Setting up a French national flash flood warning system for ungauged catchments based on the AIGA method

Occurring at small temporal and spatial scales, flash floods (FF) can cause severe economic damages and human losses. To better anticipate such events and mitigate their impacts, the French Ministry in charge of Ecology has decided to set up a national FF warning system over the French territory. This automated system will be run by the SCHAPI, the French national service in charge of flood forecasting, providing warnings for fast-responding ungauged catchments (area ranging from ~10 t ! "# $ % ! ! ! $ &$ ' ! ( )) $ ! ! ' in 2017 will be based on a discharge-threshold flood warning method called AIGA (Javelle et al. 2014). This method has been experimented in real time in the south of France in the RHYTMME project (http://rhytmme.irstea.fr). It consists in comparing discharges generated by a simple conceptual hourly hydrologic model run at a 1-km2 resolution to reference flood quantiles of different (e.g., 2-, 10and 50-year) return periods. Therefore the system characterizes in real time the severity of ongoing events by the range of the return period estimated by AIGA at any point along the river network. The hydrologic model ingests operational rainfall radar-gauge products from Météo-France and takes into account the baseflow and the initial soil humidity conditions to better estimate the basin response to rainfall inputs. To meet the requirements of the future FF warning system, the AIGA method has been extended to the whole French territory (except Corsica and overseas French territories). The calibration, regionalization and validation procedures of the hydrologic model were carried out using data for ~700 hydrometric stations from the 2002-2015 period. Performance of the warning system was evaluated with various contingency criteria (e.g., probability of detection and success rate). Furthermore, specific flood events were analysed in more details, by comparing warnings issued for exceeding different critical flood quantiles and their associated timing with field observations. The performance results show that the proposed FF warning system is useful, especially for ungauged sites. The analysis also points out the need to account for the uncertainties in the precipitation inputs and the hydrological modelling, as well as include precipitation forecasts to improve the effective warning lead time. DOI: 10.1051/ , 6 E3S Web of Conferences e3sconf/201 FLOODrisk 2016 3 European Conference on Flood Risk Management 7 071801


Context
Flash floods are typically caused by extreme rainfall events, which are highly localised and evolving rapidly [1].Depending on catchment factors such as soil permeability and slope, the hydrological response can be very fast, occurring on time scales ranging from minutes to a few hours [2].The rapid rising of waters can lead to devastating economic and human losses.Consequently, setting up early warning systems to warn communities and activate appropriate emergency procedures is a crucial and still on-going issue.For instance, in France, the June 15-16, 2010 event in the Var region in the southeast (25 casualties [3]), has emphasized the limits of the official warnings during this event, based on a large-scale weather watch [4].Following this event, the French ministry of environment has decided, among other measures, to develop an automated warnings system taking into account hydrological responses of the unmonitored streamflows submitted to intense rainfall [5].The envisioned flash flood warning system will complement the current ³flood vigilance´ system which is available only on the French monitored river network.

Limits of the river flow forecasting systems
Similarly to other conventional river flow forecasting systems (RFFS), the current French flood vigilance system is not suitable to efficiently forecast flash flooding.Indeed, as mentioned by [6], RFFS are usually defined to forecast slower events, on greater catchments, taking advantage of all hydro-meteorological monitoring networks (rain gauges, radar and satellite rainfall data, river gauges), locally calibrated hydrological models, and weather forecasts from numerical weather prediction (NWP) models.Such an approach is of limited interest for a flash flood warning systems [2].First, all catchments prone to flash floods cannot be directly monitored with rain and water levels gauges.Consequently, hydrological models can neither be locally calibrated, nor benefit from river flow data assimilation at the point of interest.Secondly, correctly forecasting convective cells responsible for flash floods is still challenging for NWP models, due to the very small space-time scales of these events, leading to large forecast uncertainties.Despite these difficulties, important advances have been recently made: rainfall estimations combining weather radars and satellite measurements, nowcasting products for improved very short term precipitation forecasts, probabilistic NWP forecasts to capture and potentially reduce forecast uncertainties, and hydrological modelling.The challenges of ungauged catchments have been effectively addressed by the scientific and operational community in the Predictions in Ungauged Basin (PUB) framework.Promising perspectives have been demonstrated by distributed hydrological modelling approaches, such as the Distributed Hydrologic Model ± Threshold frequency (DHM-TF, [7]) developed in the United States, the Grid-to-Grid (G2G, [8]) model used in the United-Kingdom, the LISFLOOD model initially developed for large European basins, but successfully adapted for small catchments prone to flash flooding [9] [10], and the CVN and MARINE models which were successfully tested on the Gard 2002 flash flood event in France [11].

Current Flash flood warning systems
Despite the recent advances made in hydrological modelling, most existing operational flash flood warning systems use simpler approaches based on rainfall threshold methods, which can be more easily interpreted by non-technical stakeholders: warnings are issued when local rainfall cumulated over a determined duration (i.e. 6 hours) and a given area exceeds some specific threshold.These thresholds are usually determined based on experience from past events.To enhance this basic approach, one can determine different threshold values depending on the initial soil moisture condition, since the more saturated the catchment, the lower the rainfall threshold.Furthermore, the Flash Flood Guidance (FFG) approach , widely used operationally in the United States [12] [13], consists in running a hydrological model in inverse mode to determine the amount of rainfall needed to exceed a predefined specific discharge (usually corresponding to a given return period).In Europe, since 2009, the operational European Flood Awareness System (EFAS) produces flash flood warnings based on the European Precipitation Index (EPIC) (www.efas.eu).This index is calculated using COSMO-LEPS ensemble weather forecasts: predicted rainfall is summed over the upstream area and for different durations (i.e. 6, 12 and 24h), and cumulated values are then compared to annual maximal quantiles derived from 20 years of COSMO climatology [14] [15] [16].Recently, EPIC has been replaced by the European Runoff Index based on Climatology (ERIC) in order to take into account initial soil moisture conditions [17].

