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Thresholds of hydrologic flow regime of a river and investigation of climate change impact—the case of the Lower Brahmaputra river Basin

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Abstract

The sustainability of social-ecological systems depends on river flows being maintained within a range to which those systems are adapted. In order to determine the extent of this natural range of variation, we assess ecological flow thresholds and the occurrence of potentially damaging flood events to society in the context of the Lower Brahmaputra river basin. The ecological flow threshold was calculated using twenty-two ‘Range of Variability (RVA)’ parameters, considering the range between ± 1 standard deviation from the mean of the natural flow. Damaging flood events were calculated using flood frequency analysis of Annual Maxima series and using the flood classification of Bangladesh. The climate change impacts on future river flow were calculated by using a weighted ensemble analysis of twelve global circulation models (GCMs) outputs driving a large-scale hydrologic model. The simulated climate change induced altered flow regime of the Lower Brahmaputra River Basin was then investigated and compared with the calculated threshold flows. The results demonstrate that various parameters including the monthly mean of low flow (January, February and March) and high flow (June, July and August) periods, the 7-day average minimum flow, and the yearly maximum flow will exceed the threshold conditions by 1956–1995 under the business-as-usual A1B and A2 future scenarios. The results have a number of policy level implications for government agencies of the Lower Brahmaputra River Basin, specifically for Bangladesh. The calculated thresholds may be used as a good basis for negotiations with other riparian countries of the basin. The methodological approach presented in this study can be applied to other river basins and provide a useful basis for transboundary water resources management.

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References

  • Ahmed AU (2001) Adaptability of Bangladesh’s crop agriculture to climate change: possibilities and limitations. Asia Pac J Environ Dev 7(1):71–93

    Google Scholar 

  • Apel H, Thieken AH, Merz B, Blöschl G (2006) A probabilistic modelling system for assessing flood risks. Nat Hazard 38(1–2):79–100

    Article  Google Scholar 

  • Bergström S (1976) The HBV model. In: Singh VP (ed) Computer models of watershed hydrology. Water Resources Publications, Colorado, pp 443–476

    Google Scholar 

  • Biswas SP, Boruah S (2000) Ecology of the River Dolphin (Platanista gangetica) in the Upper Brahmaputra. Hydrobiologia 430:97–111

    Article  Google Scholar 

  • Boruah S, Biswas SP (2002) Ecohydrology and fisheries of the Upper Brahmaputra basin. Environmentalist 22:119–131

    Article  Google Scholar 

  • Brammer H, Asaduzzaman H, Sultana P (1996) Effects of climate and sea-level changes on the natural resources of Bangladesh. In: Ahmad QK, Warrick RA (eds) The implications of climate and sea-level change for Bangladesh. Kluwer, Dordrecht, pp 143–193

    Chapter  Google Scholar 

  • Gain AK, Immerzeel WW, Sperna Weiland FC, Bierkens MFP (2011) Impact of climate change on the stream flow of the lower Brahmaputra: trends in high and low flows based on discharge-weighted ensemble modelling. Hydrol Earth Syst Sci 15(5):1537–1545

    Article  Google Scholar 

  • Gain AK, Uddin MN, Sana P (2008) Impact of River Salinity on Fish Diversity in the South-West Coastal Region of Bangladesh. Int J Ecol Env Sci 34:49–54

    Google Scholar 

  • Gallopín GC (2006) Linkages between vulnerability, resilience, and adaptive capacity. Glob Environ Chang 16:293–303

    Article  Google Scholar 

  • Giorgi F, Mearns LO (2002) Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the “Reliability Ensemble Averageing” (REA) method. J Clim 15:1141–1158

    Article  Google Scholar 

  • Gleckler PJ, Taylor KE, Doutriaux C (2008) Performance metrics for climate models. J Geophys Res-Atmos 113, D06104

    Article  Google Scholar 

  • Grumbine RE, Pandit MK (2013) Threats from India’s Himalaya dams. Science 339:36–37

    Article  Google Scholar 

  • Gupta AD, Babel MS, Albert X, Mark O (2005) Water sector of Bangladesh in the context of integrated water resources management: a review. Int J Water Resour Dev 21(2):385–398

    Article  Google Scholar 

  • Gunderson LH, Holling CS, Light SS (1995) Barriers and Bridges to the Renewal of Ecosystems and Institutions. Columbia University Press, New York

    Google Scholar 

  • Hofer T, Messerli B (2006) Floods in Bangladesh: History, dynamics and rethinking the role of the Himalayas. United Nations University Press, Tokyo

    Google Scholar 

  • Hosking JRM, Wallis JR (1997) Regional frequency analysis, an approach based on L-moments. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Immerzeel W (2008) Historical trends and future predictions of climate variability in the Brahmaputra basin. Int J Climatol 28:243–254

    Article  Google Scholar 

  • Immerzeel WW, van Beek LP, Bierkens MFP (2010) Climate change will affect the Asian water towers. Science 328:1382–1385

    Article  Google Scholar 

  • Knutti R (2008) Should we believe model predictions of future climate change? Philos T R Soc A 366:4647–4664

    Article  Google Scholar 

  • Meehl GA, Stocker TF, Collins WD, Friedlingstein P, Gaye AT, Gregory JM, Kitoh A, Knutti R, Murphy JM, Noda A, Raper SCB, Watterson IG, Weaver AJ, Zhao Z-C (2007) Global climate projections. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge, pp 747–846

    Google Scholar 

  • Mirza MMQ (1998) Diversion of the Ganges Water at Farakka and its effects on salinity in Bangladesh. Environ Manag 22:711–722

