Variability of Future Extreme Rainfall Statistics: Comparison of Multiple IDF Projections
Publication: Journal of Hydrologic Engineering
Volume 22, Issue 10
Abstract
A variety of potential approaches and data sets can be used to develop future rainfall intensity-duration-frequency (IDF) statistics at the local scale. The aim of this study was to characterize the variability in an ensemble of future IDF curves generated using a combination of five different climate models, three climate change scenarios, and two downscaling methods. These data sets were prepared for six rainfall stations across two local study sites in southern Ontario: the Toronto and Windsor areas. Several distribution functions used in the derivation of IDF curves were also tested and the best-fit, generalized extreme value (GEV), was used during downscaling. For the 2050s, there was statistically significant variability in the direction of change and magnitude among IDF projections at the Toronto Area stations, with some member cases showing increases and decreases in intensity values within the ensemble. At the Windsor stations, there was a statistically significant trend of increasing storm intensity for the future, but variability in the magnitude of change within the ensemble was apparent. In general, variability among IDF projections for both study areas increased with storm intensity. The variability due to the selection of climate model data sets was greater than that arising from spatial variability in extreme rainfall, with downscaling methods and radiative forcing/emission scenarios contributing far less to the variability.
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Acknowledgments
The authors are grateful for the funding support for this work from the County of Essex, the towns of Amherstburg, Essex, Kingsville, LaSalle, and Tecumseh, the cities of Windsor and Toronto, and the regional municipalities of Peel and York. We further acknowledge the contribution of Marc D’Alessandro in assisting with data preparation and analysis. Finally, we acknowledge the feedback of Heather Auld and Neil Comer of Risk Sciences International, Fabio Tonto (TRCA), and members of the Ontario Climate Advisory Committee.
References
Adamowski, K., and Bougadis, J. (2003). “Detection of trends in annual extreme rainfall.” Hydrol. Processes, 17(18), 3547–3560.
Alam, M. S., and Elshorbagy, A. (2015). “Quantification of the climate change-induced variations in intensity-duration–frequency curves in the Canadian Prairies.” J. Hydrol., 527, 990–1005.
Alexander, L. V., et al. (2006). “Global observed changes in daily climate extremes of temperature and precipitation.” J. Geophys. Res. Atmos., 111(D5), 1–22.
Al Mamoon, A., and Rahman, A. (2014). “Uncertainty in design rainfall estimation: A review.” J. Hydrol. Environ. Res., 2(1), 65–75.
Anctil, F., and Rat, A. (2005). “Evaluation of neural network streamflow forecasting on 47 watersheds.” J. Hydrol. Eng., 85–88.
ASCE. (2013). Standard guidelines for the design of urban subsurface drainage, Reston, VA.
Barsugli, J. J., et al. (2013). “The practitioner’s dilemma: How to assess the credibility of downscaled climate projections.” Trans. Am. Geophys. Union, 94(46), 424–425.
Bougadis, J., and Adamowski, K. (2006). “Scaling model of a rainfall intensity-duration-frequency relationship.” Hydrol. Processes, 20(17), 3747–3757.
Bürger, G., Murdock, T. Q., Werner, A. T., Sobie, S. R., and Cannon, A. J. (2012). “Downscaling extremes—An intercomparison of multiple statistical methods for present climate.” J. Clim., 25(12), 4366–4388.
Burn, D. H., Mansour, R., Zhang, K., and Whitfield, P. H. (2011). “Trends and variability in extreme rainfall events in British Columbia.” Can. Water Resour. J., 36(1), 67–82.
Burn, D. H., and Taleghani, A. (2010). “Estimates of changes in design rainfall values for Canada.” Hydrol. Processes, 27(11), 1590–1599.
Ceglar, A., and Kajfež-Bogataj, L. (2012). “Simulation of maize yield in current and changed climatic conditions: Addressing modelling uncertainties and the importance of bias correction in climate model simulations.” Eur. J. Agron., 37(1), 83–95.
Chandra, R., Saha, U., and Mujumdar, P. P. (2015). “Model and parameter uncertainty in IDF relationships under climate change.” Adv. Water Resour., 79(1), 127–139.
Charron, I. (2014). A guidebook on climate scenarios: Using climate information to guide adaptation research and decisions, Ouranos Consortium, Montreal.
Chen, J., Brissette, F. P., Chaumont, D., and Braun, M. (2013). “Finding appropriate bias correction methods in downscaling precipitation for hydrologic impact studies over North America.” Water Resour. Res., 49(7), 4187–4205.
Cheng, C. S., Li, G., Li, Q., and Auld, H. (2010). “A synoptic weather typing approach to simulate daily rainfall and extremes in Ontario, Canada: Potential for climate change projections.” J. Appl. Meteorol. Climatol., 49(5), 845–866.
