Increases in timber demand and urban development in the Atlantic Coastal Plain over the past decade have motivated studies on the hydrology, water quality, and sustainable management of coastal plain watersheds. However, studies on baseline water budgets are limited for the low‐lying, forested watersheds of the Atlantic Coastal Plain. The purpose of this study was to document the hydrology and a method to quantify the water budget of a first‐order forested watershed, WS80, located within the USDA Forest Service Santee Experimental Forest northeast of Charleston, South Carolina. Annual Rainfall for the 2003 and 2004 periods were 1,671 mm (300 mm above normal) and 962 mm (over 400 mm below normal), respectively. Runoff coefficients (outflow as a fraction of total rainfall) for the 2003 and 2004 periods were 0.47 and 0.08, respectively, indicating a wide variability of outflows as affected by antecedent conditions. A spreadsheet‐based Thornthwaite monthly water balance model was tested on WS80 using three different potential evapotranspiration estimators [Hamon, Thornthwaite, and Penman‐Monteith (P‐M)]. The Hamon and P‐M‐based methods performed reasonably well with average absolute monthly deviations of 12.6 and 13.9 mm, respectively, between the measured and predicted outflows. Estimated closure errors were all within 9% for the 2003, 2004, and seasonal water budgets. These results may have implications on forest management practices and provide necessary baseline or reference information for Atlantic Coastal Plain watersheds.
A study has been conducted to evaluate a spreadsheet-based conceptual Thornthwaite monthly water balance model and the process-based DRAINMOD model for their reliability in predicting tnonthly water buclgets of a poorly drained, first order forested watershed at the Santee Experixnental Forest Located along the Lower Coastal Plain of South Carolina. Measured precipitation, weather, stream flow and soil hydraulic data from a 160 ha low-gradient, naturally drained watershed on a mixed pine hardwood forest (WS80) were used in the testing of the models. The Penman-Monteith and 'Thonlthwaite based potential evapotranspiration (PET) methods were used in both models. While rooting depth and field capacity of the soil were the only parameters needed for the Thomthwaite model, complete data on soil water retention and saturated hydraulic coridr~ctivity by layers, root depths, surface storage, and drainage design parameters were needed for DRAINMOD to simulate monthly and annual hydrology. As expected, results rising two and a half years (January 2003 -June 2005 of data showed that DRAINMOD was a better predictor (Nash-Sutclifi-e E = 0.92 and absolute average monthly deviation, Eedrnd =^ 11 .0 mm) of ~~lonthly outflows compared to the Thornthwaite model (E == 0.83 and Edamd = 16.8 mm). Although DRAMMOD can also be used to analyze the daily water table dynamics in contrast to the Thomthwaite model, it was not considered in this study. A DRAINMOD sirnulatiotl was later conducted with a 46-year (1 956-2002) weather dataset to evaluate the long-tern~ hydrology of the watershed, specifically to describe the variability in predicted outflows as affected by the year-to-year climatic variations. Despite the limitations of these models, they can be useful tools for land rnanagers and planners to estimate water tables, q~lantify fyrnonthly and seasonal water budgets as well as estimate nutrient and sediment loadings from poorly drained coastal forests. KEYWORDS: Hydrologic models, poorly drained, DRAINMOD, Thornthwaite, runoff, ETForests have an importailt role in controlling hydrologic patterns in the Southeastern US where 55% of the region is forested (Sun et al., 2002). Several factors in the past few decades have motivated stucties on the hydrologic characteristics and effective management of these ecosystems. First, the timber production in the Southeast U.S. has more than doubled from 1953 to 1997 (Wear and Cireis, 20021, and timber management practices including fertilizer and herbicide use, short harvesting rotations, and drainage can have negative consequences in the form of nonpoint-source pollution. Secondly, the Southeastern U.S. is expected to lose about 4.9 million forest hectares (ha) to urbanization between 1992 and 2020 with a significant part of the loss concentrated in the Atlantic Coastal Plain (Wear and Greis, 2002). A significant fraction of these ecosystems is forested wetlands, and if not properly managed, both the timber management practices and the increased development can adversely impact these ecosystem...
