International Sava River Basin Commission

Transcription

1 International Sava River Basin Commission Pilot project on climate change: Building the link between the Flood Risk Management planning and climate change assessment in the Sava River Basin - climate change scenarios and adaptation measures University of Ljubljana; Faculty of Civil and Geodetic Engineering Faculty of Mathematics and Physics,

2 Pilot project on climate change REPORT ON METEOROLOGICAL PART OF DEVELOPMENT OF CLIMATE PROJECTIONS FOR SAVA RIVER BASIN part one CLIMATE CHANGE IMPACT ON FLOOD DISCHARGE - HYDROLOGY REPORT - part two FLOOD PROTECTION AND ADAPTATION MEASURES part three

3 REPORT ON METEOROLOGICAL PART OF DEVELOPMENT OF CLIMATE PROJECTIONS FOR SAVA RIVER BASIN Authors: prof. dr. Jože RAKOVEC, dr. Andrej CEGLAR

4 DATA 16 different ENSEMBLES GCM-RCM model runs simulations for the 21st Century by IPCC SRES A1B emission scenario horizontal resolution of RCM simulations is 0.25 degree. meteorological variables; daily precipitation, daily mean air temperature and monthly evapotranspiration. E-OBS data (daily precipitation) between 1961 and 2010

5 Table 1: ENSEMBLES GCM RCM simulations on spatial resolution 0.25 degree, which were used in our study. For METO-HC GCM, there are standard, low and high sensitivity runs (differing by the value of entrainment parameter, which controls the mixing between ascending plumes and the surrounding environment in the HADCM3 parameterization of convection; for details, see van der Linden and Mitchell, 2009) RCM GCM C4I RCA3 DMI HIRHAM 5 ETHZ CLM GKSS CLM METO-HC LOW METO-HC STD 2100 METO-HC HIGH 2100 MPIMET ECHAM5 NERSC BCM CNRM ARPEGE IPSL KNMI RACMO2 METNO HIRHAM METO- HC HADRM MPI REMO SMHI RCA

6 evaluation of climate models against observed data The transfer function was derived using data from 1961 to transfer functions applied to RCM simulations from 1991 to the procedure was repeated for each of climate model runs, each month and each grid cell. For each grid point, 90th percentile of daily precipitation intensity was calculated for each season and used to divide the PDF into two parts. The first part was in the range from 0.1 mm/day to 90th percentile, the second part above 90th percentile. Two parts of the PDF are then normalized and PSS is calculated for each of them. Modified PSS is better to assess the quality of simulation of extreme precipitation events.

7 BIAS CORRECTION OF MODEL SIMULATIONS correcting rainfall frequency correcting precipitation intensity correcting temperature simulations procedure for the Sava River Basin climate projections for Sava River Basin

8 procedure for the Sava River Basin The bias correction procedure was applied to each of 16 model runs Histograms were defined for each grid point, using the data from 16 model runs and observational data from E-OBS. Wet day frequency was corrected by fitting the gamma distribution to simulated and observed precipitation 6 parameters were therefore defined for each grid cell: 2 parameters for gamma distribution and 1 parameter for wet day frequency (from simulations and observations). Procedure was repeated for temperature data, using normal theoretical distribution.

9 climate projections for Sava River Basin transfer functions from the period validation period , Three periods were used for assessing future climate change: , and Absolute values for seasonal precipitation and extreme precipitation were determined

10 Results the bias correction procedure improved the quality of model simulations over the basin, except over the central part of Bosnia and Herzegovina. The quality of temperature simulations was generally improved in spring, summer and autumn, whereas in winter there were no significant differences across the basin Projections of seasonal precipitation were made for three future periods: (P1), (P2) and (P3).

