대한지리학회지 (Journal of the Korean Geographical Society)

대한지리학회 (The Korean Geographical Society)
권호 표지

수치고도모델의 격자크기와 유수흐름 알고리듬의 선택이 토양경관 모델링에 미치는 영향

Influence of Grid Cell Size and Flow Routing Algorithm on Soil-Landform Modeling

  • Park, S.J. (Department of Geography, Seoul National University) ;
  • Ruecker, G.R. (German Aerospace Center (DLR), German Remote Sensing Date Center (DFD)) ;
  • Agyare, W.A. (Savanna Agricultural Research Institute) ;
  • Akramhanov, A. (Center for Development Research, University of Bonn) ;
  • Kim, D. (Department of Geography, Texas A&M University) ;
  • Vlek, P.L.G. (Center for Development Research, University of Bonn)
  • 발행 : 2009.06.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

수치고도모형으로부터 산출된 지형변수는 지표면 프로세스와 관련된 공간모델의 개발에 있어 중요한 요소이다. 이 논문에서는 사면유역지수(upslope contributing area)가 토양성질의 공간적 분포를 예측하는 능력이, 사용한 알고리듬과 격자크기에 따라 어떻게 변하는지를 연구하였다. 상이한 환경조건을 지니는 여덟 군데의 연구지역에서 토양-경관 자료를 획득하여 이중 4개의 토양성질을 분석에 포함시켰다. 다섯 가지의 알고리듬을 통해 사면유역지수를 산출하여 이 지수들이 수치고도모형의 해상도에 얼마나 민감한지를 분석하였다. 다방향유수흐름 알고리듬(multiple flow algorithm)을 통해 계산된 지형변수가 대부분의 토양변수와 높은 상관관계를 보임과 동시에 격자크기의 변화에 낮은 민감도를 보였다. 지형변수와 토양변수 사이의 높은 상관관계는 15-50 m의 해상도에서 유사한 예측능력을보였다. 격자크기를 증가시켰을때 발생하는 미세지형정보의 손실을 감안한다면, 15-30 m 정도의 공간적 스케일이 토양경관 모델링에 적합할 것으로 판단된다.

Terrain parameters calculated from digital elevation models (DEM) have become increasingly important in current spatially distributed models of earth surface processes. This paper investigated how the ability of upslope area for predicting the spatial distribution of soil properties varies depending on the selection of spatial resolutions of DEM and algorithms. Four soil attributes from eight soil-terrain data sets collected from different environments were used. Five different methods of calculating upslope area were first compared for their dependency on different grid sizes of DEM. Multiple flow algorithms produced the highest correlation coefficients for most soil attributes and the lowest variations amongst different DEM resolutions and soil attributes. The high correlation coefficient remained unchanged at resolutions from 15 m to 50 m. Considering decreasing topographical details with increasing grid size, we suggest that the size of 15-30 m may be most suitable for soil-landscape analysis purposes in our study areas.

