Within the Explore2 national project, a new set of bias-corrected regional climate projections sub-sampled from the EURO-CORDEX (EUR11) ensemble has been produced to describe the impact of climate change on water resources and to support impact studies over mainland France. This dataset has been specially selected to reflect the expected changes in temperature and precipitation of the complete EURO-CORDEX (EUR11) ensemble while taking those of CMIP6 into account as consistency constraint. Yet, the selection allows to obtain a smaller ensemble size to handle with. The process of GCM/RCM couples selection is fully described in the article. The dataset makes it possible to characterize and partition the various sources of uncertainty about the evolution of the climate in France, by taking into account three greenhouse gas emission scenarios (RCP 2.6, RCP 4.5 and RCP 8.5), multiple regional climate models (allowing to dispose to 9 to 17 GCM/RCM couples depending on the emission scenario), two methods of statistical bias correction (ADAMONT and CDF-t) and continuous time series to explore internal variability.This dataset contains 10 climate variables at daily resolution, enabling the calculation of a very large number of climate impact indicators, as well as its use to drive a wide variety of hydrological models in France. Examples of climate change representations suitable for this dataset are provided for cumulative precipitation at seasonal scale. These representation methods are intended to guide potential users of this data when aiming to characterize the robustness of the changes (according to individual simulations, time horizons or climate change scenarios) and to identify contrasting scenarios across a territory. A narrative approach is also proposed to facilitate the exploration of individual projections of climate change, allowing for a more accurate consideration of inter-annual variability and extremes Four narratives were selected among the 17 GCM/RCM couples in collaboration with hydrologists which correspond to contrasting changes of temperature and precipitation in order to reflect a plurality of contrasting possible climate futures within the dispersion of the Explore2–2022 dataset.The richness of this dataset and the inclusion of the most recent regional climate simulations for France justified its use in constructing and illustrating the reference warming trajectory for climate change adaptation (TRACC) in France, backed by the 3rd National Climate Change Adaptation Plan.The Explore2 project worked to build a data-set meeting the FAIR Data Principles1 to maximize transparency, easiness and re-usability of data.

Multi-scenario, multi-model ensembles of hydrological projections are widely used to describe possible futures of regional hydrology and inform adaptation strategies. The Explore2 dataset is such an ensemble of river flow projections in Metropolitan France. It provides future simulations for 1735 catchments with modeling chains composed of different hydrological models forced by 36 regional climate projections based on bias-adjusted EUROCORDEX simulations. This study assesses the uncertainties of this ensemble with QUALYPSO, a method specifically designed to deal with incomplete ensembles and to disentangle and quantify all uncertainty sources, including that due to internal variability.Focusing on results obtained at the end of the century, this study shows a strong agreement between modeling chains towards decreases in low flows in a large southern part of France for a high-emission scenario, and very uncertain changes for the annual mean and high flows. Emission scenario uncertainty is the dominant source of uncertainty for low flows over the whole of France, and for mean annual flows in southeastern France. The contribution of the global and regional climate models is important for mean and high flows, especially in rainfall-dominated areas. Regional climate models contribute considerable uncertainty to low flows, much more than global models. The contribution of hydrological model uncertainty is large for low flows, moderate for mean annual flows, and small for high flows. For all climate and hydrological indicators, internal variability is often large and cannot be overlooked. It is often of the same order and sometimes larger than the uncertainty on the climate change response.

Calculating aquifer recharge provides a means of estimating the renewable fraction of groundwater resources, which is often difficult to quantify. This paper introduces the RECHARGE method, developed to calculate potential groundwater recharge from precipitation infiltration, and its application across mainland France over an extended historical period.The method relies on a simple soil water budget approach to estimate effective precipitation, using meteorological data and a spatial parameter that accounts for land cover and allows the seasonal variability of evapotranspiration to be reflected. An effective precipitation infiltration ratio (EPIR) is then derived for catchments with homogeneous geological lithology, based on linear regressions involving the baseflow index and a GIS-derived parameter. Given the low interannual variability of the baseflow index, the EPIR is assumed to remain constant over time and is subsequently used to convert effective precipitation into potential recharge at the scale of all groundwater bodies in mainland France.To validate this approach, annual effective precipitation estimates were compared for 556 selected catchments, both with observed annual river flows and with outputs from the physically based SURFEX model. The calculated potential recharge was also evaluated at both annual and seasonal scales for the entire French territory, using SURFEX as a reference. Results demonstrate that the RECHARGE model can effectively estimate annual and seasonal potential aquifer recharge. It is suitable for large-scale applications without requiring detailed knowledge of aquifer properties. Future improvements are envisioned, particularly to enhance monthly-scale accuracy in mountainous regions.

