Journal of Wetlands Research (한국습지학회지)

Korean Wetlands Society (한국습지학회)
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Estimation of baseflow considering recession characteristics of hydrograph

수문곡선의 감수부 특성을 고려한 기저유출 산정

  • Jung, Younghun (Institute of Environmental Research, Kangwon National University) ;
  • Lim, Kyoung Jae (Regional Infrastructure Engineering, Kangwon National University) ;
  • Kim, Hungsoo (Department of Civil Engineering, Inha university)
  • Received : 2014.03.21
  • Accepted : 2014.04.15
  • Published : 2014.05.31
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Abstract

Recession of hydrograph gives a significant contribution to estimation of baseflow using rainfall-runoff models and baseflow separation methods, because recession affects baseflow. This study attempted to enhance the accuracy of streamflow predictions using a Soil and Water Assessment Tool (SWAT) model and to separate baseflow from the predicted streamflow. For this, this study used two scenarios: 1) to calibrate eleven parameters using an auto-calibration tool with the alpha factor obtained from RECESS (S1); and 2) to calibrate twelve SWAT parameters including alpha factor (one of SWAT parameters) using an auto-calibration tool (S2). Then, baseflow spearation from the predicted streamflow was conducted by using Web-based Hydrograph Analysis Tool (WHAT). The results show that there is no significant difference between Nash-Sutcliffe efficiency (NSE) values of S1 and S2 for calibrations to streamflow. However, calibrations to baseflow showed that NSEs are 0.777 for S1 and 0.844 for S2, which means a significant difference. Quantitatively compared to the observed streamflow, relative errors were 20.78 % for S1 and 6.59 % for S2. Finally, this study showed the importance of recession in baseflow separated from the predicted streamflow using a rainfall-runoff model.

수문곡선의 감수부는 기저유출의 특성을 반영하기 때문에 강우유출 모형과 기저유출분리법을 이용한 기저유출 산정과정에서 감수부의 특성을 고려해야한다. 따라서 본 연구는 감수특성을 고려하여 Soil and Water Assessment Tool(SWAT)의 보정에서 유량예측의 정확성을 높이고, 보정된 SWAT으로부터 예측된 유량으로부터 기저유출을 분리하고자 하였다. 이를 위하여 RECESS으로부터 산정된 alpha factor와 11개의 다른 매개변수를 자동보정모듈에 적용한 시나리오 (S1)와 SWAT의 매개변수인 alpha factor를 포함한 12개의 매개변수를 자동보정모듈에 적용한 시나리오 (S2)에 대해 SWAT을 이용해 유량 모의를 하였다. 또한, 두 시나리오에 대해 SWAT으로 예측된 유량을 Web-based Hydrograph Analysis Tool (WHAT)을 적용하여 기저유출을 산정하였다. 보정 결과는 유량에 대한 두 시나리오의 Nash-Sutcliffe Efficiency (NSE) 값들 사이에 큰 차이는 보이지 않았으나 기저유출의 경우 S1에 대한 NSE는 0.777이고, S2의 NSE 결과는 0.844로 다소 큰 차이를 보였다. 연평균 유량의 분포의 정량적 비교를 위한 관측유량과 상대오차를 산정하였으며 S1에 대하여 20.78%, S2에 대하여 6.59%의 상대오차를 보였다. 본 연구는 모형을 이용하여 예측된 유량으로부터 기저유출을 산정하는데 있어 감수부 특성의 중요성을 보여주었다.

