Robust Strategy for Assessing the Costs of Urban Drainage System Designs under Climate Change Scenarios
Publication: Journal of Water Resources Planning and Management
Volume 146, Issue 11
Abstract
Uncertainty inherent in precipitation predictions from general circulation model (GCMs) may lead urban drainage systems to be underdesigned (or overdesigned) in the future. This issue can be mitigated with the use of risk analysis models. In this study, a decision-making tool, developed based on six models (minimin, minimax, expected value, Hurwicz, Savage, and scenario-based multiobjective robust optimization), was used to select GCM/representative concentration pathways (RCP) scenarios that would lead to robust designs of an urban drainage system located in Fortaleza, Brazil. The implementation costs of the studied drainage system were estimated using runoff derived from rainfall predictions from six GCMs and two RCPs. After applying the proposed decision-making tool, three GCM/RCP scenarios were selected for yielding the most resilient and reliable designs. The range of feasible GCM/RCP scenarios reflects the level of optimism or pessimism held by a decision maker. We strongly recommend that this method be incorporated in urban drainage system design in order to help municipal planners make better decisions in view of climate change uncertainty.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
The GCM data were extracted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) website (http://cmip-pcmdi.llnl.gov/cmip5/) in the NetCDF format.
Some or all data, models, or code used during the study were provided by a third party. Direct requests for these materials may be made to the provider as indicated in the Acknowledgments.
Acknowledgments
We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for coupled model intercomparison project (CMIP), and we thank the climate modeling groups listed in Table 2 for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led the development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. Author Marcos Abilio Medeiros de Saboia gratefully acknowledges the financial support provided by the government of the state of Ceará, Brazil.
References
Anderson, M. L., Z.-Q. Chen, M. L. Kavvas, and A. Feldman. 2002. “Coupling HEC-HMS with atmospheric models for prediction of watershed runoff.” J. Hydrol. Eng. 7 (4): 312–318. https://doi.org/10.1061/(ASCE)1084-0699(2002)7:4(312).
Andrade, E. L. 1989. Introdução à pesquisa operacional: Métodos e técnicas para análise de decisão, 377. Rio de Janeiro, Brazil: Livros Técnicos e Científicos.
Andrews, T., J. M. Gregory, and M. J. Webb. 2015. “The dependence of radiative forcing and feedback on evolving patterns of surface temperature change in climate models.” J. Clim. 28 (4): 1630–1648. https://doi.org/10.1175/JCLI-D-14-00545.1.
Bekman, O. R., and P. L. O. Costa Neto. 1980. Análise estatística da decisão. São Paulo, Brazil: Edgard Blucher.
Caixa Econômica Federal. 2020. “SINAPI-Sistema Nacional de Pesquisa de Custos e Índices da Construção Civil.” Accessed February 9, 2020. http://www.caixa.gov.br/site/paginas/downloads.aspx.
Chu, X., and A. Steinman. 2009. “Event and continuous hydrologic modeling with HEC-HMS.” J. Irrig. Drain. Eng. 135 (1): 119–124. https://doi.org/10.1061/(ASCE)0733-9437(2009)135:1(119).
Climate Changes in Australia. 2019. “Greenhouse gas scenarios.” Accessed June 28, 2019. https://www.climatechangeinaustralia.gov.au/en/climate-campus/modelling-and-projections/projecting-future-climate/greenhouse-gas-scenarios/.
De Silva, M. M. G. T., S. B. Weerakoon, and S. Herath. 2014. “Modeling of event and continuous flow hydrographs with HEC–HMS: Case study in the Kelani River basin, Sri Lanka.” J. Hydrol. Eng. 19 (4): 800–806. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000846.
Eker, S., and J. H. Kwakkel. 2018. “Including robustness considerations in the search phase of many-objective robust decision making.” Environ. Modell. Software 105 (2018): 201–216. https://doi.org/10.1016/j.envsoft.2018.03.029.
Espinet, X., A. Schweikert, and P. Chinowsky. 2017. “Robust prioritization framework for transport infrastructure adaptation investments under uncertainty of climate change.” J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 3 (1): E4015001. https://doi.org/10.1061/AJRUA6.0000852.