Study Region The 42km2 Claduègne catchment in southern France, under Mediterranean climate is subject to long, dry summers with limited water resources and intense, convective storm events leading to flash floods and overland flow (OF). Study Focus The impact of simulated mid- and end-century climate on hydrology, specifically seasonality, hydrological extremes (high and low flows), and flow processes (OF versus groundwater GW) was investigated, using hourly climate projections and a spatially distributed process-based hydrological model (J2000P). Potential differences between native hourly projections with a convection-permitting regional climate model (CP-RCM) and temporally downscaled projections were evaluated. New Hydrological Insights for the Region All projections agreed on a longer and drier summer. Simulated low flows decreased significantly throughout the century, while flood discharge may increase by the end of the century. A higher overland flow and lower GW contribution were projected in the future due to a changed temporal distribution of precipitation. The CP-RCM improved simulated sub-daily extreme precipitation and seasonal distribution of flow generating processes compared to temporally downscaled projections. There were no notable advantages for the simulation of streamflow extremes or other hydrological variables.

A large transient multi-scenario and multi-model ensemble of future streamflow and groundwater projections in France developed in a national project named Explore2 was recently made available. The main objective of Explore2 is to provide rich and spatially-consistent information for the future evolution of hydrological (surface and groundwater) resources and extremes in France to support adaptation strategies. The Explore2 dataset was obtained using a nested multi-scenario multi-model approach to estimate future uncertainty and to assess local climate at the catchment scale: three greenhouse gas (GHG) emission scenarios, a set of 17 combinations of Global Climate Models and Regional Climate Models (GCM/RCM), and two bias correction methods provide the meteorological forcing for nine surface hydrology models and four groundwater hydrology models (one to simulate groundwater recharge and three to simulate groundwater level). In this paper, we present the methodology underlying the dataset, the evaluation of the hydrological models against daily observations of streamflow and groundwater level, and the key messages on the impact of climate change on both mean river flows and groundwater recharge. This large set of hydrological projections shows a high model agreement on the decrease in seasonal flows in the South of France under the RCP8.5 high-emission scenario, confirming its hotspot status. The surface hydrological models agree on the decrease in summer flows across France under the RCP8.5 scenario, with the exception of northern part France. This area may indeed benefit from more active winter recharge that may counterbalance decrease in summer precipitation and increase in evapotranspiration. In addition to northern France, annual groundwater recharge is projected to increase slightly in the north-east while remaining unchanged elsewhere by the end of the century, according to the RCP8.5 scenario. In the mountainous areas, winter flows will increase as a result of higher air temperature and the high degree of agreement between the models holds regardless of the RCP considered. Unsurprisingly, the higher the GHG emission scenario, the higher the median changes. Most of these changes are organised in France along a north-south gradient, regardless of the RCP considered.