    Article  Google Scholar 

  • Mirza MMQ (2002) Global warming and changes in the probability of occurrence of floods in Bangladesh and implications. Glob Environ Chang 12(2):127–138

    Article  Google Scholar 

  • Monk WA, Wood PJ, Hannah DM, Wilson DA (2007) Selection of river flow indices for the assessment of hydroecological change. River Res App 23(1):113–122

    Article  Google Scholar 

  • Murphy JM, Sexton DMH, Barnett DN, Jones GS, Webb MJ, Collins M, Stainforth DA (2004) Quantification of modelling uncertainties in a large ensemble of climate change simulations. Nature 430:768–772

    Article  Google Scholar 

  • Olden JD, Poff NL (2003) Redundancy and the choice of hydrologic indices for characterizing streamflow regimes. River Res App 19(2):101–121

    Article  Google Scholar 

  • Poff NL, Allan JD, Bain MB, Karr JR, Prestegaard KL, Brian D, Sparks RE, Stromberg JC, Richter BD (1997) The natural flow regime - a paradigm for river conservation and restoration. BioScience 47(11):769–784

    Article  Google Scholar 

  • Poff NL, Brinson MM, Day JW (2002) Aquatic ecosystems and global climate change: potential impacts on inland freshwater and coastal wetland ecosystems in the United States. The Pew Center on Global Climate Change, Philadelphia

  • Poff NL, Tokar S, Johnson P (1996) Stream hydrological and ecological responses to climate change assessed with an artificial neural network. Limnol Oceanogr 41(5):857–863

    Article  Google Scholar 

  • Poff NL, Ward J (1990) The physical habitat template of the lotic systems: recovery in the context of historical pattern of spatio-temporal heterogeneity. Environ Manag 14:5–37

    Article  Google Scholar 

  • Räisänen J, Ruokolainen L, Ylhäisi J (2010) Weighting of model results for improving best estimate of climate change. Climate Dyn 35:407–422

    Article  Google Scholar 

  • Renaud FG, Birkmann J, Damm M, Gallopín GC (2010) Understanding multiple thresholds of coupled social-ecological systems exposed to natural hazards as external shocks. Nat Hazards 55:749–763

    Article  Google Scholar 

  • Richter BD, Davis MM, Apse C, Konrad C (2011) Short Communication: a presumptive standard for environmental flow protection. River Res App. doi:10.1002/rra.1511

    Google Scholar 

  • Richter BD, Baumgartner JV, Wigington R, Braun DP (1997) How much water does a river need? Freshw Biol 37:231–249

    Article  Google Scholar 

  • Richter BD, Baumgartner JV, Powell J, Braun DP (1996) A method for assessing hydrologic alteration within ecosystems. Conserv Biol 10:1163–1174

    Article  Google Scholar 

  • Sanz DB, Garcίa del Jalόn D, Gutiérrez Teira B, Vizcaίno Martίnez P (2005) Basin influence on natural variability of rivers in semi-arid environments. Int J River Basin Mgt 3:247–259

    Article  Google Scholar 

  • Smakhtin VU, Shilpakar RL, Hughes DA (2006) Hydrology-based assessment of environmental flows: an example from Nepal. Hydrol Sci J 51:207–222

    Article  Google Scholar 

  • Sperna Weiland FC, van Beek LPH, Weerts AH, Bierkens MFP (2012) Extracting information from an ensemble of GCMs to reliably assess global future runoff change. J Hydrol 412–413:66–75

    Article  Google Scholar 

  • Tebaldi D, Knutti R (2007) The use of the multi-model ensemble in probabilistic climate projections. Philos Trans Roy Soc A 365:2053–2075

    Article  Google Scholar 

  • Tockner K, Stanford JA (2002) Riverine floodplains: present state and future trends. Environ Conserv 29:308–330

    Article  Google Scholar 

  • Van Beek LPH, Bierkens MFP (2008) The Global Hydrological Model PCR-GLOBWB: Conceptualization, Parameterization and Verification. Report, Department of Physical Geography, Utrecht University., available at http://vanbeek.geo.uu.nl/suppinfo/vanbeekbierkens2009.pdf

  • Wharton CH, Lambou VW, Newsome J, Winger PV, Gaddy LL, Mancke R (1981) The fauna of bottomland hardwoods in the southeastern United States. In: Clark JR, Benforado J (eds) Wetlands of bottom- land hardwood forests. Elsevier Scientific Publishing Co, New York, pp 87–160

    Chapter  Google Scholar 

  • Xu J, Grumbine RE, Shrestha A, Eriksson M, Yang X, Wang Y, Wilkes A (2009) The melting Himalayas: cascading effects of climate change on water, biodiversity and livelihoods. Conserv Biol 23(3):520–530

    Article  Google Scholar 

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Acknowledgment

Part of this research was conducted at Ca’ Foscari University of Venice and at the United Nations University – Institute for Environment and Human Security (UNU-EHS), whose support is gratefully acknowledged. The authors are grateful to Bangladesh Water Development Board for providing the discharge data.

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Correspondence to Animesh K. Gain.

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Gain, A.K., Apel, H., Renaud, F.G. et al. Thresholds of hydrologic flow regime of a river and investigation of climate change impact—the case of the Lower Brahmaputra river Basin. Climatic Change 120, 463–475 (2013). https://doi.org/10.1007/s10584-013-0800-x

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  • DOI: https://doi.org/10.1007/s10584-013-0800-x

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