Articles | Volume 29, issue 21 
            
                
                    
            
            
            https://doi.org/10.5194/hess-29-5851-2025
                    © Author(s) 2025. This work is distributed under 
the Creative Commons Attribution 4.0 License.
                the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-5851-2025
                    © Author(s) 2025. This work is distributed under 
the Creative Commons Attribution 4.0 License.
                the Creative Commons Attribution 4.0 License.
The impact of climate change on dam overtopping floods in Australia
                                            Department of Infrastructure Engineering, The University of Melbourne, Melbourne, 3010, Australia
                                        
                                    Declan O'Shea
                                            Department of Infrastructure Engineering, The University of Melbourne, Melbourne, 3010, Australia
                                        
                                    
                                            HARC-Hydrology and Risk Consulting, Melbourne, 3130, Australia
                                        
                                    Conrad Wasko
                                            School of Civil Engineering, The University of Sydney, Sydney, 2050, Australia
                                        
                                    Rory Nathan
                                            Department of Infrastructure Engineering, The University of Melbourne, Melbourne, 3010, Australia
                                        
                                    Ashish Sharma
                                            School of Civil and Environmental Engineering, The University of New South Wales, Sydney, 2052, Australia
                                        
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                                        Cited articles
                        
                        Ahmadisharaf, E. and Kalyanapu, A. J.: Investigation of the Impact of Streamflow Temporal Variation on Dam Overtopping Risk: Case Study of a High-Hazard Dam, in: World Environmental and Water Resources Congress 2015, 1050–1057, https://doi.org/10.1061/9780784479162.103, 2015. 
                    
                
                        
                        Ali, H., Fowler, H. J., Lenderink, G., Lewis, E., and Pritchard, D.: Consistent Large-Scale Response of Hourly Extreme Precipitation to Temperature Variation Over Land, Geophysical Research Letters, 48, e2020GL090317, https://doi.org/10.1029/2020GL090317, 2021. 
                    
                
                        
                        Allan, R. P. and Soden, B. J.: Atmospheric Warming and the Amplification of Precipitation Extremes, Science, 321, 1481–1484, https://doi.org/10.1126/science.1160787, 2008. 
                    
                
                        
                        Ball, J., Babister, M., Nathan, R., Weeks, W., Weinmann, E., Retallick, M., and Testoni, I. (Eds.): Australian Rainfall and Runoff: A Guide to Flood Estimation, Commonwealth of Australia (Geoscience Australia), ISBN 978-1-925848-36-6, 2019. 
                    
                
                        
                        Barnett, T. P., Pierce, D. W., Hidalgo, H. G., Bonfils, C., Santer, B. D., Das, T., Bala, G., Wood, A. W., Nozawa, T., Mirin, A. A., Cayan, D. R., and Dettinger, M. D.: Human-Induced Changes in the Hydrology of the Western United States, Science, 319, 1080–1083, https://doi.org/10.1126/science.1152538, 2008. 
                    
                
                        
                        Bates, B., Kundzewicz, Z. W., and IPCC (Eds.): Climate change and water, 200 pp., ISBN 978-92-9169-123-4, 2008. 
                    
                
                        
                        Boulange, J., Hanasaki, N., Yamazaki, D., and Pokhrel, Y.: Role of dams in reducing global flood exposure under climate change, Nature Communications, 12, 417, https://doi.org/10.1038/s41467-020-20704-0, 2021. 
                    
                
                        
                        Bureau of Meteorology: Guidebook to the Estimation of Probable Maximum Precipitation: Generalised Southeast Australia Method, Bureau of Meteorology, 2006. 
                    
                
                        
                        Chan, S. C., Kendon, E. J., Roberts, N. M., Fowler, H. J., and Blenkinsop, S.: Downturn in scaling of UK extreme rainfall with temperature for future hottest days, Nature Geoscience, 9, 24–28, https://doi.org/10.1038/ngeo2596, 2016. 
                    
                
                        
                        Chang, W., Stein, M. L., Wang, J., Kotamarthi, V. R., and Moyer, E. J.: Changes in Spatiotemporal Precipitation Patterns in Changing Climate Conditions, Journal of Climate, 29, 8355–8376, https://doi.org/10.1175/JCLI-D-15-0844.1, 2016. 
                    
                
                        
                        Chevuturi, A., Klingaman, N. P., Turner, A. G., and Hannah, S.: Projected Changes in the Asian-Australian Monsoon Region in 1.5 °C and 2.0 °C Global-Warming Scenarios, Earth's Future, 6, 339–358, https://doi.org/10.1002/2017EF000734, 2018. 
                    
                
                        
                        Cho, E., Ahmadisharaf, E., Ahmadisharaf, A., Nematirad, R., and AghaKouchak, A.: Unraveling the Relationships between Trend of Dam Inflows, Hydrometeorological Variables, and Vegetation in Western and Southwestern United States, Journal of Hydrometeorology, 25, 1793–1808, https://doi.org/10.1175/JHM-D-23-0217.1, 2024. 
                    