Fischer, E. M., and R. Knutti. 2015. “Anthropogenic contribution to global occurrence of heavy-precipitation and high-temperature extremes.” Nat. Clim. Change 5 (6): 560–564. https://doi.org/10.1038/nclimate2617.
Green, D. 2016. “The spatial distribution of extreme climate events, another climate inequity for the world’s most vulnerable people.” Environ. Res. Lett. 11 (9): 091002. https://doi.org/10.1088/1748-9326/11/9/091002.
Guo, Y. P. 2006. “Updating rainfall IDF relationships to maintain urban drainage design standards.” J. Hydrol. Eng. 11 (5): 506–509. https://doi.org/10.1061/(ASCE)1084-0699(2006)11:5(506).
Harrington, L. J., D. J. Frame, E. M. Fischer, E. Hawkins, M. Joshi, and C. D. Jones. 2016. “Poorest countries experience earlier anthropogenic emergence of daily temperature extremes.” Environ. Res. Lett. 11 (5): 055007. https://doi.org/10.1088/1748-9326/11/5/055007.
Hassanzadeh, E., A. Nazemi, and A. Elshorbagy. 2014. “Quantile-based downscaling of precipitation using genetic programming: Application to IDF curves in Saskatoon.” J. Hydrol. Eng. 19 (5): 943–955. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000854.
Herman, J. D., P. M. Reed, H. B. Zeff, and G. W. Characklis. 2015. “How should robustness be defined for water systems planning under change?” J. Water Resour. Plann. Manage. 141 (10): 04015012. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000509.
IPCC (Intergovernmental Panel on Climate Change). 2007. Climate change 2007: Impacts, adaptation and vulnerability. Geneva: IPCC.
IPCC (Intergovernmental Panel on Climate Change). 2012. Managing the risks of extreme events and disasters to advance climate change adaptation. Cambridge, UK: Cambridge University Press.
IPCC (Intergovernmental Panel on Climate Change). 2014. Climate change 2014: Synthesis report—Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change. Edited by Core Writing Team, R. K. Pachauri, and L. A. Meyer, 151. Geneva: IPCC.
Kang, D., and K. Lansey. 2013. “Scenario-based robust optimization of regional water and wastewater infrastructure.” J. Water Resour. Plann. Manage. 139 (3): 325–338. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000236.
Kasprzyk, J. R., S. Nataraj, P. M. Reed, and R. J. Lempert. 2013. “Many objective robust decision making for complex environmental systems undergoing change.” Environ. Modell. Software 42 (Apr): 55–71. https://doi.org/10.1016/j.envsoft.2012.12.007.
Kassa, A. M. 2017. “Application of decision making with uncertainty techniques: A case of production volume of maize in Ethiopia.” Int. J. Qual. Res. 11 (2): 331–344. https://doi.org/10.18421/IJQR11.02-06.
Khodakivskyia, O., Y. Khodakivskaa, O. Kuzmenkob, M. Shcherbynaa, and O. Kolesnichenko. 2019. “Improvement of the railway transport system by increasing the level of goal-oriented activity.” Procedia Comput. Sci. 149 (2019): 415–421. https://doi.org/10.1016/j.procs.2019.01.156.
Kim, H. G., D. K. Lee, C. Park, S. Kil, Y. Son, and J. H. Park. 2015. “Evaluating landslide hazards using RCP 4.5 and 8.5 scenarios.” Environ. Earth Sci. 73 (3): 1385–1400. https://doi.org/10.1007/s12665-014-3775-7.
Lau, H. C. W., Z. Jiang, W. H. Ip, and D. Wang. 2010. “A credibility-based fuzzy location model with Hurwicz criteria for the design of distribution systems in B2C e-commerce.” Comput. Ind. Eng. 59 (4): 873–886. https://doi.org/10.1016/j.cie.2010.08.018.
Li, H., J. Sheffield, and E. F. Wood. 2010. “Bias correction of monthly precipitation and temperature fields from intergovernmental panel on climate change AR4 models using equidistant quantile matching.” J. Geophys. Res. 115 (D10): D10101. https://doi.org/10.1029/2009JD012882.
Mailhot, A., and S. Duchesne. 2010. “Design criteria of urban drainage infrastructures under climate change.” J. Water Resour. Plann. Manage. 136 (2): 201–208. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000023.
