Flash Flood Forecasting Based on Rainfall Thresholds

  • Lorenzo AlfieriEmail author
  • Marc Berenguer
  • Valentin Knechtl
  • Katharina Liechti
  • Daniel Sempere-Torres
  • Massimiliano Zappa
Reference work entry


Extreme rainstorms often trigger catastrophic flash floods in Europe and in several areas of the world. Despite notable advances in weather forecasting, most operational early warning systems for extreme rainstorms and flash floods are based on rainfall observations derived from rain gauge networks and weather radars, rather than on forecasts. As a result, warning lead times are bounded to few hours, and warnings are usually issued when the event is already taking place.

This chapter illustrates three recently developed systems that use information on observed and forecasted precipitation to issue flash flood warnings. The first approach is an indicator for heavy precipitation events, developed to complement the flood early warning of the European Flood Awareness System (EFAS) and targeted to short and intense events, possibly leading to flash flooding in small catchments. The system is based on the European Precipitation Index Based on Simulated Climatology (EPIC), which in EFAS is computed using COSMO-LEPS ensemble weather forecasts and a 20-year consistent reforecast dataset.

The second system is a flash flood early warning tool developed based on precipitation statistics. A total of 759 sub-catchments in southern Switzerland is considered. Intensity-duration-frequency (IDF) curves for each catchment have been calculated based on gridded precipitation products for the period 1961–2012 and gridded reforecast of the COSMO-LEPS for the period 1971–2000. The different IDF curves at the catchment level in combination with precipitation forecasts are the basis for the flash flood early warning tool. The forecast models used are COSMO-2 (deterministic, updated every 3 h and with a lead time of 24 h) and COSMO-LEPS (probabilistic, 16-member and with a lead time of 5 days).

The third system (FF-EWS) uses probabilistic high-resolution precipitation products generated from the observations of the weather radar network to monitor situations prone to trigger flash floods in Catalonia (NE Spain). These ensemble precipitation estimates and nowcasts are used to calculate the basin-aggregated rainfall (that is, the rainfall accumulated upstream of each point of the drainage network), which is the variable used to characterize the potential flash flood hazard.

Examples of successful and less skilful forecasts for all three systems are shown and commented to highlight pros and cons.


Extreme precipitation events Numerical weather predictions Flash flood early warning EPIC IDF Ensemble forecasting Reforecasts 


  1. ACA, Recomanacions tècniques per als estudis d’inundabilitat d’àmbit local (Agència Catalana de l’Aigua, Barcelona, 2003), p. 106Google Scholar
  2. N. Addor, S. Jaun, F. Fundel, M. Zappa, An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios. Hydrol. Earth Syst. Sci. 15, 2327–2347 (2011). Scholar
  3. J.R.A. Aldrich, Fisher and the making of maximum likelihood 1912–1922. Stat. Sci. 12(3), 162–176 (1997)CrossRefGoogle Scholar
  4. L. Alfieri, J. Thielen, A European precipitation index for extreme rain-storm and flash flood early warning. Meteorol. Appl. 22(1), 3–13 (2015). Scholar