                
                        
                        Cho, E., Ahmadisharaf, E., Villarini, G., and AghaKouchak, A.: Historical changes in overtopping probability of dams in the United States, Nature Communications, 16, 6693, https://doi.org/10.1038/s41467-025-59536-1, 2025. 
                    
                
                        
                        Doss-Gollin, J., Farnham, D. J., Ho, M., and Lall, U.: Adaptation over Fatalism: Leveraging High-Impact Climate Disasters to Boost Societal Resilience, Journal of Water Resources Planning and Management, 146, 01820001, https://doi.org/10.1061/(ASCE)WR.1943-5452.0001190, 2020. 
                    
                
                        
                        Dykman, C., Sharma, A., Wasko, C., and Nathan, R.: Pyraingen: A python package for constrained continuous rainfall generation, Environmental Modelling & Software, 175, 105984, https://doi.org/10.1016/j.envsoft.2024.105984, 2024. 
                    
                
                        
                        Emori, S. and Brown, S. J.: Dynamic and thermodynamic changes in mean and extreme precipitation under changed climate, Geophysical Research Letters, 32, https://doi.org/10.1029/2005GL023272, 2005. 
                    
                
                        
                        Faulkner, D., Warren, S., Spencer, P., and Sharkey, P.: Can we still predict the future from the past? Implementing non-stationary flood frequency analysis in the UK, Journal of Flood Risk Management, 13, e12582, https://doi.org/10.1111/jfr3.12582, 2020. 
                    
                
                        
                        Ferdowsi, A., Zolghadr-Asli, B., and AghaKouchak, A.: Dangers of aging water infrastructure, Science, 386, 158–158, https://doi.org/10.1126/science.adr1054, 2024. 
                    
                
                        
                        Filipova, V., Lawrence, D., and Skaugen, T.: A stochastic event-based approach for flood estimation in catchments with mixed rainfall and snowmelt flood regimes, Nat. Hazards Earth Syst. Sci., 19, 1–18, https://doi.org/10.5194/nhess-19-1-2019, 2019. 
                    
                
                        
                        Fluixá-Sanmartín, J., Altarejos-García, L., Morales-Torres, A., and Escuder-Bueno, I.: Review article: Climate change impacts on dam safety, Nat. Hazards Earth Syst. Sci., 18, 2471–2488, https://doi.org/10.5194/nhess-18-2471-2018, 2018. 
                    
                
                        
                        Fluixá-Sanmartín, J., Escuder-Bueno, I., Morales-Torres, A., and Castillo-Rodríguez, J. T.: Accounting for Climate Change Uncertainty in Long-Term Dam Risk Management, Journal of Water Resources Planning and Management, 147, 04021012, https://doi.org/10.1061/(ASCE)WR.1943-5452.0001355, 2021. 
                    
                
                        
                        France, J. W., Alvi, I. A., Dickson, P. A., Falvey, H. T., Rigbey, S. J., and Trojanowski, J.: Independent Forensic Team Report Oroville Dam Spillway Incident, 2018. 
                    
                
                        
                        Fyfe, J., Fox-Kemper, B., Kopp, R., and Garner, G.: Summary for Policymakers of the Working Group I Contribution to the IPCC Sixth Assessment Report – data for Figure SPM.8 (v20210809), https://doi.org/10.5285/98af2184e13e4b91893ab72f301790db, 2021. 
                    
                
                        
                        Garg, S. and Mishra, V.: Role of Extreme Precipitation and Initial Hydrologic Conditions on Floods in Godavari River Basin, India, Water Resources Research, 55, 9191–9210, https://doi.org/10.1029/2019WR025863, 2019. 
                    
                
                        
                        Ghanghas, A., Sharma, A., Dey, S., and Merwade, V.: How Is Spatial Homogeneity in Precipitation Extremes Changing Globally?, Geophysical Research Letters, 50, e2023GL103233, https://doi.org/10.1029/2023GL103233, 2023. 
                    
                
                        
                        Ghanghas, A., Sharma, A., and Merwade, V.: Unveiling the Evolution of Extreme Rainfall Storm Structure Across Space and Time in a Warming Climate, Earth's Future, 12, e2024EF004675, https://doi.org/10.1029/2024EF004675, 2024. 
                    
                
                        
                        Gourevitch, J. D., Kousky, C., Liao, Y. (Penny), Nolte, C., Pollack, A. B., Porter, J. R., and Weill, J. A.: Unpriced climate risk and the potential consequences of overvaluation in US housing markets, Nature Climate Change, 13, 250–257, https://doi.org/10.1038/s41558-023-01594-8, 2023. 
                    
                
                        
                        Graham, N. E.: Simulation of Recent Global Temperature Trends, Science, 267, 666–671, https://doi.org/10.1126/science.267.5198.666, 1995. 
                    