키워드

참고문헌

  1. Anderson, D. W. and Ingram, J. S. I., 1993, Tropical Soil Biology and Fertility: A Handbook of Methods, CAB International, Wallingford, UK
  2. Bauer, J., Rohdenburg, H., and Bork, H. R., 1985, Ein digitales reliefmodell als vorraussetzung f$\"{u}$er ein deterministisches modell der wasser- und stofffluesse, in Bork, H. R. and Rohdenburg, H. (eds.), Parameteraufbereitung f$\"{u}$er deterministische Gebiets-Wassermodelle, Grundlagenarbeiten zu Analyse von Agrar-Oekosystemen, Landscha ftsgenese und Landschaftsoekologie, 1-15
  3. Beckett, P. H. T. and Webster, R., 1971, Soil variability: A review, Soils and Fertilizers, 34, 1-15
  4. Beven, K., 1995, Linking parameters across scales: Subgrid parameterizations and scale dependent hydrological models, in Kalma, J. D. and Sivapalan, M. (eds.), Scale Issues in Hydrological Modelling, John Wiley & Sons, Chichester, 263- 282
  5. Beven, K. J. and Kirkby, M. J., 1979, A physically-based, variable contributing area model of basin hydrology, Hydrological Sciences Bulletin, 24, 43-69 https://doi.org/10.1080/02626667909491834
  6. Bloschl, G. and Sivapalan, M., 1995, Scale issues in hydrological modelling: A review, Hydrological Processes, 9, 313-330 https://doi.org/10.1002/hyp.3360090307
  7. Bolstad, P. V. and Stowe, T., 1994, An evaluation of DEM accuracy: Elevation, slope, and aspect, Photogrammetric Engineering and Remote Sensing, 60, 1327-1332
  8. Burt, T. P. and Butcher, D. P., 1985, Topographic controls of soil moisture distributions, Journal of Soil Science, 36, 469-486 https://doi.org/10.1111/j.1365-2389.1985.tb00351.x
  9. Conrad, O., 1998, DiGem-Software for Digital Elevation Model, Ph.D. Thesis (in German), University of Goettingen, Germany, Available at http:// downloads.sourceforge.net/saga-gis/digem_2.0_ bin.zip
  10. Costa-Cabral, M. C. and Burges, S. J., 1994, Digital elevation model networks (DEMON): A model of flow over hillslopes for computation of contributing and dispersal area, Water Resources Research, 30, 1681-1692 https://doi.org/10.1029/93WR03512
  11. Desmet, P. J. J. and Govers, G., 1996, Comparison of routing algorithms for digital elevation models and their implications for predicting ephemeral gullies, International Journal of Geographical Information Systems, 10, 311-331 https://doi.org/10.1080/026937996138061
  12. Erskine, R. H., Green, T. R., Ramirez, J. A., and MacDonald, L. H., 2006, Comparison of gridbased algorithms for computing upslope contributing area, Water Resources Research, 42, W09416, doi:10.1029/2005WR004648
  13. Erskine, R. H., Green, T. R., Ramirez, J. A., and MacDonald, L. H., 2007, Digital elevation accuracy and grid cell size: effects on estimated terrain attributes, Soil Science Society of America Journal, 71, 1371-1380 https://doi.org/10.2136/sssaj2005.0142
  14. Fairfield, J. and Leymarie, P., 1991, Drainage networks from grid digital elevation models, Water Resources Research, 27, 709-717 https://doi.org/10.1029/90WR02658
  15. Freeman, G. T., 1991, Calculating catchment area with divergent flow based on regular grid, Computers and Geosciences, 17, 413-422 https://doi.org/10.1016/0098-3004(91)90048-I
  16. Gallant, J. C. and Wilson, J. P., 2000, Primary topographic attributes, in Wilson, J. P. and Gallant, J. C. (eds.), Terrain Analysis: Principles and Application, John Wiley & Sons, New York, 51-86
  17. Garbrecht, J. and Martz, L. W., 1994, Grid size dependency of parameters extracted from digital elevation models, Computers and Geosciences, 20, 85-87 https://doi.org/10.1016/0098-3004(94)90098-1
  18. Gessler, P. E., Moore, I. D., McKenzie, N. J., and Ryan, P. J., 1995, Soil-landscape modeling and spatial prediction of soil attributes, International Journal of Geographical Information Systems, 9, 421-432 https://doi.org/10.1080/02693799508902047