  5. L. Alfieri, D. Velasco, J. Thielen, Flash flood detection through a multi-stage probabilistic warning system for heavy precipitation events. Adv. Geosci. 29, 69–75 (2011). Scholar
  6. L. Alfieri, J. Thielen, F. Pappenberger, Ensemble hydro-meteorological simulation for flash flood early detection in southern Switzerland. J. Hydrol. 424–425, 143–153 (2012). Scholar
  7. L. Alfieri, F. Pappenberger, F. Wetterhall, The extreme runoff index for flood early warning in Europe. Nat. Hazards Earth Syst. Sci. 14(6), 1505–1515 (2014). Scholar
  8. F. Ament, T. Weusthoff, M. Arpagaus, Evaluation of MAP D-PHASE heavy precipitation alerts in Switzerland during summer 2007. Atmos. Res. 100(2–3), 178–189 (2011)CrossRefGoogle Scholar
  9. N. Andres, A. Badoux, C. Hegg, Unwetterschäden in der Schweiz im Jahre 2014. Rutschungen, Murgänge, Hochwasser und Sturzereignisse. Wasser Energie Luft 107(1), 47–54 (2015)Google Scholar
  10. M. Antonetti, R. Buss, S. Scherrer, M. Margreth, M. Zappa, Mapping dominant runoff processes: an evaluation of different approaches using similarity measures and synthetic runoff simulations, Hydrol. Earth Syst. Sci. Discuss. 12, 13257–13299 (2015). Scholar
  11. M. Barnolas, A. Atencia, M.C. Llasat, T. Rigo, Characterization of a Mediterranean flash flood event using rain gauges, radar, GIS and lightning data. Adv. Geosci. 17, 35–41 (2008). Scholar
  12. J.C. Bartholmes, J. Thielen, M.H. Ramos, S. Gentilini, The European flood alert system EFAS – part 2, statistical skill assessment of probabilistic and deterministic operational forecasts. Hydrol. Earth Syst. Sci. 13(2), 141–153 (2009)CrossRefGoogle Scholar
  13. J. Beck, O. Bousquet, Using gap-filling radars in mountainous regions to complement a national radar network: improvements in multiple-doppler wind syntheses. J. Appl. Meteorol. Climatol. 52, 1836–1850 (2013). Scholar
  14. M. Berenguer, C. Corral, R. Sanchez-Diezma, D. Sempere-Torres, Hydrological validation of a radar-based nowcasting technique. J. Hydrometeorol. 6, 532–549 (2005). Scholar
  15. M. Berenguer, D. Sempere-Torres, G.G.S. Pegram, SBMcast – an ensemble nowcasting technique to assess the uncertainty in rainfall forecasts by Lagrangian extrapolation. J. Hydrol. 404, 226–240 (2011). Scholar
  16. M. Berenguer, M. Surcel, I. Zawadzki, M. Xue, F. Kong, The diurnal cycle of precipitation from continental radar mosaics and numerical weather prediction models, part II: intercomparison among numerical models and with nowcasting. Mon. Weather Rev. 140, 2689–2705 (2012). Scholar
  17. A. Binley, K. Beven, Three dimensional modelling of hillslope hydrology. Hydrol. Process. 6(3), 253–368 (1992)CrossRefGoogle Scholar
  18. N.E. Bowler, C.E. Pierce, A.W. Seed, STEPS: a probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP. Q. J. Roy. Meteorol. Soc. 132, 2127–2155 (2006). Scholar
  19. L.S. Campbell, W.J. Steenburgh, Finescale orographic precipitation variability and gap-filling radar potential in little Cottonwood Canyon, Utah. Weather Forecast. 29, 912–935 (2014). Scholar
  20. V.T. Chow, D.R. Maidment, L.W. Mays, Applied Hydrology. (McGraw-Hill Science/Engineering/Math., McGraw-Hill: New York. ISBN 0-07-010810-2, 1988)Google Scholar
  21. S. Coles, An Introduction to Statistical Modeling of Extreme Values, vol. 208 (Springer, London, 2001)CrossRefGoogle Scholar
