DOI QR코드

DOI QR Code

A Study to Determine the Slope Length and Steepness Factor of Universal Soil Loss Equation with Determining and Adapting Major Slope Length at Field Scale

필지 단위 주경사장 산정 및 적용을 통한 범용토양유실공식 지형인자 산정 개선 연구

  • Park, Youn Shik (Department of Rural Construction Engineering, Kongju National University) ;
  • Park, Jong-Yoon (Environmental Assessment Group, Korea Environment Institute) ;
  • Jang, Won Seok (The Sustainability Innovation Lab, University of Colorado Boulder) ;
  • Kim, Jonggun (Department of Regional Infrastructures Engineering, Kangwon National University)
  • Received : 2019.08.26
  • Accepted : 2019.10.21
  • Published : 2019.11.30

Abstract

Universal Soil Loss Equation (USLE) is to estimate potential soil loss and has benefit in use with its simplicity. The equation is composed of five factors, one of the factors is the slope length and steepness factor (LS factor) that is for topographic property of fields to estimate potential soil loss. Since the USLE was developed, many equations to compute LS was suggested with field measurement. Nowadays the factor is often computed in GIS software with digital elevation model, however it was reported that the factor is very sensitive to the resolution of digital elevation model. In addition, the digital elevation model of high resolution less than 3 meter is required in small field application, however these inputs are not associate with the empirical models' backgrounds since the empirical models were derived in 22.1 meter field measurements. In the study, four equation to compute LS factor and two approaches to determine slope length and steepness were examined, and correction factor was suggested to provide reasonable precision in LS estimations. The correction factor is computed with field area and cell size of digital elevation model, thus the correction factor can be adapted in any USLE-based models using LS factor at field level.

