ATMOSPHERIC SCIENCE LETTERS Atmos. Sci. Let. 8: 113–119 (2007) Published online in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/asl.161
Development of decision support products based on ensemble forecasts in the European flood alert system Maria-Helena Ramos,1,2 * Jens Bartholmes1 and Jutta Thielen-del Pozo1 1 European Commission, DG Joint Research Centre, Institute for Environment 2 Cemagref, Hydrology and Hydraulics Research Unit, Lyon, France
*Correspondence to: Maria-Helena Ramos, Cemagref Parc de Tourvoie, BP 44, 92163 Antony Cedex, France. E-mail: maria
[email protected]
Received: 26 April 2007 Revised: 12 September 2007 Accepted: 22 October 2007
and Sustainability, Ispra, Italy
Abstract The study presents the development of flood warning decision support products based on ensemble forecasts in the European Flood Alert System (EFAS). EFAS aims to extend the lead time of flood forecasts to 3–10 days in transnational river basins and complement Member States’ activities on flood forecasting. Weather forecasts are used as input to a hydrological model and simulated discharges are evaluated for exceedances of flood thresholds. Products were developed in collaboration with users for a concise and useful visualization of probabilistic results. Forecasts of flood events observed in the Danube river basin in 2005 illustrate the analysis. Copyright 2007 Royal Meteorological Society Keywords:
flood forecasting; ensemble prediction; uncertainty; warning
1. Introduction The concept of probabilistic forecasting by Ensemble Prediction Systems (EPS) was introduced in meteorology in the beginning of the 1990s and has been used more and more in operational weather forecasting. It has been gradually expanded to short-range highresolution probabilistic forecasting in view of improving warnings for extreme weather events on local scales (Stensrud et al., 1999; Molteni et al., 2001; Nicolau, 2002). In hydrology, the main approaches developed for probabilistic streamflow prediction are based on: (1) generating ensemble runs with different calibrated hydrological models, (2) using analogbased techniques to statistically assess the probability of a future event based on observed past situations, or (3) nesting single or combined sources of uncertainty from model structure, parameters, input and/or measurements in rainfall-runoff simulations (Georgakakos et al., 2004; Bartholmes and Todini, 2005; Pappenberger et al., 2005; Siccardi et al., 2005; Carpenter and Georgakakos, 2006; Diomede et al., 2006; Gourley and Vieux, 2006; Vrugt et al., 2006, and references therein). The use of probabilistic flood forecasting for risk assessment and decision making in flood warning is a challenge for the scientific community (Krzysztofowicz, 2001), which stresses the need of efficient communication of probabilistic forecasts to end users. Only between 1998 and 2002, the European Environmental Agency (EEA) estimated that floods caused about 700 deaths, the displacement of about half a million people and at least 25 billion euros in insured economic losses in Europe (EEA, 2003). The possibility of improving early warnings for large-scale floods was explored on an experimental basis during the European Flood Forecasting System (EFFS) Copyright 2007 Royal Meteorological Society
research project (De Roo et al., 2003, Thielen, 2004, Gouweleeuw et al., 2005). On the basis of the experience gained, the development of an integrated meteorological–hydrological forecasting system was launched. The European Flood Alert System (EFAS) has operated in testing mode since 2005. It has been developed in close collaboration with a large network of users from a diversity of national operational hydrological services. Considering that during a potential flood forecast situation users have little time to process new information arriving daily and make their decisions, it is a challenge to develop products showing forecasts in a clear, concise and an easy-tounderstand way. This article focuses on the development of decision support flood forecasting products based on ensemble weather forecasts in EFAS. An overview of the system and the main products developed are presented. Results are illustrated on flood events observed in the Danube river in 2005.
