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Assessment of streamflow variation considering long-term land-use change in a watershed

  • Noh, Joonwoo (Integrated Water Resources Management Research Center, K-water Research Institute) ;
  • Kim, Yeonsu (Integrated Water Resources Management Research Center, K-water Research Institute) ;
  • Yu, Wansik (Integrated Water Resources Management Research Center, K-water Research Institute) ;
  • Yu, Jisoo (River Basin Management Department, Yeongsangang&Seomjingang Rivers Basin Head Office, K-water)
  • Received : 2021.06.28
  • Accepted : 2021.08.24
  • Published : 2021.09.01

Abstract

Land-use change has an important role in the hydrologic characteristics of watersheds because it alters various hydrologic components such as interception, infiltration, and evapotranspiration. For example, rapid urbanization in a watershed reduces infiltration rates and increases peak flow which lead to changes in the hydrologic responses. In this study, a physical hydrologic model the soil and water assessment tool (SWAT) was used to assess long-term continuous daily streamflow corresponding to land-use changes that occurred in the Naesungchun river watershed. For a 30-year model simulation, 3 different land-use maps of the 1990s, 2000s, and 2010s were used to identify the impacts of the land-use changes. Using SWAT-CUP (calibration and uncertainty program), an automated parameter calibration tool, 23 parameters were selected, optimized and compared with the daily streamflow data observed at the upstream, midstream and downstream locations of the watershed. The statistical indexes used for the model calibration and validation show that the model performance is improved at the downstream location of the Naesungchun river. The simulated streamflow in the mainstream considering land-use change increases up to -2 - 30 cm compared with the results simulated with the single land-use map. However, the difference was not significant in the tributaries with or without the impact of land-use change.

Keywords

References

  1. Abbaspour KC, Yang J, Maximove I, Siber R, Bogner K, Mieleitner J, Zobrist J, Srinivasan R. 2007. Modeling hydrology and water quality in the pre-alpine/apline Thur watershed using SWAT. Journal of Hydrology 333:413-430. https://doi.org/10.1016/j.jhydrol.2006.09.014
  2. Arnold JG, Allen PM, Bernhardt G. 1993. A comprehensive surface-groundwater flow model. Journal of Hydrology 142:47-69. https://doi.org/10.1016/0022-1694(93)90004-S
  3. Borah DK, Bera M. 2004. Watershed-scale hydrologic and nonpoint-source pollution models: Review of applications. Transactions of the ASAE 47:789-803. https://doi.org/10.13031/2013.16110
  4. Du J, Rui H, Zuo T, Li Q, Zheng D, Chen A, Xu Y, Xu CY. 2013. Hydrological simulation by SWAT model with fixed and varied parameterization approaches under land use change. Water Resources Management 27:2823-2838. https://doi.org/10.1007/s11269-013-0317-0
  5. Ferraz SFB, Lima WP, Rodrigues CB. 2013. Managing forest plantation landscapes for water conservation. Forest Ecology and Management 301:58-66. https://doi.org/10.1016/j.foreco.2012.10.015
  6. Jin X, Jin Y, Yuan D, Mao X. 2019. Effects of land-use data resolution on hydrologic modelling, a case study in the upper reach of the Heihe river, Northwest China. Ecological Modeling 404:61-68. https://doi.org/10.1016/j.ecolmodel.2019.02.011
  7. Kim D, An H, Jang M, Kim S. 2018. Development of a distributed hydrological model considering hydrological change. Korean Journal of Agricultural Science 45:521-532. [in Korean] https://doi.org/10.7744/KJOAS.20180040
  8. Lim KJ, Engel BA, Kim Y, Bhaduri B, Harbor J. 1999. Development of the long term hydrologic impact assessment (LTHIA) WWW systems. pp. 1018-1023. In Sustaining the Global Farm the 10th International Soil Conservation Organization Meeting.
  9. Mainali J, Chang H. 2018. Landscape and anthropogenic factors affecting spatial patterns of water quality trends in a large river basin, South Korea. Journal of Hydrology 564:26-40. https://doi.org/10.1016/j.jhydrol.2018.06.074
  10. Moriasi DN, Gitau MW, Pai N, Daggupati P. 2015. Hydrologic and water quality models: Performance measures and evaluation criteria. Transactions of ASABE 58:1763-1785. https://doi.org/10.13031/trans.58.10715
  11. Pai N, Saraswat D. 2011. SWAT2009_LUC: A tool to activate the land use change module in SWAT 2009. Transactions of the ASABE 54:1649-1658. https://doi.org/10.13031/2013.39854
  12. Wang G, Mang S, Cai H, Liu S, Zhang Z, Wang L, Innes JL. 2016. Integrated watershed management: Evolution, development and emerging trends. Journal of Foresty Research 27:967-994. https://doi.org/10.1007/s11676-016-0293-3
  13. Worku T, Khare D, Tripathi SK. 2017. Modeling runoff-sediment response to land use/land cover changes using integrated GIS and SWAT model in the Beressa watershed. Environmental Earth Science 76:1-14. https://doi.org/10.1007/s12665-016-6304-z
  14. Yang J, Reichert P, Abbaspour KC, Xia J, Yang H. 2008. Comparing uncertainty analysis techniques for a SWAT application to the Chaohe basin in China. Journal of Hydrology 358:1-23. https://doi.org/10.1016/j.jhydrol.2008.05.012
  15. Yu J, Noh J, Cho Y. 2020. SWAT model calibration/ validation using SWAT-CUP I: Analysis for uncertainties of objective functions. Journal of Korea Water Resources Association 53:45-56. [in Korean]
  16. Zhang H, Wang B, Liu DL, Zhang M, Leslie LM, Yu Q. 2020. Using an improved SWAT model to simulate hydrological responses to land use change: A case study of a catchment in tropical Australia. Journal of Hydrology 585:124822. https://doi.org/10.1016/j.jhydrol.2020.124822