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Swiss Rainfall Mass Curves and their Influence on Extreme Flood Simulation

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Abstract

Extreme flood estimates for dam safety are routinely obtained from hydrologic simulations driven by selected design storms. The temporal structure of such design storms can be obtained from Rainfall Mass Curves (RMCs), which are adimensionalized curves of the cumulative precipitation depth as a function of event duration. This paper assesses for the first time the spatialand temporal variability of observed RMCs for Switzerland, an Alpine region with complex topography. The relevance of the detected RMC variability for extreme flood estimation is illustrated based on an application to a high elevation catchment, the Mattmark dam catchment in the Swiss Alps. The obtained results underline that quantile RCMs represent a simple yet powerful tool to construct design storms for dam safety verification and that regional, seasonal and event-duration effects on RMCs are small enough to justify the use of a unique set of Swiss-wide quantile RMCs. The presented analysis could be refined in the future by explicitly accounting for orographic, convective or frontal precipitation events.

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References

  • Alfieri L, Laio F, Claps P (2008) A simulation experiment for optimal design hyetograph selection. Hydrol Process 22(6):813–820

    Article  Google Scholar 

  • Azli M, Rao AR (2010) Development of Huff curves for Peninsular Malaysia. J Hydrol 388(1–2):77–84

    Article  Google Scholar 

  • Back AJ (2011) Time distribution of heavy rainfall events in Urussanga, Santa Catarina State, Brazil. Acta Sci Agron 33(4):583–588

    Article  Google Scholar 

  • Bérod D, Devred D, Laglaine V, Chaix O, Altinakar M, Delley P (1992) Calcul des crues extrêmes par des méthodes déterministes du type pluie maximale probable (PMP) / crue maximual probable (PMF), Application au cas de la Suisse. Institut d’aménagement des terres et des eaux, Ecole Polytechnique Fédérale de Lausanne (EPFL); Bonnard et Gardel, Ingénieurs Conseils SA (BG); SA Ufficio d’ingegneria Maggia, Locarno (IM), Lausanne

  • Bonta J (2004) Development and utility of Huff curves for disaggregating precipitation amounts. Appl Eng Agric 20(5):641

    Article  Google Scholar 

  • Bonta J, Shahalam A (2003) Cumulative storm rainfall distributions: comparison of Huff curves. J Hydrol N Z 42(1):65–74

    Google Scholar 

  • Caballero W, Rahman A (2013) Variability in Rainfall Temporal Patterns: A Case Study for New South Wales, Australia. J Hydro Environ Res 1(1):41–48

    Google Scholar 

  • Chen X, Hossain F, Leung LR (2017) Probable maximum precipitation in the u.s. pacific northwest in a changing climate. Water Resour Res. https://doi.org/10.1002/2017WR021094

  • Dolsak D, Bezak N, Sraj M (2016) Temporal characteristics of rainfall events under three climate types in slovenia. J Hydrol 541:1395–1405. https://doi.org/10.1016/j.jhydrol.2016.08.047

    Article  Google Scholar 

  • Ghassabi Z, Kamali GA, Meshkatee AH, Hajam S, Javaheri N (2016) Time distribution of heavy rainfall events in south west of Iran. J Atmos Sol Terr Phys 145:53–60

    Article  Google Scholar 

  • Golian S, Saghafian B, Maknoon R (2010) Derivation of probabilistic thresholds of spatially distributed rainfall for flood forecasting. Water Resour Manag 24(13):3547–3559

    Article  Google Scholar 

  • Guo JC, Hargadin K (2009) Conservative design rainfall distribution. J Hydrol Eng 14(5):528–530

    Article  Google Scholar 

  • Hertig JA, Fallot JM (2009) Validation et utilisation des cartes de PMP pour l’obtention de la PMF. Projet CRUEX: Directives Crues de l’OFEN. unpublished report

  • Hertig JA, Audouard A, Plancherel A (2005) Cartes des précipitations extrêmes pour la Suisse (PMP 2005). Rapport EFLUM-EPFL

  • Huff FA (1967) Time distribution of rainfall in heavy storms. Water Resour Res 3(4):1007–1019

    Article  Google Scholar 

  • Jordan F, Brauchli T, Garcia Hernandez J, Bieri M, Boillat JL (2012) RS 2012, Rainfall-Runoff Modelling. User guide. unpublished manual, e-dric.ch, Lausanne

  • Keifer C, Chu H (1957) Synthetic storm pattern for drainage design. ASCE Journal of the Hydraulics Division 83(HY4):1–25

    Google Scholar 

  • Kimoto A, Canfield HE, Stewart D (2011) Comparison of Synthetic Design Storms with Observed Storms in Southern Arizona. J Hydrol Eng 16(11):935–941

    Article  Google Scholar 

  • National Environment Research Council (1975) Flood Studies Report, Meteorological studies, vol 2. Whitefriars Press Ltd., London

    Google Scholar 

  • Natural Resources Conservation Service (1986) Technical Release 55 (TR-55). Urban hydrology for small watersheds, Natural Resources Conservation Service, Engineering Division, Washington, D.C.

