Geostatistical Assessment of Shallow Groundwater Risk in Urban Coastal Virginia: A Case Study from Virginia Beach

Urban groundwater assessments in coastal cities commonly rely on public monitoring datasets that are spatially uneven and temporally discontinuous, which complicates reliable risk evaluation. This study assesses shallow groundwater risk in the urban domain of Virginia Beach, Virginia, using publicly available groundwater-level and groundwater-quality data collected between 1991 and 2020. The analysis integrates long-term groundwater levels from 121 monitoring wells and groundwater-quality measurements for chloride (Cl), iron (Fe), and manganese (Mn) from 55 wells.
To ensure spatial consistency and data support, the assessment is restricted to the NLCD 2024 urban land-cover class. Groundwater levels and a Composite Contamination Index (CCI) are modeled within a three-dimensional block framework (50 × 50 × 5 m) using Sequential Gaussian Simulation, generating 50 conditional realizations per variable. Simulation outputs are summarized through E-type estimates, percentile scenarios, and uncertainty metrics to explicitly characterize spatial variability under data limitations.
Results indicate that groundwater conditions suitable for new abstraction are extremely limited. More than 94% of the urban domain is classified as not recommended, while less than 1% exhibits acceptable to favorable conditions. Shallow groundwater levels, elevated spatial uncertainty, and groundwater-quality stress overlap most strongly in urban–wetland transition areas south of the Green Line, previously identified as hydrogeologically sensitive.
The study provides a screening-level framework for urban groundwater management by integrating groundwater depth, quality, and uncertainty into a unified risk-based assessment. This approach supports monitoring prioritization and precautionary decision-making in Virginia Beach and is transferable to other coastal cities that depend on heterogeneous public groundwater datasets.