2. The European flood alert system: Overview EFAS provides flood warnings in European transnational river basins 3 to 10 days in advance and has been developed to suit the needs of increasing preparedness and generating forecast products that are seamless across national boundaries. Weather forecasts, provided by the European Centre for Mediumrange Weather Forecasts (ECMWF) and the German Weather Service–Deutscher Wetterdienst (DWD), are used as input to the LISFLOOD distributed hydrological model (De Roo et al., 2000; Van Der Knijff and De Roo, 2006). The current preoperational prototype runs deterministic and probabilistic weather forecasts issued twice a day (12UTC and 00UTC). For the
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examples presented here, the meteorological data have the following main features: (1) the deterministic forecasts from DWD have a forecast range of 7 days (7-km resolution local model for the first 3 days and 40km resolution global model for the remaining 4 days); (2) the 10-day deterministic forecasts from ECMWF have a grid spacing of about 40 km; and (3) the 10day ECMWF-EPS has 50 perturbed members and 1 control run, with about 80 km grid spacing at midlatitudes. Observed meteorological data from an extended synoptic station network (JRC-MARS) across Europe are used for calculating the initial conditions at the onset of the flood simulations. Hydrological simulations are obtained with a 5 × 5km grid space resolution from the LISFLOOD water balance and flood simulation model. The simulated processes include snow melt, infiltration, rainfall interception, leaf drainage, evaporation, surface runoff, subsurface and groundwater flow. Input parameters are either estimated from physical properties or by calibration against measured streamflows. For warning purposes, forecasted discharges are evaluated in terms of exceedances of predefined flood alert thresholds. In the absence of exhaustive discharge data and following a coherent model framework, the thresholds were determined through the statistical analysis of a 14-year (1991–2004) daily simulation performed with the same hydrological model set up for the operational forecasting system and with observed meteorological
M.-H. Ramos, J. Bartholmes and J. Thielen-del Pozo
data as input. For each river pixel, the simulated discharges were ranked to allow the automatic extraction of four critical thresholds. They correspond to the maximum value and the 99, 98 and 97% quantiles, and define, respectively, four levels: Severe (very high possibility of flooding, potentially severe flooding), High (high possibility of flooding, bankful conditions or higher expected), Medium (water levels high but no flooding expected) and Low (increased water levels but no flooding expected). Forecasts are summarized in maps and temporal diagrams, showing where and when the thresholds were exceeded in the simulations. The maps of flood threshold exceedances, for instance, summarize the spatial information by showing the highest critical level exceeded by the forecasted discharges at any time during the forecast range. Additionally, at any point inside a catchment, temporal diagrams allow to visualize the evolution of the forecasted critical levels in sequential boxes, each box representing 24 h of lead time (see Figure 1(c) for an illustration). EFAS simulations based on weather forecasts from 12UTC at day d-1 and 00UTC at day d are analyzed daily by a forecaster at about 1 pm and automatically reported in a logbook. If a potential flood situation is forecasted, and if operational partners exist for the catchment, EFAS information reports are sent to them. In early 2006, 22 hydrological services across Europe were part of this network. The first EFAS information reports were sent out in July
Figure 1. Basic products implemented in EFAS for EPS-based forecasts. (a) EFAS-EPS high threshold exceedance map: maximum number of EPS exceeding the EFAS high threshold during the 10-day forecast range; (b) At a point: discharge charts (51 hydrographs based on EPS forecasts with thresholds values indicated on top) and EPS-based temporal diagrams (number of EPS above EFAS high – EPS > HAL – and severe – EPS > SAL – flood thresholds for each day of lead time); (c) Combined deterministic and EPS-based forecasts at a point: EFAS diagrams (left) and discharge curves (right); Deterministic DWD-based forecast (black curve), Deterministic ECMWF-based forecast (brown curve) and EPS-based forecasts with a box-plot diagram representation (blue). Critical thresholds (top) and upstream rainfalls (inverted axis on the right hand side) from the DWD (blue shading) and ECMWF (red shading) forecasts are also shown. Copyright 2007 Royal Meteorological Society