                
                        
                        Green, J., Walland, D., Nandakumar, N., and Nathan, R.: Temporal patterns for the derivation of PMPDF and PMF estimates in the GTSM region of Australia, Australasian Journal of Water Resources, 8, 111–121, https://doi.org/10.1080/13241583.2005.11465248, 2005. 
                    
                
                        
                        Green, J., Johnson, F., Beesley, C., and The, C.: Book 2: rainfall estimation, Chapter 3: design rainfall, in: Australian Rainfall and Runoff: A Guide to Flood Estimation, edited by: Ball, J., Babister, M., Nathan, R., Weeks, W., Weinmann, E., and Testoni, I., Commonwealth of Australia (Geoscience Australia), ISBN 978-1-925848-36-6, 2019. 
                    
                
                        
                        Gutiérrez, J. M., Jones, R. G., Narisma, G. T., Alves, L. M., Amjad, M., Gorodetskaya, I. V., Grose, M., Klutse, N. A. B., Krakovska, S., Li, J., Martínez-Castro, D., Mearns, L. O., Mernild, S. H., Ngo-Duc, T., van den Hurk, B., and Yoon, J.-H.: Atlas, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1927–2058, https://doi.org/10.1017/9781009157896.021, 2021. 
                    
                
                        
                        Haan, C. T.: Statistical methods in hydrology, 2nd edn., Iowa State Press, Ames, Iowa, ISBN 0-8138-1503-7, 1974. 
                    
                
                        
                        Hakala, K., Addor, N., Teutschbein, C., Vis, M., Dakhlaoui, H., and Seibert, J.: Hydrological Modeling of Climate Change Impacts, in: Encyclopedia of Water, 1–20, https://doi.org/10.1002/9781119300762.wsts0062, 2019. 
                    
                
                        
                        Hardwick Jones, R., Westra, S., and Sharma, A.: Observed relationships between extreme sub-daily precipitation, surface temperature, and relative humidity, Geophysical Research Letters, 37, https://doi.org/10.1029/2010GL045081, 2010. 
                    
                
                        
                        Herath, S. M., Sarukkalige, R., and Nguyen, V. T. V.: Evaluation of empirical relationships between extreme rainfall and daily maximum temperature in Australia, Journal of Hydrology, 556, 1171–1181, https://doi.org/10.1016/j.jhydrol.2017.01.060, 2018. 
                    
                
                        
                        Hershfield, D. M.: Method for Estimating Probable Maximum Rainfall, Journal AWWA, 57, 965–972, https://doi.org/10.1002/j.1551-8833.1965.tb01486.x, 1965. 
                    
                
                        
                        Hill, P. and Thomson, R.: Chapter 3. Losses, in: Book 5 Flood Hydrograph Estimation, edited by: Ball, J., Babister, M., Nathan, R., Weeks, W., Weinmann, E., Retallick, M., and Testoni, I., ISBN 978-1-925848-36-6, 2019. 
                    
                
                        
                        Hill, P., Graszkiewicz, Z., Taylor, M., and Nathan, R.: Australian Rainfall and Runoff Revision Project 6: Loss models for catchment simulation: Phase 4 analysis of rural catchments, 2014. 
                    
                
                        
                        Ho, M., Lall, U., Allaire, M., Devineni, N., Kwon, H. H., Pal, I., Raff, D., and Wegner, D.: The future role of dams in the United States of America, Water Resources Research, 53, 982–998, https://doi.org/10.1002/2016WR019905, 2017. 
                    
                
                        
                        Ho, M., Nathan, R., Wasko, C., Vogel, E., and Sharma, A.: Projecting changes in flood event runoff coefficients under climate change, Journal of Hydrology, 615, 128689, https://doi.org/10.1016/j.jhydrol.2022.128689, 2022. 
                    
                
                        
                        Ho, M., Wasko, C., O'Shea, D., Nathan, R., Vogel, E., and Sharma, A.: Changes in flood-associated rainfall losses under climate change, Journal of Hydrology, 625, 129950, https://doi.org/10.1016/j.jhydrol.2023.129950, 2023. 
                    
                
                        
                        Hsu, Y.-C., Tung, Y.-K., and Kuo, J.-T.: Evaluation of dam overtopping probability induced by flood and wind, Stoch. Environ. Res. Risk Assess., 25, 35–49, https://doi.org/10.1007/s00477-010-0435-7, 2011. 
                    
                
                        
                        Hwang, J. and Lall, U.: Increasing dam failure risk in the USA due to compound rainfall clusters as climate changes, npj Natural Hazards, 1, 27, https://doi.org/10.1038/s44304-024-00027-6, 2024. 
                    
                
                        
                        ICOLD: ICOLD Constitution, 2011. 
                    
                
                        
                        IPCC: Climate Change 2021: The Physical Science Basis, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Pean, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekci, O., Yu, R., and Zhou, B., Cambridge University Press, https://doi.org/10.1017/9781009157896.001, 2021a. 
                    
