Losing Ground: The Analysis of the Universal Soil Loss Equation Model CHRISTOPHER J. PORTER NORTH CAROLINA AGRICULTURAL AND TECHNICAL STATE UNIVERSITY.

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Presentation transcript:

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

Presentation Overview  Hypothesis  Project Background  Methodology  Data/Results  Conclusion  Acknowledgements

HYPOTHESIS  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?

PROJECT BACKGROUND  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

USLE – UNIVERSAL SOIL LOSS EQUATION A = R*K*LS*C*P  Normally calculated in tons 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)

Project Methodology  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 Variables VariableValueUnitsCondition(s) R225 Interpolated from Rainfall Map K0.3 Silty Loam Soil LS0.0038Dimensionless Interpolated from LS Matrix C15Dimensionless Continuous Fallow, Rows on Contour P0.6 or 0.5Dimensionless If %slope is 0.2, P = 0.6 If %slope is 0.3, P = 0.5

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

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

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

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

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

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

CONCLUSION & DISCUSSION  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

REFERENCES 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, 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, Print.

ACKNOWLEDGEMENTS  This material is based upon work supported by the National Science Foundation under NSF Grant #DGE 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