st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 Drought Monitoring with Hydrological Modelling Stefan Niemeyer IES - Institute for Environment and Sustainability Ispra - Italy http://ies.jrc.ec.europa.eu/ http://www.jrc.ec.europa.eu/
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 Why Modelling? (Hydrological) models simulations confirm/reject assumptions of the (hydrological) system if proved to be valuable, the selected aspects of reality can be reproduced in the chosen spatial and temporal resolution information without detailed observation / measurement of the variables of interest! potential for future simulations, forecasting, etc. drawback: Calibration & Validation!
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 Hydrological Models = representation of the hydrological cycle precipitation (rain / snow) partition on land surface into interception, direct runoff, and infiltration (soil) evaporation, transpiration from vegetation soil water balance, soil moisture (vertical flow, lateral?) groundwater storage (and flow) runoff production (surface runoff, interflow, base flow, ) hydraulic routing in the river bed
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 Hydrological Models spatial scale and resolution spatial reference is the river catchment area typically regional application (some 000 km ) depending on model type, the region of study is divided into smaller homogeneous areas polygons or regular grids grid spatial resolution typically from 00 m to -5 km
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 5 Hydrological Models temporal scale and resolution simulation of days to years and decades temporal resolution depending on application: hourly to 6- hourly for flood modelling daily to monthly for water balance estimation
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 6 Hydrological Models type of models: physically based: process oriented, highly parameterized statistical models: based on statistics rather than physics lumped models: low spatial differentiation, average values for large areas distributed models: high spatial differentiation, high resolution input data required
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 7 Hydrological versus Atmospheric Models atmospheric processes <> hydrological processes several levels in atmosphere <> surface meteorology only land surface, soil in one layer <> many vegetation and soil layers high temporal resolution (hours) <> typically daily temporal resolution low spatial resolution (50+km) <> typically km spatial resolution never local, regional, often global <> local / regional / catchment turbulent flux densities of latent heat <> evapotranspiration (mm) But: Both models types extend increasingly into the other domain. Future: coupled models! For Global Circulation Models (GCM) link to water balance models For Regional Climate Models (RCM) link to rainfall-runoff models requires collaboration of two traditionally separated scientific communities!
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 8 Hydrological Model at JRC LISFLOOD a hydrological rainfall-runoff model capable of simulating the hydrological processes in a catchment developed by the FLOODS Action of IES/JRC specific objective to produce a tool for use in large and transnational catchments for a variety of applications, including: Flood forecasting Assessing the effects of river regulation measures Assessing the effects of land-use change Assessing the effects of climate change
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 9 Hydrological Model at JRC: LISFLOOD sketch of processes included in The model
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 0 LISFLOOD A physically based distributed rainfall-runoff model programmed in a dynamic GIS-language Rainfall/Snow partitioning Interception Evapotranspiration Leaf drainage Snow melt Soil water processes Groundwater flow River channel flow (kinematic and diffusion wave) Reservoir operations Retention storage / polders Lakes Dyke breaks (in prep)
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 LISFLOOD (static) input data CIS CORINE land cover EU Soil Data Base Point Data Cross sections, reservoirs, lakes, polders,
European Flood Alert System st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 medium-range weather forecasts forecasting synoptic stations observed discharge soil moisture, VI s, snow cover,.. (RS) forecast ensembles forecast reception and processing static data data reception and processing downscaling model calibration LISFLOOD model run discharge forecast data assimilation updating evaluation Long-term water balance statistical thresholds ensembles critical value exceedance flood alerts probability
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 Drought Products from LISFLOOD simulations at JRC. low flow estimates applied to climate change scenarios. soil moisture estimates soil moisture anomaly Soil moisture forecasts (medium-range) Common: 5 km spatial resolution Daily time step
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 Low flow estimates from LISFLOOD model driven by high-resolution regional climate simulations two periods of each 0 years: end of previous & end of this century scenario derived from greenhouse gas emission scenario A of IPCC HIRHAM RCM of PRUDENCE project km spatial resolution
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 5 Low flow estimates from LISFLOOD simulation of time series of daily discharge 7-days moving average, construction of flow duration curve derivation of annual minimum flow for 0 years and both model runs block maxima and partial duration series to obtain minimum flows and flow deficits scientific publication: Feyen & Dankers (009) J. Geophys. Res.,, D76, 009
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 6 LISFLOOD calibration 8 parameters controlling: infiltration, snowmelt, overland and river flow, residence times in the soil and subsurface reservoirs estimated in catchments by calibrating the model against historical records of river discharge at least years between 995 and 00 For catchments without discharge measurements simple regionalization techniques (regional averages) were applied to obtain the parameters
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 7 Location of the discharge gauging stations used in the calibration of the hydrological model (indicated by the small gray circles) and for validation of the climate driven simulations (indicated by the larger white circles). Feyen & Dankers (009).
