Olivier Vannier
email: oliviervannier@gmail.com

Sandrine Anquetin

Isabelle Braud

Investigating the role of geology in the hydrological response of Mediterranean catchments prone to flash-floods: regional modelling

Keywords: hydrological modelling, process understanding, ash-oods, geology, regional modelling

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Introduction

In the eld of catchment hydrology, many eorts are made to better understand the climate and landscape controls on the water cycle and catchments response dynamics. This thirst of knowledge is largely related to the most challenging problem that has driven the hydrologic community researches for the last decade: predicting the response of ungauged catchments. This challenge, conceptualized within the PUB initiative [START_REF] Sivapalan | IAHS Decade on Predictions in Ungauged Basins (PUB), 2003-2012: Shaping an exciting future for the hydrological sciences[END_REF], has resulted in a large amount of recent hydrological studies, as reviewed by Hrachowitz et al. (2013), focusing on crucial questions such as process understanding (Tetzla et al., 2007;Blume et al., 2008, for example), catchments classication (Sawicz et al., 2011, among many), uncertainty analyses (McMillan et al., 2010, e.g.), model parameter transferability (Oudin et al., 2010, e.g.) or emerging observation techniques (Selker et al., 2006). Even if progress still need to be made to reach the ambitious target dened in the PUB initiative, signicant advances have been made in the eld of regionalisation methods (Parajka et al., 2005;[START_REF] Oudin | Spatial proximity, physical similarity, regression and ungaged catchments: A comparison of regionalization approaches based on 913 French catchments[END_REF][START_REF] Parajka | Comparative assessment of predictions in ungauged basins -Part 1: Runo-hydrograph studies[END_REF]Salinas et al., 2013, e.g.) and emerging modelling approaches (Fenicia et al., 2008a,b;[START_REF] Savenije | HESS Opinions "Topography driven conceptual modelling (FLEX-Topo)[END_REF][START_REF] Clark | Pursuing the method of multiple working hypotheses for hydrological modeling[END_REF].

Among the dominant factors driving the hydrological behaviour of catchments, geology is regularly cited as an important one [START_REF] Yadav | Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins[END_REF]Tetzla et al., 2007;Oudin et al., 2010, e.g.). At the catchment scale, geology aects the governing hydrological processes through many ways, such as (for example): i) groundwater ow paths direct implication on the transit time distribution of water within catchments [START_REF] Sayama | A new time-space accounting scheme to predict stream water residence time and hydrograph source components at the watershed scale[END_REF][START_REF] Rinaldo | Catchment travel time distributions and water ow in soils[END_REF]; ii) the nature of the interface between soil horizons and bedrock determining the formation of preferential ows that governs the quick response during ood events [START_REF] Weiler | Simulating surface and subsurface initiation of macropore ow[END_REF][START_REF] Weiler | Conceptualizing lateral preferential ow and ow networks and simulating the eects on gauged and ungauged hillslopes[END_REF]; iii) bedrock permeability strongly impacting the water balance at the catchment scale (Tromp-van Meerveld et al., 2007).

More generally, we consider that geology is directly linked to the catchments water storage capacity, which has been shown to be of primary importance in the water cycle dynamics [START_REF] Sayama | How much water can a watershed store?[END_REF]Tetzla et al., 2011;[START_REF] Mcnamara | Storage as a Metric of Catchment Comparison[END_REF] and which strongly inuences the antecedent wetness conditions that acts as a threshold on the response of catchments during ood events (Troch et al., 2003;[START_REF] Latron | Runo generation processes in a small Mediterranean research catchment (Vallcebre, Eastern Pyrenees)[END_REF][START_REF] Zehe | Plot and eld scale soil moisture dynamics and subsurface wetness control on runo generation in a headwater in the Ore Mountains[END_REF].

To better understand the role played by landscape characteristics in the hy-at developping and assessing forecast tools and ash-ood warning systems also focus on the Cevennes-Vivarais region [START_REF] Bouilloud | Coupling the ISBA land surface model and the TOPMODEL hydrological model for mediterraneanash-ood forecasting: Description, calibration, and validation[END_REF][START_REF] Vincendon | Benet of coupling the ISBA land surface model with a TOPMODEL hydrological model version dedicated to Mediterranean ash-oods[END_REF]Aleri et al., 2011), or on neighbouring french mediterranean regions like the Var department, hit by massive oods in June 2010 [START_REF] Javelle | Evaluating ashood warnings at ungauged locations using post-event surveys: a case study with the AIGA warning system[END_REF][START_REF] Caseri | Generating precipitation ensembles for ood alert and risk management[END_REF]. However, the purpose of the current work signicantly diverges from forecast-oriented studies, in the sense that it is governed by the understanding of unknown processes, instead of the will to obtain the best results as possible.

Recently, the FloodScale reasearch project2 [START_REF] Braud | Multi-scale hydrometeorological observation and modelling for ash ood understanding[END_REF], which is a contribution to the international HyMeX program 3 , has been federating the french hydrologic community on research questions related to the understanding and simulation of the hydrological processes leading to ash oods in mediterranean catchments. Here, we use the CVN-p process-oriented distributed model, deriving from CVN [START_REF] Manus | A modeling approach to assess the hydrological response of small mediterranean catchments to the variability of soil characteristics in a context of extreme events[END_REF], set-up over the entire Cevennes-Vivarais region, and accounting for evapotranspiration and vegetation-related processes to perform continuous simulations. This study follows the works of Vannier et al. (2014), who analysed observed streamow recession curves and derived catchment-scale aquifer eective thicknesses and hydraulic conductivity, for the dierent geological entities of the region, using the approach proposed by [START_REF] Brutsaert | Regionalized drought ow hydrographs from a mature glaciated plateau[END_REF].

Here a weathered porous rock layer is added in the model, to ll the lack of water storage capacity identied when considering soil horizons only [START_REF] Roux | A physically-based parsimonious hydrological model for ash oods in Mediterranean catchments[END_REF][START_REF] Braud | Multi-scale hydrometeorological observation and modelling for ash ood understanding[END_REF][START_REF] Garambois | Characterization of catchment behaviour and rainfall selection for ash ood hydrological model calibration: catchments of the eastern Pyrenees[END_REF].

The paper is organized as follows. We rst describe the model used in this study and, in section 3, how the CVN-p hydrological model is set-up over the study area. In the fourth section we present the results of the simulations performed with and without the addition of the weathered porous rock layer, and we evaluate the model performances obtained for year 2008, with a focus on two ood-events that occured during the autumn. Subsequently, we discuss the results obtained and the observed spatial dierences in the model performances, in link with the geology of catchments ('Discussion' section). The nal section consists of brief conclusions and of some perspectives for future developments on this subject.

Model description

The model used in this study is the CVN-p hydrological model. The CVN-p model is an evolution of the event-based rainfall-runo model CVN [START_REF] Manus | A modeling approach to assess the hydrological response of small mediterranean catchments to the variability of soil characteristics in a context of extreme events[END_REF]. Several processes have been implemented in the model so that it can run long-term continuous simulations.

Structure and processes represented

The CVN-p model was built within the LIQUID hydrological modelling platform (Viallet et al., 2006;[START_REF] Branger | Towards multi-scale integrated hydrological models using the LIQUID R framework. Overview of the concepts and rst application examples[END_REF], which is a framework providing users the possibility to assemble hydrologic modules together, each one solving a physical process. In its early version, CVN was an event-based model, representing two main processes: the vertical water transfer through soils, and the routing of the generated runo along the hydrographic network [START_REF] Manus | A modeling approach to assess the hydrological response of small mediterranean catchments to the variability of soil characteristics in a context of extreme events[END_REF].

6

Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172

The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ For the regional simulation purposes, the model evolved to perform continuous

Spatial discretization

The CVN-p model spatial discretization is based on the Representative Elementary Watershed approach (REW) [START_REF] Reggiani | A unifying framework for watershed thermodynamics: balance equations for mass, momentum, energy and entropy, and the second law of thermodynamics[END_REF][START_REF] Reggiani | A unifying framework for watershed thermodynamics: constitutive relationships[END_REF] The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ by [START_REF] Dehotin | Which spatial discretization for distributed hydrological models? Proposition of a methodology and illustration for medium to large-scale catchments[END_REF] who proposed the hydrolandscape concept used here.

An hydrolandscape is an elementary hydrological response unit, homogeneous in terms of hydrological processes. In this study, following the approach of Manus et al. (2009), we assume that topography and soil typology represent the dominant control processes on the Cevennes-Vivarais region hydrological behaviour.

Accordingly, the hydrolandscapes are dened as the crossing of two successive discretization steps: i) rst the study domain is splitted into sub-catchments using an automated DEM-based tool [START_REF] Tarboton | A new method for the determination of ow directions and upslope areas in grid digital elevation models[END_REF], with a threshold of 0.5 km 2 ; ii) then a second level of discretization is applied, using a pedological soil map. The dominant vegetation type is nally assigned to each hydrolandscape.

The hydrolandscapes are the elementary cells of the soil and vegetation processes solved by the CVN-p model. The river network, where runo extracted from each hydrolandscape is sent and routed, is extracted from the DEM analysis: each subcatchment is associated to a river reach.

