A5033045774- Hydrology and Watershed Management Studies
- Climate variability and models
- Hydrology and Drought Analysis
- Cryospheric studies and observations
- Flood Risk Assessment and Management
- Meteorological Phenomena and Simulations
- Energy and Environment Impacts
- Water resources management and optimization
- Integrated Energy Systems Optimization
- Water-Energy-Food Nexus Studies
- Soil erosion and sediment transport
- Climate change and permafrost
- Hybrid Renewable Energy Systems
- Solar Radiation and Photovoltaics
- Precipitation Measurement and Analysis
- Climate Change Policy and Economics
- Smart Grid Energy Management
- Hydrology and Sediment Transport Processes
- Atmospheric and Environmental Gas Dynamics
- Electric Power System Optimization
- demographic modeling and climate adaptation
- Agriculture and Rural Development Research
- Climate Change Communication and Perception
- Energy Load and Power Forecasting
- Conferences and Exhibitions Management
Institut polytechnique de Grenoble
2015-2024
Université Grenoble Alpes
2015-2024
Institut des Géosciences de l'Environnement
2017-2024
Institut de Recherche pour le Développement
2011-2024
Centre National de la Recherche Scientifique
2015-2024
Université Félix Houphouët-Boigny
2021-2024
Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement
2023
Laboratoire de Glaciologie et Géophysique de l’Environnement
2008-2016
Université Joseph Fourier
2011
Delft University of Technology
2010
VALUE is an open European collaboration to intercompare downscaling approaches for climate change research, focusing on different validation aspects (marginal, temporal, extremes, spatial, process‐based, etc.). Here we describe the participating methods and first results from experiment, using “perfect” reanalysis (and reanalysis‐driven regional model (RCM)) predictors assess intrinsic performance of precipitation temperatures over a set 86 stations representative main climatic regions in...
Abstract. This paper addresses two major challenges in climate change impact analysis on water resources systems: (i) incorporation of a large range potential scenarios and (ii) quantification related modelling uncertainties. The methodology is developed illustrated through application to hydropower plant the Swiss Alps that uses discharge highly glacierised catchment. impacts are analysed terms system performance for control period (1961–1990) future (2070–2099) under scenarios. simulated...
Abstract This study analyses the uncertainty induced by use of different state‐of‐the‐art climate models on prediction climate‐change impacts runoff regimes 11 mountainous catchments in Swiss Alps having current proportions glacier cover between 0 and 50%. The scenarios analysed are result 19 regional model (RCM) runs obtained for period 2070–2099 based two greenhouse‐gas emission (the A2 B2 defined Intergovernmental Panel Climate Change) three coupled atmosphere‐ocean general circulation...
Abstract. In high mountainous catchments, the spatial precipitation and therefore overall water balance is generally difficult to estimate. The present paper describes structure calibration of a semi-lumped conceptual glacio-hydrological model for joint simulation daily discharge annual glacier mass that represents better integrator balance. has been developed climate change impact studies parsimonious structure; it requires three input times series - precipitation, temperature potential...
Abstract A multireplicate multimodel ensemble of hydrological simulations covering the 1860–2099 period has been produced for Upper Durance River basin (French Alps). An original quasi‐ergodic analysis variance was applied to quantify uncertainties related General Circulation Models (GCMs), Statistical Downscaling (SDMs) and internal variability each GCM/SDM simulation chain. For temperature, GCM uncertainty prevails SDM is nonnegligible. Significant warming in turn significant changes are...
Abstract. Many multi-site stochastic models have been proposed for the generation of daily precipitation, but they generally focus on reproduction low to high precipitation amounts at stations concerned. This paper proposes significant extensions model introduced by Wilks, with aim reproducing statistical features extremely rare events (in terms frequency and magnitude) different temporal spatial scales. In particular, first extended version integrates heavy-tailed distributions, tail...
Abstract A simple and robust framework is proposed for the partitioning of different components internal variability model uncertainty in an unbalanced multimember multimodel ensemble (MM2E) climate projections obtained a suite statistical downscaling models (SDMs) global (GCMs). It based on quasi-ergodic assumption transient simulations. Model are estimated from noise-free signals modeling chains using two-way analysis variance (ANOVA) framework. The residuals used to estimate large-...
