Hydrogeology and Ground-Water Quality of Brunswick County, North Carolina

Harden, Stephen L.; Fine, Jason M.; Spruill, Timothy B.

doi:10.3133/wri034051

Cited by 1 publication

(6 citation statements)

References 13 publications

(22 reference statements)

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“…These estimates are consistent with model predictions for some of our sub-watersheds, though the average for the entire area is lower than estimates given by Wilder et al [66] and Hardin et al [67]. Our study area extends further inland than either of Wilder et al [66] or Hardin et al [67] studies; rainfall generally decreases with distance from the coast throughout North Carolina and is one factor that can explain the differences in the average predicted SURQ rates. The lower than average precipitation during this period is also a likely an influencer of the low SURQ predictions in the upland areas, as more rainwater would be expected to infiltrate the surface when the soils are unsaturated or partially saturated as opposed to entering streams as runoff.…”

Section: Surq and Percsupporting

confidence: 88%

“…Our study area extends further inland than either of Wilder et al [66] or Hardin et al [67] studies; rainfall generally decreases with distance from the coast throughout North Carolina and is one factor that can explain the differences in the average predicted SURQ rates. mm/yr [67]. These estimates are consistent with model predictions for some of our sub-watersheds, though the average for the entire area is lower than estimates given by Wilder et al [66] and Hardin et al [67].…”

Section: Surq and Percmentioning

confidence: 77%

“…The calibrated sub-watersheds for the Chinquapin and Black ranged from 7 to 106 mm/yr. In northeastern North Carolina, the estimated annual surface runoff is about 125 mm/yr [66] based on an average precipitation of 1270 mm/yr, while in Brunswick County (located south-southeast of our study area) annual surface runoff is estimated to be about 230 mm/yr based on an average precipitation of 1400 mm/yr [67]. These estimates are consistent with model predictions for some of our sub-watersheds, though the average for the entire area is lower than estimates given by Wilder et al [66] and Hardin et al [67].…”

Section: Surq and Percmentioning

confidence: 99%

“…In northeastern North Carolina, the estimated annual surface runoff is about 125 mm/yr [66] based on an average precipitation of 1270 mm/yr, while in Brunswick County (located south-southeast of our study area) annual surface runoff is estimated to be about 230 mm/yr based on an average precipitation of 1400 mm/yr [67]. These estimates are consistent with model predictions for some of our sub-watersheds, though the average for the entire area is lower than estimates given by Wilder et al [66] and Hardin et al [67]. Our study area extends further inland than either of Wilder et al [66] or Hardin et al [67] studies; rainfall generally decreases with distance from the coast throughout North Carolina and is one factor that can explain the differences in the average predicted SURQ rates.…”

Section: Surq and Percmentioning

confidence: 99%

“…mm/yr [67]. These estimates are consistent with model predictions for some of our sub-watersheds, though the average for the entire area is lower than estimates given by Wilder et al [66] and Hardin et al [67]. Our study area extends further inland than either of Wilder et al [66] or Hardin et al [67] studies; rainfall generally decreases with distance from the coast throughout North Carolina and is one factor that can explain the differences in the average predicted SURQ rates.…”

Section: Surq and Percmentioning

confidence: 99%

See 4 more Smart Citations

Evaluating SWAT Model Performance for Runoff, Percolation, and Sediment Loss Estimation in Low-Gradient Watersheds of the Atlantic Coastal Plain

Mapes

Pricope

2020

Hydrology

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With predicted alterations in climate and land use, managing water resources is of the utmost importance, especially in areas such as the United States (U.S.) Coastal Plain where extensive connections exist between surface and groundwater systems. These changes create the need for models that effectively assess shifting hydrologic regimes and, in that context, we examine the performance of the Soil and Water Assessment Tool (SWAT) in a low-gradient, shallow-aquifer-dominated watershed of the U.S. Coastal Plain using a gridded reanalysis dataset. We evaluate accuracy, uncertainty, and parameter sensitivity by comparing observed and predicted streamflow at two gaging stations and assess model predictions for yearly average runoff (SURQ), percolation (PERC), and sediment loss (SYLD). Streamflow performance was acceptable during calibration (NSE = 0.67 and 0.60) and very good during validation (NSE = 0.84 and 0.91). Model predictions for SURQ, PERC, and SYLD coincided with expected ranges for this region. Parameters related to shallow aquifer properties or groundwater were highly sensitive, which indicates the need for continued study of spatial and temporal variability within the sub-surface components of these hydrologic systems. Our findings highlight the applicability of this reanalysis dataset for modeling hydrologic processes in poorly gaged watersheds and adds to the body of research that seeks to develop effective assessment tools for shallow-aquifer-dominated systems. Our methodology can effectively assist watershed managers in establishing baseline rates of hydrologic processes as is crucial with future predicted shifts in hydrologic regimes due to land-use alteration and climate change.

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Section: Surq and Percsupporting

confidence: 88%