Implementation of a weathered rock layer

Vannier et al. (2014) proposed a methodology to dene catchment-scaledeep -soil properties through the analysis of streamow recession data, based on the works of [START_REF] Brutsaert | Regionalized drought ow hydrographs from a mature glaciated plateau[END_REF]. They performed this analysis after they lacked information on the physical (thickness) and hydraulic (conductivity) properties of weathered rock layers, which stands below well-described upper-soil horizons (Fig. 2a).

The application of the streamow recession analysis over a sample of catchments, located in the Cevennes-Vivarais region (south of France), highlighted a 8

Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172

The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ strong link between the dominant geology and the estimated values of the thickness and hydraulic conductivity of these deep horizons (Fig. 2b). Values of saturated hydraulic conductivities presented in Fig. 2b can be seen as very large, and thus out of the range of standard values of conductivities reported for soils or porous rocks. This is due to the nature of the values characterized by [START_REF] Braud | Multi-scale hydrometeorological observation and modelling for ash ood understanding[END_REF]: rst, the presence of various poorly-known processes such as macroporosity, rock fracturing, or preferential ow directions, may result in ow conditions that signicantlty diverge from the theory, and in addition, these values are representative of catchment-wide integrated processes since they derive from streamow recession analyses. Consequently, values reported in Fig. 2b must rather be considered as eective parameters than as actual hydraulic conductivities. The condence intervals result from the uncertainty in the value of drainable porosity(between 0.05 m 3 .m -3 and 0.1 m 3 .m -3 ). Values implemented (Table 1) have been added to the gure.

In 2 ) catchments at their conuence with the Rhône river, the Vidourle at Som- mières(650 km 2 ), the Vistre at its conuence with the Rhony river (493 km 2 ), the Hérault at Gignac (1410 km 2 ) and the Tarn at Montbrun (589 km 2 ) rivers. The location of these catchments is shown on the map in Fig. 3, as well as the geology of the region and the location of the stream gauges.

The Digital Elevation Model (DEM) used for the discretisation procedure is the 25m-resolution DEM provided by the french National Geographic Institute (IGN). Soil data are provided by the BD-sols Ardèche and Languedoc-Roussillon spatial databases (Robbez- [START_REF] Robbez-Masson | Bases de données pédologiques et systèmes d'informations géographiques. L'exemple de la région Languedoc-Roussillon[END_REF]. These pedological databases provide information on the dominant soil units (1:250 000 scale), as well as on the physical properties (texture, structure) of the main soil types that compose these units. root depths of dierent types of vegetation are extracted from the ECOCLIMAP database [START_REF] Masson | A global database of land surface parameters at 1-km resolution in meteorological and climate models[END_REF]. Geology derives from the 1:1 000 000 scale national geological map 4 .

Spatial vegetation information

Forcings

The set-up of the CVN-p model requires dierent kinds of data. Meteorological forcings are rainfall and reference evapotranspiration ET 0 . For inter- events periods, rainfall data is extracted from SAFRAN meteorological reanalyses [START_REF] Quintana-Seguí | Analysis of near-surface atmospheric variables: Validation of the SAFRAN analysis over France[END_REF]Vidal et al., 2010), whereas for events simulation we The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ use kriged hourly raingauges measurements. ET 0 is computed on the basis of other meteorological variables provided by SAFRAN (temperature, wind speed, long and short-wave radiation, specic air humidity). The Penman-Monteith formulation [START_REF] Monteith | Evaporation and environment. In: The State and Movement of Water in Living Organisms[END_REF]) is used, with parameters values chosen according to the Food and Agricultural Organization (FAO) recommandations [START_REF] Allen | Crop evapotranspiration -Guidelines for computing crop water requirements[END_REF].

The input forcing variables are given on spatial grids, with a resolution varying from 8x8 km 2 (SAFRAN meteorological reanalyses) to 1x1 km 2 (hourly kriged rainfall products). The temporal resolution is 1 hour, even if in the case of SAFRAN, rainfall intensities have been shown to be slightly biaised at this temporal resolution (see Vidal et al. ( 2010) for more details).

Parameters specication

The modelling approach used in this study is based on the testing of hydrological functioning hypotheses, without any calibration of the model. Consequently, parameters values derive from an a priori knowledge provided by observations, maps, and available databases. As an example, soil hydraulic properties required within the [START_REF] Brooks | Hydraulic properties of porous media[END_REF] relationships (FRER1D module) are computed according to the [START_REF] Rawls | Prediction of soil water properties for hydrologic modeling[END_REF] pedotransfer function, using structural and textural information given by the BD-sols databases. Other parameters values can be directly given by databases (Vegetation parameters), or result from regional observations analyses (river geometry, weathered rock horizons properties).

13

Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172

The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

Simulations strategy

In this region, rainfall-runo simulations are performed over the entire 2008 year. The choice of year 2008 was made for two main reasons : a) Two major rainfall events occured during the autumn : the rst one between October 21th and October 23rd, and the second one between October 31th and November 5th. These two events aected dierent areas, and also dier each other by intensity and duration, as shown in Fig. 4: the rst event is characterized by a shorter duration (approximately 24 hours) and high rainfall intensities (up to several tens of mm per hour) while the second event lasted for more than one day, with lower rainfall rates.

b) The large availability of discharge data measured by the streamgauges of the region in 2008, as compared to other years. In 2008, almost all of the streamgauges worked correctly, even during ood events.

The whole 2008 year is simulated, split into four periods for which rainfall forcings dier (Table 2). Long-term (i.e. inter-events) simulations are performed with SAFRAN rainfall, while events simulations are forced with hourly kriged rainfall elds. The nal state of a long-term simulation (soil wetness, water level in the river) is used as initial state of the following event simulation. The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ 15

Evaluation of the simulations

Author

Event simulations

The contribution of the implemented weathered rock layer is assessed in the same way during ood events, for the same selected catchments. For each catchment, the considered event is the one which caused the largest observed hydrologic response (highest discharge values). At the regional scale, the evaluation of the event simulations is performed for a wide range of catchment sizes, for which two types of observations are available: The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ gion, for catchment sizes ranging from 30 to 2300 km 2 . Discharge values derive from automatic water level devices recording at variable timestep. A record is made for each variation of water level larger than a dened threshold (which is specic to each station).

Along with these direct comparison to observations, event simulations results are also compared at the regional scale to CRUPEDIX 10-years return period discharge estimates. Q 10 is computed according to equation 1, after the CRU- PEDIX formula (1980), which is an empirical estimation of the instantaneous 10-years return period peak discharges for catchment size lower than 2000 km 2 .

Q 10 = A 0.8 (P d10 /80) 2 C (1)
where Q 10 is the 10-years return period instantaneous peak discharge (m 3 .s -1 ); A is the catchment area (km 2 ); P d10 the 10-years return period daily rainfall depth for the considered catchment (mm), and C is a regional coecient (with a dimension of [T -1 .L -0.6 ]), here considered equal to 1.7 (Versini et al., 2010). The estimation of the P d10 rainfall for all the considered catchments is based on the grided SAFRAN meteorological reanalyses: an estimation of the 10-years return period daily rainfall is performed for each SAFRAN grid cell according to its statistical distribution. Then the areal rainfall for each catchment is computed through the aggregation of all the values aected to the SAFRAN grid cells contained within the considered catchment, and the use of an Areal Reduction Factor (ARF) [START_REF] De Michele | The derivation of areal reduction factor of storm rainfall from its scaling properties[END_REF], with specic coecient values for the Cevennes-Vivarais region [START_REF] Ceresetti | Structure spatio-temporelle des fortes précipitations : application à la région Cévennes-Vivarais[END_REF]. Due to its simplicity, the CRUPEDIX method does not provide a perfectly accurate estimation of the 10-years return period peak 18

Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172

The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ discharge. We performed a comparison (not shown here) between CRUPEDIX estimates and data-based 10-years return period peak discharge obtained by tting annual maxima to a Gumbel distribution, on all streamgauges of the region.

It showed a globally fair agreement, despite a tendency of CRUPEDIX to overestimate 10-years return period peak discharges on small catchments (< 200 km 2 ).

Note that a more recent method, named SHYREG [START_REF] Aubert | The SHYREG ow methodapplication to 1605 basins in metropolitan France[END_REF], has been developed for the estimation of reference peak discharge in mediterranean catchments. But the homogeneous application of the CRUPEDIX method over the whole study area, even on ungauged streams, allows its use as a common reference for the evaluation of regional ood discharges. Consequently, the ratio Q max /Q 10 , where Q max is the maximum simulated peak discharge, gives a clear indication of the simulated severity of the ood, on each reach of the hydrographic network.

Results

Contribution of the implemented weathered rock layer

The contribution of the implementation of a weathered rock layer in the model is assessed through a comparison between measured discharge and simulated discharge obtained with and without the weathered rock layer. Results are compared and analysed for each geology type. Tables 3 and4 summarise the scores obtained for each simulation.

