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CIMA - Centro di Ricerca Interuniversitario in Monitoraggio Ambientale,

The uncertainty in the prediction of flash floods in the Northern Mediterranean environment; single site approach and multi-catchment system approach. CIMA - Centro di Ricerca Interuniversitario in Monitoraggio Ambientale, Università di Genova, Università della Basilicata. R. Rudari.

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CIMA - Centro di Ricerca Interuniversitario in Monitoraggio Ambientale,

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  1. The uncertainty in the prediction of flash floods in the Northern Mediterranean environment; single site approach and multi-catchment system approach CIMA - Centro di Ricerca Interuniversitario in Monitoraggio Ambientale, Università di Genova, Università della Basilicata R. Rudari Thanks to: L. Ferraris, F. Siccardi, G. Boni, F. Giannoni

  2. Civil Protection Authorities have to take decisions based on probability assessment of the possible land effects Scenarios and Civil Protection plans Warnings: from 24 to 12 hours before the possible events

  3. Scales of the basins of interest La Barbera, P.; Lanza, L. G. 2001 On the cumulative area distribution of natural drainage basins along a coastal boundaryWater Resour. Res. Vol. 37 , No. 5 , p. 1503

  4. Land effects 22/09/1992 - 10.45 22/09/1992 - 15.30 22/09/1992 - 15.40 22/09/1992 - 15.45

  5. Single Site DETERMINISTIC PROBABILISTIC GCM EPS LAM LEPS Downscaling DHM CDF of peak discharges Forecast Hydrograph

  6. Example of single site 1994 Piemonte flood CDF PLAM-TEPS1= 0.51 PLAM-TEPS2= 0.17 PLAM-TEPS3= 0.12 PLAM-TEPS4= 0.12 PLAM-TEPS5= 0.08 Conditioned CDF Ferraris, L., Rudari, R. and F. Siccardi, 2002 The uncertainty in the prediction of flash floods in the northern Mediterranean environmentJournal of Hydrometeorology (AMS) in press.

  7. Admission of ignorance • Aggregate the rainfall volume to the scale where we have a reliable evaluation of its probability of occurrence on that area through the use of EPS. • We downscale from the aggregate scale down to the scale of interest with a purely stochastic model

  8. Single site & multi-catchment approach • The limit among single site and multi-catchment system approaches is in the scale at which EPS can give a reliable estimation of the probability of the rainfall volume: The bigger the aggregation area, the smaller the stochastic ensemble, the bigger the catchment where I can apply the single site warning Area Dimension Stochastic ensemble size Drainage Area Distribution n=1…N

  9. Different approach – multi-catchment distributed warning Class A (< 10 km2) Class B (10 < Area < 150 km2) Class C (> 150 km2)

  10. Multi-catchment approach PROBABILISTIC EPS LEPS Downscaling Exceeding probability curves DHM

  11. Regional framework STATISTICALLY HOMOGENEOUS REGION Peak discharge values of the Liguria region belong to the same statistical distribution Through the Qindex is possible to specify the growth curve in each site of the region Qindex Within a regional procedure it is possible to make dimensionless all the simulated discharge peak values (TCEV)

  12. Exceeding probability of a given discharge quantile in one catchment chosen randomly inside the multi-basin system

  13. If catchments and simulations were independent it would be possible to compute exceedence probability of a given quantile in at least one site of the multi-basin system directly from probability theory

  14. Discharge realizations are not independent. Each disaggregation history is considered separately

  15. Questions to be answered by: • The EPS community: • What is the scale where I have a reliable estimation of rainfall volumes with their probability? • How does it change when a different target region is concerned? • How does it change when a different synoptic condition is concerned? • What do I gain from LAMs? • What do I loose by clustering? • What are we calling probability? • The Downscaling community: • What is the best downscaling model (stochastic, physical, mixed approach)? • Is it possible to exploit better the Meteorological model info at different scales (Data fusion)? • The Hydrologic community: • How do I improve the I. C. of the hydrological models (remote measures, data assimilation)? • All the communities: • How do the uncertainty propagates through the chain? • How do we convey the Probabilistic Information?

  16. Pebble creek Hydrologic scale inconsistency Giannoni, 2001 Space Time

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