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Impacts of baseflow contribution on the streamflow variability of major river systems in Korea

  • Jeongho Han
  • Jonggun Kim
  • Kyoungjae Lim
  • Younghun Jung
Article

Abstract

High streamflow variability is a potential risk factor in river management in Korea because the use of water resources in Korea depends primarily on surface water. In this regard, analysis of streamflow variability is critical for efficient water resources management. Because streamflow variability is mainly influenced by the contributions of direct runoff and baseflow, the relationship between baseflow and streamflow is an important hydrological indicator that reflects river characteristics. Accordingly, this study was conducted to estimate the effect of baseflow on streamflow variability. For this purpose, a number of streamflow variability indices (SVIs), such as the Richard–Baker flashiness index, the coefficient of variation, the ratio of high flow to low flow (Q5:Q95), and the coefficient of flow regime, were calculated for Korea’s major river systems to determine which SVI best reflects the characteristics of Korean rivers. In addition, baseflow separation was performed to calculate the relationship between SVIs and the baseflow index. The results of this study show that the baseflow index is inversely proportional to streamflow variability. In particular, the impact of baseflow on streamflow variability was highest in the Yeongsan–Sumjin River system. These results are valuable information expected to be used in river management to better secure water resources.

Keywords

Baseflow contribution Baseflow index Streamflow variability Baseflow separation Streamflow variability index 

Notes

Acknowledgements

This research was supported by “Environmental Basic Research Program, Hanriver watershed management committee”.