Metamorphic schists and sedimentary rocks

On the Gardon river catchments, the dominant geology is composed of metamorhic schists on the upper part, and limestone and other sedimentary rocks (marls, sandstone) on the lower part. The long-term simulation results are evaluated in Table 3 and the scores obtained for the October, 2008 event are shown in This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ stay closer from 0 than 1 in most of the case. This is particularly true for the event simulation, for which negative Nash-Sutclie eciencies are obtained. Nevertheless, correlation coecients R 2 larger than 0.7 are obtained for long-term simulations.

A visual evaluation of the model performances gives indications on the causes of such poor performances. As an example, Fig. 6 compares the measured and the two simulated hydrographs on the Gardon at Mialet (220 km 2 ), which is a schist- dominated catchment. For the long-term simulation (Fig. 6a), the implementation of a weathered rock layer reduces the tendancy of the model to simulate frequent variations in the series. This result is similar to the eect observed for granitic catchments, but in this case the smoothing eect due to the weathered rock layer is not sucient to reproduce satisfyingly the observed discharge series. Similarly, the benets of adding the layer for simulating ood events are incomplete (Fig. 6b). Once again, the implementation of this weatherd rock layer decreases the simulated water volume and peak discharge, but the simulated hydrograph still remains larger than the observed one by order of magnitudes (PBIAS criteria exceeds 400 % on this catchment). Apparently, the added layer does not store enough water in the case of schists and sedimentary rocks.

Regional simulations of the 2008 events

Cases of the two ood events

The two 2008 ood events dier signicantly, although their magnitudes remain approximately similar. The simulated hydrological signature of the two events is shown in Fig. 7, where the ratio between simulated peak discharge Q and 10-years return period CRUPEDIX estimated peak discharge Q 10 (computed according to equation 1) is presented at the regional scale. Fig. 7 highlights the different scales for which the events are the most intense. The October event appears as intense at all scales, from the smallest catchments (∼1 km

2 ) located where the largest rainfall amounts have been observed, to the largest (Cèze, Gardon, Vidourle catchments, with an area > 500 km 2 ), as the consequence of a routing eect of the ood. Please note that ratio values computed on small catchments must be considered carefully, because of the known tendency of CRUPEDIX to overestimate 10-years return period peak discharges on catchments smaller than 200 km 2 , as mentionned in section 3. On the other hand, the November event is simulated as very intense only at the largest scales (except one small area located in the Ardèche catchment), by accumulation eect.

These dierences can be explained by the dierent natures of streamow generation processes simulated by the CVN-p model. be associated with groundwater ow essentially. The areas where surface runo is produced during the October event (Fig. 8a) spatially match with the zone of high severity (Q max /Q 10 >1.5) in Fig. 7a. This clearly shows that the simulation of the October event leads to intense surface runo, responsible of the severity of the ood.

Two reasons probably explain why surface runo is produced by the model during the October event and much less during the November event:

a) The rst stands in the rainfall intensities. b) The second reason is linked to the location of the rainfall, as regard as the soil properties. The largest part of the precipitation of the November event was located on the mountainous area of the Cevennes-Vivarais region (western part of the catchments). This area is mainly covered by forest, with a steep terrain and permeable soils located on cristalline or metamorphic rocks, whereas the soils encountered in the sedimentary plain area, dominated by agricultural land uses, are found to be much less conductive, as shown by experimental in situ inltration measurements [START_REF] Desprats | Cartographie de la perméabilité des sols pour l'aide à la prévision des crues; cas d'étude sur le Gardon d'Anduze[END_REF]. This also explains the tendency of the model to mainly simulate surface runo on the plain areas aected by the October event, and groundwater ow on the areas aected by the November event.

Results presented in Fig. 7 and Fig. 8, despite they provide usefull information on the spatio-temporal dierences between events and on the corresponding simulated streamow processes, should be considered with caution because they are only model results. In the folowing sections, those results are compared to observations. 4.2.2. Regional evaluation of the simulations Small-to-medium scale (1-100 km The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ were estimated in 35 locations according to the methodology described by [START_REF] Gaume | Post-ood eld investigations in upland catchments after major ash oods: proposal of a methodology and illustrations[END_REF]. Fig. 9 compares simulated specic peak discharges to post-ood survey estimates. We choose to confront specic peak discharge instead of absolute peak discharge for an enhanced regional overview of the results. A look at g.9a) and b) shows that the CVN-p model simulates two areas where specifc discharge values are larger than 12 m 3 .s -1 .km -2 : a rst one at the border be- tween the Gardon and the Ceze catchments, and a second at the southern border between the Gardon and the Vidourle catchments. These two zones correspond to the two most investigated areas during the post-ood event survey, since they were the most aected by the ood. Globally, the spatial coherence between The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ The tendency of the model to perform well on a certain type of geology and not on others is thus conrmed at the regional scale.

These results also prove that the performances are not event-dependent: both ood events provide very similar results. We can thus claim that our results only arise from the structure of the hydrological model and from its parametrization, and can consequently be reproduced for other ood events.

Discussion

The role of the sub-soil compartment in the streamow dynamics

The results of section 4.1 suggest the importance of the sub-soil compartment in the long-term dynamics as well as in the ood event response of catchments. The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ this parameter. Sometimes, models and their water storage capacities are set up using the knowledge provided by soil databases [START_REF] Manus | A modeling approach to assess the hydrological response of small mediterranean catchments to the variability of soil characteristics in a context of extreme events[END_REF]Braud et al., 2010, e.g.). Only considering soil horizons can lead to the use of correction coefcients to account for an eective water storage capacity, generally much larger than the soil storage capacity [START_REF] Roux | A physically-based parsimonious hydrological model for ash oods in Mediterranean catchments[END_REF][START_REF] Garambois | Characterization of catchment behaviour and rainfall selection for ash ood hydrological model calibration: catchments of the eastern Pyrenees[END_REF]. To face the lack of available data which can be used in process-oriented distributed models, the present study demonstrates the applicability and reliability of the The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ addition, simulations were performed on another ood event that impacted both the Tarn (crystalline rocks) and the upper Gardon (schists): the 19-20 October 2006 event. Results, not shown here, are almost identical to those discussed in this study. This proves the robustness of the results presented here.

If the model structure is not able to reproduce the storage and draining behaviour of weathered schist rock layers, whatever the thickness and conductivity considered, this means that this geology acts dierently than crystalline rocks on the sub-surface owpaths and thus on the response of the catchments. The potential hydrologic specicity of schist rocks, despite poorly described in litterature, has been suggested by [START_REF] Martin | Fonctionnement hydrologique des bassins versants de roches métamorphiques : exemple du bassin versant des Maurets (massif des Maures, Var, France)[END_REF] and [START_REF] Maréchal | Sur l'origine morphologique des écoulements par l'analyse d'observations hydrologiques distribuées. Application à deux bassins versants cévenols (Gard, France)[END_REF], both looking at french mediterranean catchments. In these two studies, the authors observe that schist catchments behave dierently from others. [START_REF] Martin | Fonctionnement hydrologique des bassins versants de roches métamorphiques : exemple du bassin versant des Maurets (massif des Maures, Var, France)[END_REF] assume that the planar structure of schisty rocks represents a preferential sloping direction for the subsurface or groundwater ows and that consequently, depending on the direction of the schist layers regarding the topography, schists can whether accelerate groundwater ows or increase water storage. We believe that this behaviour largely explains the results presented here. Of course, this assumption needs to be conrmed, through other modelling studies as well as complementary observations. Usefullness of process-oriented and multi-scale regional models Through this work, we hope to convince hydrologists about the usefullness of regional process-oriented models. Three important features of the modelling approach used here are highlighted:

35

Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172

The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ 1. A regional set-up of the model. As opposed to most of the modelling works performed in the Cevennes-Vivarais region, focusing on a single catchment, the present study covers the entire region (seven catchments, with an area of several thousands of km 2 ). This regional approach allows a direct comparison of the simulated streamow dynamics of catchments which can dier by their physiographic characteristics (such as geology). This inter-catchments comparison, coupled to a classical evaluation of the goodness of the simulations, reveals some important behavioural dierences existing between catchments that would have been dicult to detect using a classical catchment-by-catchment modelling approach.

2. A multiscale modelling strategy. Another important characteristic of the modelling strategy followed here stands in the wide range of spatial scales covered by CVN-p. The continuity between scales, from the elementary response unit (< 1 km 2 ) to the outlet of the largest catchments (> 2000 km 2 ), gives an integrated view of the hydrological response to ood events. It allows a meaningfull multiscale comparison of dierent ood events and of their magnitude, such as in Fig. 7.

3. An uncalibrated modelling approach. The absence of calibration is not an end in itself, but is necessary in the purpose of testing hydrological functioning hypotheses. The strength of this approach is illustrated in this study when assessing the contribution of the weathered rock layers in the model perfor- The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ model structure to reproduce the dynamics of crystalline rock catchments and discovered that this structure is not suitable for schist rocks catchments.

