Abstract

Quantification of submarine groundwater discharge (SGD) remains a challenge due to its large spatial and temporal variability exacerbated by natural heterogeneity (e.g., climatic conditions and hydrogeologic settings) and anthropogenic disturbances (e.g., dredging, oil/gas extraction, and oil-field brine discharges). This study investigates the spatial and temporal variability of SGD during different hydroclimatic conditions in a semi-arid, anthropogenically disturbed estuary using Darcy’s law (i.e., fresh/terrestrial SGD) and radon (222Rn, total SGD) and radium (226Ra, saline/recirculated SGD) isotope mass balances. Continuous electrical resistivity imaging and 222Rn surveys revealed potential subsurface influences on SGD with the highest SGD rates in areas with sandier substrates and near transitions from low hydraulic conductivity to higher hydraulic conductivity bottom sediments. Darcy estimates ranged over two orders of magnitude and were slightly higher following the flooding recession (0.09–8.28 m·d−1) than following a period of low precipitation (−0.02–7.84 m·d−1). Mobile continuous 222Rn estimates (0.79–1.81 m·d−1) support higher and more variable SGD rates, similar trends to those previously reported from time-series 222Rn measurements (0.13–3.85 m·d−1 across seasons). Radium-226 derived SGD (1.3 × 10−2–2.7 × 10−2 m·d−1 using the average groundwater endmember) fall short of 222Rn-derived SGD due to inability to account for radium tracer reactivity within the sediment. However, local Darcy estimates agree well with the range of 222Rn, likely due to the steeper gradients near shore. Radium activity ratios and SGD rates reflect mixing of shallow and deep groundwater beneath the bay, likely due to anthropogenic disturbances with a greater influence from deep groundwater 3–6 months following major precipitation events. This study strongly suggests that semi-arid systems receive significant SGD, which in highly anthropogenically disturbed systems are derived from both shallower and deeper groundwater flowpaths and lag the climatic conditions by weeks (shallow inputs) and months or longer (deeper inputs).

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