Geosciences Journal

, Volume 16, Issue 2, pp 181–192 | Cite as

Impacts of GIS data quality on determination of runoff and suspended sediments in the Imha watershed in Korea

Article

Abstract

Excessive soil loss during heavy rainfall results in serious turbid water problem in the reservoir. For the purpose of efficient turbid water management in the upland area of the Imha watershed in Korea, this study applied SWAT (Soil and Water Assessment Tools) for assessment of the soil erosion and attempted to evaluate the impact of GIS data on model response to test the model efficiency. First, the outputs of runoff and suspended sediment were investigated corresponding to the various DEM grid sizes (i.e., 30, 60, 90, 120, and 150 m). Further analysis was based on the 8 different scenarios combining with different scales of land use (i.e., 1:25,000 and 1:50,000) and soil type maps (i.e., 1:50,000 and 1:250,000) associated with two different DEM grid sizes. Statistical analysis of the simulated results revealed that model efficiency improved with 30 m resolution DEMs for estimation of runoff and suspended sediment. However, no significant improvement was expected associated with detailed scales of land cover and soil maps. The findings of this study will contribute to select the quality of GIS data, with no expense of the accuracy of model prediction to simulate runoff and suspended sediments.

Key words

SWAT GIS data resolution runoff suspended sediment Imha watershed 

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References

  1. Chaplot, V., 2005, Impact of DEM mesh size and soil map scale on SWAT runoff, sediment, and NO3-N loads predictions. Journal of Hydrology, 312, 207–222.CrossRefGoogle Scholar
  2. Di Luzio, M., Arnold, J.G., and Srinivasan, R., 2005, Effect of GIS data quality on small watershed stream flow. Hydrological Processes, 19, 629–650.CrossRefGoogle Scholar
  3. Kim, J., Son, K.H., Noh, J., and Lee, S.U., 2008, Estimation of Suspended Sediment Load in Imha-Andong Watershed using SWAT model. Korean Society of Environmental Engineers, 30, 1209–1217. (in Korean with English abstract)Google Scholar
  4. Nash, J.E. and Sutcliffe, J.V., 1970, River flow forecasting through conceptual models part I A discussion of principles. Journal of Hydrology, 10, 282–290.CrossRefGoogle Scholar
  5. Neitsch, S.L., Arnold, J.G., Kiniry, J.R., and Williams, J.R., 2000, Soil and Water Assessment Tool User’s Manual Version 2000. Grassland, soil and water research laboratory, Agricultural Research Service, 808 East Blackland Road, Temple, Texas, 76502.Google Scholar
  6. Saxton, K.E. and Rawls, W.J., 2006, Soil Water Characteristic Estimates by Texture and Organic Matter for Hydrologic Solutions. Soil Science Society American Journal, 70, 1569–1578.CrossRefGoogle Scholar
  7. Williams, J.R., 1975, Sediment yield prediction with universal equation using runoff energy factor. Agricultural Research Service, USDA, ARS-S-40, Present and prospective technology for predicting sediment yield and sources. In: Proceeding of the sediment yield workshop, 244–252.Google Scholar
  8. Williams, J.R. and Berndt, H.D., 1977, Sediment yield prediction based on watershed hydrology. Transactions of the ASABE, 20, 1100–1104.Google Scholar
  9. Williams, J.R., 1995, The EPIC model. In: Singh, V.P. (ed.), Computer Models of Watershed Hydrology. Water Resources Publications, Highlands Ranch, CO, 909–1000 (Chapter 25).Google Scholar
  10. Wischmeier, W.H., 1960, Cropping-management factor evaluation for a universal soil loss equation, In: Proceedings of the Soil Science Society of America, 24, 322–326.CrossRefGoogle Scholar

Copyright information

© The Association of Korean Geoscience Societies and Springer-Verlag Berlin Heidelberg  2012

Authors and Affiliations

  • Jeongkon Kim
    • 1
  • Joonwoo Noh
    • 1
  • Kyungho Son
    • 2
  • Ikjae Kim
    • 3
  1. 1.K-water Research InstituteDaejeonRepublic of Korea
  2. 2.Department of Environmental Science and EngineeringUniversity of CaliforniaSanta BarbaraUSA
  3. 3.Korea Environment InstituteSeoulRepublic of Korea

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