Conclusions

This work represents a step towards a better understanding of the governing hydrological processes in the mediterranean area, and especially on the role played by geology in catchments prone to ash oods. Through a regional multiscale hydrological modelling approach, focusing both on event and inter-event (long term) simulations, we assess the eect of adding weathered rock layers into the model, with hydraulic properties varying with geology and estimated after the results obtained by Vannier et al. (2014). Simulation results highlight the importance of the sub-soil layers and their associated storage capacity in the general streamow dynamic of catchments, during and between ood events. Results also enhance some behavioural dierences between catchments, related to their dominant geology. The addition of sub-soil layers in the CVN-p model largely improves the results, and allows to satisfyingly reproduce the streamow dynamic and the ood response of crystalline rocks catchments. On other geologies, the improvement is real but still not sucient to perfectly agree with the observations. On a methodological point of view, this work proves the reliabilty of uncalibrated, process-oriented modelling studies, especially when set up at a regional scale. Such approaches are very eective to bring out behavioural similarities or dierences between neighbouring catchments, or to identify the key hydrological processes over a wide range of spatial and temporal scales. Combined with a multi-criteria evaluation strategy, and proceeding in an iterative way to test 37

Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172

The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ hydrological functioning hypotheses, such modeling approaches need to be encouraged and developed.

Further eld observations and modelling studies are required to conrm the preliminary results obtained and shown in this work, especially to investigate and better reproduce the groundwater transfers that exist in schists and sedimentary rocks sub-soil layers. We also recommend to use similar modelling appoaches over dierent regions and under other climatic conditions, to assess the robustness of the proposed methodology.

  simulations. Root extraction, vegetation growth, interception and evapotranspiration processes were added, in order to simulate a realistic water balance and get a dynamic evolution of soil wetness. The box-type structure of the model CVN-p, with the implemented modules and their inter-connexions is given and compared to the previous CVN version in Fig.1. A detailed description of the dierent hydrological modules coupled within the continuous CVN-p model is presented in Appendix A.The model is forced with two spatialised variables : precipitation and reference evapotranspiration (ET 0 ). Precipitation is necessarily liquid (the model does not account for snow accumulation nor melting). Forcings are interpolated over the model mesh using weighted averages by a dedicated module (INPUT).

Figure 1 :

 1 Figure 1: Structure of the event-based model CVN (Manus et al., 2009; Anquetin et al., 2010; Braud et al., 2010) (a) and the continuous model CVN-p used in this study (b). The modules are coloured according to the type of process: brown for the soil compartiment, blue for runo and river ow, and green for the vegetation-related processes.

later adapted 7

 7 Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172

Figure 2 :

 2 Figure 2: Figures adapted from Vannier et al. (2014) : a) Typical pedologic prole, after Kang & Tripathi (1992) and level of description in the Cevennes-Vivarais BD-sols soil databases.b) Depth to bedrock D and lateral hydraulic conductivity k calculated using streamow recession analysis.

3.

  Regional set-up of the model 3.1. Presentation of the area and available data The CVN-p model is set-up over the seven largest catchments in the Cevennes-Vivarais region : the Ardèche (2263 km 2 ) Cèze (1372 km 2 ) and Gardon (1914 km

Figure 3 :

 3 Figure 3: Location of the seven selected catchments, and dominant geology of the Cevennes-Vivarais region (deriving from the 1:1 000 000 french geological map). The location of the streamgauges from which measurements are used in this study is simbolized by yellow points.

  4 http://www.brgm.fr 12 Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172

  When complete measured hydrographs are available, an evaluation of the model performance through the calculation of four score indices is performed. 14 Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172

Figure 4 :

 4 Figure 4: Maps of the cumulated rainfall amounts observed over the Cevennes-Vivarais region during the October 21 -October 23, 2008 event (a) and the October 31 -November 5, 2008 event (b). These maps represent the cumulated rainfall measured on raingauges interpolated through a kriging technique over a 1x1 km 2 resolution grid. The blue and red crosses indicate the location of the Bessèges and Loubaresse raingauges, for which the measured hyetograms are shown in (c).

Nash-

  Sutclie eciency(Nash & Sutclie, 1970) (NSE), Nash-Sutclie eciency of the logarithmic discharge (LNSE), correlation coecient R 2 and bias indicator PBIAS[START_REF] Kling | On the development of regionalization relationships for lumped watershed models: The impact of ignoring sub-basin scale variability[END_REF] are computed. Along with the tradtional performance indices computation, a deep attention is paid to visual comparison between observed and simulated hydrographs, to evaluate the model ability to reproduce catchments response. Visual comparison is complementary to quantitative evaluation, in a sense that it gives indications on the ability of the model to reproduce ow dynamics, recession rates or ood timing, which are not easily summarised in score indices. In addition, visual evaluation allows the distinction between time periods where the model gives good results, and periods where it is not the case, and thus makes the interpretation of the results easier.Long-term simulationsIn order to assess the role of the added weathered rock layer, same simulations are done with and without weathered rock layer. This evaluation is performed on several catchments of dierent sizes: three Tarn sub-catchments, essentially composed of granites and gneiss (the Rieumalet, the Tarn at Pont-de-Montvert, and the Tarn at Bedouès, #8, #9 and #11, respectively, in Fig.3); and ve Gardon 16 Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ sub-catchments, where schists are dominant on the upper part while sedimentary rocks mainly cover the downstream part (Gardon at Saint-Martin, Mialet, Ners and Russan, #18, #21, #22, #23 and #25, respectively, in Fig.3).Compared discharge series begin on April 1, 2008 and end on October 21, 2008.In these simulations the three rst months are ignored (simulations eectively start on January 1, 2008) in order to avoid initialisation artefacts. Sensitivity tests (not shown here) were performed to assess the average necessary spin-up duration, and a value of three months appeared as enough in the large majority of cases;

  a) Peak discharge estimated a posteriori in 35 catchments, ranging from 1 to 100 km 2 , during the post ood investigation of the October 21-23 event. The post ood survey follows the methodology dened by Gaume & Borga (2008); b) Discharge measurements, available on 34 operationnal streamgauges in the re-17 Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172

  4.1.1. Granite and gneissOn crystalline rock (granite and gneiss) catchments located on the Tarn river, the benets of including a deep weathered rock layer are clear, whether for event or 19Author-produced version of the article published in Journal of Hydrology, Volume 541,Part A, October 2016, Pages 158-172 The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ long-term simulations. For long-term simulations, adding a deep weathered rock horizon signicantly increases the Nash-Sutclie eciency and the Nash-Sutclie eciency of the logarithmic discharge (Table3), which turns from negative to better than 0.7 values on each of the three catchments. R 2 criteria values also improve in all cases. One must notice a slight increase of the PBIAS index values (becoming positive in all cases) when adding the weathered rock layer. For event simulations, results are also improved when adding the deep weathered rock horizon (4): on each of the catchments, the four performance indicators get better values when adding the deep layer. Especially, Nash-Sutclie eciency of the logarithmic discharge and PBIAS index reach satisfying values for non-calibrated event simulations (Table4).As an example, Fig.5acompares the measured and the two simulated hydrographs (one with and one without the weathered rock layer) on one of the grantic catchments (Tarn at Pont-de-Montvert, #9) during several months. The visual improvement of the model's behavior when using the weathered rock layer is very signicant. The model version in which there is no weathered rock layer produces a noisy discharge signal during long-term simulations, corresponding to a direct response to the precipitation signal. When adding the weathered rock layer, the long-term simulated discharge signal is smoother: the layer acts as a buer, delaying the hydrologic response in time. This behavior is very similar to the observed response, and the model in this version reproduces very well the streamow dynamics of the granitic catchment. In Fig.5b, the same comparison during the November, 2008 event is shown. Once again, the visual improvement when using the weathered rock layer is clear. While the simulated volume and peak discharge are overestimated by the unmodied model version, the addition 20 Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172 The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ of the weathered rock layer brings the simulated hydrograph much closer to the observation. The reason probably stands in the additionnal storage capacity implemented in the model: the added weathered rock layer stores a signicant part of the inltrated water, and releases it progressively. On the other hand, the model without additional layer overreacts to precipitation forcings because of its lack of storage: in this case water quickly percolates and almost instantaneously enters the stream network.

Figure 5 :

 5 Figure 5: Comparison of measured discharge and discharge simulated by the CVN-p model with and without deep weathered rock layer on a granitic catchment: Tarn in Pont-de-Montvert (67 km 2 ). a) long-term simulation between April 1, 2008 and October 21, 2008 (discharge scale is logarithmic). b) Event simulation between October 31, 2008 and November 5, 2008.

Figure 6 :

 6 Figure 6: Comparison of measured discharge and discharge simulated by the CVN-p model with and without deep weathered rock layer on a schist catchment: Gardon in Mialet (220 km 2 ). a) Long-term simulation between April 1, 2008 and October 21, 2008 (discharge scale is logarithmic). b) Event simulation between October 21, 2008 and October 23, 2008.

Figure 7 :

 7 Figure 7: Maps of the ratio between simulated peak discharge Qmax and estimated peak discharge Q10 of a 10-years return period ood event. The ratio is computed on each river reach. Q10 is estimated according to the CRUPEDIX method (1980). a) October 21 -October 23, 2008 event; (b) October 31 -November 5, 2008 event. The contours of the cumulated kriged rainfall amounts appear in blue.

