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Evaluation of Evapotranspiration and Soil Moisture of SWAT Simulation for Mixed Forest in the Seolmacheon Catchment

설마천유역 혼효림에서 실측된 증발산과 토양수분을 이용한 SWAT모형의 적용성 평가

  • Joh, Hyung-Kyung (Department of Civil and Environmental System Engineering/Earth Information Engineering Laboratory, Konkuk University) ;
  • Lee, Ji-Wan (Department of Civil and Environmental System Engineering/Earth Information Engineering Laboratory, Konkuk University) ;
  • Shin, Hyung-Jin (Department of Civil and Environmental System Engineering/Earth Information Engineering Laboratory, Konkuk University) ;
  • Park, Geun-Ae (Department of Civil and Environmental System Engineering/Earth Information Engineering Laboratory, Konkuk University) ;
  • Kim, Seong-Joon (Department of Civil and Environmental System Engineering/Earth Information Engineering Laboratory, Konkuk University)
  • 조형경 (건국대학교 사회환경시스템공학과/지구정보공학연구실) ;
  • 이지완 (건국대학교 사회환경시스템공학과/지구정보공학연구실) ;
  • 신형진 (건국대학교 사회환경시스템공학과/지구정보공학연구실) ;
  • 박근애 (건국대학교 사회환경시스템공학과/지구정보공학연구실) ;
  • 김성준 (건국대학교 사회환경시스템공학과/지구정보공학연구실)
  • Received : 2010.08.30
  • Accepted : 2010.10.20
  • Published : 2010.12.30

Abstract

Common practice of Soil Water Assessment Tool (SWAT) model validation is to use a single variable (i.e., streamlfow) to calibrate SWAT model due to the paucity of actual hydrological measurement data in Korea. This approach, however, often causes errors in the simulated results because of numerous sources of uncertainty and complexity of SWAT model. We employed multi-variables (i.e., streamflow, evapotranspiration, and soil moisture), which were measured at mixed forest in Seolmacheon catchment ($8.54\;km^2$), in order to assess the performance and reduce the uncertainties of SWAT model output. Meteorological and surface topographical data of the catchment were obtained as basic input variables and SWAT model was calibrated using daily data of streamflow (Jan. - Dec.), evapotranspiration (Sep. - Dec.), and soil moisture (Jun. - Dec.) collected in 2007. The model performance was assessed by comparing its results with the observation (i.e., streamflow of 2003 to 2008 and evapotranspiration and soil moisture of 2008). When the multi-variable measurements were used to calibrate the SWAT model, the model results showed better agreement with the measurements compared to those using a single variable measurement by showing increases in coefficient of determination ($R^2$) from 0.72 to 0.76 for streamflow, from 0.49 to 0.59 for soil moisture, and from 0.52 to 0.59 for evapotranspiration. The findings highlight the importance of reliable and accurate collective observation data for improving performance of SWAT model and promote its facilitation for estimating more realistic hydrological cycles at catchment scale.

국내 수문관측자료의 부족으로SWAT(Soil Water Assessment Tool) 모형의 적용성 평가는 대부분 유출자료만을 사용하여 이루어진다. 본 연구는 실측된 여러 수문자료가 SWAT수문모형의 불확실성 및 오차의 감소를 위해 어떻게 이용될 수 있는 지에 대하여 알아보고자 하였다. 이를 위해 전형적인 산지 유역인 설마천 유역을 대상으로 준분포형 장기강우유출모형인 SWAT 모형을 적용하여 수문성분의 특성을 살펴보았다. 먼저 모형의 입력자료인 기상자료 및 지형자료를 획득하여 구축하였고, 모형의 검 보정 위하여 유출, 증발산, 토양수분 실측자료를 획득하였다. SWAT 모형은 유츨량, 증발산, 토양수분 자료가 동시에 측정된 2007년 자료를 사용하여 보정된 후, SWAT 모형의 모의값은 유출량은 2003~2008년, 증발산과 토양수분은 2008년의 관측값과 비교, 분석한 뒤 전체적인 검증을 통해 모형의 적용성 평가를 실시하였다. 유출량의 검 보정 이용한 모의결과보다 다른 실측자료를 이용한 모의결과가 신뢰성이 높게 나타났다(결정계수($R^2$) 상향: 유출량은 0.72에서 0.76, 토양수분은 0.49에서 0.59, 증발산은 0.52에서 0.59). 유역의 실제적인 상황을 근접하게 모의하기 위해서는 다른 수문성분의 정확하고 신뢰성 있는 자료의 구축과 적용이 매우 중요하다고 판단된다.