  19. Holmes, K. W., Chadwick, O. A., and Kyriakidis, P. C., 2000, Error in a USGS 30-meter digital elevation model and its impact on terrain modeling, Journal of Hydrology, 233, 154-173 https://doi.org/10.1016/S0022-1694(00)00229-8
  20. Hutchinson, M. F. and Dowling, T. I., 1991, A continental hydrological assessment of a new grid-based digital elevation model of Australia, Hydrological Processes, 5, 45-58 https://doi.org/10.1002/hyp.3360050105
  21. Hutchinson, M. F. and Gallant, J. C., 2000, Digitial elevation models and representation of terrain shape, in Wilson, J. P. and Gallant, J. C. (eds.), Terrain Analysis: Principles and Application, John Wiley & Sons, New York, 29-50
  22. Jenson, S. K., 1991, Applications of hydrologic information automatically extracted from digital elevation models, Hydrological Processes, 5, 31- 44 https://doi.org/10.1002/hyp.3360050104
  23. Kim, D., Yu, K. B., and Park, S. J., 2008, Identification and visualization of complex spatial pattern of coastal dune soil properties using GIS-based terrain analysis and geostatistics, Journal of Coastal Research, 24(4C), 50-60
  24. Lea, N. J., 1992, An aspect-driven kinematic routing algorithm, in Parsons, A. J. and Abrahams, A. D. (eds.), Overland Flow: Hydraulics and Erosion Mechanics, UCL Press, London, 393-407
  25. McBratney, A. B., Odeh, I. O. A., Bishop, T. F. A., Dunbar, M. S., and Shatar, T. M., 2000, An overview of pedometric techniques for use in soil survey, Geoderma, 97, 293-327 https://doi.org/10.1016/S0016-7061(00)00043-4
  26. Mitasova, H., Hofierka, J., Zlocha, M., and Iverson, L. R., 1996, Modeling topographic potential for erosion and deposition using GIS, International Journal of Geographical Information Systems, 10, 629-641 https://doi.org/10.1080/026937996137918
  27. Moore, I. D., Turner, A. K., Wilson, J. P., Jenson, S. K., and Band, L. E., 1993a, GIS and land surfacesubsurface modeling, in Goodchild, M. F., Parks, B. O., and Steyaert, L. T. (eds.), Environmental Modeling with GIS, Oxford University Press, New York, 196-230
  28. Moore, I. D., Gessler, P. E., Nielsen, G. A., and Peterson, G. A., 1993b, Soil attribute prediction using terrain analysis, Soil Science Society of America Journal, 57, 443-452 https://doi.org/10.2136/sssaj1993.03615995005700020026x
  29. Moore, I. D., Gessler, P. E., Nielsen, G. A., and Peterson, G. A., 1993b, Soil attribute prediction using terrain analysis, Soil Science Society of America Journal, 57, 443-452 https://doi.org/10.2136/sssaj1993.03615995005700020026x
  30. O'Callaghan, J. F. and Mark, D. M., 1984, The extraction of drainage networks from digital elevation data, Computer Vision, Graphics and Image Processing, 28, 323-344 https://doi.org/10.1016/S0734-189X(84)80011-0
  31. O'Callaghan, J. F. and Mark, D. M., 1984, The extraction of drainage networks from digital elevation data, Computer Vision, Graphics and Image Processing, 28, 323-344 https://doi.org/10.1016/S0734-189X(84)80011-0
  32. Oksanen, J. and Sarjakoski, T., 2005, Error propagation analysis of DEM-based drainage basin delineation, International Journal of Remote Sensing, 26, 3085-3102 https://doi.org/10.1080/01431160500057947
  33. Panuska, J. C., Moore, I. D., and Kramer, L. A., 1991, Terrain analysis: Integration into the agriculture non-point source (AGNPS) pollution model, Journal of Soil Water Conservation, 46, 59-64
  34. Park, S. J. and Burt, T. P., 2002, Identification and characterization of pedogeomorphological processes on a hillslope using an indirect gradient analysis, Soil Science Society of America Journal, 66, 1897-1910 https://doi.org/10.2136/sssaj2002.1897
  35. Park, S. J. and Vlek, P. L. G., 2002a, Soil-landscape analysis as a tool for sustainable land resource management in developing countries, Geographical Journal of Korea, 36, 31-49
