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This study analyzes the impact of tidal effects on the dispersion of simulated contaminant concentrations in coastal aquifers. By comparing simulations with and without tidal fluctuations, the study highlights the importance of transient dispersion in modeling contaminant transport in these complex environments.
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Cover SWIM 20th Salt Water Intrusion Meeting Tidal Effects on Transient Dispersion of Simulated Contaminant Concentrations in Coastal Aquifers Ivana La LicataChristian Langevin Alyssa Dausmann Luca Alberti
Introduction Simulation of contaminant transport in coastal aquifers is intrinsically complex and computationally expensive because: The extent of saltwater intrusion is affected by a large number of physical and hydraulic parameters (dispersivity) Moreover contaminant migration in groundwater is affected by the characteristics of the transition zone The effect of tides necessitates the use of a short simulation time step, resulting in substantial computational effort
Purpose No Tide - Simulations that neglectedtidally fluctuating ocean boundary Tide - Simulations that included tidally fluctuating ocean boundary To investigate the influence of transient dispersion on the concentration distribution in a variable-density flow and transport model Comparison between simulations are simple two-dimensional cross-sectional models computer program: SEAWAT (Langevin & Guo, 2006)
Problem Description 500 m Tide (6.283 d-1; period = 1 day) constant longitudinal and transverse dispersivities: 8 stress periods per tidal cycle
The plume moves toward the freshwater–seawater interface and rises as it reaches the transition zone At the end of the 2-year simulation, the contaminant is at steady state and has reached the ocean Simulation and Results
contamination source The tidally driven hydraulic transients in Tide increase the overall mixing resulting in a relatively broader saltwater/freshwater transition zone The increased mixing in Tide also caused contaminant concentrations near the ocean to be lower than for the No Tide simulation contamination source Simulation and Results Contaminant concentrations were compared for Tide and No Tide simulations to analyze the influence of tidal variations on the contaminant and salinity distributions salt water salt water
“…those values that yield the best match or calibration of the solute transport model under steady state flow conditions to a plume that developed under transient flow conditions.”(Goode & Konikow, 1990) Apparent Dispersivity Simulation and Results - spatially varying dispersivity Percent difference in contaminant concentration between steady-state (No Tide) and transient (Tide) simulation Simulations with spatially varying dispersivity values were performed with the No Tide model to determine if the mixing due to tidally driven hydraulic transients could be approximated with an increase in dispersivity
(Kinzelbach & Ackerer, 1986) [m] Transverse Apparent Dispersivity Simulation and Results - dispersivity distribution Percent difference in contaminant concentration between steady-state (No Tide) and transient (Tide) simulation Distribution of Apparent Dispersivity
Without tide, the error that occurs in the estimation of concentration near the ocean is a function of the dispersivity in correspondence of the transition zone Difference in the contaminant and salinity concentration distributions occurs when tides are represented the mixing from tides results in a more mixed contaminant and salinity concentration distribution it may be possible to replace tidal effects with a change in the dispersivity value in this zone when calibrating a model Conclusion This study presents a comparison of numerical results between contaminant transport simulations with (Tide) and without (No Tide) tidal effects
A more rigorous approach based on the calculation and use of apparent dispersivity distribution, created using the velocities from a transient model, provides a better method for including the effects of tidal mixing in a steady-state model the calculated apparent dispersivity correction appears to be a practical way to replace tidal effects when calibrating a model Conclusion It’s possible to save time and money in model calibration because the steady-state model does not require multiple stress periods; the model simulations require less time to run