  22. C.G. Collier, Flash flood forecasting: what are the limits of predictability? Q. J. Roy. Meteorol. Soc. 133(622), 3–23 (2007)CrossRefGoogle Scholar
  23. C. Corral, D. Velasco, D. Forcadell, D. Sempere-Torres, Advances in radar-based flood warning systems. The EHIMI system and the experience in the Besòs flash-flood pilot basin, in Flood Risk Management: Research and Practice, ed. by P. Samuels, S. Huntington, W. Allsop, J. Harrop (Taylor & Francis, London, 2009), pp. 1295–1303Google Scholar
  24. D.P. Dee, S.M. Uppala, A.J. Simmons, P. Berrisford, P. Poli, S. Kobayashi, U. Andrae, M.A. Balmaseda, G. Balsamo, P. Bauer, P. Bechtold, A.C.M. Beljaars, L. van de Berg, J. Bidlot, N. Bormann, C. Delsol, R. Dragani, M. Fuentes, A.J. Geer, L. Haimberger, S.B. Healy, H. Hersbach, E.V. Hólm, L. Isaksen, P. Kållberg, M. Köhler, M. Matricardi, A.P. McNally, B.M. Monge‐Sanz, J.-J. Morcrette, B.-K. Park, C. Peubey, P. de Rosnay, C. Tavolato, J.-N. Thépaut, F. Vitart, The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. Roy. Meteor. Soc. 137(656), 553–597 (2011). Scholar
  25. G. Delrieu, J.D. Creutin, H. Andrieu, Simulation of radar mountain returns using a digitized terrain model. J. Atmos. Oceanic Tech. 12, 1038–1049 (1995).<1038:SORMRU>2.0.CO;2CrossRefGoogle Scholar
  26. M. Fiorentino, F. Rossi, P. Villani, Effect of the basin geomorphoclimatic characteristics on the mean annual flood reduction curve. Proc. IASTED Int. Conf. Model. Simul. 5, 1777–1784 (1987)Google Scholar
  27. L. Foresti, A. Seed, The effect of flow and orography on the spatial distribution of the very short-term predictability of rainfall from composite radar images. Hydrol. Earth Syst. Sci. 18, 4671–4686 (2014). Scholar
  28. M. Franco, R. Sánchez-Diezma, D. Sempere-Torres, Improvements in weather radar rain rate estimates using a method for identifying the vertical profile of reflectivity from volume radar scans. Meteorol. Z. 15, 521–536 (2006). Scholar
  29. M. Franco, R. Sánchez-Diezma, D. Sempere-Torres, I. Zawadzki, Improving radar precipitation estimates by applying a VPR correction method based on separating precipitation types, 5th European Conference on Radar in Meteorology and Hydrology (Helsinki, 2008), P14.16Google Scholar
  30. J. French, R. Ing, S. Von Allmen, R. Wood, Mortality from flash floods: a review of national weather service reports, 1969–81. Public Health Rep. 98(6), 584 (1983)Google Scholar
  31. F. Fundel, M. Zappa, Hydrological ensemble forecasting in mesoscale catchments: sensitivity to initial conditions and value of reforecasts. Water Resour. Res. 47, W09520 (2011). Scholar
  32. F. Fundel, A. Walser, M.A. Liniger, C. Appenzeller, Calibrated precipitation forecasts for a limited-area ensemble forecast system using reforecasts. Mon. Weather Rev. 138(1), 176–189 (2010)CrossRefGoogle Scholar
  33. E. Gaume, V. Bain, P. Bernardara, O. Newinger, M. Barbuc, A. Bateman, L. Blaškovičová, G. Blöschl, M. Borga, A. Dumitrescu, I. Daliakopoulos, J. Garcia, A. Irimescu, S. Kohnova, A. Koutroulis, L. Marchi, S. Matreata, V. Medina, E. Preciso, D. Sempere-Torres, G. Stancalie, J. Szolgay, I. Tsanis, D. Velasco, A. Viglione, A compilation of data on European flash floods. J. Hydrol. 367(1–2), 70–78 (2009)CrossRefGoogle Scholar
  34. K.P. Georgakakos, Analytical results for operational flash flood guidance. J. Hydrol. 317(1), 81–103 (2006)CrossRefGoogle Scholar