Abstract In most meteorological or hydrological models, the distinction between snow and rain is based only on a given air temperature. However, other factors such as moisture can be used to better distinguish two phases. this study, number of models using different combinations variables are tested determine their pertinence for discrimination precipitation Spatial robustness also evaluated. Thirty years (1981–2010) Swiss data used, consisting radio soundings from Payerne well present...
The quantification of uncertainty sources in ensembles climate projections obtained from combinations different scenarios and impact models is a key issue studies. small size the simulation chains their incomplete sampling scenario model makes analysis difficult. In popular single-time ANOVA approach for instance, precise estimate internal variability requires multiple members each chain (e.g., emission scenario–climate combination), but are typically available few only. most also, partition...
Abstract. This paper proposes a methodology for estimating the transient probability distribution of yearly hydrological variables conditional to an ensemble projections built from multiple general circulation models (GCMs), statistical downscaling methods (SDMs), and (HMs). The is based on quasi-ergodic analysis variance (QE-ANOVA) framework that allows quantifying contributions different sources total uncertainty, by critically taking account large-scale internal variability stemming...
Abstract The development of renewable electricity in Africa could be massive coming decades, as a response to the rapid rising demand while complying with Paris Agreements. This study shows that high-resolution climate experiments CORDEX-AFRICA, annual mean solar potential is expected decrease on average by 4% over most continent end century, reaching up 6% Horn Africa, direct result radiation and increase air surface temperature. These projections are associated large uncertainties,...
Abstract Many solar photovoltaic (PV) energy projects are currently being planned and/or developed in West Africa to sustainably bridge the increasing gap between electricity demand and supply. However, climate change will likely affect power generation atmospheric factors that control it. For first time, state-of-the-art CMIP models (CMIP6) used investigate potential future evolution of its main drivers Africa. A multi-model analyses carried out revealed a decrease PV throughout 21st...
Abstract. In this study, we analyze how precipitation, antecedent conditions, and their spatial patterns interactions lead to extreme floods in a large catchment. The analysis is based on 10 000 years of continuous simulations from hydro-meteorological modelling chain for catchment, the Aare River basin, Switzerland. To account different flood-generating processes, our work with hourly time resolution. consisted stochastic weather generator (GWEX), bucket-type hydrological model (HBV),...
Abstract This paper presents a calibration framework for precipitation–runoff model flood prediction in mesoscale Alpine basin with discharges strongly influenced by hydraulic works. The developed methodology addresses two classical hydrological challenges: computational limitations to run optimization algorithms distributed hourly models and the absence of concomitant meteorological natural discharge time series. presented processes-oriented, multi-signal approach is based on data from...
Abstract Over the past decades, large variations of precipitation were observed in Africa, which often led to dramatic consequences for local society and economy. To avoid such disasters future, it is crucial better anticipate expected changes, especially current context climate change population growth. this date, however, projections over Africa are still associated with very uncertainties. understand how uncertainty can be reduced, study uses an advanced Bayesian analysis variance (ANOVA)...
Abstract. Large multiscenario multimodel ensembles (MMEs) of regional climate model (RCM) experiments driven by global models (GCMs) are made available worldwide and aim at providing robust estimates changes associated uncertainties. Due to many missing combinations emission scenarios leading sparse scenario–GCM–RCM matrices, these large ensembles, however, very unbalanced, which makes uncertainty analyses impossible with standard approaches. In this paper, the assessment is carried out...
The Mediterranean region is a climate change hotspot for water resources. However, uncertainty analyses of hydrological projections are rarely quantified. In this study, an in-depth analysis and uncertainties high low flows performed. Climatic derived from recent downscaling method were used, two representative concentration pathway scenarios (RCPs), five general circulation model/regional model (GCM/RCM) couples, three models (HMs), 29 calibration schemes. A quasi-ergodic variance was used...
High-resolution weather scenarios generated for climate change impact studies from the output of models must be spatially consistent. Analog (AMs) offer a high potential generation such scenarios. For each prediction day, scenario they provide is observed days in historical archive that are analogous according to different predictors. When same “analog date” chosen at several sites, spatial consistency automatically satisfied. The optimal predictors and consequently analog dates, however,...