                
                        
                        IPCC: Summary for Policymakers, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzel, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 3–32, https://doi.org/10.1017/9781009157896.001, 2021b. 
                    
                
                        
                        Ivancic, T. J. and Shaw, S. B.: Examining why trends in very heavy precipitation should not be mistaken for trends in very high river discharge, Climatic Change, 133, 681–693, https://doi.org/10.1007/s10584-015-1476-1, 2015. 
                    
                
                        
                        Jakob, D., Smalley, R., Meighen, J., Xuereb, K., and Taylor, B.: Climate change and probable maximum precipitation, Bureau of Meteorology, Melbourne, 2009. 
                    
                
                        
                        Jayaweera, L., Wasko, C., Nathan, R., and Johnson, F.: Non-stationarity in extreme rainfalls across Australia, Journal of Hydrology, 624, 129872, https://doi.org/10.1016/j.jhydrol.2023.129872, 2023. 
                    
                
                        
                        Jayaweera, L., Wasko, C., and Nathan, R.: Modelling non-stationarity in extreme rainfall using large-scale climate drivers, Journal of Hydrology, 636, 131309, https://doi.org/10.1016/j.jhydrol.2024.131309, 2024. 
                    
                
                        
                        Ju, J., Wu, C., Yeh, P. J.-F., Dai, H., and Hu, B. X.: Global precipitation-related extremes at 1.5 °C and 2 °C of global warming targets: Projection and uncertainty assessment based on the CESM-LWR experiment, Atmospheric Research, 264, 105868, https://doi.org/10.1016/j.atmosres.2021.105868, 2021. 
                    
                
                        
                        Kao, S.-C., DeNeale, S. T., and Watson, D. B.: Hurricane Harvey Highlights: Need to Assess the Adequacy of Probable Maximum Precipitation Estimation Methods, Journal of Hydrologic Engineering, 24, 05019005, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001768, 2019. 
                    
                
                        
                        Kiem, A. S. and Austin, E. K.: Disconnect between science and end-users as a barrier to climate change adaptation, Climate Research, 58, 29–41, https://doi.org/10.3354/cr01181, 2013. 
                    
                
                        
                        Kiem, A. S., Franks, S. W., and Kuczera, G.: Multi-decadal variability of flood risk, Geophysical Research Letters, 30, https://doi.org/10.1029/2002GL015992, 2003. 
                    
                
                        
                        Kim, S., Sharma, A., Wasko, C., and Nathan, R.: Linking Total Precipitable Water to Precipitation Extremes Globally, Earth's Future, 10, e2021EF002473, https://doi.org/10.1029/2021EF002473, 2022. 
                    
                
                        
                        Kim, S., Wasko, C., Sharma, A., and Nathan, R.: The role of regional water vapor dynamics in creating precipitation extremes, Journal of Hydrology X, 24, 100181, https://doi.org/10.1016/j.hydroa.2024.100181, 2024. 
                    
                
                        
                        Kuczera, G., Lambert, M., Heneker, T., Jennings, S., Frost, A., and Coombes, P.: Joint probability and design storms at the crossroads, Australasian Journal of Water Resources, 10, 63–79, https://doi.org/10.1080/13241583.2006.11465282, 2006. 
                    
                
                        
                        Kundzewicz, Z. W., Kanae, S., Seneviratne, S. I., Handmer, J., Nicholls, N., Peduzzi, P., Mechler, R., Bouwer, L. M., Arnell, N., Mach, K., Muir-Wood, R., Brakenridge, G. R., Kron, W., Benito, G., Honda, Y., Takahashi, K., and Sherstyukov, B.: Flood risk and climate change: global and regional perspectives, Hydrological Sciences Journal, 59, 1–28, https://doi.org/10.1080/02626667.2013.857411, 2014. 
                    
                
                        
                        Kunkel, K. E., Karl, T. R., Easterling, D. R., Redmond, K., Young, J., Yin, X., and Hennon, P.: Probable maximum precipitation and climate change, Geophysical Research Letters, 40, 1402–1408, https://doi.org/10.1002/grl.50334, 2013. 
                    
                
                        
                        Kunkel, K. E., Schlef, K., Brown, C., François, B., Demissie, Y., Yan, E., Lettenmaier, D. P., Wang, K. J., Wagner, A., Wigmosta, M. S., Karl, T. R., and Easterling, D. R.: Best Practices for Incorporating Non-stationarity in Extreme Precipitation and Flooding Design Values, Virginia, US, report no. RC-2517, 2020. 
                    
                
                        
                        Kuo, J.-T., Yen, B.-C., Hsu, Y.-C., and Lin, H.-F.: Risk Analysis for Dam Overtopping – Feitsui Reservoir as a Case Study, Journal of Hydraulic Engineering, 133, 955–963, https://doi.org/10.1061/(ASCE)0733-9429(2007)133:8(955), 2007. 
                    
                
                        
                        Kwon, H.-H. and Moon, Y.-I.: Improvement of overtopping risk evaluations using probabilistic concepts for existing dams, Stochastic Environmental Research and Risk Assessment, 20, 223–237, https://doi.org/10.1007/s00477-005-0017-2, 2006. 
                    