Maimone, M., S. Malter, J. Rockwell, and V. Raj. 2019. “Transforming global climate model precipitation output for use in urban stormwater applications.” J. Water Resour. Plann. Manage. 145 (6): 04019021. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001071.
Marengo, J. A., R. R. Torres, and L. M. Alves. 2017. “Drought in northeast Brazil—Past, present, and future.” Theor. Appl. Climatol. 129 (3–4): 1189–1200. https://doi.org/10.1007/s00704-016-1840-8.
Maurer, E. P., and H. G. Hidalgo. 2008. “Utility of daily vs. monthly large-scale climate data: An intercomparison of two statistical downscaling methods.” Hydrol. Earth Syst. Sci. 12: 551–563. https://doi.org/10.5194/hess-12-551-2008.
Maurer, E. P., G. Kayser, L. Doyle, and A. W. Wood. 2017. “Adjusting flood peak frequency changes to account for climate change impacts in the western United States.” J. Water Resour. Plann. Manage. 144 (3): 05017025. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000903.
Mavromatidis, G., K. Orehounig, and J. Carmeliet. 2018. “Comparison of alternative decision-making criteria in a two-stage stochastic program for the design of distributed energy systems under uncertainty.” Energy 156 (Aug): 709–724. https://doi.org/10.1016/j.energy.2018.05.081.
Mirhosseini, G., P. Srivastava, and L. Stefanova. 2013. “The impact of climate change on rainfall intensity–duration–frequency (IDF) curves in Alabama.” Supplement, Reg. Environ. Change 13 (S1): 25–33. https://doi.org/10.1007/s10113-012-0375-5.
Mishra, V., A. R. Ganguly, B. Nijssen, and D. P. Lettenmaier. 2015. “Changes in observed climate extremes in global urban areas.” Environ. Res. Lett. 10 (2): 024005. https://doi.org/10.1088/1748-9326/10/2/024005.
Mortazavi-Naeini, M., G. Kuczera, A. S. Kiem, L. Cui, B. Henley, B. Berghout, and E. Turner. 2015. “Robust optimization to secure urban bulk water supply against extreme drought and uncertain climate change.” Environ. Modell. Software 69 (2015): 437–451. https://doi.org/10.1016/j.envsoft.2015.02.021.
Mota, S. 2012. Introdução à engenharia ambiental. 5th ed. Rio de Janeiro: Associação Brasileira de Engenharia Sanitária e Ambiental.
Municipal Secretariat of Urbanism and Environment. 2013. “Diagnosis of drainage conditions of the municipality of Fortaleza.” Accessed February 23, 2016. http://www.fortaleza.ce.gov.br/sites/default/files/drenagem_situacao_de_fortaleza.pdf.
Myhre, G., O. Boucher, F. M. Bréon, P. Forster, and D. Shindell. 2015. “Declining uncertainty in transient climate response as forcing dominates future climate change.” Nat. Geosci. 8 (3): 181–185. https://doi.org/10.1038/ngeo2371.
Phillip, R. 2011. Kit de Treinamento SWITCH: Gestão integrada das águas na cidade do futuro. Módulo 4. Manejo de águas pluviais: Explorando opções. 1st ed., 54. São Paulo, Brazil: ICLEI Brazil.
Phillip, R., B. Anton, and P. V. D. Steen. 2011. Kit de Treinamento SWITCH: Gestão integrada das águas na cidade do futuro. Módulo 1. Planejamento estratégico: Preparando-se para o futuro. 1st ed., 53. São Paulo, Brazil: ICLEI Brazil.
Prein, A. F., R. M. Rasmussen, K. Ikeda, C. Liu, M. P. Clark, and G. J. Holland. 2017. “The future intensification of hourly precipitation extremes.” Nat. Clim. Change 7 (1): 48–52. https://doi.org/10.1038/nclimate3168.
Ragno, E., A. AghaKouchak, C. A. Love, L. Cheng, F. Vahedifard, and C. H. R. Lima. 2018. “Quantifying changes in future intensity-duration-frequency curves using multimodel ensemble simulations.” Water Resour. Res. 54 (3): 1751–1764. https://doi.org/10.1002/2017WR021975.
