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Urban floods in Hyderabad, India, under present and future rainfall scenarios: a case study

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Abstract

This study assesses and evaluates the impacts of future extreme rainfall event(s) on conveyance capacity of urban Storm Water Network (SWN) of Hyderabad City, India, along with flood risk analysis and inundation mapping. The catchment runoff volume was simulated using Storm Water Management Model (SWMM). The runoff simulations were carried out for historic and future extreme rainfall event(s). Future rainfall events were simulated under climate change scenarios using Global Climate Model (GCM), GFDL-CM3 of Coupled Model Intercomparison Project Phase 5 (CMIP5). Nonlinear regression-based statistical downscaling was used to obtain rainfall at regional scale for Representative Concentration Pathways (RCPs) 2.6, 4.5, 6.0 and 8.5. It was found that RCPs 2.6, 4.5, 6.0 and 8.5 predicted a future extreme rainfall of 693 mm, 431 mm, 282 mm and 564 mm for the years 2088, 2098, 2040 and 2068, respectively. SWMM results indicated that the future extreme rainfall in Hyderabad can result in increased runoff volumes causing flooding. The existing SWN was capable of handling RCP 6.0 with 82% runoff. However, it was inadequate to convey runoff from RCPs 2.6, 4.5 and 8.5. Modelling results suggest that the conveyance capacity of storm drains can be increased by 25–30% by desilting major drains and outlets.

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References

  • Agilan V, Umamahesh N (2015) Detection and attribution of non-stationarity in intensity and frequency of daily and 4-h extreme rainfall of Hyderabad. India J Hydrol 530:677–697

    Article  Google Scholar 

  • Ahmed Z, Rao DRM, Reddy KRM, Raj YE (2013) Urban flooding-case study of Hyderabad global journal of engineering. Des Technol 2:63–66

    Google Scholar 

  • Akshara G, Srinivasa Raju K, Singh AP, Vasan A (2018) Application of multiple linear regression as downscaling methodology for lower Godavari basin. In: Singh V, Yadav S, Yadava R (eds) Climate change impacts. Water Science and Technology Library, vol 82. Springer, Singapore, pp 25–34. https://doi.org/10.1007/978-981-10-5714-4_3

    Chapter  Google Scholar 

  • American Society of Civil Engineers (ASCE) (1992) Design and construction of urban stormwater management systems. American Society of Civil Engineers, New York

    Google Scholar 

  • Anandhi A, Srinivas V, Nanjundiah RS, Nagesh Kumar D (2008) Downscaling precipitation to river basin in India for IPCC SRES scenarios using support vector machine. Int J Climatol 28:401–420

    Article  Google Scholar 

  • Assessment AR (2016) Chennai floods 2015. https://itra.medialabasia.in/img/Che0nnai%20Floods-Rapid%20Assessment%20Report-May%2023,%202016.pdf. Accessed on July 2018

  • Bi EG, Gachon P, Vrac M, Monette F (2017) Which downscaled rainfall data for climate change impact studies in urban areas? Rev Curr Approaches Trends Theor Appl Climatol 127:685–699

    Article  Google Scholar 

  • GHMC Disaster Management cell (2018) http://www.ghmc.gov.in/Disaster.aspx. Accessed on July 2018

  • Chatterjee M (2010) Slum dwellers response to flooding events in the megacities of India. Mitig Adapt Strat Glob Change 15:337–353

    Article  Google Scholar 

  • Chaturvedi RK, Joshi J, Jayaraman M, Bala G, Ravindranath N (2012) Multi-model climate change projections for India under representative concentration pathways. Curr Sci 103:791–802

    Google Scholar 

  • Dahm RJ, Singh UK, Lal M, Marchand M, Sperna Weiland FC, Singh SK, Singh MP (2016) Downscaling GCM data for climate change impact assessments on rainfall: a practical application for the Brahmani-Baitarani river basin. Hydrol Earth Sys Sci. https://doi.org/10.5194/hess-2015-499

    Google Scholar 

  • De Iorio M, Muller P, Rosner GL, MacEachern SN (2004) An ANOVA model for dependent random measures. J Am Stat As 99:205–215

    Article  Google Scholar 

  • Deccan Chronicle (2016) Hyderabad floods: 16.7 cm rain breaks 16-year-old record. https://www.deccanchronicle.com/nation/current-affairs/220916/hyderabad-floods-167-cm-rain-breaks-16-year-old-record.html. Accessed on Aug 2017

  • Deccan Chronicle (2017) Drainage shortage cripples Hyderabad. https://www.deccanchronicle.com/nation/current-affairs/070917/drainage-shortage-cripples-hyderabad.html. Accessed on Jan 2018