  • Pan CL, Wang XW, Liu L, Huang HB, Wang DS (2017) Improvement to the huff curve for design storms and urban flooding simulations in guangzhou, china. Water 9(6). https://doi.org/10.3390/w9060411

  • Pedrozzi G (2004) Triggering of landslides in canton ticino (switzerland) and prediction by the rainfall intensity and duration method. Bull Eng Geol Environ 63(4):281–291. https://doi.org/10.1007/s10064-004-0240-y

    Article  Google Scholar 

  • Prodanovic P, Simonovic SP (2004) Generation of Synthetic Design Storms for the Upper Thames River Basin. CFCAS Project: Assessment of Water Resources Risk and Vulnerability to Changing Climatic Conditions. Tech. rep. The University of Western Ontario, Department of Civil and Environmental Engineering

  • Rajczak J, Schär C (2017) Projections of future precipitation extremes over europe: A multimodel assessment of climate simulations. J Geophys Res-Atmos 122(20):10,773–10,800. https://doi.org/10.1002/2017JD027176

    Article  Google Scholar 

  • Schaefli B, Zehe E (2009) Hydrological model performance and parameter estimation in the wavelet-domain. Hydrol Earth Syst Sci 13(10):1921–1936

    Article  Google Scholar 

  • Schaefli B, Hingray B, Niggli M, Musy A (2005) A conceptual glaciohydrological model for high mountainous catchments. Hydrol Earth Syst Sci 9(1/2):95–109

    Article  Google Scholar 

  • Shaw L, Hamilton PA, Kent CE (1984) Temporal Distribution of Rainfall in Virginia. Tech. rep., Virginia Highway & Transportation Research Council

  • Swiss Federal Office for the Environment (2001) Die biogeographischen Regionen der Schweiz. Umwelt-Materialien UM, Federal Office for the Environment FOEN, Bern

  • Tsihrintzis VA, Sidan CB (1998) Modeling urban stormwater runoff processes using the santa barbara method. Water Resour Manag 12(2):139–166

    Article  Google Scholar 

  • Veneziano D, Villani P (1999) Best linear unbiased design hyetograph. Water Resour Res 35(9):2725–2738

    Article  Google Scholar 

  • Vernieuwe H, Vandenberghe S, De Baets B, Verhoest N (2015) A continuous rainfall model based on vine copulas. Hydrol Earth Syst Sci 19(6):2685–2699

    Article  Google Scholar 

  • Watt E, Marsalek J (2013) Critical review of the evolution of the design storm event concept. Can J Civ Eng 40(2):105–113

    Article  Google Scholar 

  • World Meteorological Organisation (2009) Manual on Estimation of Probable Maximum Precipitation (PMP), vol WMO-No.1045. World Meteorological Organization, Geneva

  • Zeimetz F (2017) Development of a methodology for extreme flood estimations in alpine catchments for the verification of dam safety. phd thesis, ecole polytechnique federale de lausanne, available at library.epfl.ch/theses (last Accessed 01. 12. 2017). PhD thesis

  • Zeimetz F, Schaefli B, Artigue G, García Hernández J, Schleiss AJ (2017) Relevance of the correlation between precipitation and the 0°c isothermal altitude for extreme flood estimation. J Hydrol 551:177–187. https://doi.org/10.1016/j.jhydrol.2017.05.022

    Article  Google Scholar 

  • Zeimetz F, Schaefli B, Artigue G, García Hernández J, Schleiss A (in press) A new approach to identify critical initial conditions for extreme flood simulations based on deterministic and stochastic simulation. Journal of Hydrologic Engineering

Download references

Acknowledgements

This work was funded by the Swiss Federal Office of Energy (SFOE). The work of B. Schaefli was supported by the the Swiss Competence Center on Energy Research-Supply of Energy, and by the Swiss National Science Foundation, grant number PP00P2_157611. Precipitation data has been provided by MeteoSwiss. The authors also thank the engineering company e-dric.ch for their hydrological modeling software and the engineering company Hertig & Lador SA for the PMP data (elaborated for the SFOE). The Swiss PMP values should become freely available in the near future. The data corresponding to the identified Swiss-wide reference quantile RMCs is available in the Supplementary Material.

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Correspondence to Fränz Zeimetz.

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Zeimetz, F., Schaefli, B., Artigue, G. et al. Swiss Rainfall Mass Curves and their Influence on Extreme Flood Simulation. Water Resour Manage 32, 2625–2638 (2018). https://doi.org/10.1007/s11269-018-1948-y

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  • DOI: https://doi.org/10.1007/s11269-018-1948-y

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