Cheng, C. S., Li, G., Li, Q., and Auld, H. (2011). “A synoptic weather-typing approach to project future daily rainfall and extremes at local scale in Ontario, Canada.” J. Clim., 24(14), 3667–3685.
Cheng, L., and AghaKouchak, A. (2015). “Nonstationary precipitation intensity-duration–frequency curves for infrastructure design in a changing climate.” Sci. Rep., 4(1), 7093.
Coulibaly, P., Dibike, Y. B., and Anctil, F. (2005). “Downscaling precipitation and temperature with temporal neural networks.” J. Hydrometeorol., 6(4), 483–496.
Coulibaly, P., and Shi, X. (2005). “Identification of the effect of climate change on future design standards of drainage infrastructure in Ontario.”, Ministry of Transportation of Ontario, Hamilton, Canada.
CSA (Canadian Standards Association). (2012a). Development, interpretation, and use of rainfall intensity-duration-frequency (IDF) information: Guideline for Canadian water resources practitioners, Missussauga, ON.
CSA (Canadian Standards Association). (2012b). “Technical Guide—Development, interpretation and use of rainfall intensity-duration-frequency (IDF) information: Guideline for Canadian water resources practitioners.”, Mississauga, ON, Canada.
Das, S., Millington, N., and Simonovic, S. P. (2013). “Distribution choice for the assessment of design rainfall for the city of London (Ontario, Canada) under climate change.” Can. J. Civil Eng., 40(2), 121–129.
Environment and Climate Change Canada (ECCC). (2015). “Technical documentation, digital archive of Canadian climatological data.” <ftp://ftp.tor.ec.gc.ca/Pub/Documentation_Technical/Technical_Documentation.pdf> (Feb. 27, 2015).
Eum, H. I., and Simonovic, S. P. (2012). “Assessment on variability of extreme climate events for the Upper Thames River basin in Canada.” Hydrol. Processes, 26(4), 485–499.
Flato, G., et al. (2013). “Evaluation of climate models.” Climate change 2013—The physical science basis, Cambridge University Press, Cambridge, U.K., 741–866.
Fung, F., et al. (2013). “Using large climate ensembles to plan for the hydrological impact of climate change in the freshwater environment.” Water Resour. Manage., 27(4), 1063–1084.
Hassanzadeh, E., Nazemi, A., and Elshorbagy, A. (2013). “Quantile-based downscaling of precipitation using genetic programming: Application to IDF curves in Saskatoon.” J. Hydrol. Eng., 943–955.
Hershfield, D. M. (1961). “Rainfall frequency atlas of the United States for durations from 30 minutes to 24 hours and return periods from 1 to 100 years.”, U.S. Weather Bureau, Washington, DC.
Huff, F. A., and Angel, J. R. (1992). “Rainfall frequency atlas of the Midwest.”, Midwestern Climate Center and Illinois State Water Service, Champaign, IL, 5–6.
Hydrological Atlas of Canada. (1978). Fisheries and environment Canada, Ottawa.
Ines, A. V. M., and Hansen, J. W. (2006). “Bias correction of daily GCM rainfall for crop simulation studies.” Agric. For. Meteorol., 138(1), 44–53.
IPCC (Intergovernmental Panel on Climate Change). (2007). “Climate change 2007: The physical science basis.” Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change, S. Solomon, et al., eds., Cambridge University Press, Cambridge, U.K.
IPCC (Intergovernmental Panel on Climate Change). (2014). “Summary for policy makers.” Climate change 2014: Impacts, adaptation and vulnerability—Contributions of the working group II to the fifth assessment report, Cambridge University Press, U.K., 1–32.
Jakob, T. M., Gobiet, A., and Leuprecht, A. (2011). “Empirical-statistical downscaling and error correction of daily precipitation from regional climate models.” Int. J. Climatol., 31(10), 1530–1544.
Kendon, E. J., et al. (2016). “Do convection-permitting regional climate models improve projections of future precipitation change?” Bull. Am. Meteorol. Soc., 98(1), 79–93.
Khan, M. S., and Coulibaly, P. (2010). “Assessing hydrologic impact of climate change with uncertainty estimates: Bayesian neural network approach.” J. Hydrometeorol., 11(2), 482–495.
Kharin, V. V., Zwiers, F. W., Zhang, X., and Wehner, M. (2013). “Changes in temperature and precipitation extremes in the CMIP5 ensemble.” Clim. Change, 119(2), 345–357.
Koutroulis, A. G., Tsanis, I. K., Daliakopoulos, I. N., and Jacob, D. (2013). “Impact of climate change on water resources status: A case study for Crete Island, Greece.” J. Hydrol., 479(4), 146–158.
Kuiper, R. M., Hoijtink, H., and Silvapulle, M. J. (2011). “An Akaike-type information criterion for model selection under inequality constraints.” Biometrika, 98(2), 495–501.