                
                        
                        Laurenson, E. M.: A catchment storage model for runoff routing, Journal of Hydrology, 2, 141–163, https://doi.org/10.1016/0022-1694(64)90025-3, 1964. 
                    
                
                        
                        Laurenson, E. M., Mein, R. G., and Nathan, R. J.: RORB version 6 runoff routing program – User manual, 2010. 
                    
                
                        
                        Lave, T. R. and Lave, L. B.: Public Perception of the Risks of Floods: Implications for Communication, Risk Analysis, 11, 255–267, https://doi.org/10.1111/j.1539-6924.1991.tb00602.x, 1991. 
                    
                
                        
                        Lee, B.-S. and You, G. J.-Y.: An assessment of long-term overtopping risk and optimal termination time of dam under climate change, Journal of Environmental Management, 121, 57–71, https://doi.org/10.1016/j.jenvman.2013.02.025, 2013. 
                    
                
                        
                        Lochbihler, K., Lenderink, G., and Siebesma, A. P.: The spatial extent of rainfall events and its relation to precipitation scaling, Geophysical Research Letters, 44, 8629–8636, https://doi.org/10.1002/2017GL074857, 2017. 
                    
                
                        
                        Lompi, M., Mediero, L., Soriano, E., and Caporali, E.: Climate change and hydrological dam safety: a stochastic methodology based on climate projections, Hydrological Sciences Journal, 68, 745–763, https://doi.org/10.1080/02626667.2023.2192873, 2023. 
                    
                
                        
                        Madani, K. and Lund, J. R.: Estimated impacts of climate warming on California's high-elevation hydropower, Climatic Change, 102, 521–538, https://doi.org/10.1007/s10584-009-9750-8, 2010. 
                    
                
                        
                        Magan, B., Kim, S., Wasko, C., Barbero, R., Moron, V., Nathan, R., and Sharma, A.: Impact of atmospheric circulation on the rainfall-temperature relationship in Australia, Environmental Research Letters, 15, 094098, https://doi.org/10.1088/1748-9326/abab35, 2020. 
                    
                
                        
                        Malakar, Y., Snow, S., Fleming, A., Fielke, S., Jakku, E., Tozer, C., and Darbyshire, R.: Multi-decadal climate services help farmers assess and manage future risks, Nature Climate Change, 14, 586–591, https://doi.org/10.1038/s41558-024-02021-2, 2024. 
                    
                
                        
                        Malerba, M. E., Wright, N., and Macreadie, P. I.: Australian farm dams are becoming less reliable water sources under climate change, Science of The Total Environment, 829, 154360, https://doi.org/10.1016/j.scitotenv.2022.154360, 2022. 
                    
                
                        
                        Massari, C., Pellet, V., Tramblay, Y., Crow, W. T., Gründemann, G. J., Hascoetf, T., Penna, D., Modanesi, S., Brocca, L., Camici, S., and Marra, F.: On the relation between antecedent basin conditions and runoff coefficient for European floods, Journal of Hydrology, 130012, https://doi.org/10.1016/j.jhydrol.2023.130012, 2023. 
                    
                
                        
                        Matalas, N. C.: Stochastic Hydrology in the Context of Climate Change, Climatic Change, 37, 89–101, https://doi.org/10.1023/A:1005374000318, 1997. 
                    
                
                        
                        Mein, R. G., Laurenson, E. M., and McMahon, T. A.: Simple Nonlinear Model for Flood Estimation, Journal of the Hydraulics Division, 100, 1507–1518, https://doi.org/10.1061/JYCEAJ.0004101, 1974. 
                    
                
                        
                        Micevski, T., Franks, S. W., and Kuczera, G.: Multidecadal variability in coastal eastern Australian flood data, Journal of Hydrology, 327, 219–225, https://doi.org/10.1016/j.jhydrol.2005.11.017, 2006. 
                    
                
                        
                        Michailidi, E. M. and Bacchi, B.: Dealing with uncertainty in the probability of overtopping of a flood mitigation dam, Hydrol. Earth Syst. Sci., 21, 2497–2507, https://doi.org/10.5194/hess-21-2497-2017, 2017. 
                    
                
                        
                        Mitchell, J. F. B.: The “Greenhouse” effect and climate change, Reviews of Geophysics, 27, 115–139, https://doi.org/10.1029/RG027i001p00115, 1989. 
                    
                
                        
                        Nathan, R. and Weinmann, E.: Book 8 Very Rare to Extreme Flood Estimation, in: Book 8 Very Rare to Extreme Flood Estimation, ISBN 978-1-925848-36-6, 2019a. 
                    
                
                        
                        Nathan, R. and Weinmann, E.: Chapter 4. Treatment of Joint Probability, in: Book 4 Catchment Simulation, edited by: Ball, J., Babister, M., Nathan, R., Weeks, W., Weinmann, E., Retallick, M., and Testoni, I., Commonwealth of Australia (Geoscience Australia), ISBN 978-1-925848-36-6, 2019b. 
                    
