Guillaume Evin

Chargé de recherche

Domaine de compétence

  • Extremes and spatial extremes in mountain geophysics.
  • Stochastic modelling of geophysical processes.
  • Bayesian inference and prediction in hydrological modelling.
  • Dependence structures with copulas, Mixture distributions.
  • Bayesian spatial and spatio-temporal models, MCMC inference methods in mountain geophysics.
  • Foreign languages: fluent in English.




Projets réalisés et en cours

Current projects:

  • 2017-2020. Contribution to Cross disciplinary program (CDP) Trajectories (Grenoble IDEX).
  • 2017-2020. Contribution to H2020 program NAIAD (Nature Insurance Value).
  • 2017-2020. Contribution to H2020 program PROSNOW (Optimization of snow in Alpine ski resorts).
  • 2015-2017. Contribution to Adamont (French Intergovernemental project on adaptation to climate change
  • 2015-2018. Contribution to C2ROP (French National project on rockfall risk).
  • 2016-2018. Contribution to EXAR (Swiss project): Hazard information for extreme flood events on the rivers Aare and Rhine.


Past projects:

  • 2014-2016: Main contributor to EDF (Electricité de France) project on rainfall extremes. Improvement of their rainfall probabilistic model (operationally applied for extreme flood estimation) using regionalization.
  • 2013-2014: Contribution to INFUZ project (incubation of a startup company in the semiconductor industry). Software development integrating advanced metrology and statistical techniques for "High-Level" data fusion.
  • 2010-2012: Contribution to BATEA project: software development of BATEA (Bayesian Total Error Analysis for hydrological models). This project aimed at providing research support for the Australian Bureau of Meteorology (BoM). I tested BATEA on hundreds of catchments in Australia, solved various parameter estimation issues and participated to the operational integration of BATEA in BoM services, including its deployment and training of BoM employees.
  • 2008-2009: Contribution to “Innovation - Production - Modelling of extreme hydrological event” project for Hydro-Québec. Development of new decision tools for flood frequency analysis. Bayesian modelling of volumes and annual peak discharges, using mixture models and Hidden-Markov chains.


[1]. Huard, D., Evin, G. and Favre, A.-C. (2006) Bayesian copula selection. Computational Statistics & Data Analysis, 51(2):809–822.

[2]. Evin, G. and Favre, A.-C. (2007) A new rainfall model based on the Neyman-Scott process using cubic copulas. Water Resources Research, 44, W03433.

[3]. Saint-Laurent, D., Mesfioui, M. and Evin, G. (2009) Hydroclimatic Variability and Relation with Flood Events (Southern Québec, Canada). Water Resources, 36(1):43–56.

[4]. Evin, G., Merleau, J. and Perreault, L. (2011) Two-component mixtures of normal, gamma, and Gumbel distributions for hydrological applications. Water Resources Research, 47, W08525.

[5]. Evin, G. and Favre, A.-C. (2012) Further developments of a transient Poisson-cluster model for rainfall. Stochastic Environmental Research and Risk Assessment, 27(4):831–847.

[6]. Evin, G., Kavetski, D., Thyer, M. and Kuczera, G. (2013) Pitfalls and improvements in the joint inference of heteroscedasticity and autocorrelation in hydrological model calibration. Water Resources Research, 49(7):4518–4524.

[7]. Evin, G., Thyer, M., Kavetski, D., McInerney, D. and Kuczera, G. (2014) Comparison of joint versus postprocessor approaches for hydrological uncertainty estimation accounting for error autocorrelation and heteroscedasticity. Water Resources Research, 50.

[8]. Evin, G., Blanchet, J., Paquet, E., Garavaglia, F. and Penot, D. (2016) A regional model for extreme rainfall based on weather patterns subsampling. Journal of Hydrology, 541(B) 1185-1198.

[9]. Evin, G., Favre, A.-C.  and Hingray, B. (2018) Stochastic generation of multi-site daily precipitation focusing on extreme events. Hydrol. Earth Syst. Sci., 22 (1): 655‑72.

[10]. Evin, G., Favre, A.-C.  and Hingray, B. (2018) Stochastic Generators of Multi-Site Daily Temperature: Comparison of Performances in Various Applications. Theoretical and Applied Climatology, 1‑14.

[11]. Evin, G., Curt, T. and Eckert, N. (2018) Has Fire Policy Decreased the Return Period of
the Largest Wildfire Events in France? A Bayesian Assessment Based on Extreme Value
Theory. Natural Hazards and Earth System Sciences, 18 (10): 2641–51.
[12]. Evin, G., Wilhelm, B. and Jenny, J.-P. (2018) Flood Hazard Assessment of the Rhône
River Revisited with Reconstructed Discharges from Lake Sediments. Global and Planetary
Change. In Press.


Irstea, Torrent erosion, snow and avalanches research unit - ETNA

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