Kuo, C. C., and Gan, T. Y. (2015). “Risk of exceeding extreme design storm events under possible impact of climate change.” J. Hydrol. Eng., 04015038.
Kuo, C. C., Jahan, N., Gizaw, M. S., Gan, T. Y., and Chan, S. (2013). “The climate change impact on future IDF curves in central Alberta.” Proc., Engineering Institute of Canada (EIC) Climate Change Technology Conf., Vol. 2729, Concordia Univ., Montreal, Canada.
Lafon, T., and Dadson, S. (2013). “Bias correction of daily precipitation simulated by a regional climate model: A comparison of methods.” Int. J. Climatol., 33(6), 1367–1381.
Liu, C., et al. (2016). “Continental-scale convection-permitting modeling of the current and future climate of North America.” Clim. Dyn., 49(1–2), 71–95.
Mailhot, A., Duchesne, S., Caya, D., and Talbot, G. (2007). “Assessment of future change in intensity-duration-frequency (IDF) curves for Southern Quebec using the Canadian Regional Climate Model (CRCM).” J. Hydrol., 347(1–2), 197–210.
Mamo, T. G. (2015). “Evaluation of the potential impact of rainfall intensity variation due to climate change on existing drainage infrastructure.” J. Irrig. Drain. Eng., 05015002.
MATLAB [Computer software]. MathWorks, Natick, MA.
Meylan, P., Favre, A. C., and Musy, A. (2012). Predictive hydrology: A frequency analysis approach, CRC Press, Boca Raton, FL.
Milly, P. C. D., et al. (2008). “Stationarity is dead: Whither water management?” Science, 319(5863), 573–574.
Mirhosseini, G., Srivastava, P., and Fang, X. (2014). “Developing rainfall intensity-duration-frequency (IDF) curves for Alabama under future climate scenarios using artificial neural network (ANN).” J. Hydrol. Eng., 04014022.
Moglen, G. E., and Vidal, G. E. R. (2014). “Climate change and stormwater infrastructure in the U.S. mid-Atlantic region: A design mismatch coming?” J. Hydrol. Eng., 04014026.
Nguyen, V., Desramaut, N., and Nguyen, T. (2008). “Estimation of design storms in consideration of climate variability and change.” Proc., 11 Int. Conf. on Urban Drainage, International Association of Hydro-Environmental Engineering Research/International Water Association, Edinburgh, Scotland, 1–10.
Olsson, J. (2012). “Seventh framework programme project: 247708—SUDPLAN project, sustainable urban development planner for climate change adaptation.”.
Olsson, J., Gidhagen, L., and Gamerith, V. (2012). “Downscaling of short-term precipitation from regional climate models for sustainable urban planning.” Sustainability, 4(12), 866–887.
Olsson, J., Gidhagen, L., and Kawamura, A. (2011). “Downscaling of short-term precipitation time series 2 downscaling method: Delta change.” Int. Symp. on Environmental Software Systems, Int. Federation for Information Processing, Springer, Berlin, 625–630.
Opere, A. O., Awuor, V. O., Kooke, S. O., and Omoto, W. O. (2006). “Rainfall characteristics as an indicator of drought in semi-arid Kitui district of Kenya.” Discovery Innovation, 18(3), 235–245.
Paixao, E., Auld, H., and Mirza, M. M. Q. (2011). “Regionalization of heavy rainfall to improve climatic design values for infrastructure: Case study in southern Ontario, Canada.” Hydrol. Sci. J., 56(7), 1067–1089.
Peck, A., Prodanovic, P., and Simonovic, S. P. (2012). “Rainfall intensity duration frequency curves under climate change: city of London, Ontario, Canada.” Can. Water Resour. J., 37(3), 177–189.
Piani, C., Weedon, G. P., and Best, M. (2010). “Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models.” J. Hydrol., 395(3), 199–215.
Prein, A. F., Rasmussen, R. M., Ikeda, K., Liu, C., Clark, M. P., and Holland, G. J. (2016). “The future intensification of hourly precipitation extremes.” Nat. Clim. Change., 7(1), 48–52.
Samuel, J., Coulibaly, P., and Metcalfe, R. A. (2012). “Evaluation of future flow variability in ungauged basins: Validation of combined methods.” Adv. Water Resour., 35, 121–140.
Schardong, A., Srivastav, R. K., and Simonovic, S. P. (2015). “Computerized tool for the development of intensity-duration-frequency curves under a changing climate—Users manual.” Dept. of Civil and Environmental Engineering, Western Univ., London.
SENES Consultants Ltd. (2011). Toronto’s future weather and climate driver study: Volume 1—Overview, Toronto.
Serinaldi, F., and Kilsby, C. G. (2015). “Stationarity is undead: Uncertainty dominates the distribution of extremes.” Adv. Water Resour., 77, 17–36.