Keywords

References

  1. Ambroise, B., J. L. Perrin, and D. Reutenauer, 1995: Multicriterion validations of a semidistributed conceptual model of the water cycle in the Fecht catchment(Vosges, Massif. France). Water Resources Research 31, 1467-1481. https://doi.org/10.1029/94WR03293
  2. Arnold, J. G., and P. M. Allen, 1996: Estimating Hydrologic Budgets for Three Illinois Watersheds. Journal of Hydrology 176(1), 57-77. https://doi.org/10.1016/0022-1694(95)02782-3
  3. Bastidas, L. A., H. Gupta, V. K-l. Hsu, and S. Sorooshian, 2003: Parameter, structure, and model performance evaluation for land-surface schemes. Water Science and Applications 6, 239-254. https://doi.org/10.1029/WS006p0239
  4. Han, U. G, 2009: A runoff simulation using SWAT model depending on changes to land use. M. E. Thesis. Jeju National University, 8-30.
  5. Hong, W. Y., M. J. Park, J. Y. Park, R. Ha, G. A. Park, and S. J. Kim, 2009: The Correlation Analysis Between SWAT Predicted Forest Soil Moisture and MODIS NDVI During Spring Season. Journal of the Korean Society of Agricultural Engineers 51(2), 7-14. (in Korean with English abstract) https://doi.org/10.5389/KSAE.2009.51.2.007
  6. Jang, J. S., 2003: Introduction of hydrologic models and parameters. Korean Commission on Irrigation and Drainage Journal, 10(1), 95-102. (in Korean)
  7. Jung, J. W., K. S. Yoon, K. H. Han, W. Y. Choi, J. B. Lee, and H. G. Choi, 2009: Evaluation of SWAT Model for Nutrient Load from Small Watershed in Juam Lake.Journal of the Korean Society of Environmental Sciences 18(9), 1027-1033. (in Korean with English abstract) https://doi.org/10.5322/JES.2009.18.9.1027
  8. Kim, B. K., S. D. Kim, E. T. Lee, and H. S. Kim, 2007: Methodology for Estimating Ranges of SWAT Model Parameters: Application to Imha Lake Inflow and Suspended Sediments. Journal of the Korean Society of the Civil Engineers 27(6B), 661-668. (in Korean with English abstract)
  9. Kim, N. W., I. M. Chung, and Y. S. Won, 2006: An Intergrated Surface Water-Groundwater Modeling by Using Fully Combined SWAT-MODFLOW Model. Journal of the Korean Society of the Civil Engineers 26(5B), 481-488. (in Korean with English abstract)
  10. Kim, N. W., J. Lee, I. M. Chung, and D. P. Kim, 2008: Hydrologic Component Analysis of the Seolma-Cheon Watershed by Using SWAT-K Model. Journal of the Korean Society of the Environmental Sciences 17(12), 1363-1372. (in Korean with English abstract) https://doi.org/10.5322/JES.2008.17.12.1363
  11. Koren, V., F. Moreda, and M. Smith, 2008: Use of soil moisture observations to improve parameter consistency in watershed calibration. Physics and Chemistry of the Earth 33, 1068-1080. https://doi.org/10.1016/j.pce.2008.01.003
  12. Kuczera, G., and M. Mroczkowski, 1998: Assessment of hydrological parameter uncertainty and the worth of multi-response data. Water Resources Research 34, 1481-1489. https://doi.org/10.1029/98WR00496
  13. Kwon, H. J., J. H. Lee, Y. K. Lee, J. W. Lee, S. W. Jung, and J. Kim, 2009: Seasonal Variations of Evapotranspiration Observed in a Mixed forest in the Seolmacheon Catchment. Korean Journal of Agricultural and Forest Meteorology 11(1), 39-47. (in Korean with English abstract) https://doi.org/10.5532/KJAFM.2009.11.1.039
  14. Lee, B. R., S. Kang, E. Kim, T. Hwang, J. H. Lim, and J. Kim, 2007: Evaluation of Hydro-ecologic Model, RHESSys(Regional Hydro-Ecologic Simulation System): Parameterization and Application at two Complex Terrain Watershed. Journal of Korean Society of Agricultural and Forest Meteorology 9, 247-259. (in Korean with English abstract) https://doi.org/10.5532/KJAFM.2007.9.4.247
  15. Manguerra, H. B., and B. A. Engel, 1998: Hydrologic Parameterization of Watersheds for Runoff Prediction Using SWAT. Journal of the American Resources Association 34(5), 1149-1162. https://doi.org/10.1111/j.1752-1688.1998.tb04161.x
  16. Nash, J. E., and J. E. Sutcliffe, 1970: River Flow Forecasting though Conceptual Models, Part I-A discussion of principles. Journal of Hydrology 10(3), 282-290. https://doi.org/10.1016/0022-1694(70)90255-6
  17. Neitsch, S. L., J. G. Arnold, J. R. Kiniry, and J. R. Williams 2001a: Soil and water assessment tool theoretical documentation version 2000: Draft-April 2001. Temple, TX, USA: Grassland, Soil and Water Research Laboratory, Agricultural Research Service, Blackland Research Center, Texas Agricultural Experiment Station.
  18. Park, J. Y., M. S. Lee, Y. J. Lee, and S. J. Kim, 2008: The Analysis of Future Land Use Change Impact on Hydrology and Water Quality Using SWAT Model. Journal of the Korean Society of Civil Engineers 28(2B), 187-197. (in Korean with English abstract)
  19. Peterson, J. R., and J. M. Hamlett, 1998: Hydrologic Calibration of the SWAT Model in a Watershed Containing Fragipan Soils. Journal of the American Water Resources Association 34(3), 531-544. https://doi.org/10.1111/j.1752-1688.1998.tb00952.x
  20. Refsgaard, J. C., and B. Storm, 1996: Storm Construction Calibration and Validation of Hydrological Models. Distributed Hydrological Modeling, M. B. Abbott and Refsgaard (Eds.), Kluwer Academic Publishers, 41-54.
  21. Seibert, J., and J. J. McDonnell, 2003: The quest for an improved dialog between modeler and experimentalist. Water Science and Applications 6, 301-316. https://doi.org/10.1029/WS006p0301
  22. Sophocleous, M. A., J. K. Koelliker, R. S. Govindaraju, T. Birdie, S. R. Ramireddygari, and S. P. Perkins, 1999: Integrated Numerical Modeling for Basin-Wide Water Management: The Case of the Rattlesnake Creek Basin in South-Central Kansas. Journal of Hydrology 214(1), 179-196. https://doi.org/10.1016/S0022-1694(98)00289-3
  23. Yoon, Y. N, 2009: Hydrology – basis and practice –, Chungmoongak Publishers, 135-184. (in Korean)
  24. http://kict.datapcs.co.kr/ (2010. 8. 5)

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