Atmos. Sci. Let. 8: 113–119 (2007) DOI: 10.1002/asl
Ensemble forecasts and decision support products in EFAS
2005. One year later, about 30 flood events had been reported.
3. EPS-based flood forecasts: Implementing decision support products The first attempts to visualize LISFLOOD simulated discharges based on EPS are presented in Gouweleeuw et al. (2005) for two case studies in the Odra and Meuse rivers. Flood forecasts were plotted as time series of forecast probability values for given discharge thresholds (proportion of ensemble members exceeding the thresholds). The authors concluded that ensemble-based streamflow predictions provide valuable additional information for deterministic forecasts, but stressed the need of developing more concise tools for visualizing the results. Since July 2005, the ECMWF-EPS (Molteni et al., 1996; Buizza et al., 2001) has been running daily through the preoperational prototype of the EFASLISFLOOD system. A challenge was raised on how to communicate uncertain forecasts in a simple way for a correct interpretation of the forecasted situation by users with different scientific background and forecasting experience. New visualization products for combined deterministic and probabilistic forecasts were developed (Figure 1). The EFAS-EPS threshold exceedance maps show the maximum number of EPS exceeding the EFAS high threshold (Figure 1(a)) or the EFAS severe threshold (not shown) during the 10day forecast range. At a point, the system provides a discharge chart with the 51 hydrographs based on the EPS forecasts (Figure 1(b), top). In order to simplify this representation, EPS-based temporal diagrams were implemented (Figure 1(b), bottom). They show the number of EPS-based simulations above EFAS high and severe thresholds for each day of lead time. The system also provides combined deterministic and EPSbased forecasts at a point (Figure 1(c)). In the temporal diagrams, the forecaster can see the deterministic forecasts (DWD and ECMWF) and the EPS-based exceedances of high and severe thresholds for any target day of the forecast range (Figure 1(c), left). The discharge curves (Figure 1(c), right) show the deterministic forecasts and a statistical representation of the ensemble forecasts with the maximum, the 75% quantile, the median, the 25% quantile and the minimum values. The use of the implemented products in decision making under potential flood warning situations was tested in a workshop organized with a group of operational forecasters from eight European countries (Thielen et al., 2005). Three flood forecasting situations were analyzed by individual workgroups and forecasters had to decide if they would contact the civil protection authorities with a flood warning. Information provided was either deterministic or both deterministic and probabilistic. At the end, time was given to a plenary session, where participants were invited to present Copyright 2007 Royal Meteorological Society
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their decisions and discuss the way they had used the probabilistic EPS-based forecasts, the difficulties they had encountered and their views on the best way to communicate uncertainty in flood forecasting. The main results showed that the information EPS-based forecasts contain help in the decision-making process. In terms of visualization, the box counting approach adopted in the temporal diagrams (Figure 1(b)) was found to be useful in providing the essential information, while being also easy to understand. Forecasters found it difficult to extract crucial information from the ensemble of hydrographs at one glance and, instead, preferred the statistical box-plot representation (Figure 1(c)). They also found that the combination of probabilistic results with higher resolution multimodel deterministic forecasts in simplified temporal diagrams (Figure 1(c)) was a major step forward in understanding and gaining a good overview of the situation. It was highlighted that the EPS-based products were increasingly well understood while working with the case studies, which shows the importance of training for better use of ensemble forecasts in operational mode.