References

  1. Arnold JG, Allen PM (1999) Automated methods for estimating baseflow and ground water recharge from streamflow records1. J Am Water Resour Assoc 35:411–424CrossRefGoogle Scholar
  2. Bae D, Jung I, Chang H (2008) Long-term trend of precipitation and runoff in Korean river basins. Hydrol Process 22:2644–2656CrossRefGoogle Scholar
  3. Baker DB, Richards RP, Loftus TT, Kramer JW (2004) A new flashiness index: characteristics and applications to midwestern rivers and streams1. J Am Water Resour Assoc 40:503–522CrossRefGoogle Scholar
  4. Berhanu B, Seleshi Y, Demisse SS, Melesse AM (2015) Flow regime classification and hydrological characterization: a case study of Ethiopian rivers. Water 7:3149–3165CrossRefGoogle Scholar
  5. Britain G (2005) Science project: groundwater: surface water interactions in the hyporheic zone. Environment Agency, BristolGoogle Scholar
  6. Brodie RS, Hostetler S (2005) A review of techniques for analysing baseflow from stream hydrographs. In: Proceedings of the NZHS-IAH-NZSSS 2005 conferenceGoogle Scholar
  7. Constantinescu G, Garcia M, Hanes D (2016) River Flow 2016. CRC Press, Boca RatonCrossRefGoogle Scholar
  8. Deelstra J, Iital A (2008) The use of the flashiness index as a possible indicator for nutrient loss prediction in agricultural catchments. Boreal Environ Res 13:209–221Google Scholar
  9. Déry SJ, Mlynowski TJ, Hernández-Henríquez MA, Straneo F (2011) Interannual variability and interdecadal trends in Hudson Bay streamflow. J Mar Syst 88:341–351CrossRefGoogle Scholar
  10. Déry SJ, Hernández-Henríquez MA, Owens PN et al (2012) A century of hydrological variability and trends in the Fraser River Basin. Environ Res Lett 7:24019CrossRefGoogle Scholar
  11. Dettinger MD, Diaz HF (2000) Global characteristics of stream flow seasonality and variability. J Hydrometeorol 1:289–310CrossRefGoogle Scholar
  12. Dodov B, Foufoula-Georgiou E (2005) Fluvial processes and streamflow variability: Interplay in the scale-frequency continuum and implications for scaling. Water Resour Res 41:W05005CrossRefGoogle Scholar
  13. Durrant J, Byleveld S (2009) Streamflow trends in south-west Western Australia, surface water hydrology series–Report no. HY32, Department of Water, Government of Western AustraliaGoogle Scholar
  14. Eckhardt K (2005) How to construct recursive digital filters for baseflow separation. Hydrol Process 19:507–515CrossRefGoogle Scholar
  15. Eckhardt K (2008) A comparison of baseflow indices, which were calculated with seven different baseflow separation methods. J Hydrol.  https://doi.org/10.1016/j.jhydrol.2008.01.005 Google Scholar
  16. Fongers D, Manning K, Rathbun J (2007) Application of the Richards-Baker Flashiness Index to gaged Michigan rivers and streams. DEQ Michigan’s Nonpoint Source ProgramGoogle Scholar
  17. Gustard A, Bullock A, Dixon JM (1992) Low flow estimation in the United Kingdom. Institute of Hydrology, WallingfordGoogle Scholar
  18. Haddeland I, Heinke J, Biemans H et al (2014) Global water resources affected by human interventions and climate change. Proc Natl Acad Sci 111:3251–3256CrossRefPubMedGoogle Scholar
  19. Henning A, Pettyjohn T (1979) Hysep-hydrograph separation program. US Geological Survey, RestonGoogle Scholar
  20. Jordan P, Menary W, Daly K et al (2005) Patterns and processes of phosphorus transfer from Irish grassland soils to rivers—integration of laboratory and catchment studies. J Hydrol 304:20–34CrossRefGoogle Scholar
  21. Kang S-K, Lee D-R, Moon J-W, Choi S-J (2010) Effects of dams and water use on flow regime alteration of the Geum River Basin. J Korea Water Resour Assoc 43:325–336CrossRefGoogle Scholar
  22. Konrad CP, Booth DB (2002) Hydrologic trends associated with urban development for selected streams in the Puget Sound Basin, Western Washington. US Geological Survey, RestonGoogle Scholar
  23. Kumambala PG, Ervine A (2009) Site selection for combine hydro, irrigation and water supply in Malawi: assessment of water resource availability. Desalination 248:537–545CrossRefGoogle Scholar
  24. Lee JW, Kim HS, Woo HS (1993) An analysis of the effect of damming on flow duration characteristics of five major rivers in Korea. Korean Soc Civ Eng 13:79–91Google Scholar
  25. Lee HS, Park KS, Jung SH, Choi SK (2013) Catchment similarity assessment based on catchment characteristics of GIS in Geum River Catchments, Korea. J Korean Soc Geospatial Inf Syst 21:37–46CrossRefGoogle Scholar
  26. Leite V, de Figueiredo T, Pinheiro T et al (2012) Dealing with the very small: first steps of a picohydro demonstration project in an university campus. Renew Energy Power Qual J 1:683–685Google Scholar
  27. Lim KJ, Engel BA, Tang Z et al (2005) Automated web gis based hydrograph analysis tool, WHAT1. J Am Water Resour Assoc 41:1407–1416CrossRefGoogle Scholar
  28. Lim KJ, Park YS, Kim J et al (2010) Development of genetic algorithm-based optimization module in WHAT system for hydrograph analysis and model application. Comput Geosci 36:936–944CrossRefGoogle Scholar
  29. Luo Y, Jia J, Shao M, Lin L (2012) Study on flood control planning and design for comprehensive improvement project of main-stream of Longganghe river. Water Resour Hydropower Eng 8:15Google Scholar
  30. Lyne V, Hollick M (1979) Stochastic time-variable rainfall-runoff modelling. In: Institute of engineers Australia national conference. pp 89–93Google Scholar
