Submarine Groundwater and River Discharges Affect Carbon Cycle in a Highly Urbanized and River-Dominated Coastal Area

Riverine carbon flux to the ocean has been considered in estimating coastal carbon budgets, but submarine groundwater discharge (SGD) has long been ignored. In this paper, the effects of both SGD and river discharges on the carbon cycle were investigated in the Guangdong-HongKong-Macao Greater Bay Area (GBA), a highly urbanized and river-dominated coastal area in China. SGD-derived nitrate (NO3–), dissolved organic carbon (DOC), and dissolved inorganic carbon (DIC) fluxes were estimated using a radium model to be (0.73–16.4) × 108 g/d, (0.60–9.94) × 109 g/d, and (0.77–3.29) × 1010 g/d, respectively. SGD-derived DOC and DIC fluxes are ∼2 times as great as riverine inputs, but SGD-derived NO3– flux is one-fourth of the riverine input. The additional nitrate and carbon inputs can stimulate new primary production, enhance biological pump efficiency, and affect the balance of the carbonate system in marine water. We found that SGD in the studied system is a potential net source of atmospheric CO2 with a flux of 1.46 × 109 g C/d, and river, however, is a potential net sink of atmospheric CO2 with a flux of 3.75 × 109 g C/d during the dry winter season. Two conceptual models were proposed illustrating the major potential processes of the carbon cycle induced by SGD and river discharges. These findings from this study suggested that SGD, as important as rivers, plays a significant role in the carbon cycle and should be considered in carbon budget estimations at regional and global scales future.

Artificial Intelligence Search Strategies for Autonomous Underwater Vehicles Applied for Submarine Groundwater Discharge Site Investigation

In this study, a set of different search strategies for locating submarine groundwater discharge (SGD) are investigated. This set includes pre-defined path planning (PPP), adapted random walk (RW), particle swarm optimisation (PSO), inertia Levy-flight (ILF), self-organising-migration-algorithm (SOMA), and bumblebee search algorithm (BB). The influences of self-localisation and communication errors and limited travel distance of the autonomous underwater vehicles (AUVs) on the performance of the proposed algorithms are investigated. This study shows that the proposed search strategies could not outperform the classic search heuristic based on full coverage path planning if all AUVs followed the same search strategy. In this study, the influence of self-localisation and communication errors was investigated. The simulations showed that, based on the median error of the search runs, the performance of SOMA was in the same order of magnitude regardless the strength of the localisation error. Furthermore, it was shown that the performance of BB was highly affected by increasing localisation errors. From the simulations, it was revealed that all the algorithms, except for PSO and SOMA, were unaffected by disturbed communications. Here, the best performance was shown by PPP, followed by BB, SOMA, ILF, PSO, and RW. Furthermore, the influence of the limited travel distances of the AUVs on the search performance was evaluated. It was shown that all the algorithms, except for PSO, were affected by the shorter maximum travel distances of the AUVs. The performance of PPP increased with increasing maximum travel distances. However, for maximum travel distances > 1800 m the median error appeared constant. The effect of shorter travel distances on SOMA was smaller than on PPP. For maximum travel distances < 1200 m, SOMA outperformed all other strategies. In addition, it can be observed that only BB showed better performances for shorter travel distances than for longer ones. On the other hand, with different search strategies for each AUV, the search performance of the whole swarm can be improved by incorporating population-based search strategies such as PSO and SOMA within the PPP scheme. The best performance was achieved for the combination of two AUVs following PPP, while the third AUV utilised PSO. The best fitness of this combination was 15.9. This fitness was 26.4% better than the performance of PPP, which was 20.4 on average. In addition, a novel mechanism for dynamically selecting a search strategy for an AUV is proposed. This mechanism is based on fuzzy logic. This dynamic approach is able to perform at least as well as PPP and SOMA for different travel distances of AUVs. However, due to the better adaptation to the current situation, the overall performance, calculated based on the fitness achieved for different maximum travel distances, the proposed dynamic search strategy selection performed 32.8% better than PPP and 34.0% better than SOMA.

Integrated geophysical and geochemical assessment of submarine groundwater discharge in coastal terrace of Tiruchendur, Southern India

Submarine groundwater discharge (SGD) study is essential for groundwater in coastal terrace at Tiruchendur. The famous Murugan Temple is located in the area and around 25,000 people who visit this temple use the SGD well water at NaaliKinaru (a small open well) as holy water and drink it. The rock and soil type are sandy clay, silt, beach sand, calcarenite, kankar, gneissic rock and charnockite in base rock. Megascopic identification method was used to identify the porous and permeable rocks such as calcarenite, sandstone and kankar to support to increase SGD flux. Grain size study was used to identify the paleo-coastal estuarine environment with sediment deposits in the terrace. The square array electrical resistivity method was used to study the subsurface geology and aquifer depth. The 2d ERT technique was used to identify the subsurface shallow perched aquifer of freshwater. The magnetotelluric survey method was used to scan the entire subsurface geological and tectonic uplift, coastal ridges, rock folded subsurface structural features of continental and oceanic tectonism. Darcy’s law was used to calculate the SGD flux rate in the above study area.

Traditional and novel time-series approaches reveal submarine groundwater discharge dynamics under baseline and extreme event conditions

Groundwater is a vital resource for humans and groundwater dependent ecosystems. Coastal aquifers and submarine groundwater discharge (SGD), both influenced by terrestrial and marine forces, are increasingly affected by climate variations and sea-level rise. Despite this, coastal groundwater resources and discharge are frequently poorly constrained, limiting our understanding of aquifer responses to external forces. We apply traditional and novel time-series approaches using an SGD dataset of previously unpublished resolution and duration, to analyze the dependencies between precipitation, groundwater level, and SGD at a model site (Kīholo Bay, Hawaiʻi). Our objectives include (1) determining the relative contribution of SGD drivers over tidal and seasonal periods, (2) establishing temporal relationships and thresholds of processes influencing SGD, and (3) evaluating the impacts of anomalous events, such as tropical storms, on SGD. This analysis reveals, for example, that precipitation is only a dominant influence during wet periods, and otherwise tides and waves dictate the dynamics of SGD. It also provides time lags between intense storm events and higher SGD rates, as well as thresholds for precipitation, wave height and tides affecting SGD. Overall, we demonstrate an approach for modeling a hydrological system while elucidating coastal aquifer and SGD response in unprecedented detail.