  Fig.4c shows that the October event, shorter, was associated with larger rainfall intensities than the November event. High rainfall intensities strongly increase the probability of the 26 Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172 The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ model to produce inltration excess overland ow. This is what happens during the simulation of the October event;

  2

  ) evaluation: comparison to post-ood survey estimates Since the October 21 -23 event caused damages (road cuts, landslides, ooding of several places), a post-ood event survey was thus organized. Peak discharges 27 Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172

Figure 8 :

 8 Figure 8: Maps of the ratio between surface runo and groundwater ow simulated by the CVN-p model. a) October 21 -October 23, 2008 event; (b) October 31 -November 5, 2008 event. The contours of the cumulated kriged rainfall amounts appear in blue.

  Fig.10presents an evaluation of the simulations for the two ood events. These maps show the calculated value of the three performance criteria previously introduced (NSE, PBIAS and R2), computed at all the gauging sites. On these maps, the size of the circles gives the magnitude of the observed peak discharge, thus indicating the relative importance that must be accorded to the computed score 29

Figure 9 :

 9 Figure 9: Comparison of the peak specic discharges simulated on each river reach to the peak specic discharge estimated during the post-ood survey, for the October 21 -October 23, 2008 event. River reaches and points denoting the location of the post-ood survey (PFS) estimates are coloured according to the magnitude of the peak specic discharge. a) Map of the regional simulation results; b) Zoom on the locations of post-ood survey estimates; c) Scatter plot of the results.

Fig. 10

 10 Fig.10 clearly indicates very distinct performances obtained by the model, depending on the considered catchment. On the Ardèche and the Tarn catchments,the model provides fair results (for a non-calibrated model) in terms of Nash-Sutclie Eciencies for both events (note that the October event did not aect strongly the Tarn river), with positive NSE, with a score larger than 0.4 on most of the gauging locations. By contrast, the results obtained on the other catchments (Cèze, Gardon, Vistre, Vidourle, Hérault) are poor, with negative values of NSE calculated almost everywhere, for both events.

  Vannier et al.(2014) showed the necessity to account for sub-soil (i.e. weathered rock layers) water storage capacity to correctly reproduce the water balance of Cevennes-Vivarais catchments. The direct implementation of a weathered rock layer into the regional rainfall-runo model CVN-p, with the parametrization proposed by Vannier et al. (2014), involves a massive -although unequal -improvement of the model results, both for ood event and long-term simulations.These ndings conrm the need to properly represent the overall water storage capacity of catchments into hydrological models[START_REF] Sayama | How much water can a watershed store?[END_REF]. Because of a generalized lack of reliable information on the water retention capacity of rocks that compose the sub-soil compartment, hydrologists often rely on calibration of 32 Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172

Figure 10 :

 10 Figure 10: Spatial representation of the performance indices calculated for the simulations of the two ood events of year 2008 in the Cevennes-Vivarais region, using the CVN-p rainfall-runo model and using the weathered rocks horizons.

  method proposed by Vannier et al.(2014) to add a weathered rock layer below upper soil horizons and to characterize it in terms of eective thickness and hydraulic conductivity.The dierent hydrological behaviours induced by distinct geologiesThe present work shows that in the Cevennes-Vivarais region, geology appears as an important control factor over the hydrological behaviour of catchments. The response of crystalline catchments is properly reproduced by the model, but the results remain perfectible for schist-dominated catchments. Several sensitivity studies (not shown) have been performed on these schist catchments to see if this could have had a positive impact on the simulated streamow dynamics. The result is that no dierent parameters combination turned out to provide better simulation results than those presented in this article. This highlights a lack in the model structure more than in the parametrization. It is important to add that the results shown here are not specic to the two events selected. The gardon catchment, for which the CVN-p model overestimates both volume and peak discharge during the October 2008 event, behaves similarly during the November 2008 event (this is not shown here, but results are presented in Vannier (2013)). In 34 Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172

  mance: the parameters that characterize the weathered rock horizons are not calibrated, the values estimated by Vannier et al. (2014) are directly given as input into the model. Through this approach, we found out the adequate 36 Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172

Table 2 :

 2 -produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172 The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ Simulation table

	Temporal window	Type of simulation	Rainfall forcing
	01/01/2008 -21/10/2008	Initialisation	SAFRAN
	21/10/2008 -23/10/2008	Event	Kriged rainfall
	23/10/2008 -31/10/2008	Transition	SAFRAN
	31/10/2008 -05/11/2008	Event	Kriged rainfall

Table 4 .

 4 In this case, the benets of adding a weathered rock layer in the model are not as important as in the case of grantic catchments. Even if almost all of

	Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172
	The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822
	doi : 10.1016/j.jhydrol.2016.04.001
	©.
	the performance criteria values increase signicantly when adding the layer, this
	is not sucient to reach what can generally be considered as good performance.
	Especially, Nash-Sutclie values computed on discharge and logarithmic discharge
	21

  max 22 Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

		WRL	0.72	0.75	0.82	0.69	0.76	0.77	0.75	0.81
	R2
		No	WRL	0.36	0.69	0.64	0.44	0.52	0.54	0.46	0.64
	PBIAS	No WRL WRL	19.60 -25.53	2.15 -35.69	1.14 -2.20	105.73 21.39	-6.66 -11.22	136.11 49.97	88.77 20.43	94.01 35.86
	LNSE	No WRL WRL	-1.29 0.71	0.24 0.88	-3.09 0.88	0.18 0.49	-0.47 0.52	-0.97 0.41	-0.12 NA 1 0.68 NA 1
	NSE	No WRL WRL	-0.49 0.67	0.44 0.65	-0.26 0.80	-4.14 -0.06	-0.18 0.63	-4.41 0.18	-2.14 0.61	-2.14 0.51
	Catchment Dominant geology Area (km 2 )	Rieumalet (Pont-de-Montvert, #8) Granite 20	Tarn (Pont-de-Montvert, #9) Granite 67	Tarn (Bedouès, #11) Granite 189	Gardon (Saint-Martin, #18) Schist 30	Gardon (Mialet, #21) Schist 220	Gardon (Anduze, #22) Schist 543	Gardon (Ners, #23) Limestone / Schist 1100	Gardon (Russan, #25) Limestone / Schist 1520	1 Undened value because of null values in the measured discharge series

Table 3 :

 3 Performance indices of the simulations performed on 8 catchments of various geologies between January 1, 2008 and October 21, 2008. The rst three months are not taken into account in the score calculations, to avoid initialisation artefacts. This table compares the results obtained by simulations performed without adding any weathered rock layer in the model (No WRL), and simulations including these weathered rock layer (WRL). Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172 The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

23

Table 4 :

 4 Performance indices of the simulations performed on 6 catchments of various geologies, during two rainfall events of 2008. This table compares the results obtained by simulations performed without adding any weathered rock layer in the model (No WRL), and simulations including these weathered rock layer (WRL).Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

24

http://floodscale.irstea.fr

http://www.hymex.org

Acknowledgements

This work is part of the FloodScale project, which is funded by the French National Research Agency (ANR) under contract n • ANR 2011 BS56 027, which contributes to the HyMeX program. The authors would like to acknowledge Jérémy Chardon, from LTHE, for supplying the 10-years return period quantiles of SAFRAN daily rainfall depths.

Author-produced version of the article published in Journal of Hydrology, Volume 541, Part A, October 2016, Pages 158-172 The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4. The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ to a gradient of charge. In natural conditions, various poorly known processes, such as rock fracturing or macroporosity, make the actual ow conditions signicantly dier from Richards theory (Villholth & Jensen, 1991). Therfore, the use of Richards equations solver in hydrological models, like the FRER1D module, should rather be considered as a conceptual representation of the actual processes than as a physically-based resolution system.

2. Extraction of ponding and runo generation: PEM. This module takes as input the ponding depth (runo ) produced by FRER1D, and sends it -instantaneously -to the closest river reach. Since the river network is nely described, this instantaneous transfer of runo into the river does not imply an unrealistic reduction of the total water transfer time through the catchment. The spatial discretization is based on elementary watersheds with area that does not exceed 0.5 km 2 . Considering a runo velocity of 1 m/s before it reaches the river network, this hypothesis always leads to neglect less than 30 minutes of water transfer time.

3. Water transfer in the river network : RIVER1D. RIVER1D module computes the routing of water along the river network. It is based on the solution of the one-dimensionnal kinematic wave equation [START_REF] Branger | Towards multi-scale integrated hydrological models using the LIQUID R framework. Overview of the concepts and rst application examples[END_REF]. The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ otranspiration (ET 0 ) is used as a forcing, and modulated by crop coecients, depending on the vegetation (CRLINPG module). The growth of plants is prescriped by means of a dynamic evolution of the Leaf Area Index (LAI), as monthly average values (CRLINPG). VEGINT computes the fraction of water intercepted by plants during rainfall events (this fraction being subsequently available for direct evaporation) [START_REF] Noilhan | A simple parameterization of land surface processes for meteorological models[END_REF], while ETPART computes both potential vegetation transpiration and potential evaporation on soil, using a partition coecient depending on LAI and a Beer-Lambert law [START_REF] Huygen | SWAP 2.0: input and ouput manual[END_REF]. ROLI computes the actual amount of water extracted by roots in the soil according to the potential transpiration and the available water content [START_REF] Li | An exponential root-water-uptake model with water stress compensation[END_REF]. The original publication is available at http://www.sciencedirect.com/science/article/pii/S0022169416301822 doi : 10.1016/j.jhydrol.2016.04.001 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/


Isabelle Braud

Marco Borga

Jonathan Gourley

Marcel Hürlimann (')

Massimilano Zappa

Francesc Gallart

A Montanari

Cudennec, C Toth

Flash floods, hydro-geomorphic response and risk management. Preface of the special issue

Introduction

Each year, natural disasters are responsible for fatalities and economic losses worldwide with 101 billion USD in economic losses and 7000 fatalities reported for 2014 [START_REF] Swissre | Natural catastrophes and man-made disaster in 2014: convective and winter storms generate most losses[END_REF]. Even if earthquakes are responsible for most of these fatalities, flash floods and landslides are recognized as a significant source of threat to human lives [START_REF] Swissre | Natural catastrophes and man-made disaster in 2014: convective and winter storms generate most losses[END_REF]. Jonkman (2005), in a global assessment of flood-related casualties, showed that flash floods lead to the highest mortality (number of fatalities divided by the number of affected people).

