Hydrogeologic controls on groundwater discharge and nitrogen loads in a coastal watershed

© The Author(s), 2016. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Hydrology 538 (2016): 783–793, doi:10.1016/j.jhydrol.2016.05.013.Submarine groundwater discharge (SGD) is a small portion of the global water budget, but a potentially large contributor to coastal nutrient budgets due to high concentrations relative to stream discharge. A numerical groundwater flow model of the Inland Bays Watershed, Delaware, USA, was developed to identify the primary hydrogeologic factors that affect groundwater discharge rates and transit times to streams and bays. The distribution of groundwater discharge between streams and bays is sensitive to the depth of the water table below land surface. Higher recharge and reduced hydraulic conductivity raised the water table and increased discharge to streams relative to bays compared to the Reference case (in which 66% of recharge is discharged to streams). Increases to either factor decreased transit times for discharge to both streams and bays compared to the Reference case (in which mean transit times are 56.5 and 94.3 years, respectively), though sensitivity to recharge is greater. Groundwaterborne nitrogen loads were calculated from nitrogen concentrations measured in discharging fresh groundwater and modeled SGD rates. These loads combined with long SGD transit times suggest groundwater-borne nitrogen reductions and estuarine water quality improvements will lag decades behind implementation of efforts to manage nutrient sources. This work enhances understanding of the hydrogeologic controls on and uncertainties in absolute and relative rates and transit times of groundwater discharge to streams and bays in coastal watersheds.This work was funded by the National Science Foundation (EAR-0910756 and EAR- 0911805).2017-05-1

Submarine Groundwater Discharge Data at Meter Scale (223Ra, 224Ra, 226Ra, 228Ra and 222Rn) in Indian River Bay (Delaware, US)

Abstract Submarine groundwater discharge (SGD) was sampled at high-spatial resolution in Indian River Bay, DE, USA, in July 2016 to characterize the spatial variability of the activity of the radium and radon isotopes commonly used to estimate SGD. These data were part of an investigation into the methods and challenges of characterizing SGD rates and variability, especially in the coastal aquifer transition from freshwater to saltwater (Hydrogeological processes and near shore spatial variability of radium and radon isotopes for the characterization of submarine groundwater discharge (Duque et al., 2019)). Samples were collected with seepage meters and minipiezometers to obtain sufficient volumes for analytical characterization. Seepage meter samples (for 223Ra, 224Ra, 226Ra, and 228Ra) were collected at two-hour intervals over a semi-diurnal tidal cycle from 30 seepage meters. Samples for 222Rn characterization were collected with a minipiezometer from 25 cm below the bay bed at each seepage meter location. All samples were analyzed with standard and state of the art procedures

Open Data, Collaborative Working Platforms, and Interdisciplinary Collaboration: Building an Early Career Scientist Community of Practice to Leverage Ocean Observatories Initiative Data to Address Critical Questions in Marine Science

Ocean observing systems are well-recognized as platforms for long-term monitoring of near-shore and remote locations in the global ocean. High-quality observatory data is freely available and accessible to all members of the global oceanographic community—a democratization of data that is particularly useful for early career scientists (ECS), enabling ECS to conduct research independent of traditional funding models or access to laboratory and field equipment. The concurrent collection of distinct data types with relevance for oceanographic disciplines including physics, chemistry, biology, and geology yields a unique incubator for cutting-edge, timely, interdisciplinary research. These data are both an opportunity and an incentive for ECS to develop the computational skills and collaborative relationships necessary to interpret large data sets. Here, we use observatory data to demonstrate the potential for these interdisciplinary approaches by presenting a case study on the water-column response to anomalous atmospheric events (i.e., major storms) on the shelf of the Mid-Atlantic Bight southwest of Cape Cod, United States. Using data from the Ocean Observatories Initiative (OOI) Pioneer Array, we applied a simple data mining method to identify anomalous atmospheric events over a four-year period. Two closely occurring storm events in late 2018 were then selected to explore the dynamics of water-column response using mooring data from across the array. The comprehensive ECS knowledge base and computational skill sets allowed identification of data issues in the OOI data streams and technologically sound characterization of data from multiple sensor packages to broadly characterize ocean-atmosphere interactions. An ECS-driven approach that emphasizes collaborative and interdisciplinary working practices adds significant value to existing datasets and programs such as OOI and has the potential to produce meaningful scientific advances. Future success in utilizing ocean observatory data requires continued investment in ECS education, collaboration, and research; in turn, the ECS community provides feedback, develops knowledge, and builds new tools to enhance the value of ocean observing systems. These findings present an argument for building a community of practice to augment ECS ocean scientist skills and foster collaborations to extend the context, reach, and societal utility of ocean science