11 extreme daily precipitation indices absolute values were calculated for three future periods a) b) c) 95th percentile of daily seasonal precipitation interannual mean of maximum 24 hours precipitation interannual mean of maximum 48 hours precipitation d) daily precipitation intensity with return period 20 years e) daily precipitation intensity with return period 100 years

12 Precipitation intensities with 20 and 100 years return period are expected to increase in spring in central part of the basin. In summer, precipitation intensity with return period 100 years is expected to increase in parts of eastern basin; In autumn, a general increasing of 20 years and 100 years return level can be observed over majority of the basin territory. Highest increase of return levels can be observed in southern part of the basin.

13 temperature projections All models in the ensemble agree in the sign of temperature change for all seasons over the whole basin area. In spring, mean temperature is expected to increase between 2 C and 4 C by the end of the century. The highest increase can be expected over southern part of the basin. The most significant increase in variability is expected for the summer and winter. In spring and autumn, standard deviation is expected to increase for 1 C by the end of the century, whereas in winter and summer expected increase is approximately 1.5 C for the whole basin.

14 CLIMATE CHANGE IMPACT ON FLOOD DISCHARGE - HYDROLOGY REPORT prof. dr. Mitja Brilly. doc. dr. Mojca Šraj. mag. Andrej Vidmar, Miha Primožič, mag. Maja Koprivšek

15 The HBV model of SRB List of sub-basins. # Sub-basin number Sub-basin name Stream Sub-basin area [km 2 ] 1 I. Sava I Sava II. Sava II Sava III. Kolpa Kolpa IV. Sava III Sava V. Una Una VI. Sava IV Sava VII. Vrbas Vrbas VIII. Sava V Sava IX. Bosna Bosna X. Sava VI Sava XI. Drina I Drina XII. Drina II Drina XIII. Sava VII Sava All sub-basins

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19 Input data The following input data are required to calibrate/run the model: -precipitation (32 measurement stations -temperatures (8 measurement stations -discharge data (12 measurement stations -potential evapotranspiration (8 stations) For the calibration - period from June 1 to December 31, For verification - period September 1, 1978 to November 30, 1978

20 Model calibration peak discharges in m 3 /s.

21 data transformation The precipitation data in the meteorological report are in raster form and we collected the data from the cell in which the precipitation station was positioned. Maximum daily values of precipitation measured in 1974 are slightly lower than the values of EOBS. There is a high discrepancy between the EOBS data and the measurements in the area of the Dinaric Mountains, especially in Montenegro Summer daily precipitation is slightly higher than in autumn due to higher evaporation. However, runoff in the autumn season is much higher and for further calculations and analysis we chose the autumn values

22 Precipitation data Probability of maximum daily precipitation (mm) in a year and data from Table 8. return period Max prec. V1 V2 V3 V4 Station name in 1974 EOBS_20 EOBS_100 20_ _41-70 Ljubljana 190,7 106,3 72,2 95,8 88,5 110,0 110,0 148,0 Rateče 214,9 121,2 83,2 42,6 131,9 171,1 147,5 191,3 Zagreb 117,2 65,9 45,2 34,5 43,6 50,3 52,0 67,4 Slavonski brod 104,1 59,1 40,9 31,6 31,1 38,6 36,3 47,8 Bihač 155,3 89,5 62,8 82,9 69,7 83,4 81,0 101,8 Bugojno 119,9 66,2 44,5 40,4 38,0 50,4 44,8 66,6 Sarajevo 120,0 67,0 45,5 36,0 37,6 42,6 49,6 66,5 Banja luka 86,0 57,4 45,8 56,2 34,0 44,0 38,9 53,4 Beograd 126,8 66,3 41,9 39,4 36,0 46,1 46,4 66,7 Sjenica 89,9 53,3 38,5 45,1 42,9 51,3 55,9 77,6

23 EOBS data. Precipitation distribution for 100-year return period

24 climate change modelling of discharges The hydrological model represented in Chapter 1 was used for modelling of the impact of climate change forecasts on the Sava discharges at selected stations. For modelling of climate change the same data as those for the calibrated model for 1974 were used. Variant calculate s with change of set of maximum daily rainfall Variants of forecast calculated with increase of temperature: 0.8 oc in autumn in the period , 1.8 oc for autumn in the period and 2.9 Co in the period