                
                        
                        Nathan, R., Weinmann, E., and Hill, P.: Use of Monte Carlo Simulation to Estimate the Expected Probability of Large to Extreme Floods, in: 28th International Hydrology and Water Resources Symposium: About Water, Symposium Proceedings, Barton, A. C. T., 1.105–1.112, ISBN 0-85824-060-2, 2003. 
                    
                
                        
                        Nathan, R. J.: The Derivation of Design Temporal Patterns for use with the Generalised Estimates of Probable Maximum Precipitation, Transactions of the Institution of Engineers, Australia, Civil Engineering, CE34, 139–150, 1992. 
                    
                
                        
                        Natural Resources Wales, Welsh Government: Adapting to Climate Change: Guidance for Flood and Coastal Erosion Risk Management Authorities in Wales, ISBN 978-1-80535-019-4, 2022. 
                    
                
                        
                        O'Shea, D., Nathan, R., Wasko, C., and Hill, P.: Implications of event-based loss model structure on simulating large floods, Journal of Hydrology, 595, 126008, https://doi.org/10.1016/j.jhydrol.2021.126008, 2021. 
                    
                
                        
                        O'Shea, D., Nathan, R., Wasko, C., Ho, M., and Sharma, A.: Evaluation of key flood risk drivers under climate change using a bottom-up approach, Journal of Hydrology, 640, 131694, https://doi.org/10.1016/j.jhydrol.2024.131694, 2024. 
                    
                
                        
                        Peel, M. C., Finlayson, B. L., and McMahon, T. A.: Updated world map of the Köppen-Geiger climate classification, Hydrology and Earth System Sciences, 11, 1633–1644, https://doi.org/10.5194/hess-11-1633-2007, 2007. 
                    
                
                        
                        Pielke, R. A.: Nine Fallacies of Floods, Climatic Change, 42, 413–438, https://doi.org/10.1023/A:1005457318876, 1999. 
                    
                
                        
                        Pilgrim, D. H. and Cordery, I.: Chapter 9 – Flood Runoff, in: Handbook of Hydrology, edited by: Maidment, D. R., McGraw-Hill, New York, ISBN 9780071711777, 1993. 
                    
                
                        
                        Pittock, J. and Hartmann, J.: Taking a second look: climate change, periodic relicensing and improved management of dams, Mar. Freshwater Res., 62, 312–320, 2011. 
                    
                
                        
                        Prasad, R., Hibler, L. F., Coleman, A. M., and Ward, D. L.: Design-Basis Flood Estimation for Site Characterization at Nuclear Power Plants in the United States of America, https://doi.org/10.2172/1036933, 2011. 
                    
                
                        
                        Rajabzadeh, V., Hekmatzadeh, A. A., Tabatabaie Shourijeh, P., and Torabi Haghighi, A.: Introducing a probabilistic framework to measure dam overtopping risk for dams benefiting from dual spillways, Reliability Engineering & System Safety, 231, 109030, https://doi.org/10.1016/j.ress.2022.109030, 2023. 
                    
                
                        
                        Rastogi, D., Kao, S.-C., Ashfaq, M., Mei, R., Kabela, E. D., Gangrade, S., Naz, B. S., Preston, B. L., Singh, N., and Anantharaj, V. G.: Effects of climate change on probable maximum precipitation: A sensitivity study over the Alabama-Coosa-Tallapoosa River Basin, Journal of Geophysical Research: Atmospheres, 122, 4808–4828, https://doi.org/10.1002/2016JD026001, 2017. 
                    
                
                        
                        Read, L. K. and Vogel, R. M.: Reliability, return periods, and risk under nonstationarity, Water Resources Research, 51, 6381–6398, https://doi.org/10.1002/2015WR017089, 2015. 
                    
                
                        
                        Roderick, T. P., Wasko, C., and Sharma, A.: An Improved Covariate for Projecting Future Rainfall Extremes?, Water Resources Research, 56, e2019WR026924, https://doi.org/10.1029/2019WR026924, 2020. 
                    
                
                        
                        Rouhani, H. and Leconte, R.: Uncertainties of Precipitable Water Calculations for PMP Estimates in Current and Future Climates, Journal of Hydrologic Engineering, 25, 04019066, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001877, 2020. 
                    
                
                        
                        Salas, J. D., Obeysekera, J., and Vogel, R. M.: Techniques for assessing water infrastructure for nonstationary extreme events: a review, Hydrological Sciences Journal, 63, 325–352, https://doi.org/10.1080/02626667.2018.1426858, 2018. 
                    
                
                        
                        Salas, J. D., Anderson, M. L., Papalexiou, S. M., and Frances, F.: PMP and Climate Variability and Change: A Review, Journal of Hydrologic Engineering, 25, 03120002, https://doi.org/10.1061/(ASCE)HE.1943-5584.0002003, 2020. 
                    