  35. U. Germann, I. Zawadzki, B. Turner, Predictability of precipitation from continental radar images, part IV: limits to prediction. J. Atmos. Sci. 63, 2092–2108 (2006). Scholar
  36. U. Germann, M. Berenguer, D. Sempere-Torres, M. Zappa, REAL-Ensemble radar precipitation estimation for hydrology in a mountainous region. Q. J. Roy. Meteorol. Soc. 135, 445–456 (2009). Scholar
  37. P. Guillot, D. Duband, La méthode du Gradex pour le calcul de la probabilité des crues à partir les pluies. AISH Publ. 84, 560–569 (1967)Google Scholar
  38. A. Günther, M. Van Den Eeckhaut, J.P. Malet, P. Reichenbach, J. Hervás, The European landslide susceptibility map ELSUS 1000 Version 1, EGU General Assembly Conference Abstracts, 15, 10071 (2013), Last accessed 19 Aug 2015
  39. B. Heil, I. Petzold, H. Romang, J. Hess, The common information platform for natural hazards in Switzerland. Nat. Hazards 70(3), 1673–1687 (2014)CrossRefGoogle Scholar
  40. N. Hilker, A. Badoux, C. Hegg, The Swiss flood and landslide damage database 1972–2007. Nat. Hazards Earth Syst. Sci. 9, 913–925 (2009)CrossRefGoogle Scholar
  41. J.R.M. Hosking, L-moments: analysis and estimation of distributions using linear combinations of order statistics. J. R. Stat. Soc. Ser. B Methodol. 52(1), 105–124 (1990)Google Scholar
  42. A. Huuskonen, E. Saltikoff, I. Holleman, The operational weather radar network in Europe. Bull. Am. Meteorol. Soc. 95, 897–907 (2014). Scholar
  43. P. Javelle, C. Fouchier, P. Arnoud, J. Lavabre, Flash flood warning at un-gauged locations using radar rainfall and antecedent soil moisture estimations. J. Hydrol. 394, 267–274 (2010)CrossRefGoogle Scholar
  44. A.F. Jenkinson, The frequency distribution of the annual maximum (or minimum) values of meteorological elements. Q. J. Roy. Meteorol. Soc. 81(348), 158–171 (1955)CrossRefGoogle Scholar
  45. S.N. Jonkman, Global perspectives on loss of human life caused by floods. Nat. Hazards 34(2), 151–175 (2005)CrossRefGoogle Scholar
  46. S. Jörg-Hess, S. B. Kempf, F. Fundel, M. Zappa, The benefit of climatological and calibrated reforecast data for simulating hydrological droughts in Switzerland, Meteorological Applications, 22(3), 444–458 (2015) Scholar
  47. M.G. Kendall, Rank Correlation Methods (Griffin, London, 1970). ISBN 0-85264-199-0Google Scholar
  48. V. Knechtl, Flash-flood early warning tool. Use of intensity-duration-frequency curves for flash-flood warning in southern Switzerland and forecast skill evaluation, Master Thesis, ETH Zürich, 2013Google Scholar
  49. D. Koutsoyiannis, D. Kozonis, A. Manetas, A mathematical framework for studying rainfall intensity-duration-frequency relationships. J. Hydrol. 206, 118–135 (1998)CrossRefGoogle Scholar
  50. M.R. Leadbetter, G. Lindgren, H. Rootzén, Extremes and Related Properties of Random Sequences and Processes (Springer, New York a.o., XII, 336 pp, 1983)CrossRefGoogle Scholar
  51. L. Li, W. Schmid, J. Joss, Nowcasting of motion and growth of precipitation with radar over a complex orography. J. Appl. Meteorol. 34, 1286–1300 (1995).<1286:NOMAGO>2.0.CO;2CrossRefGoogle Scholar
  52. K. Liechti, L. Panziera, U. Germann, M. Zappa, The potential of radar-based ensemble forecasts for flash-flood early warning in the southern Swiss Alps. Hydrol. Earth Syst. Sci. 17, 3853–3869 (2013a). Scholar