Given South Carolina’s ongoing water planning efforts, in this study, we evaluated seasonal and annual potential evapotranspiration (PET) using measured Class A pan evaporation (PE) and 3 widely used estimation methods for the state with 3 distinct physiographic regions (Coastal, Piedmont, and Mountain). The methods were temperature-based Hargreaves-Samani (H-S), radiation-based Priestley-Taylor (P-T), and process-based Penman-Monteith (P-M). The objectives of the study were to (a) describe seasonal and temporal distribution of PET by all methods, (b) quantify differences among PET methods, and (c) identify relationships between monthly PE and estimated PET by each method. Daily weather variables from 59 National Oceanic and Atmospheric Administration weather stations distributed in the 3 regions of South Carolina (SC) were used to estimate daily PET for an 18-year period (1998–2015). Net radiation was estimated using modeled solar radiation values for weather stations. The average annual H-S PET values adjusted with the empirical radiation factor (KT) and the average annual P-T PET values for 1998–2015 were 1,232 ± 9, 1,202 ± 11, and 1,115 ± 10 mm and 1,179 ± 10, 1,137 ± 11, and 1,082 ± 11 mm, respectively, for the Coastal, Piedmont, and Mountain regions. Both the mean annual H-S and P-T PET for the Mountain region were significantly (α = 0.05) lower than for the Coastal and Piedmont regions. The mean annual P-T PET for the Coastal region was significantly (α = 0.05) greater than that for the Piedmont. Regional differences showed that estimated PET for 1998-2015 was greatest in the Coastal and lowest in the Mountain region. Comparison of all 3 methods using only common 8-year data showed mean annual P-M PET, varying from 1,142 mm in the Piedmont to 1,270 mm in the Coastal region, was significantly higher than both the H-S and P-T PET in both regions. The greatest mean monthly H-S and P-T PET values were observed in June and July. Statistical evaluation using Nash–Sutcliffe efficiency and percent bias showed a slightly better agreement of H-S PET with both the measured PE as well as the P-M method, followed by the P-T. However, the P-T method yielded a close to unity slope and slightly higher R2 than the H-S PET when compared with the PE. The P-T PET method that uses both the temperature and radiation data may be preferred for SC with a humid climate dominated by forest land use, given more rigorous ground-truthing of modeled solar radiation as data become available. Surface interpolation algorithm, inverse distance weighted, was used to spatially map both the distributed H-S and P-T PET for the state. Results from this study can be used to support several components of the ongoing water planning efforts in SC.
. -The U.S. Department of Energy sponsored the drilling of three wells in 2003 near the Nopal I uranium deposit at the Sierra Peiia Blanca, Chihuahua, Mexico. Piezometric information is being collected to understand groundwater flow at local and regional levels as part of an ongoing natural analogue study of radionuclide migration. Water level monitoring reported at these and other wells in the region is combined with archival data to provide a better understanding of the hydrology at Nopal I. Initial results suggest that the , local hydrology is dependent on the regional hydrologic setting and that this groundwater system behaves as an unconfined aquifer.The region is dominated by an alternating sequence of highlands and basins that step down from west to east. The Sierra de Peiia Blanca was downdropped from the cratonic block to the west during Cenozoic extension. The Nopal I area is near the intersection of two large listrjc faults, and the questa of ash flow tuffs that hosts the deposit has been subjected to complex structural events. The PeAa Blanca Uranium District was originally characterized by 105 airborne radiometric anomalies, indicating widespread uranium mineralization.The Nopal I uranium deposit is located in the Sierra del PeAa Blanca between the Encinillas Basin to the west, with a mean elevation of 1560 m, and the El Cuervo Basin to the east, with a mean elevation of 1230 m. The Nopal I +10 level is at an intermediate elevation of 1463 m, with a corresponding groundwater elevation of approximately 1240 m. The regional potentiometric surface indicates flow from west to east, with the El Cuervo Basin being the discharge zone for the regional flow system. However, it appears that the local groundwater potential beneath the Nopal I site is more in accordance with the water table of the El Cuervo Basin than with that of the Encinillas Basin. This might indicate that there is limited groundwater flow between the Encinillas Basin and the Nopal I area.
Groundwater levels are examined to document and evaluate short- and long-term trends observed in each of the major aquifers in the State. Data are compiled from groundwater-monitoring networks maintained by the South Carolina Department of Natural Resources (DNR), the South Carolina Department of Health and Environmental Control (DHEC), and the United States Geological Survey (USGS). The data are used in the support of groundwater management and allocation, assessment of droughts, groundwater-flow modeling, and resource assessment. Hydrographs from approximately 170 wells are reviewed with periods of record ranging from 1 to 56 years.
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