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  • 1
    Publication Date: 2024-03-22
    Description: Data collection occurred in four parts during 2018 to 2019 for the Pawcatuck River: weekly collection from the Stillman and Westerly Bridges in Westerly, RI; collections were also taken seasonally from various bridges in a transect from head of the Pawcatuck River at Warden Pond to Westerly, RI; rain water was collected at UConn Avery Point - Groton, CT; and wastewater data reported by Westerly Wastewater Facility (which was corroborated in house at UConn Avery Point). Standard data collected was nutrient concentrations of nitrate, nitrite, ammonium, and phosphate. Total dissolved nitrogen, particulate nitrogen, and chlorophyll-a were also collected and measured. Our study utilized stable isotopes of nitrate and particulate nitrogen with the intent of tracking sources, cycling, and loading along the river. We focused on δ15N-NO3, δ18O-NO3, δ17O-NO3, and δ15N-PN. Through collection of rainwater at UConn Avery Point, percent atmospheric deposition of river samples based on the mass independent fractionation between δ17O and δ18O was calculated. Loading was calculated for each nutrient source based on collected data and river discharge reported from the USGS.
    Keywords: 15N; 18O; Ammonium; Ammonium, loading; Atmospheric deposition; Bottle, Van Dorn; Calculated; Calculated (sum of Nitrate, Nitrite, Ammonium); Chlorophyll a; Comment; Conductivity; Conversion to NOx with a hot Vanadium II solution followed by detection on a Teledyne chemiluminescent NOx detector (Braman and Hedrix 1989); DATE/TIME; Discharge; Dissolved oxygen optical probe (Orion Star); Distance; Element analyser CHN, Costech; Event label; Gauge station; GS; Inverse of Nitrate, flux; Mac_Rain_Rainwater; N Isotopes; nitrate; Nitrate; Nitrate, loading; nitrogen; Nitrogen, inorganic, dissolved; Nitrogen, inorganic, dissolved, loading; Nitrogen, organic, dissolved; Nitrogen, organic, dissolved, loading; Nitrogen, particulate; Nitrogen, total; Nitrogen, total, loading; Nitrogen, total, particulate, loading; Nitrogen, total dissolved, loading; Oakton Con 450; Oxygen, dissolved; Pawcatuck River; Pawcatuck-Seasonal_Transect; Pawcatuck-Weekly_Stillman_Bridge; Pawcatuck-Weekly_Westerly_Bridge; Persulfate oxidation and colorimetry; Phosphate; Phosphate, loading; Pigments, Turner fluorometer; Present weather; River discharge, daily; Sample ID; Sample position; Sample volume; Smartchem analyser (spectrophotometric detection); Temperature, water; Thermo Delta V GC-IRMS with custom modified Gas Bench II with two cold traps and a PAL Autosampler (Sigman et al. 2001; Casciotti et al, 2002; Kaiser et al., 2007); VDB; WC_Wastewater; Δ17O, nitrate; Δ17O=δ17O-0.52 x δ18O (Thiemens 1999); δ15N, nitrate; δ15N, nitrate, standard deviation; δ15N, total particulate nitrogen; δ18O; δ18O, nitrate; δ18O, nitrate, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 5241 data points
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  • 2
  • 3
    Publication Date: 2022-05-26
    Description: © The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Estuaries and Coasts 39 (2016): 311-332, doi:10.1007/s12237-015-0011-y.
    Description: Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review, we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a “theory of everything” for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.
    Description: NKG, ALA, and RPS acknowledge support from the USGS Coastal and Marine Geology Program. DKR gratefully acknowledges support from NSF (OCE-1314642) and NIEHS (1P50-ES021923-01). MJB and JMPV gratefully acknowledge support from NOAA NOS NCCOS (NA05NOS4781201 and NA11NOS4780043). MJB and SJL gratefully acknowledge support from the Strategic Environmental Research and Development Program—Defense Coastal/Estuarine Research Program (RC-1413 and RC-2245).
    Keywords: Numerical modeling ; Hydrodynamics ; Ecological modeling ; Ecosystem modeling ; Skill assessment
    Repository Name: Woods Hole Open Access Server
    Type: Article
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