DOI QR코드

DOI QR Code

Effects of Digital Elevation Model in Water Quality Modeling using Geogrpahic Information System

  • Cho, Sung-Min (Depart. of Landscape Architecture, Honam University)
  • Received : 2021.01.17
  • Accepted : 2021.01.29
  • Published : 2021.05.31

Abstract

Aim of this research was to investigate the effects of Digital Elevation Model (DEM) for sensitivity analysis with two types of DEMs: 1 to 24,000 and 1 to 250,000 DEM. Another emphasis was given to the development of methodology for processing DEMs to create ArcGIS Pro and GRASS layers. This was done while developing water quality system modeling using DEMs which were used to model hydrological processes and SWAT model. Sensitivity analysis with DEMs resulted in different runoff volumes in the model simulation. Runoff volume was higher for the 1:24,000 DEM than 1:250,000 DEM, probably due to the finer resolution and slope which increased the estimated runoff from the watershed. Certainly the DEMs were factors in precision of the simulations and it was obvious during sensitivity analysis that DEMs had significant effect on runoff volumes. We suggest, however, that additional comparative research could be conducted involving more parameters such as soil and hydrologic parameters to provide insight into the overall physical system which the SWAT model represents.

Keywords

Acknowledgement

This results was supported by "Regional Innovation Strategy(RIS)" through the National Research Foundation of korea(NRF) funded by the Ministry of Education(MOE)

References

  1. Ramesh S. V. Teegavarapu; Chandramouli Viswanathan; and Lindell Ormsbee, "Effect of Digital Elevation Model (DEM) Resolution on the Hydrological and Water Quality Modeling." World Environmental and Water Resources Congress. May. 2006 DOI: 10.1061/40856(200)216
  2. J, Novoa, K. Chokmani, and R Rigel, "Quality Assessment from a Hydrological Perspective of a Digital Elevation Model derived from WorldView-2 Remote Sensing Data." Hydrologic Sciences Journal. Vo. 60(2), pp. 218-233. Jan. 2015. https://doi.org/10.1080/02626667.2013.875179
  3. GRASS, "Geographic Resource Analysis Support System." Version 7.8. U.S. Army Corps of Engineers, Construction Engineering Research Lab., Champaign, Illinois. 2019. https://grass.osgeo.org/
  4. J, Arnold, G., Allen, P. M., and M., Williams. "Assessment of Different Representations of Spatial Variability on SWAT Model Performance." Trans. ASABE, Vol, 53(5), pp. 1433-1443. Dec. 2010. DOI: http://dx.doi.org/10.13031/2013.34913
  5. ESRI, "Environmental Systems Research Institute." ArcGIS Pro, ESRI, Inc. Redlands, CA. 2019. https://www.esrikr.com/products/arcgis/
  6. C, Baffaut, and S. Dabney, "Hydrologic and water quality modeling: Spatial and Temporal Considerations," American Society of Agricultural and Biological Engineers. Vo. 58(6), pp 1661-1680. Aug. 2015 DOI: 10.13031/trans.58.10714
  7. V, Chaplot, "Impact of DEM Mesh Size and Soil Map Scale on SWAT Runoff, Sediment, and NO3-N Loads Predictions." J. Hydrol. Vol, 312(4), pp. 207-222. Feb, 2005. DOI: http://dx.doi.org/10.1016/j.jhydrol.