  • Delworth TL, Broccoli AJ, Rosati A, Stouffer RJ, Balaji V, Beesley JA, Cooke WF, Dixon KW, Dunne J, Dunne KA, Durachta JW (2006) GFDL’s CM2 global coupled climate models. Part I: formulation and simulation characteristics. J Clim 19:643–674

    Article  Google Scholar 

  • Denault C, Millar RG, Lence BJ (2006) Assessment of possible impacts of climate change in an urban catchment JAWRA. J Am Water Resour As 42:685–697

    Article  Google Scholar 

  • Diaz-Nieto J, Wilby RL (2005) A comparison of statistical downscaling and climate change factor methods: impacts on low flows in the River Thames, United Kingdom. Clim Change 69:245–268

    Article  Google Scholar 

  • Field CB, Barros VR (2014) IPCC, 2014: climate change 2014: impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, New York

    Google Scholar 

  • Floodlist (2016) India—11 dead in Telangana floods, dams remain dangerously high. http://floodlist.com/asia/india-floods-telangana-september-2016. Accessed on Jan 2018

  • Fowler HJ, Blenkinsop S, Tebaldi C (2007) Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. Int J Climatol 27:1547–1578

    Article  Google Scholar 

  • GHMC (2007) General information on drains of Hyderabad. Unpublished report

  • Google Earth v 6 (2016) Hyderabad, Telangana, India, 17.45 lat, 78.44 long at eye alt 35.16 miles. Accessed on May 2016

  • Gupta K (2007) Urban flood resilience planning and management and lessons for the future: a case study of Mumbai, India. Urb Water J 4:183–194

    Article  Google Scholar 

  • Harlow M, Prince G, Jones C, Tucker C, Reinhart J (2005) ArcGIS 9 geoprocessing commands quick reference guide. Environmental Science Research Institute, Redlands, California, p 175

    Google Scholar 

  • Hashmi M, Shamseldin A, Melville B (2009) Statistical downscaling of precipitation: state-of-the-art and application of bayesian multi-model approach for uncertainty assessment. Hydrol Earth Syst Sci Dis 6:6535–6579

    Article  Google Scholar 

  • Hindustan times (2016) A repeat of 2000 floods: the four days Hyderabad stood still. https://www.hindustantimes.com/india-news/a-repeat-of-2000-floods-the-four-days-hyderabad-stood-still/story-ecWIeaJwyyZtQAGvRYQ4RN.html. Accessed on June 2018

  • Huizinga J, de Moel H, Szewczyk W (2017) Global flood depth-damage functions: Methodology and the database with guidelines. Joint Research Centre, Seville site

    Google Scholar 

  • India Population (2017) http://indiapopulation2017.in/population-of-hyderabad-2017.html. Accessed on June 2018

  • Karamouz M, Nazif S (2013) Reliability-based flood management in urban watersheds considering climate change impacts. J Water Resour Plan Manag 139:520–533

    Article  Google Scholar 

  • Krebs G, Kokkonen T, Valtanen M, Koivusalo H, Setala H (2013) A high resolution application of a stormwater management model (SWMM) using genetic parameter optimization. Urb Water J 10(6):394–410

    Article  Google Scholar 

  • Land rate Telangana Registration (2017) http://registration.telangana.gov.in/ts/Unitrate.do. Accessed on Feb 2017

  • Latif M, Hannachi A, Syed F (2018) Analysis of rainfall trends over Indo-Pakistan summer monsoon and related dynamics based on CMIP5 climate model simulations. Int J Climatol 38:577–595

    Article  Google Scholar 

  • Livemint (2016) http://www.livemint.com/Politics/w9SiawKVG3Y0NDcXm6n84N/Heavy-rains-disrupt-normal-life-in-Andhra-Pradesh-many-trai.html. Accessed on July 2017

  • Lopes CL, Alves FL, Dias JM (2017) Flood risk assessment in a coastal lagoon under present and future scenarios: Ria de Aveiro case study. Nat Hazards 89:1307–1325

    Article  Google Scholar 

  • Martini F, Loat R (2010) Handbook on good practices for flood mapping in Europe. European exchange circle on flood mapping (EXCIMAP), Paris/Bern

  • Meenu R, Rehana S, Mujumdar P (2013) Assessment of hydrologic impacts of climate change in Tunga–Bhadra river basin, India with HEC-HMS and SDSM. Hydrol Process 27:1572–1589

    Article  Google Scholar 

  • Menon A, Levermann A, Schewe J, Lehmann J, Frieler K (2013) Consistent increase in Indian monsoon rainfall and its variability across CMIP-5 models. Earth Syst Dyn 4:287–300

