1. HYDROLOGICAL BALANCE OF THE DANUBE RIVER BASIN: AN INTERCOMPARISON STUDY Lucarini, V. (1,2), Kriegerova, I. (2), Danihlik, R. (2), Speranza, A. (1,2) (1) Department of Mathematics and Computer Science, University of Camerino, Italy (2) CINFAI Unit of Camerino, Italy Contact: valerio.lucarini@unicam.it I N T R O D U C T I O N The assessment of the reliability of the current climate models in the representation of the climatology of the hydrological balance, both in terms of mean value and variability, of the basin of the Danube river is crucial, because of its relevance at social, economical and environmental level. This the reason for its centrality in the project HYDROCARE. The hydrological balance of the Danube basin bears at least a twofold direct relevance to the climate of the Mediterranean region. Firstly, the Danube runoff gives a relevant contribution of freshwater flux into the Mediterranean sea. Secondly, given the geographical position and the complex orography of the basin, the Danube depends mostly on precipitated water of Mediterranean origin. Precip Evap MODELSDr.data CLM_GKSS_germany0,910,66 HIRHAM_METNO_norway0,900,53 CHRM_ETH_swiss0,870,70 PROMES_UCM_spain0,87-0,16 RACMO_KNMI_netherland0,930,71 REMO_germany0,880,72 SMHI_25_sweden0,840,75 SMHI_50_sweden0,890,79 DMI_12_denmark0,850,73 DMI_25_denmark0,870,76 DMI_50_denmark0,800,75 ICTP_italy0,840,66 Precip vs Evapor DRIVING DATA0,90 CLM_GKSS_germany0,81 HIRHAM_METNO_norway0,58 CHRM_ETH_swiss0,84 PROMES_UCM_spain0,04 RACMO_KNMI_netherland0,69 REMO_germany0,82 SMHI_25_sweden0,87 SMHI_50_sweden0,89 DMI_12_denmark0,91 DMI_25_denmark0,90 DMI_50_denmark0,92 ICTP_italy0,80 Balance (P - E)dr.data obs.data DRIVING DATA0.02 CLM_GKSS_germany0.920.02 HIRHAM_METNO_norway0.920.05 CHRM_ETH_swiss0.890.08 PROMES_UCM_spain0.900.06 RACMO_KNMI_netherland0.930.11 REMO_germany0.860.15 SMHI_25_sweden0.85-0.08 SMHI_50_sweden0.890.08 DMI_12_denmark0.86-0.01 DMI_25_denmark0.85-0.01 DMI_50_denmark0.780.14 ICTP_italy0.850.19 Import to GIS (ArcGIS 9.0) and new point layer creation Transformation to the Lambert Azimuthal Equal Area projection Point layer to polygon layer transformation Estimation of an integral value of selected characteristics(P, E, R) for each polygon of catchment Estimation of one integral value of selected characteristics(P, E, R) for the whole catchment area NC files to GIS format transformation Using NetCDF tool for conversion from NC to MAT file MAT file of rotated latitude and longitude creation Copy to XLS and DBF file creation Data collection (NC format) Observed discharge data PrecipitationRunoffEvaporation Using Thiessen polygons tool 6th European Conference on Applied Climatology Ljubljana, Slovenia, 4 – 8 September 2006 D A T A S O U R C E A N D P R O C E S S I N G Data sources: 1.ERA-40 reanalysis data 2.NCEP/NCAR reanalysis data 3.Regional Climate Models Control data – The Prudence project data portal 4.Global Runoff Data Center – GRDC 5.Met Office, Hadley Center, UK (driving data) Daily values of: 1.Precipitation (P) 2.Evaporation (E) 3.Runoff (R) 4.Observed discharge data (GRDC) Area of interest: Danube river basin - 807 000 km 2 Period of 30 years: 01.01.1961 – 31.12.1990 Calculation of integral values (over the area, using GIS tools) of: 1.P, E, R 2.Precipitation – Evaporation (hydrological balance), (P - E) Fig. 1 A scheme of data processing Basic equation of hydrology: D A N U B E C A T C H M E N T - G I S O U T P U T Fig. 2 GIS data processing a) point layer creation over the catchment areab) point layer to Thiessen polygon layer transformation c) The Lambert Azimuthal Equal Area projection of the area of interest within Europe space R E S U L T S Fig. 3a: average balance vs. variabilityFig. 3b: average balance vs. average runoff Fig. 3c: average evaporation vs. average precipitation Fig. 3d: average runoff vs. variability Fig. 4a: Seasonal variation of precipitation Table 1 shows precipitation vs. evaporation correlation coefficients calculated for datasets of the driving model and of the regional models‘. Tables 2 and 3 show correlation coefficients calculated for datasets of regional models vs. driving data for precipitation, evaporation, and balance. In all cases the correlations are high and positive, except PROMES_UCM. C O N C L U S I O N S NCEP and ECMWF Reanalyses are largely inadequate for representing the hydrology of the Danube basin; RCMs feature large discrepancies for the climatology of water balance: most underestimate the discharge of the Danube; they act as differently parameterized downscaling of the driving GCM; Only few models (METNO, SHMI, KNMI) provide estimates which are consistent with the observed discharge values of the Danube at its Delta; Most RCMs have a large and anticipated mean seasonal cycle (small damping) The agreement between mean integrated P-E and runoff is not perfect; The considered approach relies on the mass conservation principle at the air- land interface and bypasses the details of soil modelling and will be used for analyzing climate change scenarios. T H E P R O J E C T H Y D R O C A R E HYDROCARE has been approved in the 3rd call of the INTERREG IIIB - CADSES programme of the EU. The project will last 2 years starting January 1st 2006, its budget is about 2.5 M€ and it involves 11 institutions from 6 countries (Italy, Germany, Greece, Poland, Romania, and Slovakia). The project is coordinated by an Italian Lead Partner, CINFAI, which is a consortium of about 20 Italian Universities. The mission of HYDROCARE is to study the hydrological cycle of the CADSES area by adopting an integrated and multidisciplinary approach. Web-site: http://www.hydrocare-cadses.net. http://www.hydrocare-cadses.net Fig. 4b: Seasonal variation of evaporation Fig. 4c: Seasonal variation of runoff Tab. 1: Correlation Precip. vs. Evap Tab. 2: Correlation RegMod vs. Driv. Mod. For Precip. and Evap Tab. 3: Correlation RegMod vs. Driv. Mod. For Balance