In the context of underground construction projects such as large-scale linear projects, knowledge of subsoil geotechnical properties is of major importance. An effective way to analyze and represent the variability of these properties is to use geostatistical methods. Despite the good performance of such methods, their use is not yet widespread in...
In the task of predicting spatio-temporal fields in environmental science using statistical methods, introducing statistical models inspired by the physics of the underlying phenomena that are numerically efficient is of growing interest. Large space-time datasets call for new numerical methods to efficiently process them. The Stochastic Partial Di...
Quaternary glacial aquifers are important water sources for irrigation in many agricultural regions, including eastern Nebraska, USA. Quaternary glacial aquifers are heterogeneous, with juxtaposed low-permeability and high-permeability hydrofacies. Managing groundwater in such aquifers requires a realistic groundwater-flow model parameterization, a...
Published in Environmental geochemistry and health
Spatial distribution linked to geostatistical techniques contributes to sum up information into an easier-to-comprehend knowledge. This study compares copper spatial distribution in surface sediments and subsequent categorization according to its toxicological potential in two reservoirs, Rio Grande (RG) and Itupararanga (ITU) (São Paulo-Brazil), w...
Published in Frontiers in Physics
Neuronal and glial projections can be envisioned to be tubes of infinitesimal diameter as far as diffusion magnetic resonance (MR) measurements via clinical scanners are concerned. Recent experimental studies indicate that the decay of the orientationally-averaged signal in white-matter may be characterized by the power-law, Ē(q) ∝ q−1, where q is ...
In the task of predicting spatio-temporal fields in environmental science using statistical methods, introducing statistical models inspired by the physics of the underlying phenomena that are numerically efficient is of growing interest. Large space-time datasets call for new numerical methods to efficiently process them. The Stochastic Partial Di...
We consider non-linear Bayesian inversion problems targeting the geostatistical hyperparameters of a random field describing hydrogeological or geophysical properties given hydrogeological or geophysical data. This problem is of particular importance in the non-ergodic setting as there are no analytical upscaling relationships linking the data to t...
Dans les projets d’assainissement/démantèlement de sites nucléaires, l’étape de caractérisation radiologique initiale a pour objectif d’estimer la quantité et la répartition spatiale de la contamination en différents radionucléides. Pour réaliser cette estimation, des mesures sont réalisées sur site et en laboratoire. Cependant compte-tenu des envi...
Climate change is being intensified by anthropogenic emission of greenhouse gasses, highlighting the value of forests for carbon dioxide storing carbon in their biomass. Seasonally dry tropical forests are a neglected, threatened, but potentially critical biome for helping mitigate climate change. In South Amer-ica, knowing the amount and distribut...
Aquitards are common hydrogeological features in the subsurface. Typically, pumping tests are used to parameterize the hydraulic conductivity of heterogeneous aquitards. However, they do not take spatial variability and uncertainty into account. Alternatively, core-scale measurements of hydraulic conductivity are used in geostatistical upscaling me...