They are also often associated with shallow landslides and geomorphic processes that can increase threat to human lives. Analysis of a global data set of fatalities from non-seismically triggered landslides (Petley, 2012) shows that 2620 fatal landslides were recorded worldwide in the period 2004-2010, causing a total of 32,322 recorded fatalities. In addition, heavy precipitation events, at the origin of flash floods and shallow landsliding are expected to increase in the future (e.g. Scoccimarro et al., 2015 for a recent study in Europe). Progress in flash floods and landslides understanding, forecasting and warning is therefore still needed to disentangle the complex interactions between hazards, exposure and vulnerability and to increase resilience [START_REF] Ruin | Social and Hydrological Responses to Extreme Precipitations: An Interdisciplinary Strategy for Postflood Investigation[END_REF].

A previous special issue of J. Hydrology entitled "Flash floods: observations and analysis of hydro-meteorological controls", published in 2010 (Borga et al., 2010), provided first insights about the value of data collection specifically targeted towards flash floods studies and advanced common frameworks for flash flood data analysis and for flash flood forecasting. The present Special Issue "Flash floods, hydro-geomorphic response and risk management" extends the focus by examining hydrogeomorphic responses of intense rainfall and advancing analyses of socio-economic impacts and of risk management options and policies.

New data at higher resolution are now available and a number of papers of the present special issue exploit these new data to provide new insights into flash flood and landslides process understanding. Progresses in flash flood and landslide forecasting are also illustrated by several papers which report on various initiatives in different countries. A significant numbers of papers address socio-economic impacts, showing the value of multi-disciplinary approaches (e.g. [START_REF] Ruin | Social and Hydrological Responses to Extreme Precipitations: An Interdisciplinary Strategy for Postflood Investigation[END_REF], as advocated in the new Panta Rhei (Montanari et al., 2013) decade of the International Association of Hydrological Sciences.

Overview of the special issue

This special issue of the Journal of Hydrology entitled "Flash floods, hydro-geomorphic response and risk management" contains 49 papers. Several papers present new insights gained in flash flood and landslide processes understanding based on new data analyses and modeling studies, mainly thanks to data sets with higher space-time resolution. Flash flood and landslide forecasting are also topics of active research. Studies addressing socioeconomic impacts and how they can be related to flash flood physical characteristics are also presented, in relation with new data collection (including historical events) and analyses, often involving pluri-disciplinary teams. Some papers also address risk perception by people.

Several studies also address jointly flash floods and landslides as they are often related. They show how a common appraisal using approaches developed both in geomorphology and hydrology can be complementary.

The papers included into this special issue are organized in four main topics:

1/ Advancing flash flood understanding and forecasting using new data collection and modelling studies 2/ Shallow landslides and geomorphic processes understanding, modelling and forecasting 3/ Flash flood forecasting 4/ Advancing understanding of vulnerability and risk perception associated to flash floods and landslides Case studies are mostly concentrated in the Mediterranean region and in the USA, but several papers from more northern countries, the Middle East, Japan, China and Papua New Guinea show that flash floods and landslides are a concern in all parts of the world.

Theme 1: Advancing flash flood understanding and forecasting using new data collection and modelling studies

The first theme "Advancing flash flood understanding and forecasting using new data collection and modelling studies" contains 16 papers. Quantitative Precipitation Estimation (QPE) and description of rainfall space-time variability are still active topics leading to several papers aiming at improving QPE accuracy and space-time resolution to be consistent with flash floods and urban hydrology studies (1 km 2 and 1 h resolutions). Methods rely mainly on more or less sophisticated merging of radar and rain gauges data and the quantification of uncertainties (Berg et al., 2016;Boudevillain et al., 2016). Llasat et al. (2016) illustrate the value of high temporal rainfall resolution (1 to 5 minutes) to study the impact of convective rainfall on flash floods and on their evolution in northeast Spain. Ghanmi et al. (2016) improve IDF (Intensity Duration Frequency) estimates of extreme rainfall using scale invariance and daily and tippet bucket rain gauges. Silvestro et al. (2016) illustrate how the description of the space-time resolution of rainfall can explain the occurrence of a severe flash flood in Genoa (Italy) highlighting the needs for a better The original publication is available at http://www.sciencedirect.com, doi : 10.1016/j.jhydrol.2016.08.005 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ measurements. These results are of great interest as flow in karstic areas is poorly documented, although karstic areas occupy a significant area in Mediterranean regions. Flash floods are often associated with matter transport that can have an impact on coastal areas. 2016) documented a flash flood in Genoa (Italy) and measured physicochemical characteristics of the water led by the flood in the coastal area. They show that the impact is significant but of short duration and that wind conditions are more influential on the dynamics of the area.

Capello et al. (

Other papers try to better understand processes active during flash floods, combining observations and modeling in a hypothesis testing framework (Clark et al., 2011). Vannier et al. (2016) propose a distributed hydrological model set up at the regional scale in the Cévennes-Vivarais region and highlight the role of geology in modulating the hydrological response between and during flash floods. They use both continuous and post-event data to assess the model performance. Using a data driven approach to build a semi-distributed model, Adamovic et al. (2016) also highlight the role of geology in shaping the hydrological response of Mediterranean catchments. They show that a model based on the hypothesis of dominant sub-surface flow is able to reproduce quite well observed flash floods in wet conditions and low vegetation period. On the other hand, in dry and vegetated periods, the role of evapotranspiration must be taken into account. Vincendon et al. (2016) show how an improved representation of soil water transfer allows the setting of a regional scale modeling without calibration. They also use proxy data (road cuts) to assess the validity of the proposed modeling. Grillakis et al. ( 2016) use a semi-distributed model to assess the role of initial soil moisture on flash floods comparing results in Austria and Crete. The impact of soil moisture on flood peak appears to be quite low. An interesting point of this study is that initial soil moisture was derived from satellite data, which is of interest in data scarce areas (see also [START_REF] Tekeli | Evaluation of TRMM satellite-based precipitation indexes for flood forecasting over Riyadh City, Saudi Arabia[END_REF].

Theme 2: Shallow landslides and geomorphic processes understanding, modelling and forecasting In the second theme, "Shallow landslides and geomorphic processes understanding, modelling and forecasting" (10 papers), several papers revisit the threshold approach for landslides or debris flow forecasting. Three papers highlight the importance of high-resolution rainfall data for better estimation of the rainfall threshold relationship, highlighting the need of weather radar rainfall estimates for this task (Abancó et al., 2016;Iadanza et al., 2016;Marra et al., Author-produced version of the article published in Journal of Hydrology (2016) vol. 541, n° Part A, p. 1-5

The original publication is available at http://www.sciencedirect.com, doi : 10.1016/j.jhydrol.2016.08.005 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ 2016). Peres and Cancelliere (2016) use a Monte-Carlo simulation approach to compute the return period of rainfall triggering landslides. Using high resolution data collected in an experimental catchment, Abancó et al. (2016) analyzed triggering factors of landslides and found that the factors that were better discriminating triggering and non-triggering rainfall were rainfall amount, maximum and average intensity. Bezak et al. (2016) used copula to compute intensity-duration-threshold (IDF) relationships and compared their efficiency with more traditional rainfall-thresholds methods for floods, landslides and debris flow prediction.

