Global Flood Awareness System Joint Research Centre: J. Thielen, P. Burek, B. Revilla, M. Kalas, P. Salamon, V. Thiemig, T. de Groeve, A. de Roo, V. Ntegeka, F. Hirpa, Z. Zajac ECMWF: F. Pappenberger, E. Dutra, B. Kreminszki, L. Alfieri http://floods.jrc.ec.europa.eu Recovery
Subsidiarity in disaster risk reduction Forecasting and detection Global EO models Emergency response Global Humanitarian Aid Continental / supra-national EFAS River Com. Continental / supra-national Coordination at trans-national level National NMS, NHS Radar, gauges National Coordination at national level Regional Regional auth. models Regional Assisting neighbor regions Local Models, gauges, CP Civilians (112) Local Preparedness actions Immediate response 2 2
Objectives of Global Flood Awareness System (GloFAS) Novel products for international aid - Early flood warning information for preparation of aid assistance in the case of major floods - Worldwide comparable information Added value for National Hydrological Services - Catchment based information with 10-30 days lead-time - Probabilistic information (ensemble predictions)
GloFAS: Modelling framework Output from global NWP land-surface scheme forecast: HTESSEL (ECMWF) (Hydrology Tiled ECMWF Scheme for Surface Exchange over Land) -Surface heat & evaporation -Soil water budget Output: surface flux& subsurface flux Routing model: Simplified LISFLOOD (JRC) -Groundwater -Routing (kinematic wave) Post-processing for end users
Global Flood Awareness System Set-up Input: global spatial data Hydro-Meteo model Output: global daily discharge ECMWF ERA-INTERIM Re-ANALYSIS for discharge climatology (1979-2010) ECMWF VAREPS for forecasts since June 2011 Spatial resolution 0.1 degree
Simulation vs. Observation: Niger 6
Simulation vs. Observation: Ubangi 7
Skill score analysis Pierce skill score of simulated versus observed discharge for 620 selected stations 19 February 2014 8
Estimating flood magnitude in GloFAS Era-Interim HTESSEL/Lisflood Simulated discharge time series Q in m 3/s 1200 1000 800 600 400 200 0 1 366 731 1096 1461 1826 Days Thresholds are derived from simulated time series. The same model set-up and parameterisations are used in the forecasts to remain model consistent Thresholds Q20 Q5 Q2 Q1.3 Return period statistics
How does GloFAS work Finding simple ways to communicate complex information Easy and fast access to flood forecast via: Password protected Web Interface Updates every day Easy understandable hotspot maps, flood probability maps, flood threshold exceedance Hydrologically relevant meteo information 19 February 2014 10
GloFAS forecast example 15 July 2011
GloFAS and SOS/WaterML: GloFAS forecasts are already published online on a password protected website But: for a better integration into other systems more is needed Providing GloFAS simulation results at points where observed river discharge is available using the international standards for hydrologic information exchange such as WaterML2 and its associated data sharing services we are currently testing to provide. Benefits: Verification of model simulations against observations globally Better integration of GloFAS forecasts into national forecasting services
Next steps: Improving GloFAS Meteorological forcing: assess different global meteorological forcings (ERA20C, Princeton's Global Meteorological Forcing Dataset, GPCC, etc.) Hydrological model: improving river network, inclusion of lakes and reservoirs, improve transmission losses, include water use User interface: Create a stand alone user web interface for easy forecast access Web services: Improve accessibility of GloFAS forecasts using WMS and SOS
For more information: Paper published in HESS: http://www.hydrol-earth-syst-sci.net/17/1161/2013/hess-17-1161- 2013.html Contact: peter.salamon@jrc.ec.europa.eu 14