To cite this version:Claire Magand, Agnès Ducharne, Nicolas Le Moine, Simon Gascoin. Introducing hysteresis in snow depletion curves to improve the water budget of a land surface model in an Alpine catchment. Journal of Hydrometeorology, American Meteorological Society, 2014, 15 (2) ), located in the French Alps, generates 10% of French hydropower and provides drinking water to 3 million people. The Catchment land surface model (CLSM), a distributed land surface model (LSM) with a multilayer, physically based snow model, has been applied in the upstream part of this watershed, where snowfall accounts for 50% of the precipitation. The CLSM subdivides the upper Durance watershed, where elevations range from 800 to 4000 m within 3580 km 2 , into elementary catchments with an average area of 500 km 2 . The authors first show the difference between the dynamics of the accumulation and ablation of the snow cover using Moderate Resolution Imaging Spectroradiometer (MODIS) images and snow-depth measurements. The extent of snow cover increases faster during accumulation than during ablation because melting occurs at preferential locations. This difference corresponds to the presence of a hysteresis in the snow-cover depletion curve of these catchments, and the CLSM was adapted by implementing such a hysteresis in the snow-cover depletion curve of the model. Different simulations were performed to assess the influence of the parameterizations on the water budget and the evolution of the extent of the snow cover. Using six gauging stations, the authors demonstrate that introducing a hysteresis in the snow-cover depletion curve improves melting dynamics. They conclude that their adaptation of the CLSM contributes to a better representation of snowpack dynamics in an LSM that enables mountainous catchments to be modeled for impact studies such as those of climate change.

International audienceThis paper proposes a methodology for estimating the transient probability distribution of yearly hydrological variables conditional to an ensemble of projections built from multiple general circulation models (GCMs), multiple statistical downscaling methods (SDMs), and multiple hydrological models (HMs). The methodology is based on the quasi-ergodic analysis of variance (QE-ANOVA) framework that allows quantifying the contributions of the different sources of total uncertainty, by critically taking account of large-scale internal variability stemming from the transient evolution of multiple GCM runs, and of small-scale internal variability derived from multiple realizations of stochas-tic SDMs. This framework thus allows deriving a hierarchy of climate and hydrological uncertainties, which depends on the time horizon considered. It was initially developed for long-term climate averages and is here extended jointly to (1) yearly anomalies and (2) low-flow variables. It is applied to better understand possible transient futures of both winter and summer low flows for two snow-influenced catchments in the southern French Alps. The analysis takes advantage of a very large data set of transient hydrological projections that combines in a comprehensive way 11 runs from four different GCMs, three SDMs with 10 stochastic realizations each, as well as six diverse HMs. The change signal is a decrease in yearly low flows of around −20 % in 2065, except for the more elevated catchment in winter where low flows barely decrease. This signal is largely masked by both large-and small-scale internal variability, even in 2065. The time of emergence of the change signal is however detected for low-flow averages over 30-year time slices starting as early as 2020. The most striking result is that a large part of the total uncertainty – and a higher one than that due to the GCMs – stems from the difference in HM responses. An analysis of the origin of this substantial divergence in HM responses for both catchments and in both seasons suggests that both evap-otranspiration and snowpack components of HMs should be carefully checked for their robustness in a changed climate in order to provide reliable outputs for informing water resource adaptation strategies

International audienceThe optimal forest management strategies for mitigating climate change are hotly debated during political negotiations , because afforestation and forest management can increase atmospheric CO 2 removal, and the wood produced can provide a substitute for fossil fuel. Studies quantifying the carbon balance of the forest sector apply a wide variety of management and wood-use scenarios. Some model studies include future climate change effects on forest growth, but others ignore them. Here, a conceptual empirical model of sequestration efficiency, the fraction of net primary production stored in the biosphere and anthroposhere, simulates European forest carbon pools and fluxes. The sensitivity of the sequestration efficiency of European forests was quantified by varying model parameters along the forest growth and wood transformation chain: environment and climate change, harvest intensity, rotation length, fraction of harvest residues left on site and substitution efficiency. Irrespective of the evolution of the sink, the forest sector as a whole remains a net carbon absorber in 99% of the simulations at a time horizon of 100 years, even if in 25% of the simulations the forests themselves become sources. However, if the goal is to enhance the current sequestration efficiency to mitigate emissions, only in 25% of the simulations the sink efficiency was found to be enhanced. If the current sink were to reverse to a source, no management action or change in wood use would result in an increase in the current forest sequestration efficiency. In all other cases, increasing harvest levels would lead to an increase in forest sector carbon emissions, highlighting the pivotal role of the baseline used to set the emission reduction targets. Our results show that the uncertainty on the response of European forest to climate change undermines the quest for a carbon-optimal management strategy. The uncertainty in whether climate change will maintain the current forest sink or turn it into a carbon source is largely overlooked in the debate over the best forest management strategy to reduce the growth of atmospheric CO 2 concentration, yet it is large enough to change the merit order of different alternatives