Global Flood Awareness System

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Gregory Briggs
7 years ago
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de Roo, V. Ntegeka, F. Hirpa, Z. Zajac ECMWF: F. Pappenberger, E.

1 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 Recovery

2 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

Continental / supra-national Coordination at trans-national level National NMS, NHS Radar, gauges National

3 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 days lead-time - Probabilistic information (ensemble predictions)

- Worldwide comparable information Added value for National Hydrological Services - Catchment

4 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

evaporation -Soil water budget Output: surface flux& subsurface flux Routing model:

5 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 ( ) ECMWF VAREPS for forecasts since June 2011 Spatial resolution 0.1 degree

ERA-INTERIM Re-ANALYSIS for discharge climatology (1979-2010)

6 Simulation vs. Observation: Niger 6

7 Simulation vs. Observation: Ubangi 7

8 Skill score analysis Pierce skill score of simulated versus observed discharge for 620 selected stations 19 February

9 Estimating flood magnitude in GloFAS Era-Interim HTESSEL/Lisflood Simulated discharge time series Q in m 3/s 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

10 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

Updates every day Easy understandable hotspot maps, flood probability maps,

11 GloFAS forecast example 15 July 2011

12 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

international standards for hydrologic information exchange such as WaterML2 and its associated data sharing services we are currently

13 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

) Hydrological model: improving river network, inclusion of lakes and reservoirs, improve transmission losses,

14 For more information: Paper published in HESS: html Contact: 14

Towards a pan-african Flood Early Warning System: Experiences from the European Flood Alert System (EFAS) and pilot-testing in Africa

8th World General Assembly of INBO Adapting to the consequences of climate change in basins: tools for action (Dakar, 20 23 January 2010) Towards a pan-african Flood Early Warning System: Experiences from