The AIGA method
The flash flood warning system to be implemented in France by the SCHAPI (French national service in charge of flood forecasting) is based on a discharge-threshold flood warning method called AIGA [18].The AIGA method has been initially developed for the South of France by Irstea and Meteo-France [19].It has been tested in real time over the last 5 years, with end-users IURP WKH ³3URYHQFH $OSV )UHQFK 5LYLHUD´ UHJLRQ in the framework of the RHYTMME project (http://rhytmme.irstea.fr).It consists in comparing discharges generated by a simple conceptual hourly hydrologic model run based on radar rainfall estimations, to reference flood quantiles of different return periods, at any point along the river network.
The scope of this paper is to present the enhancements of the AIGA method for its integration into the future national warning system.First the enhanced hydrological model is presented.Then, performances are evaluated in two different ways: at gauging stations, as well as ungauged locations, using damage reports of two case studies.Finally, some concluding remarks are drawn.[18].It combines two distributed modules: one continuous model running at a daily time step on 1-km² grids and representing soil moisture conditions (SAJ) and an eventbased module running at an hourly time step, which uses outputs from SAJ as initial humidity states (Fig. 1).In the initial version implemented for Mediterranean catchments, initial flows were assumed to be negligible in comparison with the high flows to be modelled.However this simplification is not acceptable anymore for catchments under other climatic conditions, with potentially significant baseflows.

DOI
Therefore, in the national AIGA version presented in this paper, a third module has been included in order to include baseflow estimates in the event-based model.In this third module, the global daily continuous GR4J model (see for instance [20]) calculates daily flows at each target basin outlet covered by AIGA.These daily flows are then used to initialise the routing store of the hourly event-based model (Fig. 1).
In real time, the production and routing stores of the event-based model are initialised every day at 6AM, except if a rainfall event is ongoing.From a practical point of view, at 7AM, if the amount of catchment rainfall cumulated over the last 24 hours exceeds 10mm, the production and routing stores are not initialised to let the model simulate flows with its internal model states.Furthermore, in order to have up-dated results every 15 minutes, four chains of hourly models are running on the same time, with simply a shifting delay of 15 minutes.

Models parameters
The three hydrological models used for the national version of AIGA use the following parameters (Fig. 1): - .In our case, regional transfer is made by averaging parameters calibrated at the 3 closest neighbours from the ungauged target site.

Reference flood quantiles
7KH DLP RI WKH $,*$ PHWKRG LV WR LQIRUP DERXW WKH UDULW\ RI RQ JRLQJ IORRGV rather than provide absolute discharge estimates ,Q WKH LQLWLDO $,*$ PHWKRG [18] discharges calculated in real time were compared with reference flood quantiles provided by the SHYREG method.The SHYREG method combines a punctual stochastic rainfall simulator and a rainfall-runoff model and is now recommended at the nationally for estimating reference flood quantiles at ungauged catchments [22].
Nevertheless, since long time series of gridded rainfall are now available and the hydrological models of the national version have been modified (compared to the SHYREG rainfall-runoff model), flood quantiles were generated from a continuous simulation of AIGA over the French territory for the 1998-2015 period (18 years).Reference flood quantiles were estimated by fitting a Gumbel law on the annual maximum values of the simulated streamflows.Considering their devastating impacts, numerous post-event surveys have been carried out for administrative and research purposes.For example, for both flood events, an HYMEX field campaigns (www.hymex.org)regrouping several French laboratories have collected hydrometeorological measurements and detailed information on impacts observed on the ground.As a result, these two events are particularly well documented in terms of impacts (numbers, localization, WLPLQJ« ZKLFK HQDEOHG XV WR FRPSDUH ZDUQLQJV LVVXHG by AIGA with impacts observed on the ground. For the 15-Jun-2010 flood, information about casualties came from the Vict-In database elaborated by L. Boissier during his PhD [23], while damage information was compiled by Lefort and Koulinski [24].For the 3-Oct-2015 flood, all the information was collected by C. Saint-Martin (on-going PhD).Various data sources were used, such as police reports, media, interviews, and social network.
AIGA discharges were simulated for all watersheds having an area ranging from 5 km² to 3500km².Then, for each of them, we determined the timing of the 2-year, 10year and 50-year threshold exceedance.The simulation having being made at an hourly time step, calculated discharges were previously interpolate (linearly) at a 15-PLQ WLPH VWHS LQ RUGHU WR UHSURGXFH WKH µUHDO ¶ RSHUDWLRQDO method, which is up-dated every 15 minutes.Finally, the AIGA exceedance schedules were aggregated at a town level by taking for each return period (2-, 10-50-year), the earlier exceedance observed in each town of the studied areas.