. Instead, recovery well above the critical head is necessary to accelerate equilibration of pore-water pressure gradients and reduce residual compaction. These modeling strategies and findings offer valuable guidance for setting Sustainable Management Criteria (SMCs) in California and can be extended to other regions like Illinois, where legacy groundwater use and thick clay sequences pose similar long-term risks to land stability and infrastructure.

Geological Society of America Abstracts with Program. Vol. 57, No. 6, 2025

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