  53. K. Liechti, M. Zappa, F. Fundel, U. Germann, Probabilistic evaluation of ensemble discharge nowcasts in two nested Alpine basins prone to flash floods. Hydrol. Process. 27, 5–17 (2013b). Scholar
  54. X. Llort, C.A. Velasco-Forero, J. Roca-Sancho, D. Sempere-Torres, Characterization of uncertainty in radar-based precipitation estimates and ensemble generation, 5th European Conference on Radar in Meteorology and Hydrology (Helsinki, 2008)Google Scholar
  55. P.V. Mandapaka, U. Germann, L. Panziera, A. Hering, Can Lagrangian extrapolation of radar fields be used for precipitation nowcasting over complex Alpine orography? Weather Forecast. 27, 28–49 (2012). Scholar
  56. C. Marsigli, F. Boccanera, A. Montani, T. Paccagnella, The COSMO-LEPS mesoscale ensemble system: validation of the methodology and verification. Nonlinear Processes Geophys. 12(4), 527–536 (2005)CrossRefGoogle Scholar
  57. E.S. Martins, J.R. Stedinger, Generalized maximum-likelihood generalized extreme-value quantile estimators for hydrologic data. Water Resour. Res. 36(3), 737–744 (2000)CrossRefGoogle Scholar
  58. Meteoschweiz, Documentation of MeteoSwiss Grid-Data Products – Daily Precipitation (final analysis): RhiresD (2013), Last accessed 13 July 2015
  59. D. Norbiato, M. Borga, S. Esposti, E. Gaume, S. Anquetin, Flash flood warning based on rainfall thresholds and soil moisture conditions: an assessment for gauged and ungauged basins. J. Hydrol. 362, 274–290 (2008)CrossRefGoogle Scholar
  60. L. Panziera, U. Germann, M. Gabella, P.V. Mandapaka, NORA–Nowcasting of Orographic Rainfall by means of Analogues. Q. J. Roy. Meteorol. Soc. 137, 2106–2123 (2011). Scholar
  61. S. Park, M. Berenguer, Adaptive reconstruction of radar reflectivity in clutter-contaminated areas by accounting for the space–time variability. J. Hydrol. 520, 407–419 (2015). Scholar
  62. G.G.S. Pegram, A.N. Clothier, High-resolution space-time modelling of rainfall: the “String of Beads” model. J. Hydrol. 241, 26–41 (2001). Scholar
  63. T. Pellarin, G. Delrieu, G.M. Saulnier, H. Andrieu, B. Vignal, J.D. Creutin, Hydrologic visibility of weather radar systems operating in mountainous regions: case study for the Ardeche catchment (France). J. Hydrometeorol. 3, 539–555 (2002).<0539:hvowrs>;2CrossRefGoogle Scholar
  64. F. Quintero, D. Sempere-Torres, M. Berenguer, E. Baltas, A scenario-incorporating analysis of the propagation of uncertainty to flash flood simulations. J. Hydrol. 460–461, 90–102 (2012). Scholar
  65. D. Raynaud, J. Thielen, P. Salamon, P. Burek, S. Anquetin, L. Alfieri, A dynamic runoff co-efficient to improve flash flood early warning in Europe: evaluation on the 2013 central European floods in Germany. Meteorol. Appl. 22(3), 410–418 (2015). Scholar
  66. S. Reed, J. Schaake, Z. Zhang, A distributed hydrologic model and threshold frequency-based method for flood forecasting at ungauged locations. J. Hydrol. 337, 402–420 (2007)CrossRefGoogle Scholar
  67. R. Schiemann, M. Liniger, C. Frei, Reduced space optimal interpolation of daily rain gauge precipitation in Switzerland. J. Geophys. Res. 115, D14109 (2010). Scholar
  68. R. Schiemann, R. Erdin, M. Willi, C. Frei, M. Berenguer, D. Sempere-Torres, Geostatistical radar-raingauge combination with nonparametric correlograms: methodological considerations and application in Switzerland. Hydrol. Earth Syst. Sci. 15, 1515–1536 (2011). Scholar