4. Examples for the Danube river basin The years 2005 and 2006 were challenging for EFAS: (1) they correspond to a first attempt of running a system operating with two deterministic weather forecasts and a 51-member EPS, and (2) they were characterized by a high number of severe flood events occurring in several large European basins. The Danube river basin experienced repeated floods during this period (Figure 2). The most severe events were observed in Austria and Germany on 21st–26th August (peak discharges with estimated recurrence interval greater than 100 years) and in Romania and Bulgaria, where heavy and recurrent rainfall during the spring-summer season resulted in widespread floods and historic high water levels. Figure 3 illustrates the number of days EFAS forecasted high flood levels in at least 50% of the simulations based on ECMWF-EPS with 5 days of lead time for July and August 2005. It can be seen that the system well identifies the main critical areas in Bulgaria and Romania. Although the figure only shows a strong EPS-based signal (at least 25 simulations out of 51 exceeding high flood thresholds) for early warning, it presents a useful picture of the spatial extent and the persistence of the forecasted signal in the river basin. Persistence in the forecasted signal usually assists forecasters in their decisions. The evolution of the signal from one forecast to another helps when deciding if and at which level of risk a warning should be issued. In EFAS, a sequence of temporal diagrams of forecasted flood threshold exceedances can provide this information. Figure 4 shows the history diagrams obtained at the Isar river in Germany at the confluence with the Danube (approximately 8400 km2 ) for a 20day period in August 2005. In the deterministic-based Atmos. Sci. Let. 8: 113–119 (2007) DOI: 10.1002/asl
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Figure 2. Summary of major flood events or high water level occurrences in the Danube River Basin during 2005 (based on the 2005 Flood Archive of the Dartmouth Flood Observatory and on information from national authorities and from the JRC-European Media Monitoring (EMM)).
Figure 3. Number of days EFAS forecasts based on ECMWF-EPS weather forecasts show more than 50% of EPS-based simulations (i.e. more than 25 simulations out of 51) with discharges exceeding EFAS high flood threshold for a 5-day lead time during (a) July 2005 and (b) August 2005.
forecasts (DWD and ECMWF), the exceedances of the severe threshold are shown in pink, high threshold in red, medium threshold in yellow, and low threshold Copyright 2007 Royal Meteorological Society
in green. In EPS-based forecasts, the number of simulations exceeding the EFAS high threshold is shown. Rows go from 12th to 31st August 2005 (date of the forecast). For purposes of simplification, only weather forecasts issued at 12UTC are shown. Columns correspond to the dates for which the forecasts apply. The dates for which exceedances of EFAS high threshold were simulated based on observed meteorological data are also indicated (22nd–25th August). In the absence of measured discharges, these simulations can be considered a proxy for the observed situation. Although the ECMWF-based forecasts indicate potential flooding at the river as early as 16th August (lead time of 7 days), the signal does not persist over the following forecasts. This can cause a mistrust in the forecasted signal and a delay in the warning. However, if the decision to issue a prealert is based on persistence and on combining information from deterministic and EPS-based forecasts, the flood event can be flagged with approximately 5 days in advance. The example above shows the strengths of the history diagrams when examining persistence in consecutive forecasts and combining forecasts from different models to support a warning decision. It also points out a challenge when dealing with probabilistic forecasts: how to define persistence in EPS-based results. In this case, persistence is not only related to continuous exceedances of flood thresholds (as for the deterministic case), but also on having a steady number of EPS members above the thresholds. In a preliminary Atmos. Sci. Let. 8: 113–119 (2007) DOI: 10.1002/asl
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Figure 4. History diagrams of EFAS forecasted critical levels at the Isar river in Germany (8375 km2 ) for August 2005 based on DWD deterministic (top), ECMWF deterministic (middle) and ECMWF-EPS (bottom) weather forecasts issued at 12UTC. In deterministic forecasts, exceedances of EFAS severe threshold are in pink; high threshold in red; medium threshold in yellow; low threshold in green. In EPS-based forecasts, the number of simulations (out of 51) exceeding the high threshold is shown. Rows go from 12th to 31st August 2005 (date of the forecast). Columns correspond to the dates for which the forecasts apply (each box is a 24-h lead time). Red contour: dates for which exceedances of high flood thresholds were simulated by EFAS based on observed meteorological data.