The concept of hydroclimate services is predominantly recognised as web portals dedicated to the dissemination of data to potential users. However, the scope of climate services extends beyond the sole provision of data. This communication presents a comprehensive ecosystem of tools and resources associated with the development of an updated national hydrological projection dataset in France. The ecosystem was brought to life through a close collaboration between scientists and water managers in two joint projects: Explore2 and LIFE Eau&Climat. Tools and resources were thus developped with and for water resource managers, and designed to enhance the comprehension of both the conceptual framework and the data itself, facilitating utilisation in accordance with best practices for climate change adaptation.The project websites serve as gateways to the ecosystem and the tools: the Explore2 website contains interviews with the scientific contributors, and the LIFE Eau&Climat website is hosted by the national website dedicated to water managers. A summary of the joint final public event accompanies the replay of the one-day conference and debates on a dedicated website. A compendium of antecedent research projects on climate change impacts on hydrology has been collated to summarise the state of the art prior to the two projects. A MOOC has been developed in conjunction with scientists to facilitate the comprehension of the Explore2 project, its design, and its application in adaptation studies.Moreover, the Explore2 dataverse (https://entrepot.recherche.data.gouv.fr/dataverse/explore2) brings together a variety of products in an organised and searchable way, including thematic scientific reports, GIS layers, and other key metadata. It also contains three types of station datasheets aimed at locally contextualising outputs: hydrological model performance datasheets, projection results datasheets, and uncertainty quantification datasheets. The MEANDRE interactive data visualisation tool (https://meandre.explore2.inrae.fr/) offers a guided tour of the salient take-home messages and a comprehensive exploration of the Explore2 hydrological projection dataset. This multi-model dataset (GCMs/RCMs/bias correction methods/hydrological models) is made available through the DRIAS-Eau portal (https://drias-eau.fr/), which functions as a water mirror of the established DRIAS-Climat portal. The utilisation of this dataset for local climate change impact studies is facilitated by a methodological guide written as an adventure gamebook (https://livreec.inrae.fr/) and based on real-life studies carried out by water managers during the LIFE Eau&Climat project. Furthermore, experiments of sonification of hydrological projections offer a novel approach to apprehending future changes (https://explore2enmusique.github.io/).This ecosystem has been met with great anticipation and acclaim by local to national-scale water managers, paving the way for ongoing local prospective studies. These will be able to confront future resources with the ecological needs of aquatic environments and human water usage.This work is funded by the EU LIFE Eau&Climat project (LIFE19 GIC/FR/001259).

Cet article propose une analyse prospective sur l’avenir de la diversification maraîchère et légumière en région parisienne, en France, sous l’angle de la ressource en eau. Cette diversification est indispensable en raison de sa contribution variée et quasi-permanente le long de l’année aux systèmes alimentaires territorialisés, notamment à la restauration collective. Cependant, la demande relativement importante en eau de ces cultures d’une part, et la disponibilité de cette ressource pour l’irrigation d’autre part, soulèvent des questions sur la viabilité de cette diversification. En suivant une approche territorialisée à l’échelle du sud-ouest francilien, nous avons réalisé des enquêtes auprès d’exploitations diversifiées, ainsi qu’un travail prospectif sur les évolutions à l’horizon 2060 des besoins en eau des cultures, à partir de données climatiques et de calculs de bilans hydriques, et de la disponibilité de l’eau souterraine pour l’irrigation à partir de données hydro-climatiques issues du projet Explore2. Nos principaux résultats indiquent que l’eau est un levier d’une agriculture diversifiée au sein des projets alimentaires territoriaux et qu’il y a un fort enjeu de raréfaction de cette ressource au vu des hausses notables de la demande en eau d’environ 40 % à l’échelle d’une exploitation diversifiée, conjointement à une tendance à la baisse potentiellement prévue quant à l’eau souterraine (disponible pour l’irrigation) à l’horizon 2060. Nos résultats sont ensuite discutés, notamment à la lumière de la solution, identifiée comme prioritaire par les agriculteurs, du stockage de l’eau afin de pérenniser cette diversification, et plus largement, le projet de re-territorialisation de l’alimentation.

A large transient multi-scenario and multi-model ensemble of future streamflows and groundwater projections in France developed in a national project named Explore2 was recently published (Sauquet et al., 2024). The main objective of the Explore2 dataset is to provide a rich and spatially consistent information for the future evolution of hydrological resources in France using a large ensemble of EURO-CORDEX regional climate projections (Coppola et al., 2021) and a large variety of hydrological models.The aim of the present study is to use a classification of river flow regimes on the hydrological projections from the Explore2 dataset to assess how hydrological processes will change in response to climate change at the catchment scale.A simple, but well-adapted classification based on a hierarchical cluster analysis is adopted here. The classification is based on the twelve monthly Pardé coefficients derived from 611 time series of near natural observed streamflow, leading to seven characteristic river flow regimes in France over the period 1976-2005.The Pardé coefficients were computed on 30-year periods for four time slices, namely the baseline (1976-2005), near future (2020-2049), mid-century (2041-2070), and end of the century (2070-2099) periods for each hydrological projection and for 2500 simulation points located across France. A representative regime is assigned to each simulation point corresponding to the most frequent regime identified among all hydrological projections.River flow regime derived from the historical runs is used to assess the performance of the hydrological models at each gauged basins. The shifts in river flow regimes (between the future and baseline periods) reflect and summarize the evolution in rainfall-runoff processes due to climate change.Overall, the predominantly rain-fed hydrological regimes will change for more contrasted regime during the 21st century. The basins with transition regimes (combining snow and rain contributions) will likely shift towards pluvial regimes. Basins at higher altitudes will keep their nival character but will have less contrasted regimes, with potentially less severe low flow in winter, and a decrease in summer flow for rivers influenced by glaciers.References:Coppola et al.: Assessment of the European Climate Projections as Simulated by the Large EURO-CORDEX Regional and Global Climate Model Ensemble, J. Geophys. Res.: Atmos., 126, e2019JD032356. https://doi.org/10.1029/2019JD032356, 2021.Sauquet et al.: A large transient multi-scenario multi-model ensemble of future streamflows and groundwater projections in France, ESSD, submitted.Strohmenger et al.: On the visual detection of non-natural records in streamflow time series: challenges and impacts, Hydrol. Earth Syst. Sci., 27, 3375–3391, https://doi.org/10.5194/hess-27-3375-2023, 2023.