                
                        
                        Schlef, K. E., Kunkel, K. E., Brown, C., Demissie, Y., Lettenmaier, D. P., Wagner, A., Wigmosta, M. S., Karl, T. R., Easterling, D. R., Wang, K. J., François, B., and Yan, E.: Incorporating non-stationarity from climate change into rainfall frequency and intensity-duration-frequency (IDF) curves, Journal of Hydrology, 616, 128757, https://doi.org/10.1016/j.jhydrol.2022.128757, 2023. 
                    
                
                        
                        Shirzaei, M., Vahedifard, F., Sadhasivam, N., Ohenhen, L., Dasho, O., Tiwari, A., Werth, S., Azhar, M., Zhao, Y., Nicholls, R. J., and AghaKouchak, A.: Aging dams, political instability, poor human decisions and climate change: recipe for human disaster, npj Nat. Hazards, 2, 1–8, https://doi.org/10.1038/s44304-024-00056-1, 2025. 
                    
                
                        
                        Sivapalan, M., Blöschl, G., Merz, R., and Gutknecht, D.: Linking flood frequency to long-term water balance: Incorporating effects of seasonality, Water Resources Research, 41, https://doi.org/10.1029/2004WR003439, 2005. 
                    
                
                        
                        Stedinger, J. R. and Griffis, V. W.: Getting From Here to Where? Flood Frequency Analysis and Climate, JAWRA Journal of the American Water Resources Association, 47, 506–513, https://doi.org/10.1111/j.1752-1688.2011.00545.x, 2011. 
                    
                
                        
                        Steinschneider, S. and Brown, C.: A semiparametric multivariate, multisite weather generator with low-frequency variability for use in climate risk assessments, Water Resources Research, 49, 7205–7220, https://doi.org/10.1002/wrcr.20528, 2013. 
                    
                
                        
                        Stratz, S. A. and Hossain, F.: Probable Maximum Precipitation in a Changing Climate: Implications for Dam Design, Journal of Hydrologic Engineering, 19, 06014006, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001021, 2014. 
                    
                
                        
                        Tanaka, S. K., Zhu, T., Lund, J. R., Howitt, R. E., Jenkins, M. W., Pulido, M. A., Tauber, M., Ritzema, R. S., and Ferreira, I. C.: Climate Warming and Water Management Adaptation for California, Climatic Change, 76, 361–387, https://doi.org/10.1007/s10584-006-9079-5, 2006. 
                    
                
                        
                        Trenberth, K. E.: Conceptual Framework for Changes of Extremes of the Hydrological Cycle With Climate Change, in: Weather and Climate Extremes: Changes, Variations and a Perspective from the Insurance Industry, edited by: Karl, T. R., Nicholls, N., and Ghazi, A., Springer Netherlands, Dordrecht, 327–339, https://doi.org/10.1007/978-94-015-9265-9_18, 1999. 
                    
                
                        
                        Trenberth, K. E., Dai, A., Rasmussen, R. M., and Parsons, D. B.: The Changing Character of Precipitation, Bulletin of the American Meteorological Society, 84, 1205–1218, https://doi.org/10.1175/BAMS-84-9-1205, 2003. 
                    
                
                        
                        UK Environment Agency: Flood risk assessments: climate change allowances, https://www.gov.uk/guidance/flood-risk-assessments-climate-change-allowances (last access: 11 May 2020), 2022. 
                    
                
                        
                        Visser, J. B., Wasko, C., Sharma, A., and Nathan, R.: Eliminating the “Hook” in Precipitation–Temperature Scaling, Journal of Climate, 34, 9535–9549, https://doi.org/10.1175/JCLI-D-21-0292.1, 2021. 
                    
                
                        
                        Visser, J. B., Kim, S., Wasko, C., Nathan, R., and Sharma, A.: The Impact of Climate Change on Operational Probable Maximum Precipitation Estimates, Water Resources Research, 58, e2022WR032247, https://doi.org/10.1029/2022WR032247, 2022. 
                    
                
                        
                        Visser, J. B., Wasko, C., Sharma, A., and Nathan, R.: Changing storm temporal patterns with increasing temperatures across Australia, Journal of Climate, 1, 1–26, https://doi.org/10.1175/JCLI-D-22-0694.1, 2023. 
                    
                
                        
                        Walland, D., Meighen, J., Xuereb, K., Beesley, C., and Hoang, T.: Revision of the generalised tropical storm method for estimating probable maximum precipitation, Bureau of Meteorology, Melbourne, HRS Report No. 8, 2003. 
                    
                
                        
                        Wang, F. and Zhang, Q.-L.: Systemic Estimation of Dam Overtopping Probability: Bayesian Networks Approach, Journal of Infrastructure Systems, 23, 04016037, https://doi.org/10.1061/(ASCE)IS.1943-555X.0000328, 2017. 
                    
