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Simulation of Flow in a Complex Aquifer System Subjected to Long-Term Well Network Growth
Hua-Sheng Liao1, Zachary K Curtis1, Prasanna Venkatesh Sampath2
1Department of Civil and Environmental Engineering, Michigan State University, 428 S. Shaw Lane, East Lansing, MI, 48824.
Abstract:
In west-central Lower Peninsula of Michigan, population growth and expanded agricultural activities over recent decades have resulted in significant increases in distributed groundwater withdrawals. The growth of the extensive well network and anecdotes of water shortages (dry wells) have raised concerns over the region's groundwater sustainability. We developed an unsteady, three-dimensional (3D) groundwater flow model to describe system dynamics over the last 50 years and evaluate long-term impacts of groundwater use. Simulating this large aquifer system was challenging; the site is characterized by strong, spatially distributed, and statistically nonstationary heterogeneity, making it difficult to avoid over-parameterization using traditional approaches for conceptualizing and calibrating a flow model. Moreover, traditional pumping and water level data were lacking and prohibitively expensive to collect given the large-scale and long-term nature of this study. An integrated, stochastic-deterministic approach was developed to characterize the system and calibrate the flow model through innovative use of high-density water well datasets. This approached allowed (1) implementation of a "zone-based," nonstationary stochastic approach to conceptualize complex spatial variability using a small set of geologic material types; (2) modeling the spatiotemporal evolution of many water well withdrawals across several decades using sector-based parameterization; and (3) critical analysis of long-term water level changes at different locations in the aquifer system for characterizing the system dynamics and calibrating the model. Results show the approach is reasonably successful in calibrating a complex model for a highly complex site in a way that honors complex distributed heterogeneity and stress configurations.
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