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attempt to investigate this feature, we computed typical contingence tables (hits, misses and false alerts) from the history diagrams obtained for 70 locations in the Danube river basin during August 2005. The general methodology followed the approach in Atger (2001), with the categories in the contingence tables defined according to the number of ensemble members that forecast the event. The analysis was applied to the simulations based on ECMWF forecasts (deterministic and EPS). A forecasted event was defined as YES (or NO) if: (1) in the deterministic case, forecasted discharges exceed (or do not exceed) EFAS high thresholds in two consecutive simulations; (2) in EPS-based forecasts, forecasted discharges exceed (or do not exceed) EFAS high thresholds in two consecutive simulations, both with at least Nth EPS simulations above the threshold (Nth ranges from 1 to 50). Lead times 2 to 9 days were considered and a contingence table was computed for each Nth . The occurrences were plotted as a function of the number Nth of EPSbased simulations above high thresholds (Figure 5). It can be seen that if 1 EPS member above the EFAS high flood threshold is considered enough to flag a location as ‘under flood alert’, then one can expect a high number of hits and a low number of missed events, but also a high number of false alarms. If, on the contrary, 50 members need to exceed the flood level in order to flag a location as ‘under flood alert’, the number of false alarms will be low, but also the number of hits, while the number of missed events will be high. From these curves, some intersections emerge:
2. the EPS-threshold (Nth2 ) at which the number of EPS-based misses become more important than EPS-based hits: here, Nth2 = 7; 3. the EPS-threshold (Nth3 ) at which EPS-based misses become more important than Deterministicbased misses and EPS-based hits become less important than Deterministic-based hits: here Nth3 = 16. This threshold corresponds to the moment when the EPS-based hit rate (the proportion of hits to the total number of observed events) becomes smaller than the Deterministic-based hit rate. This preliminary investigation shows that guidance for decision making in flood prewarning can emerge from the statistical analysis of specific characteristics derived from the EFAS diagrams of forecasted flood threshold exceedances. The results presented correspond to only 1 month of forecasts. In-depth analyses over longer time periods and a variety of hydrometeorological conditions is needed to provide robust statistical measures, as well as to assess the skill of the forecasting system, which is beyond the scope of this article.
5. Conclusions This article presents the development of decision support products for flood forecasting and warning based on ensemble predictions from EFAS. Forecasts for the flood-prone year of 2005 in the Danube river basin illustrate the study. EFAS flood forecasts are based on two deterministic weather forecasts and one ensemble prediction system with 51 members. Pre-warnings (3–10 days in advance) are issued to partners from
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Figure 5. Number of Hit, Miss and False Alert occurrences for EFAS forecasts based on ECMWF deterministic and EPS weather forecasts computed over 70 locations in the Danube river basin during August 2005. Persistence of the forecasted signal is considered when defining a forecasted event: for deterministic-based forecasts, at least two consecutive simulations based on weather forecasts issued at 12UTC exceed EFAS high threshold; for EPS-based forecasts, two consecutive simulations based on weather forecasts issued at 12UTC show both Nth or more simulations above EFAS high threshold. Copyright 2007 Royal Meteorological Society
Atmos. Sci. Let. 8: 113–119 (2007) DOI: 10.1002/asl
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hydrological operational forecasting centers and forecasters can play in advance with different scenarios for location and severity of a flood event before deciding on issuing warnings. The products developed are based on maps showing the number of simulations forecasting discharges above predefined critical thresholds and at-a-point temporal diagrams showing the evolution with lead time of the forecasted threshold exceedances. Sequential temporal diagrams showing the history of forecasted threshold exceedances allow to evaluate the persistence of the forecasted signal and can assist forecasters in their decisions. The usefulness of the developed products in decision making was tested in a workshop gathering users to work on case studies. Users found that diagrams combining threshold exceedances from deterministic and probabilistic forecasts were useful to better evaluate the risk of a potential flood situation. Color schemes printable in black and white or adapted to colorblind people were also discussed and improvements are expected in the next prototypes of the system. It was also highlighted that practice with probabilistic products can improve their usefulness in operational hydrological forecasting.
Acknowledgements This work was developed within the Exploratory Research Program of the Institute for Environment and Sustainability (European Commission, Joint Research Center). We acknowledge the data providers: Deutscher Wetterdienst, European Centre for Medium-Range Weather Forecasts and JRC Agrifish unit. We also thank the national services of the Member States for their feedback and the EFAS team for their collaboration.
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Atmos. Sci. Let. 8: 113–119 (2007) DOI: 10.1002/asl