This study aims to assess the changes in the intermittence of river flows across France in the context of climate change. Projections of flow intermittence are derived from the results of the Explore2 project, which is the latest national study that proposes a wide range of potential hydrological futures for the 21st century. The multi-model approach developed within the Explore2 project enables uncertainties in future flow intermittence to be characterized. Combined with discrete observations of flow states, hydrological projections are post-processed to compute the daily probability of flow intermittence (PFI) on each element of the partition of France in hydro-ecoregions (HERs). The post-processing consists of calibrating logistic regressions between the historical flow states of the National Low-Flow Observatory (ONDE) network and the flow data simulated by the hydrological models involved in Explore2 run with the SAFRAN atmospheric reanalysis as inputs. After calibration, these regressions are used to project daily PFIs for the entire 21st century, based on flow simulations from five hydrological models driven by up to 17 climate projections under RCP2.6, RCP4.5, and RCP8.5 climate change scenarios. The results show good agreement among the hydrological models regarding the increase in flow intermittence under RCP4.5 and RCP8.5. The projected increase in mean daily PFI between July and October and the shift of the first and last days when PFI exceeds 20 % both suggest a gradual intensification and extension of dry spells throughout the century. The southern regions of France are likely to experience greater increases in runoff intermittence than the northern regions, and mountainous regions such as the Alps and the Pyrenees are likely to experience changes in their dynamics of intermittence with a reduction in winter intermittence and the apparition of or increase in summer intermittence. The uncertainty of these projected changes is larger in northern France due to greater intermodel variability in this region.

The quantification of present and future groundwater resources at regional scale is necessary for the implementation of national climate change adaptation plans. We present a method to compute the potential groundwater recharge (PGR) by precipitation applied specifically to the scale of France. A simple water balance approach taking into account the maximum soil water content capacity and the land use is first applied to derive the effective rainfall estimation from the SAFRAN national meteorological reanalysis. The BaseFlow Index (BFI) computed over 611 French river basins with minor human influence on discharge is then used to assess the effective rainfall infiltration ratio for watershed with homogeneous geological lithologies. This infiltration ratio is finally applied to convert effective rainfall into potential recharge at the scale of each groundwater body in France. A sensitivity analysis of BFI (to the automated BF separation method, the length of discharge time series, etc.) was performed. The low annual variability and uncertainty on BFI estimates allow us to consider, as an initial approximation, that the infiltration ratio remains constant over time. To validate this global approach, in the framework of the Explore2 project, we compared computed effective rainfall and potential recharge with alternative potential recharge estimates simulated by a set of hydrological models under current condition (1976-2005). Previous computed variables have been compared with SURFEX physical surface model solving energy balance over the entire re-analysis (1958-2020). Additionally, we used Euro-Cordex climatic projections as input of our model to evaluate the future potential groundwater recharge (2021-2100). Future evolution of potential recharge shows contrasting situations between the North and the South of France which were not highlighted by previous assessments.