Sarhadi, A., and E. D. Soulis. 2017. “Time-varying extreme rainfall intensity-duration-frequency curves in a changing climate.” Geophys. Res. Lett. 44 (5): 2454–2463. https://doi.org/10.1002/2016GL072201.
Schardong, A., R. K. Srivastav, and S. P. Simonovic. 2015. Computerized tool for the development of intensity-duration-frequency curves under a changing climate—User’s manual. London: Dept. of Civil and Environmental Engineering, Western Univ.
Scharffenberg, W. A. 2013. Hydrologic modeling system HEC-HMS: User’s manual. Davis, CA: US Army Corps of Engineers, Hydrologic Engineering Center.
Semadeni-Davies, A., C. Hernebring, G. Svensson, and L. Gustafsson. 2008. “The impacts of climate change and urbanisation on drainage in Helsingborg, Sweden: Combined sewer system.” J. Hydrol. 350 (1–2): 100–113. https://doi.org/10.1016/j.jhydrol.2007.05.028.
Silveira, C. S., F. A. Souza Filho, A. A. Costa, and S. L. Cabral. 2013. “Avaliação de desempenho dos modelos do cmip5 quanto à representação dos padrões de variação da precipitação no século xx sobre a região nordeste do brasil, amazônia e bacia da prata e análise das projeções para o cenário rcp8. 5.” Rev. Bras. Meteorol. 28 (3): 317–330. https://doi.org/10.1590/S0102-77862013000300008.
Silveira, C. S., F. A. Souza Filho, E. S. P. R. Martins, J. L. Oliveira, A. C. Costa, M. T. Nobrega, and R. F. V. Silva. 2016. “Mudanças climáticas na bacia do rio São Francisco: Uma análise para precipitação e temperature.” Rev. Bras. Recursos Hídricos 21 (2): 416–428. https://doi.org/10.21168/rbrh.v21n2.p416-428.
Simonovic, S. P., A. Schardong, and D. Sandink. 2016. “Mapping extreme rainfall statistics for Canada under climate change using updated intensity-duration-frequency curves.” J. Water Resour. Plann. Manage. 143 (3): 04016078. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000725.
Srivastav, R. K., A. Schardong, P. Slobodan, and S. P. Simonovic. 2014. “Equidistance quantile matching method for updating IDF curves under climate change.” Water Resour. Manage. 28 (9): 2539–2562. https://doi.org/10.1007/s11269-014-0626-y.
Steenhuis, T. S., M. Winchell, J. Rossing, J. A. Zollweg, and M. F. Walters. 1995. “SCS runoff equation revisited for variable-source runoff areas.” J. Irrig. Drain. Eng. 121 (3): 234–238. https://doi.org/10.1061/(ASCE)0733-9437(1995)121:3(234).
Thakali, R., A. Kalra, and S. Ahmad. 2016. “Understanding the effects of climate change on urban stormwater infrastructures in the Las Vegas Valley.” Hydrology 3 (4): 34. https://doi.org/10.3390/hydrology3040034.
Tucci, C. E. M. 1993. Hidrologia, ciência e aplicação, 4th ed. Porto Alegre, Brazil: Editora da Universidade.
USDA. 1986. Urban hydrology for small watersheds. Washington, DC: USDA Soil Conservation Service.
Van Vuuren, D. P., J. Edmonds, M. Kainuma, K. Riahi, A. Thomson, K. Hibbard, and T. Masui. 2011. “The representative concentration pathways: An overview.” Clim. Change 109 (1–2): 5. https://doi.org/10.1007/s10584-011-0148-z.
Williams, J. R., N. Kannan, X. Wang, C. Santhi, and J. G. Arnold. 2012. “Evolution of the SCS runoff curve number method and its application to continuous runoff simulation.” J. Hydrol. Eng. 17 (11): 1221–1229. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000529.
Yu, B. 2012. “Validation of SCS method for runoff estimation.” J. Hydrol. Eng. 17 (11): 1158–1163. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000484.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 146 • Issue 11 • November 2020
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Dec 22, 2019
Accepted: May 22, 2020
Published online: Aug 27, 2020
Published in print: Nov 1, 2020
Discussion open until: Jan 27, 2021
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.