Stories of a water-table: anomalous depressions, aquitard breaches and seasonal implications, Shelby County, Tennessee, USA.

An extensive water level survey of the water-table aquifer (i.e., shallow aquifer) within Shelby County, Tennessee, was conducted in the dry (fall 2020) and wet (spring 2021) seasons. Water-table surfaces were generated using cokriging to observe seasonal differences to identify anomalous water-table depressions, indicative of an underlying aquitard breach. Seasonal differences were attributed to non-coincident control and timing between the surveys and when optimum dry (fall) and wet (spring) conditions existed, as observed through comparisons with continuous historical water levels from 12 shallow monitoring wells. Additionally, data from fall 2020 were compared to previous studies in 2005 and 2015 to determine decadal changes in levels and shape of the water-table surface which were mostly attributed to changes in data control and potential climate variations. A prediction error map was generated from the 2020 dataset to identify areas of the county with high-prediction error (>7.0 m) to offer guidance on where future well control would be optimal.

Groundwater well optimization to minimize contaminant movement from a surficial shallow aquifer to a lower water supply aquifer using stochastic simulation-optimization modeling techniques: Strategy formulation.

The interaction between surficial shallow aquifers of poorer quality and semi-confined water-supply aquifers poses a potential risk for degradation of the water supply. Groundwater engineers and hydrogeologists use groundwater models to synthesize field data, conceptualize hydrological processes, and improve understanding of the groundwater system to support informed decision-making. Models for decision-making, called management models, aid in the efficient planning and sustainable management of groundwater systems. Management models search for the best or least-cost management strategy satisfying hydrologic and environmental regulations. In management models, a simulation model is linked or coupled with an optimization formulation. Widely used optimization formulations are linear, non-linear, quadratic, dynamic, and global search models. Management models are applied but are not limited to maximizing withdrawals, minimizing drawdown, pumping costs, and saltwater intrusion, and determining the best locations for production wells. This paper theoretically presents the development of groundwater wellfield management strategies and the corresponding modeling framework for each strategy's evaluation. Depending on the strategy, the modeling effort applies deterministic (simulation) and stochastic (simulation-optimization) techniques. The goals of the optimization strategies are to protect wells from potential contaminant sources, identify optimal future well installation sites, mitigate risks, and extend the life of wells that may face water contamination issues.•Several management strategies are formulated addressing well depth, seasonal pumping operation, and mapping no-drilling or red zones for new well installation.•Modeling methodologies are laid down that apply thousands of numerical simulations for each strategy to simulate and evaluate recurring patterns of contaminant movement.•The simulation model integrates MODFLOW and MODPATH to simulate 3D groundwater flow and advective contaminant movement, respectively and is transferred via FloPy to couple with the optimization/decision model using a custom Python script.