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En 2022, l’Europe de l’Ouest a connu un déficit de précipitations ainsi que des vagues de chaleur. La combinaison de ces conditions météorologiques a eu un impact profond sur la cryosphère des montagnes françaises, dont le manteau neigeux saisonnier. Les données issues de mesures de terrain et de la télédétection indiquent que le manteau neigeux a disparu de façon précoce dans tous les massifs. Toutefois, l’analyse révèle des différences régionales. Un fort déficit d’accumulation et une fonte particulièrement précoce dans les Alpes du Sud ont causé des étiages estivaux record. Des étiages estivaux très bas ont été aussi atteints malgré un hiver très arrosé dans des bassins sous influence nivale des Pyrénées et dans les Alpes du Nord. more...

An hourly hydrological forecasting model (GRP), used for flood forecasting in France, has been enhanced by developing a semi-distributed version (GRPS). This new model addresses some limitations of the original lumped approach by integrating flow observations from upstream stations to improve downstream flood predictions. A comparison of GRP and GRPS was conducted on a large set of flood events in nested catchments in France. Results indicate that GRPS slightly outperforms GRP up to the lead time of the last upstream flow observations reaching the downstream station, though performance gains vary widely across events. Event classification identified detrimental interactions between data assimilation methods and river routing model errors. A sensitivity test suggested that enhancing both the propagation model and the assimilation scheme could reduce poor performance at short lead times for some events. The study also demonstrated that upstream forecast quality significantly impacts downstream forecast accuracy. Overall, the findings confirm the benefits of incorporating multiple flow observations into a semi-distributed model and suggest several avenues for further improvement. more...

Study region: French part of the Moselle catchmentStudy focus: By relying on hydrological simulations forced by climate change scenarios, stakeholders can assess the magnitude of future changes in the rainfall–runoff relationship. The inclusion of human influences in water resources modelling in a non-stationary context is a way to improve the accuracy and usefulness of climate change impact studies. Here, we propose a modelling approach that explicitly considers water uses to evaluate adaptation measures for water management at the French Moselle catchment scale.New hydrological insights for the region: The results highlight the decrease in future low flows but also the change in the balance between demand and supply. Over the Moselle catchment, whatever the water use scenario considered, climate change induces lower water availability both for environmental flows and for human uses. This leads to a potential increase in the duration of water restriction of up to 8 weeks for RCP 8.5 in the long term (2070–2099) compared to 1976–2005. This study could provide water managers with more appropriate climate impact results and potentially help them to design adequate adaptation measures. more...

Study region: This study is developed in three catchments located in Denmark, France and Spain, covering different climate and physical conditions in Europe. Study focus: The simulation skill of hydrological models under contrasting climate conditions is evaluated using a Differential Split Sample Test (DSST). In each catchment, three different hydrological models are given a weight based on their simulation skill according to their robustness considering the DSST results for traditional and purpose-specific metrics. Four weighting approaches are used, each including a different set of evaluation metrics. The weights are applied to obtain reliable future projections of annual mean river discharge and purpose-specific metrics. New hydrological insights: Projections are found to be sensitive to model weightings in cases where the models show significantly different skills in the DSST. However, when the skills of the models are similar, there is no significant change when applying different weighting schemes. Nevertheless, the methodology proposed here increases the reliability of the purpose-for-fit hydrological projections in a climate change context. more...

The aim of this study is to evaluate from a hydrological perspective and in the context of climate change the future of subsurface drainage of the La Jaillière site (western France), which is representative of the pedology of the majority of French subsurface drainage. We used a uniquely large and comprehensive range of 17 hydrological indicators (HIs), describing the temporal dynamics of drainage season, soil saturation, drained water balance and flood events. The HI values are calculated from simulated discharges provided by a subsurface drainage model, the SIDRA-RU model, fed by 12 climate projections from 1975 to 2100 (CMIP5 Euro-Cordex project), with three climate change scenarios: Representative Concentration Pathways (RCP) 2.6, RCP4.5 and RCP8.5. We first verified that the HIs simulated using climate projections in the SIDRA-RU model over the historical period were not critically biased compared to the HIs obtained from the reference climatic reanalysis (SAFRAN). Second, we analysed and compared the HI evolution over different periods and under different scenarios. Our results showed that the number of significant changes in HI values increased under climate change by 2100, depending on the RCP: 2 HIs out of the 17 changed under RCP2.6; 6 HIs under RCP4.5; 10 HIs under RCP8.5. The intensity of drainage peak flows linked to flood events and the annual maximal discharge changed significantly under all RCPs. The temporality of the drainage season was substantially affected according to how pessimistic the RCP was. The worst changes were observed under RCP8.5, which exacerbated extreme events: The wet period was shorter while the dry period was longer by about 67%; the drought index increased by 100%; the summer drained water balance decreased by 9%. On the contrary, in winter, the duration of the wet period decreased while maintaining the same drained water balance, thus inducing stronger flood events leading to an earlier saturation of the drainage networks. The sustainability of the drainage system design at La Jaillière is therefore threatened, with the risk of fulfilling its function less effectively by 2100, exposing current crops to more important runoff and affecting water quality by increasing the leaching of agrochemical inputs. more...

Study Region: The upper Jordan River is the major water resource in Israel, a country which suffers from increasing shortage of natural water resources. Study Focus: In this study, we apply for the first time to this area an approach based on an ensemble of regional climate models, verify their trends vs. observations for a control period and use them for simulating future discharges of the Jordan River. New Hydrological Insights for the Region: The results of this study show that the observed negative trend of precipitation for the control period is also simulated by the climate models ensemble and projects a continued decreasing trend to the near future and further into the far future. Using the GR6J daily hydrological model for evaluating the effects of the predicted climate changes on the hydrological cycle in the region shows an increase in potential evaporation and a decrease in streamflow volumes in the Jordan River, Northern Israel. The results reveal and quantify the changes in rainfall–runoff relationships. These changes in the hydrological cycle in the region can be explained by changes in precipitation distribution and duration and decrease in soil moisture caused by the increase in evaporation. Results presented in this study could imply major consequences for the region. The findings here are relevant not only to Israel but also to the surrounding countries. Keywords: Rainfall - runoff relationships, Ensemble of regional climate models, Changes in the hydrological cycle more...

Snow is an important component of the water cycle, and its estimation in hydrological models is of great significance concerning the simulation and forecasting of flood events due to snow-melt. The assimilation of Snow Cover Area (SCA) in physical distributed hydrological models is a possible source of improvement of snowmelt-related floods. In this study, the assimilation in the LISFLOOD model of the MODIS sensor SCA has been evaluated, in order to improve the streamflow simulations of the model. This work is realized with the final scope of improving the European Flood Awareness System (EFAS) pan-European flood forecasts in the future. For this purpose daily 500 m resolution MODIS satellite SCA data have been used. Tests were performed in the Morava basin, a tributary of the Danube, for three years. The particle filter method has been chosen for assimilating the MODIS SCA data with different frequencies. Synthetic experiments were first performed to validate the assimilation schemes, before assimilating MODIS SCA data. Results of the synthetic experiments could improve modelled SCA and discharges in all cases. The assimilation of MODIS SCA data with the particle filter shows a net improvement of SCA. The Nash of resulting discharge is consequently increased in many cases. more...