25 Result of modelling recent climate flood peaks (in m 3 /s). Sub-basins WS measured calibrated EOBS_ret20 EOBS_ret100 Sava I Čatež Kolpa Šišinec Sava II Crnac Una Kostajnica Sava III Jasenovac Vrbas Delibašino selo Sava IV Slavonski Brod Bosna Doboj Sava V Županja Drina I Bajina Bašta Drina II Kozluk Sava V Sremska Mitrovica confluence with Danube

26 Result of modelling climate change flood peaks with EOBS data for 20-year return period (in m 3 /s). Subbasins WS EOBS m 3 /s m 3 /s 41-7 m 3 /s m 3 /s % % % Sava I Čatež Kolpa Šišinec Sava II Crnac Una Kostajnica Sava III Jasenovac Vrbas Delibašino selo Sava IV Slavonski Brod Bosna Doboj Sava V Županja Drina I Bajina Bašta Drina II Kozluk Sava VI confluenc e Sremska Mitrovica average max min

27 Results of modelling climate change flood peaks with EOBS data of the 100-year return period (in m 3 /s and %). Subbasins WS EOBS m 3 /s m 3 /s 41-7 m 3 /s m 3 /s % % % Sava I Čatež Kolpa Šišinec Sava II Crnac Una Kostajnica Sava III Jasenovac Vrbas Delibašin o selo Sava IV Slavonski Brod Bosna Doboj Sava V Županja Drina I Bajina Bašta Drina II Kozluk Sava VI Sremska Mitrovica confluenc e average max min

28 Probability function - WS Čatež 10 cm 80 m3/s

29 Probability function - WS Sremska Mitrovica 0,5 m 905 m3/s

30 SRB Hazard characteristics Orographic impacts in head part of watershed of Alpine and Dinaric mountains, reduced by karst poljes and alluvial deposits. Huge inundated areas downstream of town Sisak (flood discharges drop down). Sediment transport on mouth of tributaries and main stream. Hystorical events, The Drina River 1896 flood

31 FLOOD PROTECTION AND ADAPTATION MEASURES prof. dr. Mitja Brilly.

32 Integrate flood risk safety structural measures space history non-structural measures cross-border collaboration forecasting planning flood risk map ways of communicating Flood Directive ways of understanding The EU Water Framework Directive informing and warning experts public NATURA 2000 consultation

33 multiple integrated approach STRATEGIES AND TOOLS FOR FLOOD Loss REDUCTION US, FEMA 1992 (FLOODPLAIN MANAGEMENT IN THE UNITED STATES: AN ASSESSMENT REPORT) GUIDANCE ON WATER AND ADAPTATION TO CLIMATE CHANGE UN, (IWRM, ICZM, IFM), SEA Strategic environmental assesment DANUBE STUDY CLIMATE CHANGE ADAPTATION, 2012 ICPDR - Anthropogenic acting with for instance land use changes, silting up of flood plains, overgrowth of flood channels by vegetation or river regulation will also influence future flood occurrences.

34 HAZARD VULNERABILITY 10-year return period 100-year return period 1000-year return period probable maximum floods agriculture urban areas important structures nuclear power plant environment RISK

35 STRATEGIES AND TOOLS FOR FLOOD Loss REDUCTION US, FEMA 1992 STRATEGY A: MODIFY SUSCEPTIBILITY TO FLOOD DAMAGE AND DISRUPTION STRATEGY B: MODIFY FLOODING STRATEGY C: MODIFY THE IMPACT OF FLOODING ON INDIVIDUALS AND THE COMMUNITY

36 SRB strategy Adaptation needs to be flexible. Lack of knowledge and experience (social scientist know nothing about natural science or engineering) Conflicts: WFD - FD More room for river Giant levees Victims Freeboard (mapping and structures)

37 Hot spots

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