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Estimation of flood damage functions for river basin planning: a case study in Bangladesh

Abstract

Located at the low-lying deltaic floodplain of Ganges–Brahmaputra–Meghna river basin, Bangladesh suffers damages from flooding with regularity. From the perspective of long-term planning and management, a reliable flood damage function is a critical component in the estimation of flood-induced economic loss. Such functions are, however, notoriously difficult to develop. This study utilizes in-stream water level and flood-affected area (FAA) data from Flood Forecasting and Warning Center and Bangladesh Water Development Board to evaluate the best form and data input characteristics of flood damage functions for Bangladesh. The performance of various function configurations (geographic data, water level data, and function form) was tested. The Nash–Sutcliffe efficiency and residual error analysis results suggest that, in general, the logistic function performs better than the other two function forms, and the maximum of daily-maximal water level is the best suited to estimate (FAA). As expected, when information is available from all basins (the Ganges, the Brahmaputra, and the Meghna), the resulting flood damage functions provide the most accurate estimations of FAA. Furthermore, the comparison between single- and multivariable flood damage functions does not demonstrate a clear advantage of using multivariate function in our study area. When flood damage functions with finer spatial and temporal resolution can be constructed using remote sensing technology or hydrodynamic modeling, the intra-year and district-level changes to FAA can be evaluated. These findings provide a better flood management plan for Bangladesh and have potential to be generalized to other similarly flood-affected nations.

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References

  • Ahmad QK, Ahmed AU (2003) Regional cooperation in flood management in the Ganges–Brahmaputra–Meghna region Bangladesh perspective. Nat Hazards 28:181–198

    Article  Google Scholar 

  • Ahmed AU, Mirza MMQ (2000) Review of causes and dimensions of floods with particular reference to flood’98: national perspectives. In: Ahmad QK, Chowdhury AKA, Imam SH, Sarker M (eds) Perspectives on flood 1998. University Press Ltd., Dhaka

    Google Scholar 

  • Allison MA, Kepple EB (2001) Modern sediment supply to the lower delta plain of the Ganges–Brahmaputra River in Bangladesh. Geo-Mar Lett 21:66–74

    Article  Google Scholar 

  • Amarnath G (2013) An algorithm for rapid flood inundation mapping from optical data using a reflectance differencing technique. J Flood Risk Manag 12. doi:10.1111/jfr3.12045

  • Apel H, Aronica GT, Kreibich H, Thieken AH (2009) Flood risk analyses—how detailed do we need to be? Nat Hazards 49:79–98

    Article  Google Scholar 

  • Bangladesh Water Development Board (BWDB) (2012) Annual flood report 2012, Dhaka, Bangladesh

  • Bates PD, Horritt MS, Fewtrell TJ (2010) A simple inertial formulation of the shallow water equations for efficient two dimensional flood inundation modelling. J Hydrol 387:33–45

    Article  Google Scholar 

  • Bhattachaiyya NN, Bora AK (2009) Floods of the Brahmaputra River in India. Water Int 22(4):222–229

    Article  Google Scholar 

  • Biswas AK (2008) Management of Ganges–Brahmaputra–Meghna system: way forward. In: Varis O, Tortajada C, Biswas AK (eds) Management of transboundary rivers and lakes. Springer, Berlin Heidelberg

    Google Scholar 

  • Boettle M, Kropp JP, Reiber L, Roithmeier O, Rybski D, Walther C (2011) About the influence of elevation model quality and small-scale damage functions on flood damage estimation. Nat Hazards Earth Syst Sci 11:3327–3334

    Article  Google Scholar 

  • Booij MJ (2004) Flood damage assessment and modelling in the red river basin in Vietnam. International workshop on flood controls decision support system. 10–12 Feb 2004, Hanoi, Vietnam

  • Chang LF, Lin CH, Su MD (2008) Application of geographic weighted regression to establish flood-damage functions reflecting spatial variation. Water SA 34(2):209–216

    Google Scholar 

  • Dale M, Wicks J, Mylne K, Pappenberger F, Laeger S, Taylor S (2014) Probabilistic flood forecasting and decision-making: an innovative risk-based approach. Nat Hazards 70:159–172

    Article  Google Scholar 

  • Dasgupta A (2007) Floods and poverty traps: evidence from Bangladesh. Econ Polit Wkly 42(30):3166–3171

  • Davis SA (1985) Business depth-damage analysis procedures, research report 85-R-5. Institute for Water Resources, Water Resources Support Center, U. S. Army Corps of Engineers, Ft. Belvoir, Virginia, USA