    Article  Google Scholar 

  • Meyer V, Scheuer S, Haase D (2009) A multicriteria approach for flood risk mapping exemplified at the Mulde river, Germany. Nat Hazards 48:17–39

    Article  Google Scholar 

  • Mishra BK, Rafiei Emam A, Masago Y, Kumar P, Regmi RK, Fukushi K (2018) Assessment of future flood inundations under climate and land use change scenarios in the Ciliwung River Basin, Jakarta. J Flood Risk Manag 11:1105–1115

    Article  Google Scholar 

  • Mujumdar P, Kumar DN (2012) Floods in a changing climate: hydrologic modelling. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • NRSC (2017) Digital elevation model. http://bhuvan.nrsc.gov.in/bhuvan_links.php. Accessed on May 2016

  • Ojha C, Goyal MK, Adeloye A (2010) Downscaling of precipitation for lake catchment in arid region in India using linear multiple regression and neural networks. Open Hydrol J 4:122–136

    Article  Google Scholar 

  • Ongoma V, Chen H, Gao C (2018) Projected changes in mean rainfall and temperature over East Africa based on CMIP5 models. Int J Climatol 38:1375–1392

    Article  Google Scholar 

  • Pina R, Simoes N, Marques J, Sousa J (2011) Floodplain delineation with free and open source software. In: 12th International conference on urban drainage, Porto Alegre

  • Prudhomme C, Reynard N, Crooks S (2002) Downscaling of global climate models for flood frequency analysis: where are we now? Hydrol Process 16:1137–1150

    Article  Google Scholar 

  • Rai PK, Chahar B, Dhanya C (2017) GIS-based SWMM model for simulating the catchment response to flood events. Hydrol Res 48:384–394

    Article  Google Scholar 

  • Raje D, Mujumdar P (2011) A comparison of three methods for downscaling daily precipitation in the Punjab region. Hydrol Process 25:3575–3589

    Article  Google Scholar 

  • Raju KS, Sonali P, Kumar DN (2017) Ranking of CMIP5-based global climate models for India using compromise programming. Theor Appl Climatol 128:563–574

    Article  Google Scholar 

  • Ramachandraiah C, Prasad S (2004) Impact of urban growth on water bodies: the case of Hyderabad. Centre for Economic and Social Studies, Hyderabad

    Google Scholar 

  • Ranger N, Hallegatte S, Bhattacharya S, Bachu M, Priya S, Dhore K, Rafique F, Mathur P, Naville N, Henriet F, Herweijer C (2011) An assessment of the potential impact of climate change on flood risk in Mumbai. Clim Change 104:139–167

    Article  Google Scholar 

  • Reshmidevi T, Kumar DN, Mehrotra R, Sharma A (2018) Estimation of the climate change impact on a catchment water balance using an ensemble of GCMs. J Hydrol 556:1192–1204

    Article  Google Scholar 

  • Rossman L, Huber W (2016) Storm water management model reference manual volume I—hydrology (revised). US Environmental Protection Agency, Cincinnati

    Google Scholar 

  • Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15:234–281

    Article  Google Scholar 

  • Saharia AM, Sarma AK (2018) Future climate change impact evaluation on hydrologic processes in the Bharalu and Basistha basins using SWAT model. Nat Hazards 92:1463–1488

    Article  Google Scholar 

  • Sarala C, SreeLakshmi G (2014) Improvement of storm water drainage system in greater Hyderabad municipal corporation. Int J Adv Eng Technol 7(2):605

    Google Scholar 

  • Srinivasa Raju K, Kumar DN (2018) Selection of global climate models. In: Impact of climate change on water resources. Springer Climate. Springer, Singapore, pp 27–75. https://doi.org/10.1007/978-981-10-6110-3_2

  • Sun DZ, Zhang T, Covey C, Klein SA, Collins WD, Hack JJ, Kiehl JT, Meehl GA, Held IM, Suarez M (2006) Radiative and dynamical feedbacks over the equatorial cold tongue: results from nine atmospheric GCMs. J Clim 19:4059–4074

    Article  Google Scholar 

  • Swathi V, Sai Veena S, Santosh A, Raju KS (2017) Urban floods under changing climate—a case study of Greater Hyderabad. In: American geophysical union international conference, New Orleans, Louisiana. http://fall-2017.vps.agu.org/media/77

  • Swathi V, Srinivasa Raju K, Singh AP (2018) Application of storm water management model to an urban catchment. In: Singh V, Yadav S, Yadava R (eds) Hydrologic modeling. Water Science and Technology Library, vol 81. Springer, Singapore, pp 175–184. https://doi.org/10.1007/978-981-10-5801-1_13