They show that better results are obtained with the IDF approach. Ciabatta et al. ( 2016) use an early warning system for landslides set up in the Umbria region (Italy) to assess the impact of climate change on landslides occurrence and show an expected increase of up to 40% by the end of the 21 st century as compared to present. Robbins (2016) used a modified Bayesian approach for assessing thresholds of landslide probability associated with rainfall events of satellite-derived specific magnitude and duration in Papua New Guinea. The original publication is available at http://www.sciencedirect.com, doi : 10.1016/j.jhydrol.2016.08.005 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ improvements to the method in order to take into account rainfall spatial variability. Miao et al. ( 2016) also revisit the Flash Flood Guidance method to propose a flash flood forecasting system for China. The rainfall threshold identification is based on distributed rainfall-runoff model climatology and binary classification of the resulting data. Zhang et al. (2016) study the impact of radar/rain gauges reanalysis bias correction on the performance on flash flood detection. They show an improvement for larger catchments but the bias correction is detrimental for small catchments. Nguyen et al. (2016) proposed a semi-distributed hydrological model coupled with a 2D hydraulic model, aiming at simulating discharge, water height and velocity for flash flood warning. The model is set up with a priori parameters and not calibrated. A sensitivity test is performed using synthetic precipitation input showing reasonable performance of this non-calibrated model. The latter is also evaluated for several observed events. [START_REF] Vergara | Estimating a-priori kinematic wave model parameters based on regionalization for flash flood forecasting in the Conterminous United States[END_REF] propose a regionalization approach to specify parameters of a 1D hydraulic model deployed over the whole US, specifically adapted to flash flood forecasting in ungauged catchments. Tao et al. (2016) use data from the Integrated Precipitation and Hydrology Experiment (IPHEx) where an enhanced rainfall measurement set up was deployed in order to improve QPE to assess, in near real time conditions, the performance of flash flood forecasting systems. They compare different QPE products, data assimilation systems and obtain in particular promising results with the assimilation of discharge data. Artinyan et al. (2016) present an operational flash flood forecasting system set up in the Arda transboundary catchment between Bulgaria and Greece. The system is based on a calibrated distributed hydrological model, with improved river routing. The forecasting system is operated using real time transmitted rain gauge data. The system provides one line forecasting and is evaluated in the paper using a real case study. [START_REF] Tekeli | Evaluation of TRMM satellite-based precipitation indexes for flood forecasting over Riyadh City, Saudi Arabia[END_REF] use satellite derived rainfall to set up a flash flood warning system is Saudi Arabiya. Several papers propose flash flood ensemble forecasting systems. Hardy et al. (2016) propose a probabilistic flash flood forecasting system based on rainfall forecast from an ensemble Quantitative Precipitation Forecast (QPF) products. They also consider errors in intense cells location before feeding the fully distributed, non-calibrated CREST hydrological model. The method is evaluated on a case study in Oklahoma. They show that this kind of approach provides useful information to improve civil protection warning. Lagadec et al. (2016) address more specifically floods associated with quick runoff that can occur outside the river network. They propose a runoff mapping susceptibility method to the production, transfer and accumulation of runoff. They use proxy data such as regulatory maps and disruptions on roads and railway networks to assess the relevance of their method.

Author-produced version of the article published in Journal of Hydrology (2016) vol. 541, n° Part A, p. 1-5

The original publication is available at http://www.sciencedirect.com, doi : 10.1016/j.jhydrol.2016.08.005 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ Theme 4: Advancing understanding of vulnerability and risk perception associated to flash floods and landslides Thirteen papers address both physical and social vulnerability to flash flood. In terms of damages, several papers distinguish between "ordinary", "extraordinary", "catastrophic" events (Aceto et al., 2016). However, Schroeder et al. (2016) show that the definition of a generic flash flood severity index, that may apply in different hydro-climatic and/or for different environment (urban, rural) is not straightforward. Boudou et al. (2016) propose a multi-disciplinary approach to define how a flood can be qualified as "remarkable", including information on the hazard intensity, fatalities and damages and impact on society. They analyze more specifically four historical events in France and show which factors contribute to create a "remarkable" flash flood. Aceto et al. (2016) collected a data base of damages from hydro-meteorological events, including flash floods and landslides in the Calabria region. They provide trend analysis on those damaging events. Karagiornos et al. (2016) propose a method to map the susceptibility of the Greek territory to flash flood including structural building vulnerability but also social vulnerability. The original publication is available at http://www.sciencedirect.com, doi : 10.1016/j.jhydrol.2016.08.005 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ Several papers address people perception related to flash floods. Morss et al. (2016) conducted a survey to analyze people's perception of flash flood risk, understanding of the flash flood warning levels in the USA and knowledge of people reactions in case of flash floods. [START_REF] Bodoque | Improvement of resilience of urban areas by integrating social perception in flash-Author-produced version of the article[END_REF] performed a similar study in central Spain. Both studies highlight a low perception of risk and a low preparedness.

Conclusions and directions for future researches

The diversity of topics and originality of results presented in this special issue shows that flash flood and landslides studies are areas of active and innovative research. While in the past, the study of hazard, vulnerability and risk were often tackled separately; several papers in this volume show the value of multi-disciplinary approaches to better understand these combined elements. Some papers have also demonstrated the interest of high space-time resolution data to better understand processes active in flash flood and landslides generation, in particular the value of radar rainfall data to get a correct picture of forcings for flash flood and landslide processes. A new and exciting area of research is the use of information provided by social networks and citizens for a better appraisal of the spatial variability of hazard and impacts (e.g Koswate et al., 2015, Le Boursicaud et al., 2016) that is particularly relevant for flash floods. Radar observations provide the capability to estimate rainfall at scales suitable for flash flood and landslide forecasting. Hydrologic models are just now beginning to use these estimates to forecast the magnitude, specific locations, impacts, and uncertainty associated to flash floods on continental scales. Improved observations from satellite-based and airborne platforms will continue to improve the estimation of rainfall as well as to retrieve hydrologic states such as soil moisture, streamflow, and surface inundation.

The expansion of social media and the emergence of "citizen scientists" provide great capabilities for improving observations of flash flood impacts that can improve the forecast models.

Several of the papers presented in this collection make the best out of scarce data available to validate the hypothesis presented. The number of long term data inventory to verify the emerging approaches is limited. In some cases inventories are not updated anymore because of lack of funding. We think that any of the modelling approaches presented would benefit if the community would spend some more time now on retrieving data for future proof of the innovative concepts that are elaborated.

Author-produced version of the article published in Journal of Hydrology (2016) vol. 541, n° Part A, p. 1-5 The original publication is available at http://www.sciencedirect.com, doi : 10.1016/j.jhydrol.2016.08.005 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

  knowledge and forecasting of rainfall space-time patterns, a correct description at space scales of less than 8 km and time resolution of less than 3 h being needed to correctly reproduce observed characteristics of the flood. Pino et al. (2016) use the new NOAA 6 Hourly 20th Century V2 Reanalysis Data Composites to analyze the synoptic factors associated with 24 catastrophic flash floods that affected the NE Iberian Peninsula over the period 1842-2000. Such analyses are valuable as they can be used to assess possible impact of climate change on the occurrence of flash floods. Halbert et al. (2016) also show the value of historical data and post-event discharge estimation in flood frequency analysis. They compare local and regional approaches when historical flash flood and/or data from post-event surveys are included in the analysis using a Monte-Carlo approach. They show that historical and post-event data enhance results robustness for both approaches. The value of high resolution data sets to advance flash flood understanding and modelling is demonstrated in several papers. Camarasa-Belmonte (2016) use data collected since 1988 by a rain gaugedischarge network with 5 minutes time step in the Valencia region (Spain) to identify and analyze the controlling factors of flash floods in ephemeral streams. She is able to identify two types of events characterized by different characteristics in terms of rainfall amount and intensity. Le Bourgeois et al. (2016) use high temporal resolution soil moisture time series and inverse modeling to identify soil hydraulic properties associated with schist geology soils in the French Cévennes-Vivarais region, prone to flash floods. They show that rainfall can infiltrate in the weathered bedrock but that the hydraulic conductivity of this horizon is too low to avoid saturation at the weathered bedrock-soil interface, leading to local soil saturation and sub-surface flow. The method can be generalized to other geologies to better characterize infiltration capacity in flash flood prone areas. Asano et al. (2016) acquired high resolution (1 minute) surface flow and velocity in a headwater river stream to better understand flow conditions during flash floods. This provides useful information for the use of non-contact methods for gauging flooding rivers. Gazquez et al. (2016) show how hourly temperature monitoring in a cave located in a karstic area in southeast Spain provides insight into the timing and space distribution of a flash flood without the requirement of discharge Author-produced version of the article published in Journal of Hydrology (2016) vol. 541, n° Part A, p. 1-5

  Flash floods are also often associated with intense debris and sediment transport. The geomorphic impacts of flash floods are also documented. Segura-Beltran et al. (2016) use a combination of a distributed hydrological model, coupled with a 2D hydrodynamic model to get insight into geomorphic processes associated with a severe flash flood that occurred in Girona (Spain). The coupled model is validated using flow depth and flood plain extension. The model is then used to understand how paleochannels and alluvial fans were activated by the flood and how some anthropogenic elements provided disturbances to the flow. Ruiz-Villanueva et al. (2016) propose a model to assess the impact of flood shape and amplitude on the remobilization of woods, making the distinction between floods and flash floods. The model proves complementary to observations and allowed showing for instance a positive correlation between the number of remobilized woods and the length of the flood rising limbs. Albano et al. (2016) tested a new numerical method for fluid dynamics computation in order to simulate the transport of floating bodies by flash floods. The model is evaluated using a laboratory experiment simulating a dam break in a channel with floating bodies, representing for instance cars. Given the good performance of the model, the latter is used to compare several mitigations methods, aiming at limiting floating bodies' entrainment. Theme 3: Flash flood forecasting The third theme deals with "Flash flood forecasting" with 10 papers. Douinot et al. (2016) assessed the Flash Flood Guidance method in Mediterranean French catchments and proposed Author-produced version of the article published in Journal of Hydrology (2016) vol. 541, n° Part A, p. 1-5

  photographs, water marks). The authors show how man-made infrastructure contributed to the vulnerability during this event. An historical event, which occurred in 1967 in Portugal that led to more than 500 casualties, is analyzed in details byTrigo et al. (2016) in terms of hydrological and social vulnerability. This is made possible by the building of an historical data base about flash floods in Portugal. Garrote et al. (2016) built a stage-damage function for a small village in Spain, based on extensive data collection after a flash flood event. They show that the locally based function provide much more realistic results that nationally based functions. They use this function to assess the cost-benefit or protective measures. During flash floods, vulnerability is also related to population displacement. Lutoff et al. (2016) propose a multi-scale framework to analyze the social response to flash floods before peak flow and in particular how they organize themselves to face the event. Debionne et al. (2016) present a model aiming at simulating the mobility and exposure to flash floods of commuters during their daily activities.

