42 citations · 145 across the 11 of their papers we have counts for
11 papers
Multilevel Surrogate-based Control Variates
Mohamed Reda El Amri, Paul Mycek, Sophie Ricci +1
Monte Carlo (MC) sampling is a popular method for estimating the statistics (e.g. expectation and variance) of a random variable. Its slow convergence has led to the emergence of a…
Gaussian Anamorphosis for Ensemble Kalman Filter Analysis of SAR-Derived Wet Surface Ratio Observations
Thanh Huy Nguyen, Sophie Ricci, Andrea Piacentini +3
Flood simulation and forecast capability have been greatly improved thanks to advances in data assimilation (DA) strategies incorporating various types of observations; many are de…
Enhancing Flood Forecasting with Dual State-Parameter Estimation and Ensemble-based SAR Data Assimilation
Thanh Huy Nguyen, Sophie Ricci, Andrea Piacentini +4
Ensemble data assimilation in flood forecasting depends strongly on the density, frequency and statistics of errors associated with the observation network. This work focuses on th…
Assimilation of SAR-derived Flood Observations for Improving Fluvial Flood Forecast
Thanh Huy Nguyen, Sophie Ricci, Andrea Piacentini +5
As the severity and occurrence of flood events tend to intensify with climate change, the need for flood forecasting capability increases. In this regard, the Flood Detection, Aler…
Validation and Improvement of Data Assimilation for Flood Hydrodynamic Modelling Using SAR Imagery Data
Thanh Huy Nguyen, Anthéa Delmotte, Christophe Fatras +3
Relevant comprehension of flood hazards has emerged as a crucial necessity, especially as the severity and the occurrence of flood events intensify with climate changes. Flood simu…
Improvement of Flood Extent Representation with Remote Sensing Data and Data Assimilation
Thanh Huy Nguyen, Sophie Ricci, Christophe Fatras +4
Flood simulation and forecast capability have been greatly improved thanks to advances in data assimilation. Such an approach combines in-situ gauge measurements with numerical hyd…
Reconstruction of Hydraulic Data by Machine Learning
Corentin J. Lapeyre, Nicolas Cazard, Pamphile T. Roy +2
Numerical simulation models associated with hydraulic engineering take a wide array of data into account to produce predictions: rainfall contribution to the drainage basin (charac…
Sounding Spider: An Efficient Way for Representing Uncertainties in High Dimensions
Pamphile T. Roy, Sophie Ricci, Bénédicte Cuenot +1
This article proposes a visualization method for multidimensional data based on: (i) Animated functional Hypothetical Outcome Plots (f-HOPs); (ii) 3-dimensional Kiviat plot; and (i…
Comparison of Polynomial Chaos and Gaussian Process surrogates for uncertainty quantification and correlation estimation of spatially distributed open-channel steady flows
Pamphile Tupui Roy, Nabil El Moçayd, Sophie Ricci +4
Data assimilation is widely used to improve flood forecasting capability, especially through parameter inference requiring statistical information on the uncertain input parameters…
Differential influence of instruments in nuclear core activity evaluation by data assimilation
Bertrand Bouriquet, Jean-Philippe Argaud, Patrick Erhard +4
The global activity fields of a nuclear core can be reconstructed using data assimilation. Data assimilation allows to combine measurements from instruments, and information from a…
Robustness of nuclear core activity reconstruction by data assimilation
Bertrand Bouriquet, Jean-Philippe Argaud, Patrick Erhard +4
We apply a data assimilation techniques, inspired from meteorological applications, to perform an optimal reconstruction of the neutronic activity field in a nuclear core. Both mea…