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This is the data used to create the published study of the same name published in the Journal of Hydrology in 2022 (10.1016/j.jconhyd.2022.104068). Shallow (<30 m) reducing groundwater commonly contains abundant dissolved arsenic (As) in Bangladesh. We hypothesize that dissolved As in iron (Fe)-rich groundwater discharging to rivers is trapped onto Fe(III)-oxyhydroxides which precipitate in shallow riverbank sediments under the influence of tidal fluctuations. Therefore, the goal of this study is to compare the calculated mass of sediment-bound As that would be sequestered from dissolved groundwater As that discharges through riverbanks of the Meghna River to the observed mass of As trapped within riverbank sediments. To calculate groundwater discharge, a Boussinesq aquifer analytical groundwater flow model was developed and constrained by cyclical seasonal fluctuations in hydraulic heads and river stages observed at three sites along a 13 km reach in central Bangladesh. At all sites, groundwater discharges to the river year-round but most of it passes through an intertidal zone created by ocean tides propagating upstream from the Bay of Bengal in the dry season. The annualized groundwater discharge per unit width at the three sites ranges from 173 to 891 m2/yr (average 540 m2/yr). Assuming that riverbanks have been stable since the Brahmaputra River avulsed far away from this area 200 years ago and dissolved As is completely trapped within riverbank sediments, the mass of accumulated sediment As can be calculated by multiplying groundwater discharge by ambient aquifer As concentrations measured in 1969 wells. Across all sites, the range of calculated sediment As concentrations in the riverbank is 78–849 mg/kg, which is higher than the observed concentrations (17–599 mg/kg). This discovery supports the hypothesis that the dissolved As in groundwater discharge to the river is sufficient to account for the observed buried deposits of As along riverbanks. 

Quantifying and characterizing groundwater flow and discharge from barrier islands to coastal waters is crucial for assessing freshwater resources and contaminant transport to the ocean. In this study, we examined the groundwater hydrological response, discharge, and associated nutrient fluxes in Dauphin Island, a barrier island located in the northeastern Gulf of Mexico. We employed radon ( 222 Rn) and radium (Ra) isotopes as tracers to evaluate the temporal and spatial variability of fresh and recirculated submarine groundwater discharge (SGD) in the nearshore waters. The results from a 40-day continuous 222 Rn time series conducted during a rainy season suggest that the coastal area surrounding Dauphin Island was river-dominated in the days after storm events. Groundwater response was detected about 1 week after the precipitation and peak river discharge. During the period when SGD was a factor in the nutrient budget of the coastal area, the total SGD rates were as high as 1.36 m day –1 , or almost three times higher than detected fluxes during the river-dominated period. We found from a three-endmember Ra mixing model that most of the SGD from the barrier island was composed of fresh groundwater. SGD was driven by marine and terrestrial forces, and focused on the southeastern part of the island. We observed spatial variability of nutrients in the subterranean estuary across this part of the island. Reduced nitrogen (i.e., NH 4 + and dissolved organic nitrogen) fluxes dominated the eastern shore with average rates of 4.88 and 5.20 mmol m –2 day –1 , respectively. In contrast, NO 3 – was prevalent along the south-central shore, which has significant tourism developments. The contrasting nutrient dynamics resulted in N- and P-limited coastal water in the different parts of the island. This study emphasizes the importance of understanding groundwater flow and dynamics in barrier islands, particularly those urbanized, prone to storm events, or located near large estuaries. 

Submarine groundwater discharge (SGD) is an important driver of coastal biogeochemical budgets worldwide. Radon (²²²Rn) has been widely used as a natural geochemical tracer to quantify SGD, but field measurements are time consuming and costly. Here, we use deep learning to predict coastal seawater radon in SGD‐impacted regions. We hypothesize that deep learning could resolve radon trends and enable preliminary insights with limited field observations of groundwater tracers. Two deep learning models were trained on global coastal seawater radon observations (n = 39,238) with widely available inputs (e.g., salinity, temperature, water depth). The first model used a one‐dimensional convolutional neural network (1D‐CNN‐RNN) framework for site‐specific gap filling and producing short‐term future predictions. A second model applied a fully connected neural network (FCNN) framework to predict radon across geographically and hydrologically diverse settings. Both models can predict observed radon concentrations withr² > 0.76. Specifically, the FCNN model offers a compelling development because synthetic radon tracer data sets can be obtained using only basic water quality and meteorological parameters. This opens opportunities to attain radon data from regions with large data gaps, such as the Global South and other remote locations, allowing for insights that can be used to predict SGD and plan field experiments. Overall, we demonstrate how field‐based measurements combined with big‐data approaches such as deep learning can be utilized to assess radon and potentially SGD beyond local scales.

 

Terrestrial groundwater travels through subterranean estuaries before reaching the sea. Groundwater‐derived nutrients drive coastal water quality, primary production, and eutrophication. We determined how dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus (DIP), and dissolved organic nitrogen (DON) are transformed within subterranean estuaries and estimated submarine groundwater discharge (SGD) nutrient loads compiling > 10,000 groundwater samples from 216 sites worldwide. Nutrients exhibited complex, nonconservative behavior in subterranean estuaries. Fresh groundwater DIN and DIP are usually produced, and DON is consumed during transport. Median total SGD (saline and fresh) fluxes globally were 5.4, 2.6, and 0.18 Tmol yr⁻¹for DIN, DON, and DIP, respectively. Despite large natural variability, total SGD fluxes likely exceed global riverine nutrient export. Fresh SGD is a small source of new nutrients, but saline SGD is an important source of mostly recycled nutrients. Nutrients exported via SGD via subterranean estuaries are critical to coastal biogeochemistry and a significant nutrient source to the oceans.