Keywords

References

  1. Bosco, C., de Rigo, D., Dewitte, O., Poesen, J., and P. Panagos, 2015. Modelling soil erosion at European scale: Towards harmonization and reproducibility. Natural Hazards and Earth System Sciences 15: 225-245. doi:10.5194/nhess-15-225-2015.
  2. Chaubey, I., A. S. Cotter, T. A. Costello, and T. S. Soerens, 2005. Effect of DEM data resolution on SWAT output uncertainty. Hydrological Processes 19(3): 621-628. doi:10.1002/hyp.5607.
  3. Fu, X., and L. Zhang, 2014. Impact of slope length on soil erosion on sloping farmland with crop in red soil hilly region. Transactions of the Chinese Society of Agricultural Engineering 30(5): 91-98. doi:10.3969/j.issn.1002-6819.2014.05.012.
  4. Ghahramani, A., I. Yoshiharu, and S. M. Mudd, 2012. Field experiments constraining the probability distribution of particle travel distances during natural rainstorms on different slope gradients. Earth Surface Process and Landforms 37(5): 473-485. doi:10.1002/esp.2253.
  5. Griffin, M. L., D. B. Beasley, J. J. Fletcher, and G. R. Foster, 1988. Estimating soil loss on topographically non-uniform field and farm units. Journal of Soil and Water Conservation 43: 326-331.
  6. Hrabalikova, M., and M. Janecek, 2017. Comparison of different approaches to LS factor calculations based on a measured soil loss under simulated rainfall. Soil and Water Research 12: 69-77. doi:10.17221/222/2015-SWR.
  7. Kim, J., Y. S. Park, N. W. Kim, I. M. Chung, W. S. Jang, J. H. Park, J. P. Moon, and K. J. Lim, 2008. Development and evaluation of SWAT topographic feature extraction error (STOPFEE) fix module from low resolution DEM. Journal of Korean Society on Water Quality 24(4): 488-498 (in Korean).
  8. Kim, J., J. Yang, K. J. Lim, S. C. Kim, G. Lee, S. Hwang, N. Yu, and Y. S. Park, 2017. A study to define area of concern for potential soil loss in Geumgang watershed by KORSLE-based GIS model. Journal of Soil Groundwater Environment 22(6): 29-36. doi:10.7857/JSGE.2017.22.6.029 (in Korean).
  9. Kim, J., Lim, K. J., and Y. S. Park, 2018. Evaluation of regression models of LOADEST and Eight-Parameter Model for nitrogen load estimations. Water, Air, and Soil Pollution 229: 179. doi:10.1007/s11270-018-3844-8.
  10. Kongju National University, 2017. Development of Topsoil Erosion Model for Korea. Yesan-gun: Republic of Korea.
  11. Koo, J. Y., Yoon, D. S., Lee, D. J., Han, J. H., Jung, Y., Yang, J. E., and K. J. Lim, 2016. Effect of DEM resolution in USLE LS factor. Journal of Korean Society on Water Environment 32(1): 89-97. doi:1015681/KSWE.2016.32.1.89 (in Korean). https://doi.org/10.15681/KSWE.2016.32.1.89
  12. Lin, S., C. Jing, V. Chaplot, X. Yu, Z. Zhang, N. Moore, and J. Wu, 2010. Effect of DEM resolution on SWAT outputs of runoff, sediment and nutrients. Hydrology and Earth System Sciences Discussion 7(4): 4411-4435. doi:10.5194/hessd-7-4411-2010.
  13. McCool, D. K., L. C. Brown, G. R. Foster, C. K. Mutchler, and L. D. Meyer, 1987. Revised slope steepness factor for the Universal Soil Loss Equation. Transactions of the ASAE 30: 1387-1396. doi:10.13031/2013.30576.
  14. McCool, D. K., G. R. Foster, C. K. Mutchler, and L. D. Meyer, 1989. Revised slope length factor for the Universal Soil Loss Equation. Transactions of the ASAE 32: 1571-1576. doi:10.13031/2013.31192.
  15. Ministry of Environment, 2012. A bulletin on the survey of the erosion of topsoil. Sejong-si: Ministry of Environment.
  16. Mitasova, H., J. Hofierka, M. Zlocha, and R. L. Iverson, 1996. Modeling topographic potential for erosion and deposition using GIS. International Journal of Geographical Information Science 10(5): 629-641. doi:10.1080/026937996137918.
  17. Moore, I. D., and G. J. Burch, 1986. Physical basis of the length-slope factor in the Universal Soil Loss Equation. Soil Science Society of America Journal 50: 1294-1298. doi:10.2136/sssaj1986.03615995005000050042x.
  18. Moore, I. D., and J. P. Wilson, 1992. Length-slope factors for the Revised Universal Soil Loss Equation: Simplified method of estimation. Journal of Soil and Water Conservation 47: 423-428.
  19. Panagos, P., Borrelli, P., and K. Meusburger, 2015. A new European Slope Length and Steepness Factor (LS-Factor) for Modeling Soil Erosion by Water. Geosciences 5: 117-126. doi:10.3390/geosciences5020117.
  20. Park, Y. S., and B. A. Engel, 2014. Use of pollutant load regression models with various sampling frequencies for annual load estimation. Water 6: 1685-1697. doi:10.3390/w6061685.
  21. Park, Y. S., and B. A. Engel, 2015. Analysis for regression model behavior by sampling strategy for annual pollutant load estimation. Journal of Environmental Quality 44(6): 1843-1851. doi:10.2134/jeq2015.03.0137.
  22. Wischmeier, W. H., and D. D. Smith, 1965. Predicting rainfall erosion losses from cropland east of the Rocky Mountains: A guide for selection of practices for soil and water conservation Handbook No.282. Agricultural Researach Service U. S. Department of Agriculture.
  23. Wischmeier, W. H., and D. D. Smith, 1978. Predicting rainfall erosion losses: A guide to conservation planning Handbook No.537. U. S. Department of Agriculture.
  24. Yu, N. Y., D. J. Lee, J. H. Han, K. J. Lim, J. Kim, K. H. Kim, S. Kim, E. S. Kim, and Y. S. Park, 2017a. Development of ArcGIS-based model to estimate monthly potential soil loss. Journal of the Korean Society of Agricultural Engineers 59(1): 21-30. doi:10.5389/KSAE.2017.59.1.021 (in Korean).
  25. Yu, N. Y., M. H. Shin, J. Kim, and Y. S. Park, 2017b. Application of ArcGIS-based model developed to estimate monthly potential soil loss. Journal of the Korean Society of Agricultural Engineers 59(5): 109-126. doi:10.5389/KSAE.2017.59.5.109 (in Korean).