Towards predictive data-driven simulations of wildfire spread – Part I: Reduced-cost Ensemble Kalman Filter based on a Polynomial Chaos surrogate model for parameter estimation MC Rochoux, S Ricci, D Lucor, B Cuenot, A Trouvé Natural Hazards and Earth System Sciences 14, 2951-2973, 2014 | 122 | 2014 |
Towards predictive data-driven simulations of wildfire spread–Part II: Ensemble Kalman Filter for the state estimation of a front-tracking simulator of wildfire spread MC Rochoux, C Emery, S Ricci, B Cuenot, A Trouvé Natural Hazards and Earth System Sciences 15 (8), 1721-1739, 2015 | 79 | 2015 |
Regional-scale simulations of wildland fire spread informed by real-time flame front observations MC Rochoux, B Delmotte, B Cuenot, S Ricci, A Trouvé Proceedings of the Combustion Institute 34 (2), 2641-2647, 2013 | 78 | 2013 |
Comparison of polynomial chaos and Gaussian process surrogates for uncertainty quantification and correlation estimation of spatially distributed open-channel steady flows PT Roy, N El Moçayd, S Ricci, JC Jouhaud, N Goutal, M De Lozzo, ... Stochastic environmental research and risk assessment 32, 1723-1741, 2018 | 50 | 2018 |
Evaluation of a data-driven wildland fire spread forecast model with spatially-distributed parameter estimation in simulations of the FireFlux I field-scale experiment C Zhang, M Rochoux, W Tang, M Gollner, JB Filippi, A Trouvé Fire Safety Journal 91, 758-767, 2017 | 41 | 2017 |
Reduction of the uncertainties in the water level-discharge relation of a 1D hydraulic model in the context of operational flood forecasting J Habert, S Ricci, E Le Pape, O Thual, A Piacentini, N Goutal, G Jonville, ... Journal of Hydrology 532, 52-64, 2016 | 39 | 2016 |
Assimilation of wide-swath altimetry water elevation anomalies to correct large-scale river routing model parameters CM Emery, S Biancamaria, A Boone, S Ricci, MC Rochoux, V Pedinotti, ... Hydrology and Earth System Sciences 24 (5), 2207-2233, 2020 | 37 | 2020 |
Towards Data-Driven Operational Wildfire Spread Modeling: A Report of the NSF-Funded WIFIRE Workshop M Gollner, A Trouve, I Altintas, J Block, R de Callafon, C Clements, ... | 37* | 2015 |
Ensemble-based data assimilation for operational flood forecasting–On the merits of state estimation for 1D hydrodynamic forecasting through the example of the “Adour Maritime … S Barthélémy, S Ricci, MC Rochoux, E Le Pape, O Thual Journal of Hydrology 552, 210-224, 2017 | 35 | 2017 |
Application of particle filters to regional-scale wildfire spread WB da Silva, MC Rochoux, H Orlande, M Colaço, O Fudym, M El Hafi, ... High Temperatures-High Pressures, International Journal of Thermophysical …, 2014 | 32 | 2014 |
On the merits of sparse surrogates for global sensitivity analysis of multi-scale nonlinear problems: application to turbulence and fire-spotting model in wildland fire simulators A Trucchia, V Egorova, G Pagnini, MC Rochoux Communications in Nonlinear Science and Numerical Simulation 73, 120-145, 2019 | 28 | 2019 |
Front shape similarity measure for shape-oriented sensitivity analysis and data assimilation for Eikonal equation MC Rochoux, A Collin, C Zhang, A Trouvé, D Lucor, P Moireau ESAIM: Proceedings and Surveys 63, 258-279, 2018 | 26 | 2018 |
Front shape similarity measure for data-driven simulations of wildland fire spread based on state estimation: Application to the RxCADRE field-scale experiment C Zhang, A Collin, P Moireau, A Trouvé, MC Rochoux Proceedings of the Combustion Institute 37 (3), 4201-4209, 2019 | 25 | 2019 |
Data assimilation applied to combustion MC Rochoux, B Cuenot, S Ricci, A Trouvé, B Delmotte, S Massart, R Paoli, ... Comptes Rendus Mécanique 341 (1-2), 266-276, 2013 | 25 | 2013 |
Towards predictive simulation of wildfire spread at regional scale using ensemble-based data assimilation to correct the fire front position MC Rochoux, C Emery, S Ricci, B Cuenot, A Trouvé Fire Safety Science - Proceedings of the Eleventh International Symposium …, 2014 | 23 | 2014 |
Vers une meilleure prévision de la propagation d'incendies de forêt: évaluation de modèles et assimilation de données M Rochoux Ecole centrale de Paris, Châtenay-Malabry, France, 2014 | 19* | 2014 |
Uncertainty quantification for river flow simulation applied to a real test case: The garonne valley N Goutal, C Goeury, R Ata, S Ricci, NE Mocayd, M Rochoux, H Oubanas, ... Advances in Hydroinformatics: SimHydro 2017-Choosing The Right Model in …, 2018 | 18 | 2018 |
Temporal Variance-Based Sensitivity Analysis of the River-Routing Component of the Large-Scale Hydrological Model ISBA–TRIP: Application on the Amazon Basin CM Emery, S Biancamaria, A Boone, PA Garambois, S Ricci, ... Journal of Hydrometeorology 17 (12), 3007-3027, 2016 | 18 | 2016 |
State-parameter estimation approach for data-driven wildland fire spread modeling: Application to the 2012 RxCADRE S5 field-scale experiment C Zhang, A Collin, P Moireau, A Trouvé, MC Rochoux Fire Safety Journal 105, 286-299, 2019 | 17 | 2019 |
Polynomial surrogates for open-channel flows in random steady state N El Moçayd, S Ricci, N Goutal, MC Rochoux, S Boyaval, C Goeury, ... Environmental Modeling & Assessment 23, 309-331, 2018 | 15 | 2018 |