Acknowledgements

We thank the numerous reviewers who provided valuable recommendations to improve the quality of the papers presented in this special issue and the chief editor, K. Georgakakos for his advice and help. We also appreciate the help of the editorial office of J. Hydrology, in particular Pallavi Das. The work presented in this paper is partly a contribution to the HyMeX program and to the FloodScale ANR project (contract ANR 2011 BS56 027).

Author-produced version of the article published in Journal of Hydrology (2016) vol. 541, n° Part A, p. 1-5

The original publication is available at http://www.sciencedirect.com, doi : 10.1016/j.jhydrol.2016.08.005 ©. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/


Massiot Félix

Thibault Granier

Patrick Rougier

Juliette Lambert

Eric Tison-Rosebery

Géraldine Rochard

Lassalle

Development and application of a generic method to assess species exploratory potential under climate change: focus on the exploration phase of anadromous fish

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

In response to climate change, some species have shifted their latitudinal and elevational distributions by exploiting new suitable habitats outside of their ranges (Thomas and Lennon, 1999;Parmesan and Yohe, 2003;Cheung et al., 2015) Various studies have demonstrated that species' traits can be important predictors of the type and intensity of responses to climate change (Jiguet et al., 2007;Diamond et al., 2011;Chessman et al., 2013) Based on these conclusions, how can be easily assessed the exploratory potential of species in order to provide insights for biological conservation? Félix Massiot-Granier, Thibaud Rougier, Patrick Lambert, Juliette Rosebery, Géraldine Lassalle UR EABX, Aquatic Ecosystems and Global Changes Unit, 50 avenue de Verdun, 33612 Cestas-Gazinet, Cedex, France E-mail: felix.massiot-granier@irstea.fr

Validation

Compare the species ranking obtained with the exploratory potential index to mono-specific model simulations (Lassalle et al., 2008;Rougier et al., 2014) Hypothesis: species showing good repositioning capabilities in simulation model should get a high value of exploratory potential index Compare the species ranking obtained with the exploratory potential index to empirical data, e.g. the range of their (historical) distribution area Hypothesis: species with a large range that testified of a good post-glacial re-colonization should get a high value of exploratory potential index

Perspectives

Characterize geographic areas in terms of the exploratory potential of their fish assemblages Identify geographic areas hosting species with high or low (extreme) values of exploratory potential and thus of priority for biological conservation and management A generic tool that could be applied to other taxonomic groups of interest (e.g. micro-organisms, amphibians, birds...) An index globally consistent with the literature that allows to identify and "rate" different dispersal strategies and support strong discrepancies in the ability of anadromous fish of northern Atlantic to explore potential suitable habitat , ,

A generic and collaborative approach Exploratory potential index


Use of distributed water level and soil moisture data in the evaluation of the PUMMA hydrological model Application to

CONTEXT AND OBJECTIVES

  distributed hydrological models in a hypothesis testing framework (Clark et al., 2011) • Evaluation of models using distributed data Objectives: • Assessment of the value of distributed networks of surface soil moisture and water level sensors to identify problems with models parameters and representations • Application to the PUMMA (Peri-Urban Model for landscape Management, Jankowfsky et al., 2014) distributed model in the Mercier catchment (6.6 km 2 , France) 3. THE PUMMA MODEL • Model mesh made of irregular polygons corresponding to land-use patterns • Modular structure with specific modules according to land-use • Main hydrological processes accounted for:  Evapotranspiration and infiltration in soil  Saturation excess surface runoff on forest/agriculture surfaces  Subsurface flow  Flow routing in the natural and artificial hydrographic network

Figure•

  Figure 3: PUMMA model and coupling between process modules (from Jankowfsky et al., 2014)

Figure 5 : 6 Figure 6 :

 566 Figure 5: Comparison of Simulated (Top and Bottom Left) and Observed (Bottom Right) stream intermittency patterns for year 2009 divided into 24 fortnight periodsfor water level sensors @1 to @16.

Figure 4 :

 4 Figure 4 : Normalized observed surface soil moisture and simulated soil water storage

The second author thanks Polytechnique Montréal for providing the funding allowing its 6-month stay at Irstea Lyon. Most of the data used in this study were collected during the AVuPUR (Assessing the Vulnerability of PeriUrban Rivers) project funded by the French National Research Agency (ANR) under contract ANR-07-VULN-01, the IRIP project funded by Région Rhône-Alpes and Agence de l'Eau, and in the framework of OTHU (Observatoire de Terrain en Hydrologie Urbaine). We thank Judicaël Dehotin for providing the soil moisture data.

HS2.1.


Slow initial growth rate

Fast initial growth rate O Features such as a complex life history (A), the controversy about genetic structure and an important interest for conservation make European eel (Anguilla anguilla) an interesting species to study! O European eel displays a large phenotypic and tactical variability at different spatial scales (B).

O Are phenotypic plasticity and genetic polymorphisms adaptive responses to variable environment?

O How these adaptive responses affect the impact of anthropogenic pressures on population dynamics?

1. European eel

Consequences of adaptive plasticity and spatially variable selection in the European eel

Genetic Polymorphisms Population dynamics

Environmental variability

Life history traits

Demographic attributes

Life history tactics

Spatial distribution (B)

Adaptive response

Phenotypic Plasticity

Impact of anthropogenic pressures

Intra-generational spatially variable selection [START_REF] Côté | Growth, Female Size, and Sex Ratio Variability in American Eel of Different Origins in Both Controlled Conditions and the Wild: Implications for Stocking Programs[END_REF][START_REF] Pavey | RAD Sequencing Highlights Polygenic Discrimination of Habitat Ecotypes in the Panmictic American Eel[END_REF] 3. Building the optimality model GenEvEel 1.0.

O Applying pattern-oriented modelling approach [START_REF] Grimm | Pattern-oriented modelling: A "multi-scope" for predictive systems ecology[END_REF] , spatial patterns of model output are compared with those observed in real river catchment:

O The algorithm proceeds in two steps:

 Higher density downstream than upstream2 .

 Male-biased sex ratio downstream and femalebiased sex ratio upstream [START_REF] Drouineau | EvEel (evolutionary ecology-based model for eel): a model to explore the role of phenotypic plasticity as an adaptive response of three temperate eels to spatially structured environments[END_REF] .

 Faster growth rates in downstream than those from upstream [START_REF] Côté | Growth, Female Size, and Sex Ratio Variability in American Eel of Different Origins in Both Controlled Conditions and the Wild: Implications for Stocking Programs[END_REF][START_REF] Pavey | RAD Sequencing Highlights Polygenic Discrimination of Habitat Ecotypes in the Panmictic American Eel[END_REF] .

 Higher length-at-silvering upstream than downstream 2 .

First results

Perspectives

O A second version of GenEvEel will be developed to assess the impacts of anthropogenic pressures (habitat fragmentation, pollution or fishing) in terms of spawning biomass and population's demographic attributes.

O Finally, the model will be calibrated and validated on a real study case, such as the Garonne-Dordogne catchment.

O Hopefully, this model could be used as decision-support system to help management of this resource.  There are more individuals in downstream than upstream section of river.

 Males are more concentrated in downstream section of river while females are concentrated in upstream section of river.

 Individuals in downstream tend to grow fast and mature early (lower length-at-silvering). Individuals in upstream grow slowly and mature older (higher length-at-silvering).

 Silver eels are smaller downstream than upstream.

C. Length-at-silvering and abundance by sex (red line, females; black line, males) and all initial growth rates E.

  each individual, potential fitness is calculated to determine its sex and select its growth habitat in the river catchment. Fitness-maximizing is the basis of these decisions. II. Realised life-history traits are then calculated as a combination of genetic differences in growth, fitness maximization and density-dependence an individual experiences.

O

  This study is supported by IRSTEA-EDF HYNES Life History Theory, 27 th September -2 nd October, 2015 University of Groningen  Research Unit EABX (IRSTEA): 50 avenue de Verdun, 33612 Cestas ;  EDF R&D: 6 quai Watier, 78401 Chatou. Corresponding author: M. Mateo (Maria.Mateo@irstea.fr) The model mimics the four spatial patterns (C):

PurposeGenetics & Evolutionary Ecology-based model for Eel: GenEvEel M. Mateo  , P. Lambert  , S. Tétard  and H. Drouineau 