  • Dhar ON, Nandargi S (2000) A study of floods in the Brahmaputra basin in India. Int J Climatol 20:771–781

    Article  Google Scholar 

  • Dorado J, Rabunal JR, Puertas J, Santos A, Rivero D (2002) Prediction and modelling of the flow of a typical urban basin through genetic programming: applications of evolutionary computing. Lect Notes Comput Sci 2279:190–201

    Article  Google Scholar 

  • Dutta D, Herath S, Musiake K (2003) A mathematical model for flood loss estimation. J Hydrol 277:24–49

    Article  Google Scholar 

  • Hopson TM, Webster PJ (2010) A 1–10 day ensemble forecasting scheme for the major basins of Bangladesh: forecasting severe floods of 2003–07. J Hydrometeorol 11:618–641

    Article  Google Scholar 

  • Islam MR, Begum SF, Yamaguchi Y, Ogawa K (1999) The Ganges and Brahmaputra Rivers in Bangladesh: basin denudation and sedimentation. Hydrol Process 12:2907–2923

    Article  Google Scholar 

  • Islam AS, Bala SK, Haque A (2009) Flood inundation map of Bangladesh using MODIS surface reference data. In: 2nd international conference on water & flood management. Dhaka, Bangladesh

  • Islam AS, Haque A, Bala SK (2010) Hydrologic characteristics of floods in Ganges–Brahmaputra–Meghna (GBM) delta. Nat Hazards 54:797–811

    Article  Google Scholar 

  • Jamir T, Gadgil AS, De US (2008) Recent floods related natural hazards over west coast and Northeast India. J Indian Geophys Union 12(4):179–182

    Google Scholar 

  • Karamouz M, Abesi O, Moridi A, Ahmadi A (2008) Development of optimization schemes for floodplain management; a case study. Water Resour Manage 23:1743–1761

    Article  Google Scholar 

  • Lund JR (2002) Floodplain planning with risk-based optimization. J Water Resour Plan Manag 127(3):202–207

    Article  Google Scholar 

  • Malekmohammadi B, Zahraie B, Kerachian R (2010) A real-time operation optimization model for flood management in river-reservoir systems. Nat Hazards 53:459–482

    Article  Google Scholar 

  • Merz B, Kreibich H, Thieken A, Schmidtke R (2004) Estimation uncertainty of direct monetary flood damage to buildings. Nat Hazards Earth Syst Sci 4:153–163

    Article  Google Scholar 

  • Messner F, Penning-Rowsell E, Green C, Meyer V, Tunstall S, van der Veen A (2007) Evaluating flood damages: guidance and recommendations on principles and methods, UFZ, European Community’s Sixth Framework Programme. Leipzig, Germany

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

    Article  Google Scholar 

  • Mirza MMQ (2003) Three recent extreme floods in Bangladesh: a hydro-meteorological analysis. Nat Hazards 28:35–64

    Article  Google Scholar 

  • Mirza MMQ, Warrick RA, Ericksen NJ (2003) The implications of climate change on floods of the Ganges, Brahmaputra and Meghna Rivers in Bangladesh. Clim Change 57:287–318

    Article  Google Scholar 

  • Neal J, Schumann GJ-P, Bates PD (2012) A simple model for simulating river hydraulics and floodplain inundation over large and data sparse areas. Water Resour Res 48, Paper no. W11506

  • Penning-Rowsell E, Johnson C, Tunstall S, Tapsell S, Morris J, Chatterton J, Green C (2005) The benefits of flood and coastal risk management: a handbook of assessment techniques. Middlesex University Press, London

    Google Scholar 

  • Prettenthaler F, Amrusch P, Habsburg-Lothringen C (2010) Estimation of an absolute flood damage curve based on an Austrian case study under a dam breach scenario. Nat Hazards Earth Syst Sci 10:881–894

    Article  Google Scholar 

  • Rahman AF, Dragoni D, El-Masri B (2011) Response of the Sundarbans coastline to sea level rise and decreased sediment flow: a remote sensing assessment. Remote Sens Environ 115(12):3121–3128

    Article  Google Scholar 

  • Richards FJ (1959) A flexible growth function for empirical use. J Exp Bot 10:290–300

    Article  Google Scholar 

  • Sanyal J, Lu XX (2004) application of remote sensing in flood management with special reference to monsoon Asia a review. Nat Hazards 33:283–301

    Article  Google Scholar 

  • Savic DA, Walters GA, Davidson JW (1999) A genetic programming approach to rainfall-runoff modeling. Water Resour Manage 13:219–231

