3.8 Article

EVALUATING THE HYDROLOGIC AND WATER QUALITY IMPACTS OF THE REVISED SCS CN METHOD AND ITS IMPLICATIONS ON DECISION-MAKING

Journal

JOURNAL OF THE ASABE
Volume 65, Issue 6, Pages 1451-1464

Publisher

AMER SOC AGRICULTURAL & BIOLOGICAL ENGINEERS
DOI: 10.13031/ja.15132

Keywords

Hydrology; Revised curve number method; SCS Curve Number Method; Soil and Water Assessment Tool; Water quality

Funding

  1. Pennsylvania Department of Agriculture, USDA National Institute of Food and Agriculture Federal Appropriations
  2. USDA- NIFA Federal Appropriations
  3. [PEN04574]
  4. [PEN04629]

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The Soil Conservation Service (SCS) Curve Number (CN) method is a widely used model for estimating surface runoff. The model, developed by the Natural Resources Conservation Service (NRCS), considers factors such as land cover, soil type, and precipitation depth. However, due to its development over 60 years ago with limited data, the NRCS is considering revising the model with the help of an ASCE-ASABE task group. The proposed revisions aim to improve the estimation of hydrologic response and water quality variables, especially for low flow events. The revisions also have implications for design storm runoff analysis.
The Soil Conservation Service (SCS) Curve Number (CN) method is a widely used model developed by the Natural Resources Conservation Service (NRCS) that estimates surface runoff generated from a land area using factors such as land cover, soil type, and precipitation depth. However, because this empirical model was developed over 60 years ago with limited data, the NRCS is considering revising it with the help of an ASCE-ASABE task group. The proposed revisions include updating the initial abstraction (Ia) ratio in the CN equation and modifying the curve number (CN) for all land use and soil hydrologic group combinations. The proposed revisions are expected to alter the hydrologic response estimation, especially for low flow events. Since surface runoff is driving sediment, nutrients, and the transport of chemicals in natural systems, this study aims to understand how predicted hydrologic and water quality variables vary between the original and the proposed revised versions of the SCS CN method using the Soil and Water Assessment Tool (SWAT). Addi-tionally, a case study site was selected to understand how the revisions alter the design storm runoff analysis. Results from the simulation case study on a 36,900 ha mixed land-use watershed located in central Pennsylvania, USA indicate a 5% to 14% increase in annual runoff predictions with the revised equation compared to the original equation. Though most average monthly runoff depths increased by 1% to 25% using the revised equation, winter months generally simulated runoff depths that were 1% to 5% lower than the original equation. Average daily loadings at the watershed outlet increased by 11% to 19% and 4% to 11% for nitrate and mineral phosphorus, respectively. The SWAT simulation results suggest that current agricultural and urban best management practices (BMPs) will experience higher runoff volumes on a yearly time scale due to the decrease in the Ia term, while the design storm case study results suggest that urban BMPs can be smaller in size when rural lands are urbanized due to the reduction in runoff estimation from the initial land use with the revised equation. Additional detailed evaluations of the proposed SCS CN method are required for water quality simulations, storm-water and BMP

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