                
                        
                        Wang, G., Wang, D., Trenberth, K. E., Erfanian, A., Yu, M., Bosilovich, M. G., and Parr, D. T.: The peak structure and future changes of the relationships between extreme precipitation and temperature, Nature Climate Change, 7, 268–274, https://doi.org/10.1038/nclimate3239, 2017. 
                    
                
                        
                        Wasko, C. and Guo, D.: Understanding event runoff coefficient variability across Australia using the R package, Hydrological Processes, 36, e14563, https://doi.org/10.1002/hyp.14563, 2022. 
                    
                
                        
                        Wasko, C. and Sharma, A.: Global assessment of flood and storm extremes with increased temperatures, Sci. Rep., 7, 7945, https://doi.org/10.1038/s41598-017-08481-1, 2017. 
                    
                
                        
                        Wasko, C., Lu, W. T., and Mehrotra, R.: Relationship of extreme precipitation, dry-bulb temperature, and dew point temperature across Australia, Environmental Research Letters, 13, 074031, https://doi.org/10.1088/1748-9326/aad135, 2018. 
                    
                
                        
                        Wasko, C., Nathan, R., and Peel, M. C.: Changes in Antecedent Soil Moisture Modulate Flood Seasonality in a Changing Climate, Water Resources Research, 56, e2019WR026300, https://doi.org/10.1029/2019WR026300, 2020.  
                    
                
                        
                        Wasko, C., Sharma, A., and Pui, A.: Linking temperature to catastrophe damages from hydrologic and meteorological extremes, Journal of Hydrology, 602, 126731, https://doi.org/10.1016/j.jhydrol.2021.126731, 2021a. 
                    
                
                        
                        Wasko, C., Westra, S., Nathan, R., Orr, H. G., Villarini, G., Villalobos Herrera, R., and Fowler, H. J.: Incorporating climate change in flood estimation guidance, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 379, 20190548, https://doi.org/10.1098/rsta.2019.0548, 2021b. 
                    
                
                        
                        Wasko, C., Westra, S., Nathan, R., Jakob, D., Nielsen, C., Evans, J., Rodgers, S., Ho, M., Babister, M., Dowdy, A., and Sharples, W.: Chapter 6: Climate Change Considerations, in: Book 1: Scope and Philosophy, edited by: Ball, J., Babister, M., Nathan, R., Weeks, W., Weinmann, E., Retallick, M., and Testoni, I., Commonwealth of Australia (Geosciences Australia), ISBN 978-1-925848-36-6, 2024a. 
                    
                
                        
                        Wasko, C., Westra, S., Nathan, R., Pepler, A., Raupach, T. H., Dowdy, A., Johnson, F., Ho, M., McInnes, K. L., Jakob, D., Evans, J., Villarini, G., and Fowler, H. J.: A systematic review of climate change science relevant to Australian design flood estimation, Hydrol. Earth Syst. Sci., 28, 1251–1285, https://doi.org/10.5194/hess-28-1251-2024, 2024b. 
                    
                
                        
                        Watts, R. J., Richter, B. D., Opperman, J. J., and Bowmer, K. H.: Dam reoperation in an era of climate change, Mar. Freshwater Res., 62, 321–327, 2011. 
                    
                
                        
                        Willems, P.: Revision of urban drainage design rules after assessment of climate change impacts on precipitation extremes at Uccle, Belgium, Journal of Hydrology, 496, 166–177, https://doi.org/10.1016/j.jhydrol.2013.05.037, 2013. 
                    
                
                        
                        WMO: Manual on estimation of Probable Maximum Precipitation (PMP), World Meteorological Organization, Geneva, Switzerland, ISBN 978-92-63-11045-9, 2009. 
                    
                
                        
                        Woldemeskel, F. and Sharma, A.: Should flood regimes change in a warming climate? The role of antecedent moisture conditions, Geophysical Research Letters, 43, 7556–7563, https://doi.org/10.1002/2016GL069448, 2016. 
                    
                
                        
                        Yaghmaei, N., van Loenhout, J., Below, R., and Guha-Sapir, D.: Human cost of disasters: An overview of the last 20 years 2000–2019, Centre for Research on the Epidemiology of Disasters, UN Office for Disaster Risk Reduction, 2020. 
                    
                
                        
                        Zhang, W., Villarini, G., and Wehner, M.: Contrasting the responses of extreme precipitation to changes in surface air and dew point temperatures, Climatic Change, 154, 257–271, https://doi.org/10.1007/s10584-019-02415-8, 2019. 
                    
                Short summary
            There is unequivocal evidence that climate change will impact the risk profile of dams, which are critical for water supply and flood mitigation. We project changes in the overtopping risk for 18 large dams in Australia in response to global warming. We consider the impacts of climate change on rainfall depth, rainfall temporal pattern, and rainfall losses. Under 4 °C of global warming, the risk of overtopping floods was 2.4–17 times that of historical conditions.
            There is unequivocal evidence that climate change will impact the risk profile of dams, which...