    Article  Google Scholar 

  • Schroter K, Kreibich H, Vogel K, Riggelsen C, Scherbaum F, Merz B (2014) How useful are complex flood damage models? Water Resour Res 50. doi:10.1002/2013WR014396

  • Sharma N, Sankhua RN, Pandey AD (2005) Spatio-temporal modeling of hydrological variability for the river Brahmaputra using artificial neural network. In: Proceedings of the international symposium on ‘role of water sciences in transboundary river basin management. Ubon Ratchathani, Thailand

  • Sharma N, Johnson F, Hutton C, Clark M (2010) Hazard, vulnerability and risk on the Brahmaputra basin: a case study of river bank erosion. Open Hydrol J 4:211–226

    Article  Google Scholar 

  • Shrestha KY, Webster PJ, Toma VE (2014) An atmospheric–hydrologic forecasting scheme for the Indus River basin. J Hydrometeorol 15:861–890

    Article  Google Scholar 

  • Smith DI (1994) Flood damage estimation—a review of urban stage-damage curves and loss functions. Water SA 20:231–238

    Google Scholar 

  • State of California (SOC) (2012) 2012 Central Valley flood protection plan attachment 8F: flood damage analysis, the natural resources agency. Department of Water Resource, Sacramento, CA, USA

  • Stedinger JR, Grygier J (1985) Risk-cost analysis and spillway design. Comput Appl Water Resour 1208–1217

  • Thieken AH et al (2008) Methods for the evaluation of direct and indirect flood losses. In: 4th international symposium on flood defence: managing flood risk, reliability and vulnerability, Toronto, Ontario, Canada, 6–8 May 2008

  • U. S. Army Corps of Engineers (USACE) (1996) Risk-based analysis for flood damage reduction studies: engineering manual. Washington, DC, USA

  • UNSW (1981) Evaluation methodology of flood damage in Australia, technical project report. University of New South Wales, Australia

  • Villiers GT, Viljoen MF, Booysen HJ (2007) Standard residential flood damage functions for South African conditions. Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie 26(1):26–36

    Article  Google Scholar 

  • White GF (1964) Choice of adjustment to floods. Research Paper No. 93, Department of Geography, University of Chicago. Chicago, IL, USA

  • Woodward M, Gouldgy B, Kapelan Z, Hames D (2014) Multiobjective optimization for improved management of flood risk. J Water Resour Plan Manag 140(2):201–215

    Article  Google Scholar 

  • Wu H, Adler RF, Hong Y, Tian Y, Policelli F (2012) Evaluation of global flood detection using satellite-based rainfall and a hydrologic model. J Hydrometeorol 13:1268–1284

    Article  Google Scholar 

  • Yang YCE, Cai X (2011) Reservoir reoperation for fish ecosystem restoration using daily inflows—A case study of Lake Shelbyville. J Water Resour Plan Manag ASCE 136(6):470–480

    Article  Google Scholar 

  • Yang YCE, Cai X, Herricks EE (2008) Identification of hydrologic indicators related to fish diversity and abundance—a data mining approach for fish community analysis. Water Resour Res 44:W04412. doi:10.1029/2006WR005764

    Google Scholar 

  • Yazdi J, Neyshabouri SAAS (2012a) Optimal design of flood-control multi-reservoir system on a watershed scale. Nat Hazards 63:629–646

    Article  Google Scholar 

  • Yazdi J, Neyshabouri SAAS (2012b) A simulation-based optimization model for flood management on a watershed scale. Water Resour Manage 26:4569–4586

    Article  Google Scholar 

  • Yu W et al (2010) Climate change risks and food security in Bangladesh. Earthcan, Washington

    Google Scholar 

  • Zhu T, Lund JR (2009) Up or out—economic-engineering theory of flood levee height and setback. J Water Resour Plan Manag 135(2):90–95

    Article  Google Scholar 

Download references

Acknowledgments

The paper is financially supported by the World Bank project: Future Visions of the BrahmaputraEstablishing Hydrologic Baseline and Water Resources Context. Authors would also like to thank colleagues at the 4th Global Flood Partnership Workshop, Reading, UK for helpful insights. The views expressed in this paper are those of the authors and do not necessarily reflect the views of the World Bank.

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Correspondence to Y. C. Ethan Yang.

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Yang, Y.C.E., Ray, P.A., Brown, C.M. et al. Estimation of flood damage functions for river basin planning: a case study in Bangladesh. Nat Hazards 75, 2773–2791 (2015). https://doi.org/10.1007/s11069-014-1459-y

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  • DOI: https://doi.org/10.1007/s11069-014-1459-y

Keywords

  • Flood-affected area
  • Water level
  • Ganges
  • Brahmaputra
  • Meghna