  31. Masih I, Uhlenbrook S, Turral H, Karimi P (2009) Analysing streamflow variability and water allocation for sustainable management of water resources in the semi-arid Karkheh river basin, Iran. Phys Chem Earth Parts A/B/C 34:329–340CrossRefGoogle Scholar
  32. Mason-Deese W, Dowd JF, Cary RH (2013) Comparison of digital filter hydrograph separation with geochemical separation. In: Proceedings of the 2013 Georgia Water Resources ConferenceGoogle Scholar
  33. Miao C-Y, Ni J-R (2009) Variation of natural streamflow since 1470 in the Middle Yellow River, China. Int J Environ Res Public Health 6:2849–2864CrossRefPubMedPubMedCentralGoogle Scholar
  34. Minea I (2016) Assessment of the relationship between stream flow and base flow: patterns, analysis, applications. Aerul si Apa Compon ale Mediu, p 76–83Google Scholar
  35. Nam W-H, Hayes MJ, Svoboda MD et al (2015) Drought hazard assessment in the context of climate change for South Korea. Agric Water Manag 160:106–117CrossRefGoogle Scholar
  36. Nardo M, Saisana M, Saltelli A, Tarantola S (2005) Tools for composite indicators building. European Commission, EUR 21682 EN. Institute for the Protection and Security of the Citizen, JRC Ispra, ItalyGoogle Scholar
  37. Nelms DL, Harlow GE, Hayes DC (1997) Base-flow characteristics of streams in the Valley and Ridge, Blue Ridge, and Piedmont physiographic Provinces of Virginia. US Geological Survey, RestonGoogle Scholar
  38. O’Brien G, O’Keefe P, Rose J, Wisner B (2006) Climate change and disaster management. Disasters 30:64–80CrossRefPubMedGoogle Scholar
  39. Phillips CB, Scatena FN (2010) Flashiness indices for urban and rural streams in Puerto Rico. In: AWRA 2010 summer specialty conference, https://www.sas.upenn.edu/lczodata/sites/www.sas.upenn.edu.lczodata/files/ColinPhillips_AWRA%20Flash.pdf. San Juan, Puerto Rico
  40. Poff NL, Ward JV (1989) Implications of streamflow variability and predictability for lotic community structure: a regional analysis of streamflow patterns. Can J Fish Aquat Sci 46:1805–1818CrossRefGoogle Scholar
  41. Poff NL, Allan JD, Bain MB et al (1997) The natural flow regime. Bioscience 47:769–784CrossRefGoogle Scholar
  42. Richter BD, Mathews R, Harrison DL, Wigington R (2003) Ecologically sustainable water management: managing river flows for ecological integrity. Ecol Appl 13:206–224CrossRefGoogle Scholar
  43. Richards KG, Fenton O, Khalil MI, Haria AH, Humphreys J, Doody D, Moles R, Morgan G, Jordan P (2009) Good water status: The integration of sustainable grassland production and water resources in Ireland. Irish J Agric-Environ Res 7:143–162Google Scholar
  44. Rose S, Peters NE (2001) Effects of urbanization on streamflow in the Atlanta area (Georgia, USA): a comparative hydrological approach. Hydrol Process 15:1441–1457CrossRefGoogle Scholar
  45. Rutledge AT (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 Department of the Interior, US Geological Survey, RestonGoogle Scholar
  46. Rutledge AT, 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. US Geological SurveyGoogle Scholar
  47. Sato K, Masuhara K, Mochida S et al (2012) Flood control in small urban rivers: an example of river projects in Tokyo. Urban Water 122:215CrossRefGoogle Scholar
  48. Schwartz SS, Smith B, McGuire M (2012) Baseflow signatures of sustainable water resources. Final Report to the Hughes Center for Agroecology, Queenstown, MDGoogle Scholar
  49. Sear DA, Armitage PD, Dawson FH (1999) Groundwater dominated rivers. Hydrol Process 13:255–276CrossRefGoogle Scholar
  50. Stewart M, Cimino J, Ross M (2007) Calibration of base flow separation methods with streamflow conductivity. Ground Water 45:17–27CrossRefPubMedGoogle Scholar
  51. Strauch AM, MacKenzie RA, Giardina CP, Bruland GL (2015) Climate driven changes to rainfall and streamflow patterns in a model tropical island hydrological system. J Hydrol 523:160–169CrossRefGoogle Scholar
  52. Suriya S, Mudgal BV (2012) Impact of urbanization on flooding: the Thirusoolam sub watershed–a case study. J Hydrol 412:210–219CrossRefGoogle Scholar
  53. Taylor RG, Scanlon B, Döll P et al (2013) Ground water and climate change. Nat Clim Change 3:322–329CrossRefGoogle Scholar
  54. Toda O, Tanji H, Somura H et al (2004) Evaluation of tributaries contribution in the Mekong River basin during rainy and dry season. In: Proceedings of the second conference of the Asia Pacific association of hydrology and water resources, Singapore. pp 239–248Google Scholar
  55. Zhang Y-K, Schilling KE (2006) Increasing streamflow and baseflow in Mississippi River since the 1940s: effect of land use change. J Hydrol 324:412–422CrossRefGoogle Scholar
  56. Zhang Y, Arthington AH, Bunn SE et al (2012) Classification of flow regimes for environmental flow assessment in regulated rivers: the Huai River Basin, China. River Res Appl 28:989–1005CrossRefGoogle Scholar
  57. Zheng H, Zhang L, Liu C et al (2007) Changes in stream flow regime in headwater catchments of the Yellow River basin since the 1950s. Hydrol Process 21:886–893CrossRefGoogle Scholar

Copyright information

© The International Society of Paddy and Water Environment Engineering and Springer Japan KK, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Regional Infrastructure EngineeringKangwon National UniversityChuncheonRepublic of Korea
  2. 2.Institute of Agriculture and Life ScienceKangwon National UniversityChuncheonRepublic of Korea
  3. 3.Department of Construction and Disaster Prevention EngineeringKyungpook National UniversityDaeguRepublic of Korea

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