  69. I.V. Sideris, M. Gabella, R. Erdin, U. Germann, Real-time radar-rain-gauge merging using spatio-temporal co-kriging with external drift in the alpine terrain of Switzerland. Q. J. Roy. Meteorol. Soc. 140, 1097–1111 (2014). Scholar
  70. R.L. Smith, Maximum likelihood estimation in a class of non-regular cases. Biometrika 72(1), 67–90 (1985)CrossRefGoogle Scholar
  71. J. Thielen, J. Bartholmes, M.H. Ramos, A. de Roo, The European flood alert system – part 1: concept and development. Hydrol. Earth Syst. Sci. 13(2), 125–140 (2009)CrossRefGoogle Scholar
  72. J.M. van der Knijff, J. Younis, A. de Roo, A GIS-based distributed model for river basin scale water balance and flood simulation. Int. J. Geogr. Inf. Sci. 24, 189–212 (2010)CrossRefGoogle Scholar
  73. C.A. Velasco-Forero, D. Sempere-Torres, E.F. Cassiraga, J.J. Gómez-Hernández, A non-parametric automatic blending methodology to estimate rainfall fields from rain gauge and radar data. Adv. Water Resour. 32, 986–1002 (2009)CrossRefGoogle Scholar
  74. P. Versini, M. Berenguer, C. Corral, D. Sempere-Torres, An operational flood warning system for poorly gauged basins: demonstration in the Guadalhorce basin (Spain). Nat. Hazards 71, 1355–1378 (2014). Scholar
  75. A. Viglione, G. Blöschl, On the role of storm duration in the mapping of rainfall to flood return periods. Hydrol. Earth Syst. Sci. 13(2), 205–216 (2009). Scholar
  76. G. Villarini, W. Krajewski, Review of the different sources of uncertainty in single polarization radar-based estimates of rainfall. Surv. Geophys. 31, 107–129 (2009). Scholar
  77. G. Villarini, W. Krajewski, G. Ciach, D. Zimmerman, Product-error-driven generator of probable rainfall conditioned on WSR-88D precipitation estimates. Water Resour. Res. 45, W01404 (2009). Scholar
  78. D. Viviroli, M. Zappa, J. Gurtz, R. Weingartner, An introduction to the hydrological modelling system PREVAH and its pre- and post-processing-tools. Environ. Model. Software 24(10), 1209–1222 (2009)CrossRefGoogle Scholar
  79. A. Wald, J. Wolfowitz, On a test whether two samples are from the same population. Ann. Math. Stat. 11, 147–162 (1940)CrossRefGoogle Scholar
  80. M. Zappa, M. Rotach, M. Arpagaus, M. Dorninger, C. Hegg, A. Montani, R. Ranzi, F. Ament, U. Germann, G. Grossi, S. Jaun, A. Rossa, S. Vogt, A. Walser, J. Wehrhan, C. Wunram, MAP D-PHASE: real-time demonstration of hydrological ensemble prediction systems. Atmos. Sci. Lett. 9(2), 80–87 (2008)CrossRefGoogle Scholar
  81. M. Zappa, S. Jaun, U. Germann, A. Walser, F. Fundel, Superposition of three sources of uncertainties in operational flood forecasting chains. Atmos. Res. 100(2–3), 246–262 (2011). Thematic Issue on COST731CrossRefGoogle Scholar
  82. M. Zappa, F. Fundel, S. Jaun, A “Peak-Flow Box” approach for supporting interpretation and evaluation of operational ensemble flood forecasts. Hydrol. Process. 27, 117–131 (2013). Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Lorenzo Alfieri
    • 1
    Email author
  • Marc Berenguer
    • 2
  • Valentin Knechtl
    • 3
  • Katharina Liechti
    • 3
  • Daniel Sempere-Torres
    • 2
  • Massimiliano Zappa
    • 3
  1. 1.Directorate for Space, Security and MigrationEuropean Commission – Joint Research CentreIspraItaly
  2. 2.Center of Applied Research in HydrometeorologyUniversitat Politècnica de CatalunyaBarcelonaSpain
  3. 3.Swiss Federal Research Institute WSLBirmensdorfSwitzerland

Personalised recommendations