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 8 Change in the estimated minimum flow in the scenario run relative to the control run Feyen & Dankers (009)
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 9 Soil moisture estimates from LISFLOOD available at EDO
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 0 Daily Soil Moisture Map.8..6.0..8..6 5.0 very wet very dry
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 Daily Soil Moisture Anomaly - - - - 0 wetter normal drier
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 Forecasted Soil Moisture Anomaly - - - - 0 wetter normal drier
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 Regional soil moisture information
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 5 Validation: Comparison with independent products on top-soil moisture: Global Soil Moisture Archive derived from ESA ERS scatterometer data Provided by Vienna University of Technology (W. Wagner) 99 000 daily (Surface wetness) or decadal (Soil Water Index) resolution ca. 50 km spatial resolution
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 6 Global Soil Moisture Archive http://www.ipf.tuwien.ac.at/radar/ers-scat/home.htm
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 7 ERS - and - satellites, Scatterometer radar Orbit Type: Near-circular, polar, Sun-synchronous Altitude: 78 to 785 km Inclination: 98.5 deg. Period: About 00 minutes Orbits per day:. Repeat cycle: -day, 5-day and 76-day Frequency: 5. GHz (C-band) Bandwidth: 5.55 MHz Polarisation: Linear Vertical Spatial resolution ~ 5 km Swath width ~ 500 km Swath stand-off 00 km to right of sub-satellite track Localisation accuracy ± 5 km Radiometric resolution 6 %
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 8 Soil moisture retrieval Topsoil (5 cm) moisture obtained by means of change detection algorithms. Daily values Soil Water index obtained by means of an antecedent moisture model. One value every ten days. The T value has been determined by calibration on ground data
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 9 Comparison between LISFLOOD and ERS/SCAT derived soil moisture estimates: Correlation and RMSE Dependency from base information Variogram analysis Scaling behaviour
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 0 5.5 corr. coeff.=0.6 - RMSE=0.665 - Average rainfall 56 0 0 5 0 0.5 0 60 80 0 0 0 0 50 60 0 pf.5 0 P(mm) 5 50 pf ERS.5 60 70 5 pf LF.5 99 99 995 996 997 998 999 000 year 80
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 5 month 5 month 5 month 5 month pf LF pf LF pf LF pf LF 5 pf ERS month 5 5 5 pf ERS month 6 5 5 pf ERS month 7 5 5 pf ERS month 8 5 pf LF pf LF pf LF pf LF 5 pf ERS month 9 5 5 pf ERS month 0 5 5 pf ERS month 5 5 pf ERS month 5 pf LF pf LF pf LF pf LF 5 pf ERS 5 pf ERS 5 pf ERS 5 pf ERS
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 RMSE and R calculated in the temporal domain RMSE has an average of 0.5, and a standard deviation of 0.6. Given the soil texture features, a 0.05 m /m error ranges between 0.8 and.0 pf units at wilting level and between 0. and 0.60 pf units at field capacity. Legend rmse RMSE = N ( x x N ) Value 0
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 RMSE and R calculated in the temporal domain R has an average of 0.8 and a standard deviation of 0.0. cov( x, x ) = ( x µ )( x µ ) N N R( x, x ) = cov( x cov( x, x, x ) ) cov( x, x Legend corrcoeff Value ) -
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 Correl. coeff. 0.8 0.6 0. 0. 0-0. -0. -0.6-0.8 Legend - 0 0.5.5 RMSE 5 6 5 6
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 5 RMSE and R calculated in the temporal domain R has an average of 0.8 and a standard deviation of 0.0. RMSE has an average of 0.5, and a standard deviation of 0.6. Given the soil texture features, a 0.05 m /m error ranges between 0.8 and.0 pf units at wilting level and between 0. and 0.60 pf units at field capacity. The ERS/SCAT derived and the LISFLOOD modelled soil suction have a good agreement over large regions, with almost 90% of the area having a positive R and 66% having RMSE<0.5. The two datasets show large differences in the Alpine region, in eastern Spain, in northern Scandinavia and on the Carpathian mountains.
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 6 Comparison between LISFLOOD and ERS/SCAT derived soil moisture estimates: Correlation and RMSE Dependency from base information Variogram analysis Scaling behaviour
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 7 POTENTIAL ERROR SOURCES SOIL FEATURES DEPTH TEXTURE METEOROLOGICAL INPUTS POINT DATA INTERPOLATION PROCEDURES LISFLOOD MODEL SOIL MOISTURE PROCESSES FROZEN SOILS SNOW ERS-SWI CHANGE DETECTION MISSING AND FROZEN SAMPLES Predictor Explained variance RMSE R Elevation 8% 8% st layer soil depth 8% 0% Average annual rainfall % 0% Annual rainfall coefficient of variation % % % of missing samples 5% 0% % of snow/ice covered samples 0% 6%
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 8 Comparison between LISFLOOD and ERS/SCAT derived soil moisture estimates: Correlation and RMSE Dependency from base information Variogram analysis Scaling behaviour
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 9 5 km LISFLOOD 5 km ERS/SCAT 50 km 0 0 60 80 00 0 0 60 80.5 6.58 0.5 6.5 8.5.5.5.5 00 50 00 50 00 0 6 8 0 6 8 0
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 0 50 km LISFLOOD 50 km ERS/SCAT 50 km.5.5 6 6 8.5 8.5 0 0.5.5 6 6 8.58.5 0 6 8 0 6 8 0 0 6 8 0 6 8 0
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 00 km 0.5 LISFLOOD 00 km 0.5 ERS/SCAT 00 km.5.5.5.5.5.5.5.5.5.5 5.5.5.5.5 5.5.5 5.5 5 5.5 5
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 Final remarks The ERS SWI derived and the LISFLOOD modelled soil suction have a good agreement over large regions, with almost 90% of the area having a positive R and 66% having RMSE<0.5. The two datasets show large differences in the Alpine region, in eastern Spain, in northern Scandinavia and on the Carpathian mountains.
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 Outlook implement best-calibrated version of LISFLOOD with focus on soil moisture estimates look for alternative land surface schemes that include processes missing in LISFLOOD, but relevant for droughts (e.g. capillary rise) first pilot study on comparison of LS models: changing requirements, now also towards global applications additional drought information derived e.g. from ET estimates (EF?) resulting in the recommendation of the Community Land Model CLM.0 (http://www.cgd.ucar.edu/tss/clm/) increasing availability of RS products on soil moisture ERS/Metop (Eumetsat SAF), SMOS (ESA 009), SMAP (NASA 0) further comparison and verification, data assimilation?
st Joint EARS/JRC International Drought Workshop, Ljubljana,.-5. September 009 thank you!