  36. Park, S. J. and Vlek, P. L. G., 2002b, Environmental correlation of three-dimensional spatial soil variability: a comparison of three adaptive techniques, Geoderma, 109, 117-140 https://doi.org/10.1016/S0016-7061(02)00146-5
  37. Park, S. J., van de Giesen, N., and Vlek, P. L. G., 2005, Optimal spatial scale for land use change modelling: a case study in a savanna landscape in Northern Ghana, Journal of the Korean Geographical Society, 40, 221-241
  38. Quinn, P. F., Beven, K. J., and Lamb, R., 1995, The ln(A/tanβ) index: How to calculate it and how to use it within TOPMODEL framework, Hydrological Processes, 9, 161-182 https://doi.org/10.1002/hyp.3360090204
  39. Quinn, P. F., Beven, K. J., Chevallier, P., and Planchon, O., 1991, The prediction of hillslope flow paths for distributed hydrological modelling using digital terrain models, Hydrological Processes, 5, 59-79 https://doi.org/10.1002/hyp.3360050106
  40. Ruhe, R. V. and Walker, P. H., 1968, Hillslope models and soil formation II: Open systems, Transactions of the Ninth Congress of the International Soil Science Society, Adelaide, Australia, 551-560
  41. Schulze, R., 2000, Transcending scales of space and time in impact studies of climate and climate change on agrohydrological responses, Agriculture, Ecosystems and Environment, 82, 185-212 https://doi.org/10.1016/S0167-8809(00)00226-7
  42. Speight, J. G., 1974, A parametric approach to landform regions, in Brown, E. H. and Waters, R. S. (eds.), Progress in Geomorphology, Alden, London, 213- 230
  43. Strahler, A. N. and Strahler, A. H., 1984, Elements of Physical Geography, John Wiley & Sons, New York
  44. Tarboton, D. G., 1997, A new method for the determination of flow directions and upslope areas in grid digital elevation models, Water Resources Research, 33, 309-319 https://doi.org/10.1029/96WR03137
  45. Thieken, A. H., Lucke, A., Diekkrüger, B., and Richter, O., 1999, Scaling input data by GIS for hydrological modeling, Hydrological Processes, 13, 611-630 https://doi.org/10.1002/(SICI)1099-1085(199903)13:4<611::AID-HYP758>3.0.CO;2-6
  46. Thompson, J. A., Bell, J. C., and Butler, C. A., 2001, Digital elevation model resolution: Effects on terrain attribute calculation and quantitative soillandscape modelling, Geoderma, 100, 67-89 https://doi.org/10.1016/S0016-7061(00)00081-1
  47. Western, A. W. and Bloschl, G., 1999, On the spatial scaling of soil moisture, Journal of Hydrology, 217, 203-224 https://doi.org/10.1016/S0022-1694(98)00232-7
  48. Western, A. W. and Grayson, R. B., 1998, The Tarrawarra data set: Soil moisture patterns, soil characteristics and hydrological flux measurements, Water Resources Research, 34, 2765-2768 https://doi.org/10.1029/98WR01833
  49. Wilson, J. P. and Gallant, J. C., 2000, Digital terrain analysis, in Wilson, J. P. and Gallant, J. C. (eds.), Terrain Analysis: Principles and Application, John Wiley & Sons, New York, 1-27
  50. Wilson, J. P., Repetto, P. L., and Snyder, R. D., 2000, Effect of data source, grid resolution, and flow routing method on computed topographic attribute, in Wilson, J. P. and Gallant, J. C. (eds.), Terrain Analysis: Principles and Application, John Wiley & Sons, New York, 133-161
  51. Wolock, D. M. and Price, C. V., 1994, Effects of digital elevation model and map scale and data resolution on a topography-based watershed model, Water Resources Research, 30, 3041-3052 https://doi.org/10.1029/94WR01971
  52. Wolock, D. M. and McCabe, G. J., 1995, Comparison of single and multiple flow direction algorithms for computing topographic parameters in TOPMODEL, Water Resources Research, 31, 1315 -1324 https://doi.org/10.1029/95WR00471
  53. Zhang, W. H. and Montgomery, D. R., 1994, Digital elevation model grid size, landscape representation, and hydrologic simulations, Water Resources Research, 30, 1019-1028 https://doi.org/10.1029/93WR03553