Impacts of the Scale of Representation of Heterogeneity on Simulated Salinity and Saltwater Circulation in Coastal Aquifers

Abstract

Numerical models of variable‐density groundwater flow and salt transport are a primary tool for predicting salinity distributions in coastal aquifers and estimating submarine groundwater discharge (SGD). Models are particularly useful to estimate the saline component of SGD, which can occur far offshore and is difficult to measure directly. Depending on the system and application, the level of geologic detail represented can range from homogeneous or layered to fully heterogeneous hydraulic conductivity fields. These features strongly affect model results, limiting understanding of subsurface salinity distributions and associated density‐driven saltwater circulation along coasts worldwide. In this study, the impact of the scale of representation of heterogeneity on salinity distributions and SGD was investigated using numerical simulations. Upscaling hydraulic conductivity can significantly modify salinity distributions and flow paths, resulting in unpredictable variations in simulated SGD, though the values for homogeneous fields with equivalent hydraulic conductivity show consistent trends. Simulated density distributions control both the rate and direction of subsurface saltwater circulation. The length of the mixing zone perimeter, a measure of salinity distribution complexity, is shown to correlate with both the rate of subsurface saltwater circulation and the amount of groundwater circulating in the reverse direction from homogeneous cases. Overall, the results demonstrate a strong dependence of salinity distributions and saltwater circulation on the scale and distribution of geologic heterogeneity represented in numerical models. This suggests that numerical models with simplified geologic structure may substantially underestimate saltwater circulation, and attempts to calibrate them using salinity distributions or SGD measurements may be problematic.

Thermal effects on flow and salinity distributions in heterogeneous coastal aquifers with fixed-flux inland boundaries

“…We don't recommend using equivalent homogeneous models to investigate water circulations in heterogeneous aquifers. This is also demonstrated in recent studies (Michael et al, 2016;Kreyns et al, 2020;Yu and Michael, 2022). The temperature modulates density-driven circulations and influences total seawater influxes.…”

“…For aquifers with randomly-distributed permeability, salinity distributions could be changed significantly under the same boundary conditions (Pool et al, 2015;Mahmoodzadeh & Karamouz, 2019). Yu and Michael (2022) applied the upscaling hydraulic conductivity methods and found that salinity distributions considering upscaling effects are completely different from the original one. However, our results suggested that the indicators of seawater intrusion varied within a relatively small range among Monte-Carlo simulations, compared with the mean value.…”

“…Pu et al (2020) pointed out that FW-SW temperature contrasts regulate salinity distributions by changing density differences and lateral hydraulic gradients in homogeneous coastal aquifers. For heterogeneous aquifers, permeability contrasts are critical factors influencing salinity distributions (Lu et al, 2013;Yu and Michael, 2022). Thermal effects on high-permeability zones are more significant than that on low-permeability zones.…”

“…Michael et al (2016) demonstrated that combined effects of geological heterogeneity and density gradients could drive multiple circulation cells and result in more significant saltwater circulation rates. Yu and Michael (2022) also pointed out that the simplified geological model underestimates densitydriven saltwater circulations. Geng et al (2020a) found that in tidally influenced coastal beach aquifers, heterogeneity significantly alters groundwater flow in the intertidal circulation zone and leads to highly variable transit time.…”

Inference of (geostatistical) hyperparameters with the correlated pseudo-marginal method

“…In practice, the conditions necessary for the existence of a REV are often not met because geological media exhibit heterogeneity over a wide range of scales (Neuman and Di Federico, 2003). Errors occurring when only partially accounting for or ignoring heterogeneity generally grow with the non-linearity of the physical or chemical process under study and can result in misleading predictions (e.g., Dentz et al, 2011;Yu and Michael, 2021). For this reason, it is essential to characterize and account for the statistical properties of small-scale heterogeneity even when targeting mean properties.…”