The Analysis of Reduction Efficiency of Soil Erosion and Sediment Yield by a Ginseng Area using GIS Tools

  • Published : 2009.12.31

Abstract

Recently, turbidity problem is one of the hot issues in dam and reservoir management works. Main reason to bring about high density turbid water is sediment yield by rainfall intensity energy. Because existing researches didn't consider diverse types of crops, it was difficult to calculate more accurate soil erosion and sediment yield. This study was evaluated the reduction efficiency of soil erosion and sediment yield using ginseng layer extracted from IKONOS satellite image, and the area and the ratio of ginseng area represented $0.290km^2$ and 0.94%. The reduction efficiency of soil erosion considering ginseng area represented low value in 0.9% using GIS-based RUSLE model, because the area of ginseng was small compared to areas of other agricultural lands. To reflect future land use change, this study was calculated the reduction efficiency of soil erosion and sediment yield by considering many scenarios as kinds of crops of paddy, dry field, orchard, and other agricultural areas convert to the ginseng district. As result of analysis of them according to scenarios, scenario (1) in which dry field was converted to ginseng area and scenario (2) in which fully agricultural lands were converted to ginseng area showed high reduction efficiency as 31.3% and 34.8% respectively, compared to existing research which didn't consider ginseng area. Methodology suggested in this study will be very efficient tools to help reservoir management related to high density turbid water.

최근 탁수문제는 댐과 저수지관리 업무에서 중요한 이슈중의 하나가 되고 있으며, 고탁수를 유발하는 주요원인은 강우강도 에너지에 의한 유사량이다. 기존의 연구들은 다양한 작물형태를 고려하지 않아 정확한 토양 침식 및 유사량을 계산할 수 없었다. 본 연구에서는 IKONOS 위성영상으로부터 추출한 인삼밭 레이어를 이용하여 토양침식량과 유사량의 저감효과를 분석하였으며, 인삼밭의 면적과 점유비율은 각각 $0.290km^2$와 0.94%로 나타났다. GIS 기반 RUSLE 모델을 이용하여 인삼밭을 고려한 토양침식량의 저감효과를 분석한 결과는 0.9%로 낮게 나타났으며, 이는 인삼밭의 면적이 다른 농경지에 비해 상대적으로 작기 때문으로 해석된다. 미래의 토지이용변화를 반영하기 위해, 본 연구에서는 논, 밭, 과수원 그리고 기타 재배지들이 인삼밭 지역으로 전환된다는 시나리오를 고려하여 토양침식과 유사량의 저감효과를 평가하였다. 시나리오에 따른 인삼밭의 저감효과를 분석한 결과, 밭지역을 인삼밭으로 전환한 시나리오 (1)과 모든 농경지를 인삼밭으로 전환한 (4)가 인삼밭을 고려하지 않은 기존의 연구와 비교할 때 31.3% 및 34.8% 더 높은 저감효과를 나타내었다. 본 연구에서 제시한 방법론은 고탁수와 관련된 저수지관리를 지원하기 위한 매우 효과적인 도구가 될 수 있을 것이다.

Keywords

References

  1. Angima S.D., Stott D.E., O's Neill M.K., Ong C.K., Weesies G.A., 2003, Soil erosion prediction using RUSLE for central Kenyan highland conditions, Agricultural Ecosystems & Environment, 97, pp. 295-308. https://doi.org/10.1016/S0167-8809(03)00011-2
  2. Anton J.J. Van Rompaey, Gerard Govers, Etienne Van Hecke, Kristine Jacobs, 2001, The impact of land use policy on the soil erosion risk: a case study in central Belgium, Agriculture Ecosystems & Environment, 83, pp.83-94. https://doi.org/10.1016/S0167-8809(00)00173-0
  3. Bartsch K.P., 1998, Modelling Soil Loss to determine water loss risk at Camp Williams national guard base, PhD, UTAH State University, USA.
  4. Erickson A.J., 1997, Aids for estimating soil erodibility – K value class and soil loss tolerance, U.S. Department of Agriculture, Soil Conservation Services: Salt Lake City of Utah.
  5. Frentle M and Julien P.Y., 1987, Computer modeling of soil erosion and sediment yield from large watershed, Int. J. Sediment Res, 2, pp.38-68.
  6. Houghton J.T., Jenkins G.J., Ephraums J.J., 2001, Climate Change 2001, Cambridge Univ. Press, Cambridge, UK.
  7. Jensen J.R., 1996, Introductory digital image processing, ISBN 0-13-205840-5, Prentice Hall Series in Geographic Information Science, pp.197-231.
  8. Donald Gabriels, Greet Ghekiere, Wouter Schiettecatte, Ilse Rottiers, 2003, Assessment of USLE cover management C-factors for 40 crop rotation systems on arable farms in the Kemmelbeek watershed, Belgium, Soil & Tillage Research, 74, pp. 47-53. https://doi.org/10.1016/S0167-1987(03)00092-8
  9. G. S. Lee, 2006, The comparative estimation of soil erosion for Andong and Imha basins using GIS spatial analysis, Korean journal of Civil Eng., 26(2D), pp. 341-347.
  10. Lufafa, A., Tenywa, M.M., Isabirye, M., Majaliwa, M.J.G., Woomer, P.L., 2003, Prediction of soil erosion in a Lake Victoria basin catchment using a GIS-based Universal Soil Loss model, Agricultural Systems, pp.883-894.
  11. Ministry for Food Agriculture Forestry and Fisheries, 2008, Statistical Handbook of Ginseng, pp.1-15.
  12. Pionke H.B., Blanchard B.J., 1975, The remote sensing of suspended sediment concentrations of small impoundments, Water, Air, and Pollution, 4, pp.19-32. https://doi.org/10.1007/BF01794129
  13. Renard K.G., G.R. Foster, G.A. Weesies and P.J. Porter, 1991, RUSLE : Revised Universal Soil Loss Equation, Journal of Soil and Water Conservation, 46(1), pp. 30-33.
  14. Sabins Floyd F., 1997, Remote Sensing (principles and interpretation), ISBN 0-7167-2442-1, Freeman Company, pp.387-416.
  15. Wayne D. Erskine, A. Mahmoudzadeh, C. Myers, 2002, Land use effects on sediment yields and soil loss rates in small basins of Triassic sandstone near Sydney, NSW, Australia, CATENA, 49, pp.271-287. https://doi.org/10.1016/S0341-8162(02)00065-6
  16. Wischmeier W.H., 1971, A Soil Erodibility Nomograph for Farmland and Construction sites, Journal of Soil and Water Conservation, 26, pp.189-193.
  17. Wischmeier W., Smith D.D., 1978, Predicting rainfall erosion losses- a guide to conservation planning, Handbook 537, USDA-ARS.