The impact of climate change on floods varies across regions, and observed trends in flood characteristics are often explained by differential changes in the processes that cause flooding. This study explores changes in flood magnitude and flood-generating processes under different climate change scenarios for a large number of basins in France. It is based on an unprecedented exercise to model the impacts of climate change on hydrology, using a semi-distributed model (GRSD) applied to 3727 basins with 22 Euro-CORDEX bias-corrected climate projections using two greenhouse gas emission scenarios (RCP4.5 and RCP8.5). Annual maxima of daily simulated streamflow were extracted for the period 1975–2100, resulting in a set of over 10 million flood events, and a trend analysis was carried out on both flood magnitudes and flood generating processes. Increasing trends in flood magnitudes are only found in the northern regions of France, although multi-model convergence rarely exceeds 60 %. The highest increases are observed for the 20 year floods and under the RCP8.5 scenario. A classification of floods according to their generating process revealed that floods linked to soil saturation represent more than half of all floods in France. The relative change in the importance of the different flood-generating processes is not spatially homogeneous and varies by region. The proportion of floods linked to soil saturation excess is increasing in the temperate and continental climate zones in the Northeast, while decreasing in the southern Mediterranean regions. In these Mediterranean regions, the proportion of floods linked to infiltration excess related to extreme rainfall is increasing. Both the frequency and magnitude of floods linked to snowmelt processes are decreasing in mountainous areas. On the contrary, the most extreme floods associated with rainfall on dry soils tend to increase, in line with the increase of rainfall intensity. Overall, trends in antecedent soil moisture conditions are as important as trends in intense rainfall to explain flood hazard trends in the different climate projections. This study shows how important it is to decipher the changes in the different flood generating processes in order to better understand their evolution in different hydroclimatic regions.

This paper presents a forward-looking analysis of the future of market garden and vegetable diversification, from a water resources perspective. This diversification is important because of its varied and quasi-permanent contribution throughout the year to localized food systems, and in particular to mass catering. However, the relatively high demand on the one hand, and the availability of this resource for irrigation on the other hand, raise questions about the future of this diversification. Following a territorial approach at the scale of the south-west Ile-de-France region, in France, we carried out surveys of diversified farms, and carried out prospective work on changes in crop water requirements up to 2060, based on climatic data (water balances), and groundwater availability (for irrigation), based on hydro-climatic data from the Explore2 project. Our main results indicate that water is a lever for diversification, and that there is a strong risk of water scarcity in view of the significant increases in water demand, of around 40% at the scale of a diversified farm, and the downward trends potentially predicted for groundwater (for irrigation) by 2060. Our results are then discussed, particularly in the light of the priority solution of water storage to sustain this diversification, and more broadly, the project to re-territorialize food.

Analysing the significance of trends in hydrological variables across different components of the streamflow regime, from low flows to high flows, provides an overview of the state of a region in the context of ongoing global changes. This information is crucial for decision-making regarding adaptation but also for evaluating hydrological projections. MAKAHO (MAnn-Kendall Analysis of Hydrological Observations) is an interactive cartographic visualization system designed to examine trends in hydrometric observations from the 232 stations belonging to the French Reference Hydrometric Network (Giuntoli et al., 2013). These stations show a high measurement quality, time series with a historical depth of over 30 years, and they crucially gauge near-natural catchments. The statistical test used for trend detection is a variant of the Mann-Kendall test accounting for first-order autocorrelation. The trend slope is provided by the Theil-Sen estimator. The hydrological situation in France shows a marked contrast between the northern and southern regions. Between 1968 and 2020, 22 % of stations show a significantly trend in the annual maximum daily streamflow at the 90 % confidence level. Of these stations, 27 % exhibit an upward trend, with an average increase of 13 % per decade. Almost all of these stations are located in the northern part of the country. This north-south divide is also visible for low flows, with the demarcation line extending further north. 39 % of stations show a decreasing trend in the annual minimum monthly discharge, with an average intensity of about 11 % per decade. The signal in the northern part of the country is less significant. The duration of low flows has significantly increased in the south, particularly in the southwest, with an average of more than ten days per decade, reaching almost a month in extreme cases. The tool, developed using the R Shiny library, takes the form of an online graphical interface (https://makaho.sk8.inrae.fr/). It enables direct communication with the R Exstat package (https://github.com/super-lou/EXstat), which is essential for data aggregation and trend analysis. Calculations are performed on the fly, allowing greater customisation of analyses. MAKAHO users can choose the analysis period, the hydrological variable (from low flows to high flows), display time series for the variable of interest and extract summary sheets for a set of hydrometric stations. The interactive map and graphs allow switching from an overview to a detailed view of the results for each station. MAKAHO has been designed based on previous research projects involving stakeholders to encourage water managers to develop robust strategies for adapting to climate change and has received financial support from the French Ministry of Ecology. Giuntoli, I., Renard, B., Vidal, J.-P., and Bard, A. (2013). Low flows in france and their relationship to large-scale climate indices. Journal of Hydrology, 482:105–118. https:/doi.org/10.1016/j.jhydrol.2012.12.038

