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Large Scale SWAT Watershed Modeling Considering Multi-purpose Dams and Multi-function Weirs Operation - For Namhan River Basin -

다목적 댐 및 다기능 보 운영을 고려한 대유역 SWAT 모형 구축기법 연구 - 남한강 유역을 대상으로 -

Ahn, So Ra;Lee, Ji Wan;Jang, Sun Sook;Kim, Seong Joon
안소라;이지완;장선숙;김성준

  • Received : 2016.02.16
  • Accepted : 2016.07.05
  • Published : 2016.07.31

Abstract

This study is to evaluate the applicability of SWAT (Soil and Water Assessment Tool) model for multi-purpose dams and multi-function weirs operation in Namhan river basin ($12,577km^2$) of South Korea. The SWAT was calibrated (2005 ~ 2009) and validated (2010 ~ 2014) considering of 4 multi-purpose dams and 3 multi-function weirs using daily observed dam inflow and storage, evapotranspiration, soil moisture, and groundwater level data. Firstly, the dam inflow was calibrated by the five steps; (step 1) the physical rate between total runoff and evapotranspiration was controlled by ESCO, (step 2) the peak runoff was calibrated by CN, OV_N, and CH_N, (step 3) the baseflow was calibrated by GW_DELAY, (step 4) the recession curve of baseflow was calibrated by ALPHA_BF, (step 5) the flux between lateral flow and return flow was controlled by SOL_AWC and SOL_K, and (step 6) the flux between reevaporation and return flow was controlled by REVAPMN and GW_REVAP. Secondly, for the storage water level calibration, the SWAT emergency and principle spillway were applied for water level from design flood level to restricted water level for dam and from maximum to management water level for weir respectively. Finally, the parameters for evapotranspiration (ESCO), soil water (SOL_AWC) and groundwater level fluctuation (GWQMN, ALPHA_BF) were repeatedly adjusted by trial error method. For the dam inflow, the determination coefficient $R^2$ was above 0.80. The average Nash-Sutcliffe efficiency (NSE) was from 0.59 to 0.88 and the RMSE was from 3.3 mm/day to 8.6 mm/day respectively. For the water balance performance, the PBIAS was between 9.4 and 21.4 %. For the dam storage volume, the $R^2$ was above 0.63 and the PBIAS was between 6.3 and 13.5 % respectively. The average $R^2$ for evapotranspiration and soil moisture at CM (Cheongmicheon) site was 0.72 and 0.78, and the average $R^2$ for groundwater level was 0.59 and 0.60 at 2 YP (Yangpyeong) sites.

