ABSTRACT Alternating patterns of groundwater discharge and tidal intrusion along shorelines have remained difficult to characterise and quantify efficiently using empirical data. Groundwater flowpaths along estuarine coastal interfaces have profound effects on dynamic redox conditions, contaminant transport and ecology in estuarine environments. In this study, we quantify tidally influenced groundwater discharge from the McAllister Point Landfill in Newport, Rhode Island, USA using temperature with depth measurements to model bidirectional hydrological fluxes in a recursive estimation state‐space model. Zones of groundwater discharge at low tide were first located using thermal infrared and electromagnetic conductivity surveys based on strong contrasts between cooler, more electrically resistive terrestrial groundwater compared to the warmer, more electrically conductive tidal waters that occur in the summer. An array of 25 vertical temperature profilers was subsequently deployed along the southern shoreline of the site, directly adjacent to a landfill. Water samples were collected from discharge zones using a PushPoint sampler with depth, and from surface water away from these zones. Temperature with depth time‐series data were used to model one‐dimensional alternating groundwater discharge and tidal intrusion dynamics. A nonlinear cross‐spectral inversion of the bed temperature data was employed to estimate bulk sediment thermal properties at the same temporal scale as the flux models. One‐dimensional hydrological flux models were spatially upscaled via interpolation of fluxes over the southern shoreline area to estimate total volumetric flux. Models of hydrological flux show alternating periods of groundwater discharge at low tide and tidal intrusion into coastal sediments during high tide at a sub‐daily scale. Additionally, geochemical analysis of pore waters revealed contrasts in heavy metal concentrations between sampling periods and depth, indicating potential landfill leachate transport. This study represents the use of temperature with depth data to model sub‐daily changes in vertical hydrological flux through coastal sediments using a recursive estimation state‐space model.
Moore et al. (Mon,) studied this question.