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Development of a Turbidity Prediction Methodology for Runoff–Erosion Models

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Abstract

Surface water bodies can be impaired by turbidity and excessive sediment loading due to urban development, construction activities, and agricultural practices. Turbidity has been considered as a proxy for evaluating water quality, aquatic habitat, and aesthetic impairments in surface waters. The US Environment Protection Agency (USEPA) has listed turbidity and sediment as major pollutants for construction site effluent. Recently proposed USEPA regulations for construction site runoff led to increased interest in methods to predict turbidity in runoff based on parameters that are more commonly predicted in runoff–erosion models. In this study, a turbidity prediction methodology that can be easily incorporated into existing runoff–erosion models has been developed using fractions of sand, silt, and clay plus suspended sediment concentration of eight parent soils from locations in Oklahoma and South Carolina, USA.

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Acknowledgments

This research was funded in part by the Oklahoma Department of Transportation Research Program, the Oklahoma Transportation Center, and Woolpert, Inc. The authors would like to thank Magen Kegley, Riley Jones, and Hanna Huling for assistance in data collection.

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  1. Department of Biosystems and Agricultural Engineering, Oklahoma State University, 111 Agricultural Hall, Stillwater, OK, 74078, USA

    Sagar Neupane, Bill J. Barfield & Aaron R. Mittelstet

  2. Department of Biosystems and Agricultural Engineering, Oklahoma State University, 218 Agricultural Hall, Stillwater, OK, 74074, USA

    Jason R. Vogel

  3. Department of Biosystems and Agricultural Engineering, Oklahoma State University, 121 Agricultural Hall, Stillwater, OK, 74078, USA

    Daniel E. Storm

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  1. Sagar Neupane
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Correspondence to Jason R. Vogel.

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Neupane, S., Vogel, J.R., Storm, D.E. et al. Development of a Turbidity Prediction Methodology for Runoff–Erosion Models. Water Air Soil Pollut 226, 415 (2015). https://doi.org/10.1007/s11270-015-2679-9

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