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On the Flood Forecasting at the Bulgarian Part of Struma River Basin Dobri Dimitrov

НАЦИОНАЛЕН ИНСТИТУТ ПО МЕТЕОРОЛОГИЯ И ХИДРОЛОГИЯ NATIONAL INSTITUTE OF METEOROLOGY AND HYDROLOGY Българска Академия на Науките Bulgarian Academy of Science бул. Цариградско шосе N 66 66 Tzarigradsko Shosee boul София 1184 1184 Sofia, BULGARIA

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On the Flood Forecasting at the Bulgarian Part of Struma River Basin Dobri Dimitrov

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  1. НАЦИОНАЛЕН ИНСТИТУТ ПО МЕТЕОРОЛОГИЯ И ХИДРОЛОГИЯ NATIONAL INSTITUTE OF METEOROLOGY AND HYDROLOGY Българска Академия на Науките Bulgarian Academy of Science бул. Цариградско шосе N 66 66 Tzarigradsko Shosee boul София 1184 1184 Sofia, BULGARIA тел. 9753986, тх. 22490 rthsf bg tel. +3592 9753986, tx.22490 rthsf bg факс 9884494,9880380 fax. +3592 9884494, 9880380 ------------------------------------------------------------------------------------------------------------------------------------- On the Flood Forecasting at the Bulgarian Part of Struma River Basin Dobri Dimitrov Krassimir Stanev.

  2. Bulgaria - contribute waters to ·  Danube basin ·  Black Sea basin ·  Aegean Sea basin

  3. Struma river basin • Transboundary basin collecting waters from Yugoslavia, Bulgaria, Macedonia and Greece. • Pronounced mountain character with average elevation of the basin area 900 m. • About half of the basin territory is covered by forest. • Continental type climate at the north part of the basin with Mediterranean influence, better expressed at south. • Generates flush floods most often of snowmelt – rainfall type. • Division into sub-basins was made according to: homogeneity of landscape conditions; availability of monitoring hydro-meteorological stations; size of catchment area.

  4. Annual distribution of precipitation and discharges (P – Blagoevgrad at the middle of the basin, Q – MarinoPole at the closing cross-section) Annual distribution of air temperature (elevation –Sandanski 206 m, Kustendil 521 m, Musala 2925 m) Example of flood wave and the contribution of different parts of the basin

  5. Stations delivered and installed by “ScientAct” SA _______________ The data logger “Osogovo” region Reservoir “Kalin” Village “Kresna” Village “Strumeshnitza”

  6. Principle scheme of the modeling and forecasting approach Increased lead time of the hydro forecast with two days ahead meteo forecast: Adjustment of the flood forecast with real time observations: Limited Area High Resolution Meteorological Forecasting Model “ALADIN” Spatial analysis of the precipitation fields applying METEOSAT data Hydrological Rainfall/Snowmelt - Runoff Forecasting Model One day ahead forecast, according to basin concentration time Final adjustment of hydrological forecast using dynamic adaptation stochastic models

  7. Data sets used (observed, forecasted) • Daily averages for the period 1st September 2001 to 30th April 2003.; • Daily averages for the period 1st September 1990 to 31st August 2001; • 24 hours forecasts for the period 1st September 2001 to 30th April 2003.; • 48 hours forecasts for the period 1st September 2001 to 30th April 2003. • Comparison between the observed and forecasted meteorological data • the accuracy of the 24 hours forecasts is slightly better than the 48 h. ones; • the precipitation is overestimated, while air temperature is slightly underestimated; • slight increase of forecasting errors with elevation is noticed; • Forecasts are not suitable for direct calculations of the water budget. • HBV parameters calibration • The accumulated differences and Nash - R2 criteria were used; • Optimization over the first 10 years long dataset was done for each sub-basin separately; • Finally HBV was optimized over the 24 and 48h. Forecasts for each sub-basin; • Conflict situations may occur because of wrong hydrometeorological data or forecasts.

  8. HBV graphical output, used for parameters optimization

  9. Spatial distribution of some accuracy criteria

  10. Observed vs. forcasted precipitation and discharges for Kresna sub basin

  11. Conclusions • HIRLAM Aladin indicates very well the rainfall phenomena and could be quite useful in flood forecasting; • Aladin usually overestimate the higher rainfalls; • The hydrological forecasting results are slightly better for the 48 hours forecast than the 24 hours forecast; • The results from the use of HIRLA Models might be better in case of use of some kind of additional adaptation scheme. • Acknowledgements • Special thanks to the EC supporting this work via the projects: • PHARE CBC BG9803.03.02.02 “Flood Forecasting and Warning System for the Struma River Basin” • 5th FP EVG1-CT-1999-00011 “European Flood Forecasting System” EFFS

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