La présence ou non de changements dans les débits descriptifs de la ressource en eau a été appréciée par application d’un test statistique sur un ensemble de séries de débits peu influencés par les actions humaines directes (prélèvements, rejets, stockages…). Les résultats de ce test font apparaître des réductions des débits quasi généralisées. Cependant, l’intensité des changements varie selon le cours d’eau. Ces changements s’inscrivent dans une tendance globale de diminution de la ressource superficielle constatée sur le sud de la France. Ils ne sont que les prémices de ceux qui vont toucher le Sud-Ouest dans les décennies à venir.

Funded by the French Ministry of Ecology, the French Biodiversity Agency (OFB) and project partners, Explore2 aims to update knowledge about the impact of climate change on hydrology in France, and to support stakeholders in adapting their water management strategies. A multi-scenario and multi-model approach is uniformly applied across the country to encompass a wide range of possible futures for the entire 21st century and to assess uncertainties at each step of the climate and hydrology modelling.This study aims to extend the results of Explore2 towards the prediction of flow intermittence in headwaters streams, which is initially impeded by the coarse resolution of Explore2 simulations. A statistical approach is necessary to link Explore2 hydrological projections on main rivers to the daily probability of flow intermittence in headstreams (PFI). PFI observations on historical period are derived from data of the French Observatoire National des Etiages (ONDE), which carries monthly visual assessments since 2012, from May to September, at more than 3300 upstream river sites prone to drying [1]. PFI is then considered as the proportion of ONDE sites observed under drying conditions on partitions of France (76 second-level hydroecoregions (HER2) with median size of 4690 km² paving France).To predict PFI, logistic regressions are adapted from previous studies [2, 3] and are first calibrated in each HER2 using time series of daily discharge provided by the French hydrometric monitoring network, HYDRO [4]. A diagnosis analysis between 2012 and 2022 consistently demonstrates good performance, with a median Kling-Gupta Efficiency (KGE) around 0.83 across all HER2. Logistic regressions are then re-calibrated considering daily discharge time series simulated by five hydrological models (HMs) of Explore2 driven by SAFRAN meteorological reanalysis [5]. Performance varies according to the HM (KGE medians ranging from 0.60 to 0.82).Finally, the logistic regressions are applied to simulate daily PFI values at each HER2 for the entire 21st century with future discharge simulated by the five HMs driven by 17 climate projections under RCP8.5 scenario. Results suggest an increased probability of intermittence in most of the hydrological ensemble runs and under most scenarios. This presentation will focus on the spatial variability of PFI response to climate change projected at different time leads. References[1] Nowak and Durozoi. Guide de dimensionnement et de mise en œuvre du suivi national des étiages estivaux. ONEMA, 2012.[2] Beaufort et al. Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks. Hydrology and Earth System Sciences, 2018. doi:10.5194/hess-22-3033-2018.[3] Sauquet et al. Predicting flow intermittence in france under climate change. Hydrological Sciences Journal, 2021. doi:10.1080/02626667.2021.1963444Y.[4] Leleu et al. La refonte du système d’information national pour la gestion et la mise à disposition des données hydrométriques. Houille Blanche, 2014. doi:10.1051/lhb/2014004.[5] Durand et al. A meteorological estimation of relevant parameters for snow models. Annals of Glaciology, 1993. doi:10.3189/s0260305500011277.