Keywords

References

  1. Abbaspour, KC, Yang, J, Maximov, I, Siber, R, Bonger, K, Mieleitner, J, Zobrist, J and Srinivasan, R (2007). Modelling hydrology and water quality in the pre-alpine Thur watershed using SWAT, J. of Hydrology, 333(2-4), pp. 413-430. https://doi.org/10.1016/j.jhydrol.2006.09.014
  2. Ahiablame, LM, Engel, BA and Chaubey, I (2013). Effectiveness of low impact development practices in two urbanized watersheds: Retrofitting with rain barrel/cistern and porous pavement, J. of environmental management, 119(15), pp. 151-161. https://doi.org/10.1016/j.jenvman.2013.01.019
  3. Anderson, MG and Burt, TP (1980). Interpretation of recession flow, J. of Hydrology, 46(1-2), pp. 89-101. https://doi.org/10.1016/0022-1694(80)90037-2
  4. Arnold, JG and Allen, PM (1999). Validation of automated methods for estimating baseflow and groundwater recharge rrom stream flow records, J. of American Water Resources Association, 35(2), pp. 411-424. https://doi.org/10.1111/j.1752-1688.1999.tb03599.x
  5. Arnold, JG, Allen, PM and Bernhardt, G (1993). A comprehensive surface - groundwater flow model, J. of Hydrology, 142 (1-4), pp. 47-69. https://doi.org/10.1016/0022-1694(93)90004-S
  6. Arnold, JG, Allen, PM, Muttiah, R and Bernhardt, G (1995). Automated baseflow separation and recession analysis techniques, Groundwater, 33(6), pp. 1010-1018. https://doi.org/10.1111/j.1745-6584.1995.tb00046.x
  7. Eckhardt, K (2005). How to construct recursive Digital Filters for baseflow separation, Hydrological Processes, 19(2), pp. 507-515. https://doi.org/10.1002/hyp.5675
  8. Eckhardt, K and Ulbrich, U (2003). Potential impacts of climate change on groundwater recharge and streamflow in a central European low mountain range, J. of Hydrology, 284(1), pp. 244-252. https://doi.org/10.1016/j.jhydrol.2003.08.005
  9. Jung, Y, Merwade, V, Yeo, K, Shin, Y and Lee, SO (2013). An approach using a 1D hydraulic model, Landsat image and generalized likelihood uncertainty estimation for an approximation of flood discharge, Water, 5(4), pp. 1598-1621. https://doi.org/10.3390/w5041598
  10. Kienzle, SW (2006). The use of the recession index as an indicator for streamflow recovery after a multi-year drought, Water resources management, 20(6), pp. 991-1006. https://doi.org/10.1007/s11269-006-9019-1
  11. Kim, NW, Chung, IM and Won, YS (2005). Method of estimating groundwater recharge with spatial-temporal variability, J. of Korea Water Resource Association, 38(7), pp. 517-526. https://doi.org/10.3741/JKWRA.2005.38.7.517
  12. Kim, HT and Shin, HS (2009). The development and application of GIS-based geomorpho-hydrological watershed model (G2WMS), J. of Korean Society of Hazard Mitigation, 9(1), pp. 123-133.
  13. Kumar, S and Merwade, V (2011). Evaluation of NARR and CLM3.5 outputs for surface water and energy budgets in the Mississippi River Basin, J. of Geophysical Research: Atmospheres (1984-2012), 116. DOI:10.1029/2010JD014909
  14. Lim, KJ, Engel, BA, Tang, Z, Choi, J, Kim, K, Muthukrishnan, S and Tripathy, D (2005). Automated web gis based hydrograph analysis tool, WHAT1, J. of the American Water Resources Association, 41(6), pp. 1407-1416. https://doi.org/10.1111/j.1752-1688.2005.tb03808.x
  15. Loukas, A and Vasiliades, L (2014). Streamflow simulation methods for ungauged and poorly gauged watersheds, Natural Hazards and Earth System Sciences Discussions, 2(2), pp. 1033-1092. https://doi.org/10.5194/nhessd-2-1033-2014
  16. Nathan, RJ and McMahon, TA (1990). Evaluation of automated techniques for baseflow and recession analysis". Water Resources Research, 26(7), pp. 1465-1473.
  17. Neitsch, SL, Arnold, JG, Kiniry, JR, Srinivasan, R and Williams, JR (2002). Soil and Water Assessment Tool: User Manual, Version 2000. Grassland, Soil and Water Research Laboratory, Temple, TX, USA.
  18. Rutledge A (1998). Computer programs for describing the recession of ground-water discharge and for estimating mean ground-water recharge and discharge from streamflow records: Update. US Geological Survey Water-Resources Investigations Report 98-4148, USGS.
  19. Rutledge, AT and Mesko, TO (1996). Estimated hydrologic characteristics of shallow aquifer systems in the Valley and Ridge, the Blue Ridge, and the Piedmont Physiographic Provinces based on analysis of streamflow recession and base flow. U.S. Geological Survey Professional Paper 1422-B, USGS.
  20. Saleh, A, Arnold, JG, Gassman, PWA., Hauck, LM, Rosenthal, WD, Williams, JR and McFarland, AMS. (2000). Application of SWAT for the upper North Bosque River watershed, Transactions of the ASAE., 43(5), pp. 1077-1087. https://doi.org/10.13031/2013.3000
  21. Shin, HS, Kang, DK and Kim SD (2007). Analysis of the effect of water budget elemnets on flow duration characteristics using SWAT-Nak Dong, J. of Korea Water Resource Association, 40(3), pp.251-263. https://doi.org/10.3741/JKWRA.2007.40.3.251
  22. Sloto, RA and Crouse, MY (1996). HYSEP: A computer program for streamflow hydrograph separation and analysis. Water-Resources Investigations Report. US Geological Survey. 96-4040, USGS
  23. Srinivasan, R, Zhang, X and Arnold, J (2010). SWAT ungauged: hydrological budget and crop yield predictions in the Upper Mississippi River Basin, Transactions of the ASABE,, 53(5), pp. 1533-1546. https://doi.org/10.13031/2013.34903
  24. Yadav, M, Wagener, T and Gupta, H (2007). Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins, Advances in Water Resources, 30(8), pp. 1756-1774. https://doi.org/10.1016/j.advwatres.2007.01.005

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