Shardong, S., and Simonovic, S. (2015). User’s Manual: A web-based intensity-duration-frequency tool, Western Univ., London, Canada.
Sharma, M., Coulibaly, P., and Dibike, Y. (2011). “Assessing the need for downscaling RCM data for hydrologic impact study.” J. Hydrol. Eng., 746–759.
Sheffield, J., et al. (2013). “North American climate in CMIP5 experiments. I: Evaluation of historical simulations of continental and regional climatology.” J. Clim., 26(23), 9209–9245.
Shephard, M. W., et al. (2014). “Trends in Canadian short-duration extreme rainfall: Including an intensity-duration–frequency perspective.” Atmos. Ocean, 52(5), 398–417.
Sillmann, J., et al. (2013). “Climate extremes indices in the CMIP5 multimodel ensemble. Part 1: Model evaluation in the present climate.” J. Geophys. Res. Atmos., 118(4), 1716–1733.
Solaiman, T. A., and Simonovic, S. P. (2011). “Quantifying uncertainties in the modelled estimates of extreme precipitation events at the Upper Thames River basin.”, Univ. of Western Ontario, London.
Srivastav, R. K., Schardong, A., and Simonovic, S. P. (2014). “Equidistance quantile matching method for updating IDF curves under climate change.” Water Resour. Manage., 28(9), 2539–2562.
SUDPLAN. (2017). “Adaptation to climate change.” <http://sudplan.eu/> (Feb. 21, 2017).
Symonds, M. R., and Moussalli, A. (2011). “A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike’s information criterion.” Behav. Ecol. Sociobiol., 65(1), 13–21.
Taylor, K. E., Stouffer, R. J., and Meehl, G. (2012). “An overview of CMIP5 and the experiment design.” Bull. Am. Meteorolog. Soc., 93(4), 485–498.
Teegavarapu, R. S. V., Behara, P., and Goly, A. (2013). “Assessment of influences of climate variability on storm event characteristics.” Proc., World Environmental and Water Resources Congress 2013: Showcasing the Future, ASCE, Reston, VA, 1077–1085.
Teutschbein, C., and Seibert, J. (2012). “Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods.” J. Hydrol., 456–457, 12–29.
Thober, S., and Samaniego, L. (2014). “Robust ensemble selection by multivariate evaluation of extreme precipitation and temperature characteristics.” J. Geophys. Res. Atmos., 119(2), 594–613.
Vavrus, S., and Van Dorn, J. (2010). “Projected future temperature and precipitation extremes in Chicago.” J. Great Lakes Res., 36(SP2), 22–32.
Wang, J., and Zhang, X. (2008). “Downscaling and projection of winter extreme daily precipitation over North America.” J. Clim., 21(5), 923–937.
Wang, S., and Huang, G. H. (2015). “A multi-level Taguchi-factorial two-stage stochastic programming approach for characterization of parameter uncertainties and their interactions: An application to water resources management.” Eur. J. Oper. Res., 240(2), 572–581.
Wang, X., Huang, G., Lin, Q., and Liu, J. (2014). “High-resolution probabilistic projections of temperature changes over Ontario, Canada.” J. Clim., 27(14), 5259–5284.
Weigel, A. P., Knutti, R., Liniger, M. A., and Appenzeller, C. (2010). “Risks of model weighting in multimodel climate projections.” J. Clim., 23(15), 4175–4191.
Westra, S., et al. (2014). “Future changes to the intensity and frequency of short-duration extreme rainfall.” Rev. Geophys., 52(3), 522–555.
Wetterhall, F., Graham, L. P., Andreasson, J., Rosberg, J., and Yang, W. (2011). “Using ensemble climate projections to assess probabilistic hydrological change in the Nordic region.” Nat. Hazard. Earth Syst. Sci., 11(8), 2295–2306.
Wilby, R. L., Dawson, C. W., Murphy, C., O’Connor, P., and Hawkins, E. (2014). “The statistical downscaling model-decision centric (SDSM-DC): Conceptual basis and applications.” Clim. Res., 61(3), 259–276.
Wilby, R. L., and Dessai, S. (2010). “Robust adaptation to climate change.” Weather, 65(7), 180–185.
Willems, P. (2013). “Revision of urban drainage design rules after assessment of climate change impacts on precipitation extremes at Uccle, Belgium.” J. Hydrol., 496, 166–177.
Zhu, J. (2013). “Impact of climate change on extreme rainfall across the United States.” J. Hydrol. Eng., 1301–1309.
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Journal of Hydrologic Engineering
Volume 22 • Issue 10 • October 2017
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© 2017 American Society of Civil Engineers.
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Received: Apr 14, 2016
Accepted: Apr 11, 2017
Published online: Aug 4, 2017
Published in print: Oct 1, 2017
Discussion open until: Jan 4, 2018
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