1 / 24

European Drought Centre

Test-application of COST-733 WTCs: Hydrological drought in North-Western Europe. Objective Identification of weather types associated with the development of severe hydrological drought - in Denmark and UK - Regional hydrological drought defined as deficit in streamflow.

umay
Download Presentation

European Drought Centre

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. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Test-application of COST-733 WTCs: Hydrological drought in North-Western Europe Objective Identification of weather types associated with the development of severe hydrological drought - in Denmark and UK - Regional hydrological drought defined as deficit in streamflow European Drought Centre

  2. Hydrological drought Data: • 38 streamflow stations from Great Britain • 23 streamflow station in Denmark • daily data • natural or naturalized • at least 30 years of data • common standard period: 1964 – 2003 Drought definition • For each station: threshold level method (Qtr=90-percentile) • Identification of regions with “homogeneous” drought occurrence  Regional drought series

  3. Hydrological drought: “Homogenous” regions Great Britain Denmark

  4. Hydrological drought: Regional drought index Index definition • Daily series • Percentage of stations experiencing drought weighted by catchment area • “drought affected proportion of area within one region”  RDI: 0 - 1 Regional drought definition • RDI > 0.7 • Seasonal series: number of drought days per summer (summer season: 16 Apr – 15 Oct )

  5. Hydrological drought: Regional drought index Index definition • Daily series • Percentage of stations experiencing drought weighted by catchment area • “drought affected proportion of area within one region”  RDI: 0 - 1 Regional drought definition • RDI > 0.7 • Seasonal series: number of drought days per summer (summer season: 16 Apr – 15 Oct )

  6. Hydrological droughts: Regional series RDI > 0 RDI > 0.4 RDI > 0.7

  7. Selection of Weather Type Classifications

  8. Selection of Weather Type Classifications Differences in: • methods: PCA, cluster analysis, etc; • input data: MSLP, Z500, etc; • number of types; • similarity index.

  9. Selection of Weather Type Classifications Differences in: • methods: PCA, cluster analysis, etc; • input data: MSLP, Z500, etc; • number of types; • similarity index. • First choices for domain 00: OGWL, SANDRA, TPCAV, TPCA07, PCACA, EZ500C30, EZ500C10

  10. Selection of Weather Type Classifications

  11. Selection of Weather Type Classifications

  12. Selection of Weather Type Classifications

  13. WTs associated with hydrological drought • Identify WTs which are more frequent during droughts and periods leading up to severe drought events  Daily series - first 20 days of the 8 most severe events (= longest droughts)  Seasonal series - 3 summers with most drought days - preceding winters

  14. WTs associated with hydrological drought Frequency anomaly (FA) • Fds = Frequency during drought period (1 year) • Fn = Frequency during that period of the year (1964 – 2001) FA = (Fds - μFn) / σFn

  15. WTs related to severe hydrological droughts • different WTs seem to be related with drought • WTs can have a high positive FA for one event and negative FA for other events • also for WTCs with only few different types

  16. Comparison of identified WTs with composites • mean FA is positive or negative for summer / winter / event / summer and event

  17. Comparison of identified WTs with composites Do WTs with high precipitation have positive mean FA? • TPCA07: no. • TPCAV: a few times for the summer series. • SANDRA: yes, but only once among the first five WTs; more often for summer series. • OGWL: yes, sometimes; more often for summer series.

  18. Correlation analysis for seasonal series Groups of WTs: • positive mean FA over all summers • positive mean FA over all events • positive mean FA over all summers with maximum • positive mean FA over all events with maximum • negative mean FA over all summers • negative mean FA over all events • subjective selection based on composites: positive • subjective selection based on composites: negative

  19. Correlation analysis for seasonal series Results: • highest correlation with group: positive mean FA over all summers • WTCs with highest correlation:OGWL and SANDRA • general low R2

  20. Further work • correlation analysis between daily RDI-series and WT-frequencies during the 30 / 60 / 90 and 180 last days • chose WTC for domain 04 and drought from Great Britain

  21. Conclusions • selection method works better for TPCAV and TPCA07 • problematic when few types dominate too much (SANDRA) • but highest correlation with OGWL and SANDRA • disadvantage of TPCAV and TPCA07:same WT has contrasting effects during summer and winter

  22. Conclusions • selection method works better for TPCAV and TPCA07 • problematic when few types dominate too much (SANDRA) • but highest correlation with OGWL and SANDRA • disadvantage of TPCAV and TPCA07:same WT has contrasting effects during summer and winter  WTC based on other input data (total water column) ?

More Related