Inclined Physical Subsurface Barriers for Saltwater Intrusion Management in Coastal Aquifers

Impact of tidal dynamics and typhoon-induced inundation on saltwater intrusion in coastal farms

The increase in storm surge events caused by climate change exacerbates adverse effects on seawater inundation in coastal areas. An accurate description of the water level curve is crucial for understanding the process of saltwater intrusion (SWI) resulting from storm surge. Most studies involving empirical surges as inputs to groundwater models, often simplify spatial and temporal seawater inundation processes, which may increase the uncertainty in vertical seawater intrusion. To address this gap, we employed a comprehensive modeling approach using storm surge model ADCIRC and numerical simulator HydroGeoSphere to reveal SWI dynamics during a historical storm surge event in a coastal farm, considering varying tidal-surge phases and typhoon intensities. Our findings indicate pronounced SWI variations even with consistently highest water level during a storm surge, contingent on prior tidal processes. The timing of typhoon landfall on an hourly scale yielded diverse water level curves, altering the function of SWI. Intriguingly, SWI exacerbates following a high tide with 31.2 % average salinity higher, highlighting the profound modulation effect of tidal levels on SWI. Local topography significantly influenced SWI dynamics. Ponds, for instance, retained elevated salinity levels for over 15 h, indicating a more prolonged exposure to salinity than roads. These findings underscore the importance of considering both tidal influences and topographical factors in understanding and mitigating SWI in coastal agricultural management.

Stochastic simulation of seawater intrusion in the Longkou area of China based on the Monte Carlo method

Seawater intrusion is a common groundwater pollution problem, which has a great impact on ecological environment and economic development. In this paper, a numerical simulation model of variable density groundwater was constructed to simulate and predict the future seawater intrusion in Longkou city, Shandong Province of China. The influence of the sensitive parameter uncertainty of the model on the simulation results was evaluated by using the Monte Carlo method. In order to reduce the computational load from repeatedly calling the simulation model, the surrogate model was established by using the support vector regression (SVR) method. After training, the correlation coefficient R² of the input-output relationship between the SVR surrogate model and the seawater intrusion simulation model reached 0.9957, with an average relative error of 0.2%, indicating that the surrogate model has a high fitting accuracy. Stochastic simulations of seawater intrusion showed that the seawater intrusion in the Longkou area will gradually aggravate at a slow rate, and the increase of seawater intrusion in the study area after 30 years was expected to range from - 6.03% to 7.37% at the 80% confidence level.