Here we present a strategy to obtain a reliable hydrological simulation over France with the ORCHIDEE land surface model. The model is forced by the SAFRAN atmospheric reanalysis at 8 km resolution and hourly time steps from 1959 to 2020 and by a high-resolution DEM (around 1.3 km in France). Each SAFRAN grid cell is decomposed into a graph of hydrological transfer units (HTUs) based on the higher-resolution DEM to better describe lateral water movements. In particular, it is possible to accurately locate 3507 stations among the 4081 stations collected from the national hydrometric network HydroPortail (filtered to drain an upstream area larger than 64 km2). A simple trial-and-error calibration is conducted by modifying selected parameters of ORCHIDEE to reduce the biases of the simulated water budget compared to the evapotranspiration products (the GLEAM and FLUXCOM datasets) and the HydroPortail observations of river discharge. The simulation that is eventually preferred is extensively assessed with classic goodness-of-fit indicators complemented by trend analysis at 1785 stations (filtered to have records for at least 8 entire years) across France. For example, the median bias of evapotranspiration is -0.5 % against GLEAM (-4.3 % against FLUXCOM), the median bias of river discharge is 6.3 %, and the median Kling-Gupta efficiency (KGE) of square-rooted river discharge is 0.59. These indicators, however, exhibit a large spatial variability, with poor performance in the Alps and the Seine sedimentary basin. The spatial contrasts and temporal trends of river discharge across France are well represented with an accuracy of 76.4 % for the trend sign and an accuracy of 62.7 % for the trend significance. Although it does not yet integrate human impacts on river basins, the selected parameterization of ORCHIDEE offers a reliable historical overview of water resources and a robust configuration for climate change impact analysis at the nationwide scale of France.

Abstract. This study aims to assess the changes in the intermittency of river flows across France in the context of climate change. Projection of flow intermittence are derived from the results of the Explore2 project, which is the latest national study that proposes a wide range of potential hydrological futures for the 21st century. The multi-model approach developed within the Explore2 project enable to characterize uncertainties in future flow intermittence. Combined with discrete observations of flow states, hydrological projections are post-processed to compute the daily probability of flow intermittency (PFI) on each element of the partition of France in hydroecoregions (HER2). The post-processing consists of calibrating logistic regressions between the historical flow states of the Observatoire National des Étiages (ONDE) network and the flow data simulated by the hydrological models (HMs) involved in Explore2 projected with the Safran reanalysis as inputs. After calibration, these regressions are used to project daily PFIs for the whole of the 21st century, based on flow simulations from five HMs driven by up to 17 climate projections under RCP 2.6, 4.5, and 8.5 climate change scenarios. The results show good agreement among the HMs regarding the increase in flow intermittency under RCP 4.5 and 8.5. The changes in mean daily PFI between July and October, and the shifts in the first and last days when PFI exceeds 20 %, suggest a gradual intensification and extension of dry spells throughout the century. The southern regions of France are likely to experience greater increases in runoff intermittency than the northern regions. Uncertainty is greater in northern France, due to the variability of rainfall. Mountainous regions such as the Alps and the Pyrenees are likely to experience changes in the dynamics of snowmelt and groundwater recharge, which could lead to changes in their runoff regimes.

Multi-criteria model calibration can lead to a better representation of hydrological processes and reduce parameter uncertainty compared to calibration on streamflow data alone. However, the additional data may be difficult to collect or aggregate into a representative catchment average value that can be used to calibrate a lumped model. Temporary streams are highly dynamic, and their flow state can be observed visually. However, data on the state of temporary streams are still uncommon and rarely used in hydrological catchment modelling. In this study, we used a unique dataset with discrete flow state observations for temporary streams in France and evaluated how informative these data are for calibrating a lumped, bucket-type hydrological model. We calibrated the HBV model for 92 catchments using discharge or stream-level data at different temporal resolutions (daily, one daily value per month, or one daily value per season) and used the observed flow states of temporary streams as a proxy of groundwater storage. Temporary stream data generally did not result in a better overall discharge simulation for the validation period. For catchments for which the model performance based on the calibration on only discharge or stream-level data was poor, it was more likely to lead to an improvement in model performance. The use of temporary stream data in combination with discharge data reduced the uncertainties in the low-flow simulations for up to half of the catchments. This improvement was caused by a betterconstrained storage coefficient for the slowest groundwater reservoir and the elimination of parameter sets that led to substantial variations in groundwater storage. However, the improvements in low-flow simulations or parameter uncertainty due to the inclusion of temporary stream data in model calibration were not related to catchment characteristics. Thus, it remains unclear for which catchments temporary stream data can help to improve low-flow simulations and reduce parameter uncertainty.