Keywords

Multi-purpose dam;Multi-function weir;Dam operation;Spatial calibration

References

  1. Ahn, S.R. G.A. Park, and S.J. Kim, 2013a. Assessment of Agricultural Water Supply Capacity Using MODSIM-DSS Coupled with SWAT. Journal of the Korean Society of Civil Engineers 33(2): 507-519 (in Korean). https://doi.org/10.12652/Ksce.2013.33.2.507
  2. Ahn, S.R. G.A. Park, C.H. Jang, and S.J. Kim, 2013b. Assessment of Climate Change Impact on Evapotranspiration and Soil Moisture in a Mixed Forest Catchment Using Spatially Calibrated SWAT Model. Journal of Korea Water Resources Association 46(6): 569-583 (in Korean). https://doi.org/10.3741/JKWRA.2013.46.6.569
  3. 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
  4. Chen, J., J. Xia, C. Zhao, S. Zhang, G. Fu, and L. Ning. 2014. The mechanism and scenarios of how mean annual runoff varies with climate change in Asian monsoon areas. Journal of Hydrology 517: 595-606. https://doi.org/10.1016/j.jhydrol.2014.05.075
  5. Joh, H.K., J.W. Lee, H.J. Shin, G.A. Park, and S.J. Kim, 2010. Evaluation of Evapotranspiration and Soil Moisture of SWAT Simulation for Mixes Forest in the Seolmacheon Catchment. Korean Journal of Agricultural and Forest Meteorology 12(4): 289-297 (in Korean). https://doi.org/10.5532/KJAFM.2010.12.4.289
  6. Joh, H.K., J.W. Lee, M.J. Park, H.J. Shin, J.E. Yi, G.S. Kim, R. Srinivasan, and S.J. Kim, 2011. Assessing climate change impact on hydrological components of a small forest watershed through SWAT calibration of evapotranspiration and soil moisture. Transactions of the ASABE 54(5): 1773-1781. https://doi.org/10.13031/2013.39844
  7. 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
  8. K-water, 2014. Dam operation handbook, Daejeon, South Korea.
  9. Lee, D.R, J.W. Moon, and S.J. Choi, 2014. Performance Evaluation of Water Supply for a Multi-purpose Dam by Deficit-Supply Operation. Journal of Korea Water Resources Association 47(2): 195-206 (in Korean). https://doi.org/10.3741/JKWRA.2014.47.2.195
  10. Ministry of Land, Infrastructure and Transport, 2011. National Water Resources Plan (2011-2020). Sejong-si, South Korea.
  11. Ministry of Land, Infrastructure, and Transport, 2011. Dam design standard, Sejong-si, South Korea.
  12. Mkhwanazi, M., J.L. Chavez, and Rambikur, E.H. 2012. Comparison of Large aperture scintillometer and satellitebased energy balance models in sensible heat flux and crop evapotranspiration determination. International Journal of Remote Sensing Applications 12: 24-30.
  13. Molina-Navarro, E., D. Trolle, S. Martinez-Perez, A. Sastre-Merlin, and E. Jeppesen, 2014. Hydrological and water quality impact assessment of a Mediterranean limno-reservoir under climate change and land use management scenarios. Journal of Hydrology 509: 354-366. https://doi.org/10.1016/j.jhydrol.2013.11.053
  14. Moriasi, D.N., J.G. Arnold, M.W. Van Liew, R.L. Bingner, R.D. Harmel, and T.L. Veith, 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE 50(3): 885-900. https://doi.org/10.13031/2013.23153
  15. Nash, J.E., and J.V. Sutcliffe, 1970. River flow forecasting through 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
  16. Neitsch, S.L., J.G. Arnold, J.R. Kiniry, and J.R. Williams, 2001. Soil and Water Assessment Tool; the theoretical documentation. U.S Agricultural Research Service, 340-367, Temple, Texas.
  17. Neitsch, S.L., J.G. Arnold, J.R. Kiniry, J.R. Williams, 2011. Soil and water assessment tool theoretical documentation version 2009. Texas Water Resources Institute, Temple, Texas.
  18. Park, J.Y., H. Jung, C.H. Jang and S.J. Kim, 2014. Assessing climate change impact on hydrological components of Yongdam dam watershed using RCP emission scenarios and SWAT model. Journal of the Korean Society of Agricultural Engineers 56(3): 19-29 (in Korean).
  19. Perrin, J. S. Ferrant, S. Massuel, B. Dewandel, J.C. Marechal, S. Aulong, and S. Ahmed, 2012. Assessing water availability in a semi-arid watershed of southern India using a semi-distributed model. Journal of Hydrology 460: 143-55.
  20. Santhi, C., J.G. Arnold, J.R. Williams, W.A. Dugas, R. Srinivasan, and L.M. Hauck, 2001. Validation of the SWAT model on a large river basin with point and nonpoint sources. Journal of the American Water Resources Association 37: 1169-1188. https://doi.org/10.1111/j.1752-1688.2001.tb03630.x
  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. Shin, H.J., M.J. Park, and S.J. Kim, 2012. Evaluation of Forest Watershed Hydro-Ecology using Measured Data and RHESSys Model-For the Seolmacheon Catchment. Journal of Korea Water Resources Association 45(12): 1293-1307 (in Korean). https://doi.org/10.3741/JKWRA.2012.45.12.1293
  23. Wagner, P.D., S. Murty-Bhallamudi, B. Narasimhan, L.N. Kantakumar, K.P. Sudheer, S. Kumar, K. Schneider, and P. Fiener, 2016. Dynamic integration of land use changes in a hydrologic assessment of a rapidly developing Indian catchment. Science of the Total Environment 539: 153-164. https://doi.org/10.1016/j.scitotenv.2015.08.148

Acknowledgement

Supported by : 국토교통부