Runoff prediction in Eastern South Dakota: A comparison between runoff programs/curve Method and empirical data

Bryce Siverling, Erin Cortus, Todd Trooien

Research output: Contribution to conferencePaperpeer-review


Water contamination and nutrient loss from agriculture fields due to runoff events is a problem across the country. It affects not only the farmer themselves and those close to them but also those downstream. This is why teams across the country have been developing programs to help farmers know when it would be least risky to apply nutrients to their fields. These runoff risk and management tools have a tendency to be made for areas that are wetter and more runoff risk prone. The goal of this project was to determine if the runoff assessment tools like the commonly used Curve Method equation, would accurately predict total water runoff in Eastern South Dakota. To accomplish this, past data from field runoff events were examined alongside the Curve Number Method Equation (Huffman 2011). Such factors as soil, crop type, and topography were all taken into account in the examination. Linear regression alongside normalized mean square error compared the measured runoff and the predicted runoff. The R2 associated with the linear regression was 0.67, indicating a relationship between measured and predicted runoff. Normalized mean square errors, however, were excessively large and showed a 3.9 inflation of predicted runoff compared to the measured runoff. Therefore, the Curve Number Equation method has the tendency to overestimate runoff amounts in Eastern South Dakota for the watersheds used in the comparison.

Original languageEnglish (US)
StatePublished - 2017
Event2017 ASABE Annual International Meeting - Spokane, United States
Duration: Jul 16 2017Jul 19 2017


Other2017 ASABE Annual International Meeting
Country/TerritoryUnited States

Bibliographical note

Funding Information:
Support for this project was provided by a Natural Resource Conservation Service Conservation Innovation Grant, and the South Dakota State University Agricultural Experiment Station. Also, the authors wish to acknowledge the producers who have enabled long-term monitoring on their land, and the students who have collected data over the years from this site.


  • Curve Number
  • Runoff
  • Water quality


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