    Google Scholar 

  • Tatli H, Nuzhet Dalfes H, Sibel Mentes S (2004) A statistical downscaling method for monthly total precipitation over Turkey. Int J Climatol 24:161–180

    Article  Google Scholar 

  • The Hindu (2017) Remodelling of drainage system may cost a bomb. http://www.thehindu.com/news/cities/Hyderabad/remodelling-of-drainage-system-may-cost-a-bomb/article19614139.ece. Accessed on May 2016

  • The Indian Express (2016) Heavy rain alert in Hyderabad; highways, railway tracks flooded. http://indianexpress.com/article/india/india-news-india/hyderabad-heavy-rain-alert-flodding-highway-railway-tracks-water-logging-3045215/. Accessed on Sept 2017

  • The News Minute (2016) Rain and flooding in Hyderabad: What caused it and why both govt and people are responsible for it. https://www.thenewsminute.com/article/rain-and-flooding-hyderabad-what-caused-it-and-why-both-govt-and-people-are-responsible-it. Accessed on June 2018

  • The Times of India (2016) Hyderabad rain: Vehicle owners hit hard. https://timesofindia.indiatimes.com/city/hyderabad/Hyderabad-rain-Vehicle-owners-hit-hard/articleshow/54474659.cms. Accessed on Feb 2018

  • Tiwari PR, Kar S, Mohanty U, Kumari S, Sinha P, Nair A, Dey S (2014) Skill of precipitation prediction with GCMs over north India during winter season. Int J Climatol 34:3440–3455

    Article  Google Scholar 

  • Tripathi S, Srinivas V, Nanjundiah RS (2006) Downscaling of precipitation for climate change scenarios: a support vector machine approach. J hydrol 330:621–640

    Article  Google Scholar 

  • Vandana K, Islam A, Sarthi PP, Sikka, AK, Kapil H (2018) Assessment of potential impact of climate change on streamflow: a case study of the Brahmani River basin, India. J Water Clim Change. https://doi.org/10.2166/wcc.2018.129

    Google Scholar 

  • Wan B, James W (2002) SWMM calibration using genetic algorithms. In: International conference on Global Solutions for Urban Drainage. American Society of Civil Engineers, pp 1–14. https://doi.org/10.1061/40644.92

  • Waters D, Watt WE, Marsalek J, Anderson BC (2003) Adaptation of a storm drainage system to accommodate increased rainfall resulting from climate change. J Environ Plan Manag 46:755–770

    Article  Google Scholar 

  • Wu C, Huang G, Yu H (2015) Prediction of extreme floods based on CMIP5 climate models: a case study in the Beijiang River basin, South China. Hydrol Earth Syst Sci 19:1385–1399

    Article  Google Scholar 

  • Zaghloul NA (1983) Sensitivity analysis of the SWMM runoff-transport parameters and the effects of catchment discretisation. Adv Water Resour 6:214–223

    Article  Google Scholar 

  • Zahmatkesh Z, Burian SJ, Karamouz M, Tavakol Davani H, Goharian E (2014) Low-impact development practices to mitigate climate change effects on urban stormwater runoff: case study of New York City. J Irrig Drain Eng 141:04014043

    Article  Google Scholar 

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Acknowledgements

This work is supported by Information Technology Research Academy (ITRA), Government of India under, ITRA-water grant ITRA/15(68)/water/IUFM/01. Authors thank officials of Greater Hyderabad Municipal Corporation (GHMC) for providing storm water network data, brain storming discussions, valuable suggestions and facilitating for field surveys. Special acknowledgments to Mr D. Ravinder, Superintending Engineer, GHMC, for providing data and valuable thought provoking discussions. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP5, and we thank the climate modelling groups for producing and making their model output available. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organisation for Earth System Science Portals. We thank the India Meteorological Department (IMD) and National Centers for Environmental Prediction (NCEP) for providing rainfall data. We thank United States Environmental Protection Agency (US EPA) for making Storm Water Management Model (SWMM) an open source software, and authors also thank Google Earth for its open source images. We extend special acknowledgments to Dr Murari RR Varma, Prof D.Nagesh Kumar and Prof N. V. Umamahesh for suggesting improvements in the manuscript.

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  1. Department of Civil Engineering, Birla Institute of Technology and Science, Pilani-Hyderabad Campus, Hyderabad, 500078, India

    Swathi Vemula, K. Srinivasa Raju, S. Sai Veena & A. Santosh Kumar

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Vemula, S., Raju, K.S., Veena, S.S. et al. Urban floods in Hyderabad, India, under present and future rainfall scenarios: a case study. Nat Hazards 95, 637–655 (2019). https://doi.org/10.1007/s11069-018-3511-9

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