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Losing Ground: The Analysis of the Universal Soil Loss Equation Model

Losing Ground: The Analysis of the Universal Soil Loss Equation Model. Christopher J. Porter North Carolina Agricultural and Technical State University Faculty Advisor: Dr. John Albertson, Professor and Chair, Department of Civil and Environmental Engineering Tan Zi , Graduate Student

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Losing Ground: The Analysis of the Universal Soil Loss Equation Model

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  1. Losing Ground: The Analysis of the Universal Soil Loss Equation Model Christopher J. Porter North Carolina Agricultural and Technical State University Faculty Advisor: Dr. John Albertson, Professor and Chair, Department of Civil and Environmental Engineering Tan Zi, Graduate Student WISENET IGERT REU Fellow

  2. Hypothesis Project Background Methodology Data/Results Conclusion Acknowledgements Presentation Overview

  3. What precipitation factors matter in soil erosion, intensity, amount or a combination of both? • What would be the roles of different slopes and land uses in the erosion simulation? HYPOTHESIS

  4. Soil erosion - Natural process that can occur either slowly or rapidly and causes severe loss of topsoil and agricultural production In order to analyze the erosion, scientist have developed the USLE – Universal Soil Loss Equation USLE is capable of suiting the analytical need of various watersheds, depending on the region and conditions PROJECT BACKGROUND

  5. A = R*K*LS*C*P Normally calculated intons on an annual basis but other units can be utilized given the circumstances Values expressed are determined from tables, maps, charts and decades of experimentation Units: metric tons/acre/yr (common) or metric tons/ha/yr (project) USLE – UNIVERSAL SOIL LOSS EQUATION

  6. Review reference articles to find and understand meaning behind USLE Factors Generate MATLAB code for LS Factor using elevation, slope grade and slope length Determine Soil Erosion Rate and plot maps and histograms Study IPCC Report and determine projected precipitation and climate changes in relation to USLE Project Methodology

  7. Project Variables

  8. Regional Location:Located at 39.23°N by 92.12°W Figure 1: Rainfall & Runoff Factor (R) Map

  9. Topographic Factor: Slope-Length and Slope-Steepness Figure 2b: LS Factor Distribution Figure 2a: LS Factor Map

  10. Elevation vs. Stream Figure 3b: Watershed Stream Path Figure 3a: Watershed Elevation

  11. USLE Graphical Results Figure 4b: Erosion Rate Distribution Figure 4a: USLE Erosion Map

  12. Near-Term Projection Results Figure 5: Near-Term Projection Map (Annual)

  13. Long-Term Projection Results Figure 6b: Long-Term Projection (April-September) Figure 6a: Long-Term Projection (October-March)

  14. The information from the USLE is regional and useful for long-term planning and analysis Constantly changing slope and varying land use does have an impact on the rate of soil erosion There will be impacts to soil erosion rates from the changes in precipitation that will occur in the near-term and long-term future CONCLUSION & DISCUSSION

  15. Change, Intergovernmental Panel on Climate. Climate Change 2013: The Physical Science Basis: Working Group I Contribution to the IPCC Fifth Assessment Report. Cambridge: Cambridge UP, 2014. Print. Wischmeier, Walter H., and Dwight David Smith. Predicting Rainfall Erosion Losses: A Guide to Conservation Planning. Washington: Dept. of Agriculture, Science and Education Administration, 1978. Print. REFERENCES

  16. This material is based upon work supported by the National Science Foundation under NSF Grant #DGE-1068871 as part of the Integrative Graduate Education and Research Training (IGERT) program in Wireless intelligent sensor networks (WISeNET) at Duke University’s Pratt School of Engineering Dr. John Albertson Tan Zi ACKNOWLEDGEMENTS

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