Effects of DEM Resolution on Hydrological Simulation in, BASINS-BSPF Modeling

  • Jeon, Ji-Hong (Graduate Program, Department of Rural Engineering, Konkuk University) ;
  • Ham, Jong-Hwa (Graduate Program, Department of Rural Engineering, Konkuk University) ;
  • Chun G. Yoon (Department of Rural Engineering, Konkuk University) ;
  • Kim, Seong-Joon (Department of Rural Engineering, Konkuk University)
  • Published : 2002.12.01

Abstract

In this study, the effect of DEM (Digital Elevation Model) resolution (15m, 30m, 50m, 70m, 100m, 200m, 300m) on the hydrological simulation was examined using the BASINS (Better Assessment Science Integrating point and Nonpoint Source) for the Heukcheon watershed (303.3 ㎢) data from 1998 to 1999. Generally, as the cell size of DEM increased, topographical changes were observed as the original range of elevation decreased. The processing time of watershed delineation and river network needed more time and effort on smaller cell size of DEM. The larger DEM demonstrated had some errors in the junction of river network which might affect on the simulation of water quantity and quality. The area weighted average watershed slope became milder but the length weighted average channel slope became steeper as the DEM size increased. DEM resolution affected substantially on the topographical parameter but less on the hydrological simulation. Considering processing time and accuracy on hydrological simulation, DEM grid size of 100m is recommended for this range of watershed size.

Keywords

References

  1. Beasley, D.B. 1986. Distributed parameter hydrologic and water quality modeling. In Agricultural Nonpoint Source Pollution: Model Selection and Application. ed. A. Giorgini and F. Zingales. 345-362
  2. Beven, K. J., Wood, E. F., and Sivapalan, M. 1988. On hydrological heterogeneity-Catchment morphology and catchment response. Journal of Hydrology Vol. 100: 353-357 https://doi.org/10.1016/0022-1694(88)90192-8
  3. Burt, T. P., Butcher, D. P. 1985. Topographic controls of soil moisture distribution. Journal of Soil Science Vol. 36: 469-486 https://doi.org/10.1111/j.1365-2389.1985.tb00351.x
  4. Shoemaker, L., Lahlou M., Bryer D., Kumar D., and Kratt K. 1997. Compendium of Tools for Watershed Assessment and TMDL Development. EPA841-B-97-006, EPA, Washington, DC.7-35
  5. Lahlou, M., Shoemaker, L., Choudhury, S., Elmer, R, Hu, A., Manguerra, H., Parker, A. 1998. Better Assessment Science Integrating Point and Nonpoint source; User's manual. EPA- 823-B-98-006, EPA, Washington, DC
  6. Kim, S. J. 1998. Grid-Based KineMatic Wave STOrm Runoff Model (KIMSTORM) (1) Theory and Model-. Journal of Korea Water Resources Association, Vol. 31(3): 303-308
  7. Kim, S. J., Steenhuis,T. S. 2001. GRISTORM: Grid-Based Variable Source Area Storm Runoff Model. Transaction of the ASAE, Vol. 44(4): 863-875
  8. Korea Meteorological Administration. 2002. www.kma.go.kr
  9. Lopes, V. L. 1995. CHDM-Catchment hydrology distributed model. In Water Management Planning for the 21st Century, Proceedings of a symposium. American Society of Civil Engineers, San Antonio, Texas. 144-154
  10. Nash, J. E. and Sutcliffe, J. V. 1970. River flow forecasting through conceptual models 1. A discussion of principles. Journal of Hydrology, Vol. 10: 282-290
  11. Ogden, F.L., and Saghafian, B. 1995. Hydrologic modeling within GRASS-r.hydro.CASC2D. In Water Resources Engineering, Proceedings of the First International Conference, American Society of Civil Engineers, San Antonio, Texas. 892-896
  12. Palacios-Velez O., Cuevas-Renaud, B. 1986. Automated river-course, ridge and basin delineation from digital elevation data. Journal of Hydrology, Vol. 86: 299-314
  13. Servet, E. and Dezetter, A. 1991. Selection of calibration objective functions in the context of rainfall-runoff modeling in a Sudanese savannah area. Hydrology Science Journal, Vol. 36: 307-330
  14. Tarboton, D. G., Bras, R. L. and Rodriguez-Iturbe I. 1991. On the extraction of channel networks from digital elevation data. Hydrological Processes, Vol.5: 81-100
  15. Walker J. P. and Willgoose, G. R 1999. On the effect of digital elevation model accuracy on hydrology and geomorphology. Water Resources Research, Vol. 35: 2259-2268
  16. Water Reources Management System. 2002. wamis.kowaco.or.kr
  17. Wolock, D. M. and Price, C. V. 1994. Effects of digital elevationmodel map scale and data resolution on a topography-based watershed model. Water Resources Research, Vol. 30: 3041-3052
  18. Wolock, D. M., Hornberger, G. M., Beven, K. J. and Campbell, W. G. 1989. The relationship of catchment topography and soil hydraulic characteristics to lake alkalinity in the northeastern United States. Water Resource Research, Vol. 25: 829-837
  19. Yang, D., Herath, S. and Musiake, K. 2001. Spatial resolution sensitivity of catchment geomorphologic properties and the effect on hydrological simulation. Hydrological Processes, Vol. 15: 2085-2099
  20. Yang, D., Herath, S. and Musiake, K. 2000 Comparison of different distributed hydrological models for characterization of catchment spatial variability. Hydrological Processes, Vol. 14: 403-416
  21. Young, R.A., C. A. Onstad, D.D. Bosch, and W.P. Anderson. 1989. AGNPS: A nonpointsource pollution model for evaluating agriculture watersheds. Journal of Soil and Water Conservation, Vol. 44:168-173
  22. Zhang W. and Montgomery D. 1994. Digital elevation model grid size, landscape representation, and hydrologic simulation. Water Resources Research, Vol. 30: 1019-1028