DOI QR코드

DOI QR Code

Simulation of Hydrological and Sediment Behaviors in the Doam-dam Watershed considering Soil Properties of the Soil Reconditioned Agricultural Fields

객토 농경지의 토양특성을 고려한 도암댐 유역에서의 수문 및 유사 거동 모의

  • 허성구 (강원대학교 지역기반공학과) ;
  • 김재영 (강원대학교 지역기반공학과) ;
  • 유동선 (강원대학교 지역기반공학과) ;
  • 김기성 (강원대학교 지역기반공학과) ;
  • 안재훈 (농촌진흥청 고령지 농업연구소) ;
  • 윤정숙 (인하대학교 환경토목공학부) ;
  • 임경재 (강원대학교 지역기반공학과)
  • Published : 2007.03.31

Abstract

The alpine agricultural activities are usually performed at higher and steep areas in nature. Thus, significant amounts of soil erosion are occurring compared with those from other areas. Thus, the soil erosion induced environmental impacts in these areas are getting greater. The Doam watershed is located at alpine areas and it has been well known that the agricultural activities in the watershed are causing accelerated soil erosion and water quality degradations. Many modeling approaches were employed to solve soil erosion and water quality issues. In this study, the Soil and Water Assessment Tool (SWAT) model was utilized to simulate the hydrologic and sediment behaviors in the Doam watershed. In many previous modeling studies, the digital soil map and its corresponding soil properties were used without modification to reflect soil conditioning at many agricultural fields of the Doam watershed. Thus, the soil sample was taken at the agricultural field within the Doam watershed and analyzed for its physical properties. In this study, the digital topsoil properties in the agricultural fields within the Doam watershed were replaced with the soil properties for reconditioned soil analyzed in this study to simulate the impacts of using soil properties for reconditioned soil in hydrologic and sediment modeling at the Doam watershed using the SWAT model. The hydrologic component of the SWAT model was calibrated and validated for measured flow data from 2002 to 2003. The $R^2$ value was 0.79 and the EI value was 0.53 for weekly simulated data. The calibrated model parameters were used for hydrologic component validation and the $R^2$ value was 0.86 and the EI value was 0.74 for weekly data. For sediment comparison, the $R^2$ value was 0.67 and the EI value was 0.59. These statistics improved with the use of soil properties of the reconditioned soil in the field compared with the results obtained without considering soil reconditioning. The simulated sediment amounts with and without considering the soil properties of the reconditioned soil were 284,813 ton and 158,369 ton, respectively. This result indicates that there could be approximately 79% of errors in estimated sediment yield at the Doam watershed, although the model comparison with the measured data gave similar satisfactory statistics with and without considering soil properties from the reconditioned soil.

Keywords

References

  1. Arnold, J. G, P. M. Allen, and G. Bernhardt, 1993. A comprehensive surface-ground-water flow model J Hydrol. pp, 43-69
  2. Arnold, J. G., and Srinivasan, R., 1994. Integration of a BASIN-SCALE Water Quality Model with GIS. Water Resources Bulletin. American Water Resources Association. pp. 453-462
  3. Arnold, J. G., and P. M. Allen. 1999. Automated methods for estimating baseflow and ground water recharge from streamflow records. Journal of the American Water Resources Association 35 (2): 411-424 https://doi.org/10.1111/j.1752-1688.1999.tb03599.x
  4. Barnett, V. and T.lewis. 1978. outlier information statistical Data. New York: John Wiley & Sons,Inc
  5. Enviromental Geographic Information System http://egis.me.go.kr/egis/Last accessed Oct. 1, 2005
  6. Heo, S. G., K. S. Kim, M. Sagong, J. H Ahn, K. J. Lim. 2005. Evaluation of SWAT Applicability to Simulate Soil Erosion at Highland Agricultural Lands. korea society of Agricultural Planning 11(4): 67-74
  7. Heo, S. G. 2006. Water Environmental Effect Evaluation due to Forest Fragmentation for Doam-Dam Watershed. Kangwon National University. Master's Degree Thesis
  8. Joo, J. H, Y. S. Jung, J. J. Kim, C. S. Park, J. H Yang. 2002. Characteristics of the Dressed Soil in Farm Land in Naerinchun Upper Stream and Management Practices to Reduce Soil Erosion. Kangwon National University Research Institute of Agricultural Sciences. 13: 108-115
  9. Kim, K. S, S. G. Heo, Y. S. Jung, J. M. Kim, K. J. Lim. 2005. Analysis of Soil Erosion Vulnerability at Alpine Agricultural Farms of HongCheon County. korea society of Agricultural Planning. 11(2): 51-57
  10. Korea Hydro & Nuclears Power co, http:// www.khnp.co.kr, Last accessed Nov. 1, 2006
  11. Lenhart, T., K. Eckhardt, N. Fohrer, H-G. Frede. 2002. Comparison of two different approaches of sensitivity analysis. Physics and Chemistry of the Earth 645-654
  12. Nash, J. and J. V. Sutcliffe. 1970. Rever flow forecasting through conceptual medels Part I -Discussion of principles. Journal of Hydrology 10:282-290 https://doi.org/10.1016/0022-1694(70)90255-6
  13. Park, C. S., Y. S. Jung, J. H. Joo, J. H. Yang. 2004. Soil Characteristics of the Saprolite Piled Upland Fields at Highland in Kangwon Province. korea society of soil science and fertilizer. 37(2): 66-73
  14. Ramanarayanan, T. S., Williams, J. R, Dugas, W. A, Hauck, J. M., and McFarland, A. M. S., 1997. Using APEX to identify alternative practices for animal waste management. ASAE International Meeting, Minneapolis, MN. Paper No. 97-2209
  15. Rural Development Adminstration National Institute of Agricultural Sciences and Technology, 2000
  16. Rural Development Adminstration, National Institute of Highland Agriculture, 2000. Flowering Grass Cultivation Techniques of Highland
  17. Santhi, C., J. G. Arnold, J. R Williams, W. A. Dugas, R Srinivisan, and L. M. Hauck. 2001. Validation of the SWAT model on a large river basin with point and nonpoint sources. Journal of the American Water Resources Association 37 (5): 1169-1188 https://doi.org/10.1111/j.1752-1688.2001.tb03630.x
  18. Spruill, C. A., S. R. Workman, and J. L. Taraba. 2000. Simulation of daily and monthly stream discharge from a small watershed using the SWAT model. Transactions of the ASAE 43(6): 1431-1439 https://doi.org/10.13031/2013.3041
  19. Sxhlotzhauer, S. D. and R. C. Little. 1987. SAS System for Elementary Statistical Analysis. Cary, NC: SAS Institute
  20. Water Management Information System. http://www.wamis.go.kr, Last accessed Nov. 1, 2006
  21. Water Environmental Information System. http://water.nier.go.kr/weis, Last accessed Nov. 1, 2006

Cited by

  1. Development of a SWAT Patch for Better Estimation of Sediment Yield in Steep Sloping Watersheds vol.45, pp.4, 2009, https://doi.org/10.1111/j.1752-1688.2009.00339.x