COST-733 WG4
This presentation is the property of its rightful owner.
Sponsored Links
1 / 11

COST-733 WG4 Links between Weather Types and Flood events in Europe Christel Prudhomme PowerPoint PPT Presentation


  • 49 Views
  • Uploaded on
  • Presentation posted in: General

COST-733 WG4 Links between Weather Types and Flood events in Europe Christel Prudhomme. Understanding large scale antecedent conditions. Weather Types/ Classifications from COST A priori, all classifications At present only for Europe: D00 For each large flood events

Download Presentation

COST-733 WG4 Links between Weather Types and Flood events in Europe Christel Prudhomme

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Cost 733 wg4 links between weather types and flood events in europe christel prudhomme

COST-733 WG4 Links between Weather Types and Flood events in EuropeChristel Prudhomme


Cost 733 wg4 links between weather types and flood events in europe christel prudhomme

Understanding large scale antecedent conditions

  • Weather Types/ Classifications from COST

    • A priori, all classifications

  • At present only for Europe: D00

  • For each large flood events

    • Frequency of weather type : preceding day(s)

    • “ : preceding weeks

    • Frequency anomaly (i.e. is situation exceptional?)

    • Systematic occurrence of some WT ?


Cost 733 wg4 links between weather types and flood events in europe christel prudhomme

Flood events

  • Daily flow data series from different data bases

    • Global Runoff Data Centre (GRDC). Selected 176

    • Flow Regimes from International Network Data (FRIEND): 95

    • French Banque Hydro (with restriction): 132 [not yet analysed]

    • UK National River Archive (NRFA): 87 [not yet analysed]

    • European Water Archive: [not yet retrieved]

    • Total: 358 [later date : 490 + EWA]

  • Selected all over Europe

  • For each catchment select the largest flood peak events

    • Number of flood peak: 3 * number of years

    • Criterium of independence between each selected flood peak

    • POT3 data, with Flood in m3/s, and date


Cost 733 wg4 links between weather types and flood events in europe christel prudhomme

Data analysis

  • For each river basin

    • POT3 series: flood magnitude, date

    • For each day find corresponding Classification/Weather Type ClassA[WTi]

  • Index 1: Frequency anomaly of weather types PI1

    • For each river basin

    • PI1 = 100*(freq. ClassA[WTi] during flood day - freq. ClassA[WTi] any day )/ freq. ClassA[WTi] any day

    • If PI1 = -100: ClassA[WTi] never occurred during flood day

    • If PI1 <0 : ClassA[WTi] occurred less often during flood day than usual

    • If PI1 >> 100 : ClassA[WTi] occ. more often during flood day than usual

    • We want to see if, across Europe, some ClassA[Wti] systematically occur more/less often during flood days

    • Can look at days preceding flood as well


Cost 733 wg4 links between weather types and flood events in europe christel prudhomme

Data Analysis (2)

  • Index 2: Persistence of weather type PI2

    • ‘Is the persistence of k days with ClassA[Wti] linked to a flood’

    • Measure the number of times kday with ClassA[WTi] within a window of xday prior to flood events

    • Calculate conditional probability of kday given there is a flood event: PI2

    • Compare PI2 with value expected purely by chance, knowing the probability of occurence of ClassA[WTi] [Binomial/Bernouilli]

    • If PI2 greater than expected by chance, the persistence of ClassA[WTi] at least kday within xday followed by flood event is statistically significant

  • Calculate PI2 and Bernouilli for windows up to 5 days, k day varying from 0 to 5


Cost 733 wg4 links between weather types and flood events in europe christel prudhomme

Results presentation

  • Maps: for each ClassA[WTi] , one dot per catchment

    • PI1 – Positive : back / negative : grey – Size dot: PI1 magnitude

    • PI2 – Significant: black / non significant : grey – Size dot: PI2 magnitude

    • Done for the day of the flood, and up to 5 days before

    • One index per season

    • Huge number of maps (for CEC: 200 * 5 PI1; 200*5*5 PI2)

  • Histographs:for each ClassA[WTi]

    • Proportion of catchments in PI1/PI2 categories

    • Aim: to identify ClassA[WTi] with largest number of catchment with high PI1 / PI2

    • Future: plot diagrams, for each category, with evolution with Lag time; all WT together


Cost 733 wg4 links between weather types and flood events in europe christel prudhomme

Some Results for PI1 – NO CONCLUSION YET – Lag = 1 day


Cost 733 wg4 links between weather types and flood events in europe christel prudhomme

Some examples of Results PI2 – NO CONCLUSION YET


Cost 733 wg4 links between weather types and flood events in europe christel prudhomme

Further work…

  • Analysis for all catchments

    • First need to get data from other databases

    • Work on ‘summary’ graphics

  • Focus on

    • Lag: any evolution on windows of analysis

    • Meaning of PI2 compared to PI1. Which one is best

    • Threshold to assess significance of link between ClassA[WTi] and flood events

    • Regional analysis: catchments in different regions might be linked to different weather type

    • Importance of seasonal analysis

  • Identification of ‘regional flood’ days, depending on the proportion of catchment in study area has a POT3 event that day

  • Continue lit review to have more ideas for analysis!


Thank you

Thank you


  • Login