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Scientific Investigations Report 2010–5202

National Water-Quality Assessment Program

Prepared in cooperation with the U.S. Environmental Protection Agency,
National Exposure Research Laboratory

Simulation of Streamflow in the McTier Creek Watershed, South Carolina

By Toby D. Feaster, Heather E. Golden, Kenneth R. Odom, Mark A. Lowery, Paul A. Conrads, and Paul M. Bradley

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ABSTRACT

The McTier Creek watershed is located in the Sand Hills ecoregion of South Carolina and is a small catchment within the Edisto River Basin. Two watershed hydrology models were applied to the McTier Creek watershed as part of a larger scientific investigation to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River Basin. The two models are the topography-based hydrological model (TOPMODEL) and the grid-based mercury model (GBMM). TOPMODEL uses the variable-source area concept for simulating streamflow, and GBMM uses a spatially explicit modified curve-number approach for simulating streamflow. The hydrologic output from TOPMODEL can be used explicitly to simulate the transport of mercury in separate applications, whereas the hydrology output from GBMM is used implicitly in the simulation of mercury fate and transport in GBMM. The modeling efforts were a collaboration between the U.S. Geological Survey and the U.S. Environmental Protection Agency, National Exposure Research Laboratory.

Calibrations of TOPMODEL and GBMM were done independently while using the same meteorological data and the same period of record of observed data. Two U.S. Geological Survey streamflow-gaging stations were available for comparison of observed daily mean flow with simulated daily mean flow—station 02172300, McTier Creek near Monetta, South Carolina, and station 02172305, McTier Creek near New Holland, South Carolina. The period of record at the Monetta gage covers a broad range of hydrologic conditions, including a drought and a significant wet period. Calibrating the models under these extreme conditions along with the normal flow conditions included in the record enhances the robustness of the two models.

Several quantitative assessments of the goodness of fit between model simulations and the observed daily mean flows were done. These included the Nash-Sutcliffe coefficient of model-fit efficiency index, Pearson's correlation coefficient, the root mean square error, the bias, and the mean absolute error. In addition, a number of graphical tools were used to assess how well the models captured the characteristics of the observed data at the Monetta and New Holland streamflow-gaging stations. The graphical tools included temporal plots of simulated and observed daily mean flows, flow-duration curves, single-mass curves, and various residual plots. The results indicated that TOPMODEL and GBMM generally produced simulations that reasonably capture the quantity, variability, and timing of the observed streamflow. For the periods modeled, the total volume of simulated daily mean flows as compared to the total volume of the observed daily mean flow from TOPMODEL was within 1 to 5 percent, and the total volume from GBMM was within 1 to 10 percent. A noticeable characteristic of the simulated hydrographs from both models is the complexity of balancing groundwater recession and flow at the streamgage when flows peak and recede rapidly. However, GBMM results indicate that groundwater recession, which affects the receding limb of the hydrograph, was more difficult to estimate with the spatially explicit curve number approach. Although the purpose of this report is not to directly compare both models, given the characteristics of the McTier Creek watershed and the fact that GBMM uses the spatially explicit curve number approach as compared to the variable-source-area concept in TOPMODEL, GBMM was able to capture the flow characteristics reasonably well.

First posted November 24, 2010

For additional information contact:
Director
USGS South Carolina Water Science Center
720 Gracern Road, Suite 129
Columbia, SC 29210–7651
phone: 803–750–6100 http://sc.water.usgs.gov/

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Suggested citation:

Feaster, T.D., Golden, H.E., Odom, K.R., Lowery, M.A., Conrads, P.A., and Bradley, P.M., 2010, Simulation of streamflow in the McTier Creek watershed, South Carolina: U.S. Geological Survey Scientific Investigations Report 2010–5202, 61 p.



Contents

Foreword

Acknowledgments

Abstract

Introduction

Purpose and Scope

Previous Studies

Description of the McTier Creek Watershed

TOPMODEL Streamflow Concepts

Topographic Wetness Index

TOPMODEL Water Balance

GBMM Streamflow Concepts

Methods of Study

Data Collection

Calibration of TOPMODEL and GBMM

Simulation of the Streamflow for TOPMODEL and GBMM

Simulations for Monetta for the Calibration Period

Simulations at New Holland for the Confirmation Period

Goodness-of-Fit Statistics for TOPMODEL and GBMM

Goodness-of-Fit Statistics at Monetta for the Calibration Period Simulations

Goodness-of-Fit Statistics at Monetta for the Concurrent Period Simulations

Goodness-of-Fit Statistics at New Holland for Confirmation Period Simulations

Flow-Duration Curves, Single-Mass Curves, and Residuals

Flow-Duration Curves

Single-Mass Curves

Residuals

Residuals and Simulated Flow

Residuals (Temporal)

Watershed Model Uncertainties and Limitations

Watershed Model Uses

Mapping Saturated Areas

Modeling Hydrology in Subwatersheds

Loadings from TOPMODEL Flow Components

Estimating Water, Sediment, and Mercury Balances with GBMM

Identifying Spatially Explicit Mercury Source Areas in Watersheds

Summary

References Cited

Appendix 1—Model Components in TOPMODEL

Appendix 2—Model Components of GBMM: Hydrology Module


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