This research developed multiple regression models relating land use to in‐stream concentrations of total nitrogen (TOTN) and total phosphorus (TOTP) in eight, low‐order watersheds on the coastal plain of South Carolina. The study area (4860 km2) included dominant land‐use categories of agriculture, forest, urban, and wetland comprising the lower portion of the Lake Marion drainage. Land‐use data were obtained from a pre‐existing GIS database derived by classification of satellite images. The models partitioned land‐use categories according to distance from stream channels using a series of buffer zones around each stream. Effects of point source contributions were removed from observed in‐stream concentrations so that nonpoint source effects could be more clearly delineated. All models except two were significant at P < 0.05. The models for TOTN (r2 from 0.25–0.63) explained more variability of stream nutrient concentrations than those for TOTP (r2 from 0.16–0.39). Greater predictive strength for TOTN than TOTP likely reflects differing pathways from terrestrial to aquatic systems. Land close to the stream channel (<150 m) was better predictor of nutrient concentrations than land away from the channel (>150 m). Land‐use change scenarios (converting forest and wetland to agriculture) support the conclusion that management of stream water quality will be most effective with emphasis on riparian and adjacent lands. Seasonal models were generally significant (P < 0.05) and demonstrate that the seasonal profile of stream nutrient concentrations is dependent on the mosaic of land uses in a specific subbasin.

Coastal watersheds in the southeastern United States are rapidly changing due to population growth and attendant increases in residential development, industry, and tourism related commerce. This research examined spatial and temporal patterns of nutrient concentrations in streams from 10 small watersheds (< 4 km2) that drain into Murrells Inlet (impacted) and North Inlet (pristine), two high salinity estuaries along the South Carolina coast. Monthly grab samples were collected during baseflow during 1999 and analyzed for total and dissolved inorganic and organic forms of nitrogen and phosphorus. Data were grouped into forested wetland creeks (representing predevelopment reference sites), urban creeks, and urban ponds. DON and NH4 concentrations were greater in forested streams than in urban streams. NO3 and TP concentrations were greatest in urban streams. Seasonally, concentrations were highest during summer for TN, NH4, DON, and TP, while NO3 concentrations were greatest during winter. Nutrient ratios clearly highlighted the reduction in organic nitrogen due to coastal development. Multiple regression models to predict instream nutrient concentrations from land use in Murrells Inlet suggest that effects are not significant (small r2). The findings indicate that broad land use/land cover classes cannot be used to predict nutrient concentrations in streams in the very small watersheds in our study areas.

Vibrio species are marine bacteria that occur in estuaries worldwide; many are virulent human pathogens with high levels of antibiotic resistance. The average annual incidence of all Vibrio infections has increased by 41% between 1996 and 2005. V. vulnificus (Vv), a species associated with shellfish and occurring in the US Southeast, has ranges of temperature (16–33 °C) and salinity (5–20 ppt) dependencies for optimal growth. Increased water temperatures caused by atmospheric warming and increased salinity gradients caused by sea level rise raise concerns for the effect of climate change on the geographic range of Vv and the potential for increased exposure risk. This research combined monthly field sampling, laboratory analysis, and modeling to identify the current occurrence of Vv in the Winyah Bay estuary (South Carolina, USA) and assess the possible effects of climate change on future geographic range and exposure risk in the estuary. Vv concentrations ranged from 0 to 58 colony forming units (CFU)/mL, salinities ranged from 0 to 28 ppt, and temperature from 18 to 31 °C. A significant empirical relationship was found between Vv concentration and salinity and temperature that fit well with published optimal ranges for growth for these environmental parameters. These results, when coupled with an existing model of future specific conductance, indicated that sea level rise has a greater impact on exposure risk than temperature increases in the estuary. Risk increased by as much as four times compared to current conditions with the largest temporally widespread increase at the most upriver site where currently there is minimal risk.

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This paper examines the performance of a semi-distributed hydrology model (i.e., Soil and Water Assessment Tool [SWAT]) using Sequential Uncertainty FItting (SUFI-2), generalized likelihood uncertainty estimation (GLUE), parameter solution (ParaSol), and particle swarm optimization (PSO). We applied SWAT to the Waccamaw watershed, a shallow aquifer dominated Coastal Plain watershed in the Southeastern United States (U.S.). The model was calibrated (2003)(2004)(2005) and validated (2006)(2007) at two U.S. Geological Survey gaging stations, using significant parameters related to surface hydrology, hydrogeology, hydraulics, and physical properties. SWAT performed best during intervals with wet and normal antecedent conditions with varying sensitivity to effluent channel shape and characteristics. In addition, the calibration of all algorithms depended mostly on Manning's n-value for the tributary channels as the surface friction resistance factor to generate runoff. SUFI-2 and PSO simulated the same relative probability distribution tails to those observed at an upstream outlet, while all methods (except ParaSol) exhibited longer tails at a downstream outlet. The ParaSol model exhibited large skewness suggesting a global search algorithm was less capable of characterizing parameter uncertainty. Our findings provide insights regarding parameter sensitivity and uncertainty as well as modeling diagnostic analysis that can improve hydrologic theory and prediction in complex watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.(KEY TERMS: SWAT; parameter uncertainty; shallow aquifer; modeling diagnostic analysis.) Samadi, S., D.L. Tufford, and G.J. Carbone, 2017. Assessing Parameter Uncertainty of a Semi-Distributed Hydrology Model for a Shallow Aquifer Dominated Environmental System.