Building a European-wide hydrological model

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Building a European-wide hydrological model 2010 International SWAT Conference, Seoul - South Korea Christine Kuendig Eawag: Swiss Federal Institute of Aquatic Science and Technology

Contribution to GENESIS 7th Framework EU project Groundwater and Dependent Ecosystems: NEw Scientific and Technical BasIS for Assessing Climate Change and Land-use Impacts on Groundwater Systems 25 Partners from 17 different countries 9 Mio budget 5 years until spring 2013 16 case study sites

Contribution to GENESIS 7th Framework EU project Research topics comprised in 8 workpackages: Hydrogeology, agricultural land-use and management, pollutant transport, microbiology, degradation, biogeochemistry, wetlands, ecology, hydrology, climate change, tracer use, modelling, water engineering, water economy, sociology and policy Our contribution: Model the quantity and quality of groundwater recharge on a continental scale, application of land-use and climate change scenarios

Building a European-wide hydrological model Main objectives Setup up of SWAT for the European continent European Database Calibration and validation with focus on water quantity and quality, blue and green water flow Future scenarios of climate and land use change Assessment of input uncertainty (precipitation) Comparison of station data vs. gridded interpolated observation data

Building a European-wide hydrological model Recent work Setup of SWAT on the European continent using the European Database Preliminary calibration results (40 runs using SUFI-2) Nash Sutcliffe efficiency at around 150 discharge stations

European Continent

European Continent Bergen: 7.8 C / 2250 mm/y Berlin: 9.6 C / 571 mm/y Zurich: 8.5 C / 1000 mm/y Almeria: 18.7 C / 200 mm/y Athens: 17.4 C / 400 mm/y

European Continent Selection of river basins in Europe Volga 8000 m 3 /s 3700 km Rhine 2000 m 3 /s 1200 km Danube 6500 m 3 /s 2900 km

European SWAT database Data sources All datasets obtained from freely available sources on the internet NASA (National Aeronautics and Space Administration) USGS (United States Gelogical Survey) NCDC (National Climatic Data Centre) EEA (European Environmental Agency) KNMI (Royal Netherlands Meteorological Institute) GRDC (Global Runoff Data Centre)

European SWAT database Spatial maps DEM (NASA, 1 km resolution)

European SWAT database Spatial maps DEM (NASA, 1 km resolution) Land cover (CORINE project (EEA) 100 m + USGS 1km )

European SWAT database Spatial maps DEM (NASA, 1 km resolution) Land cover (CORINE project (EEA) 100 m + USGS 1km ) Soil (USGS 10km)

European SWAT database Climate data Climate data from different sources: NCDC ECAD dataset (KNMI) National Met Offices Daily temperature (red) ~2000 stations Daily precipitation (blue) ~1300 stations

European SWAT database Discharge data Discharge, monthly means: Global Runoff Data Centre

Setup of SWAT model Watershed delineation, streams and climate stations: Precipitation stations in green Temperature stations in yellow ~2000 subbasins using the option dominant land-use and soil type for HRU generation size of subbasins between 1000 and 20 000 km 2

Preliminary results After 40 simulations Nash Sutcliffe Efficiency

Preliminary results After 40 simulations Nash Sutcliffe Efficiency

Preliminary results Iberian Peninsula Pattern well represented Calibration will improve with more runs Duero Guadalquivier

Preliminary results North East Europe Pattern well represented Height of peaks not captured Catchment under influence of snow cover Kolva Pechora

Preliminary results Danube upstream and downstream Discharge underestimated Downstream station lacks more water Precipitation values? Hofkirchen Harsova

Conclusion In some regions results look promising for upcoming calibration Problems: Local climate, snow cover Climate data (precipitation) River management, hydropowerplants and reservoirs Solution: Clustering according to local characteristics, different calibration approaches for each region Use of gridded climate data Include reservoirs and inlets

Outlook Comparison of climate station data with gridded interpolated datasets (CRU, at 2.5 latitude by 3.75 longitude resolution and monthly time resolution, other datasets?) Calibration and validation Use of the calibrated model for future scenarios Climate Land use

Thank you for your attention!

Parameter ranges for calibration