Search results for: Grégoire Mariethoz

Items from 1 to 20 out of 47 results

article

Snow cover persistence as a useful predictor of alpine plant distributions

Thomas Panchard, Olivier Broennimann, Mathieu Gravey, Grégoire Mariethoz, more

Journal of Biogeography > 50 > 10 > 1789 - 1802

Aim Snow cover persistence (SCP) has significant effects on plants in high‐elevation ecosystems. It determines the length of the growing season, provides insulation against low temperatures and influences water availability, thereby shaping the vegetation mosaic. Despite its importance, SCP is rarely used in plant species distribution modelling. In this study, we examine whether incorporating SCP...

article

Influence of microclimate and geomorphological factors on alpine vegetation in the Western Swiss Alps

Elisa Giaccone, Miska Luoto, Pascal Vittoz, Antoine Guisan, more

Earth Surface Processes and Landforms > 44 > 15 > 3093 - 3107

Among the numerous environmental factors affecting plant communities in alpine ecosystems, the influence of geomorphic processes and landforms has been minimally investigated. Subjected to persistent climate warming, it is vital to understand how these factors affect vegetation properties. Here, we studied 72 vegetation plots across three sites located in the Western Swiss Alps, characterized by high...

article

Reconstructing the climatic niche breadth of land use for animal production during the African Holocene

Leanne N. Phelps, Olivier Broennimann, Katie Manning, Adrian Timpson, more

Global Ecology and Biogeography > 29 > 1 > 127 - 147

Aim Domestic animals first appeared in the archaeological record in northern Africa c. 9000 years before present and subsequently spread southwards throughout the continent. This geographic expansion is well studied and can broadly be explained in terms of the movement of pastoralist populations due to climate change. However, no studies have explicitly evaluated changes in the climatic niche of...

article

Quantitative evaluation of multiple-point simulations using image segmentation and texture descriptors

Mohammad Javad Abdollahifard, Grégoire Mariéthoz, Maryam Ghavim

Computational Geosciences > 2019 > 23 > 6 > 1349-1368

Continuous growth of multiple-point simulation algorithms for modeling environmental variables necessitates a straightforward, reliable, robust, and distinctive method for evaluating the quality of output images. A good simulation method should produce realizations consistent with the training image (TI). Moreover, it should be capable of producing diverse realizations to effectively model the variability...

article

MPS-APO: a rapid and automatic parameter optimizer for multiple-point geostatistics

Ehsanollah Baninajar, Yousef Sharghi, Gregoire Mariethoz

Stochastic Environmental Research and Risk Assessment > 2019 > 33 > 11-12 > 1969-1989

Multiple-point statistics (MPS) have been widely used in Earth and environmental sciences because of their ability to generate realistic stochastic realizations of complex natural processes. The spatial patterns and statistical information required for MPS modeling are represented by a training image. However, each MPS algorithm has a specific set of parameters that have a direct impact on the quality...

article

Fast and Interactive Editing Tools for Spatial Models

Julien Straubhaar, Philippe Renard, Grégoire Mariethoz, Tatiana Chugunova, more

Mathematical Geosciences > 2019 > 51 > 1 > 109-125

Multiple point statistics (MPS) algorithms allow generation of random fields reproducing the spatial features of a training image (TI). Although many MPS techniques offer options to prescribe characteristics deviating from those of the TI (e.g., facies proportions), providing a TI representing the target features as well as possible is important. In this paper, methods for editing stationary images...

article

Numerical investigation on the implications of spring temperature and discharge rate with respect to the geothermal background in a fault zone

Zhenjiao Jiang, Tianfu Xu, Gregoire Mariethoz

Hydrogeology Journal > 2018 > 26 > 7 > 2121-2132

Geothermal springs are some of the most obvious indicators of the existence of high-temperature geothermal resources in the subsurface. However, geothermal springs can also occur in areas of low average subsurface temperatures, which makes it difficult to assess exploitable zones. To address this problem, this study quantitatively analyzes the conditions associated with the formation of geothermal...

article

Accelerating Sequential Gaussian Simulation with a constant path

Raphaël Nussbaumer, Grégoire Mariethoz, Mathieu Gravey, Erwan Gloaguen, more

Computers & Geosciences > 2018 > 112 > C > 121-132

Sequential Gaussian Simulation (SGS) is a stochastic simulation technique commonly employed for generating realizations of Gaussian random fields. Arguably, the main limitation of this technique is the high computational cost associated with determining the kriging weights. This problem is compounded by the fact that often many realizations are required to allow for an adequate uncertainty assessment...

article

Nurturing a growing field: Computers & Geosciences

Gregoire Mariethoz, Edzer Pebesma

Computers & Geosciences > 2017 > 107 > C > A1-A2

article

Erratum to: Which Path to Choose in Sequential Gaussian Simulation

Raphaël Nussbaumer, Grégoire Mariethoz, Erwan Gloaguen, Klaus Holliger

Mathematical Geosciences > 2018 > 50 > 1 > 121-121

The online version of the original article can be found under doi: 10.1007/s11004-017-9699-5 .

article

Which Path to Choose in Sequential Gaussian Simulation

Raphaël Nussbaumer, Grégoire Mariethoz, Erwan Gloaguen, Klaus Holliger

Mathematical Geosciences > 2018 > 50 > 1 > 97-120

Sequential Gaussian Simulation is a commonly used geostatistical method for populating a grid with a Gaussian random field. The theoretical foundation of this method implies that all previously simulated nodes, referred to as neighbors, should be included in the kriging system of each newly simulated node. This would, however, require solving a large number of linear systems of increasing size as...

article

A Fast Approximation for Seismic Inverse Modeling: Adaptive Spatial Resampling

Cheolkyun Jeong, Tapan Mukerji, Gregoire Mariethoz

Mathematical Geosciences > 2017 > 49 > 7 > 845-869

Seismic inverse modeling, which transforms appropriately processed geophysical data into the physical properties of the Earth, is an essential process for reservoir characterization. This paper proposes a work flow based on a Markov chain Monte Carlo method consistent with geology, well-logs, seismic data, and rock-physics information. It uses direct sampling as a multiple-point geostatistical method...

article

Simulating rainfall time-series: how to account for statistical variability at multiple scales?

Fabio Oriani, Raj Mehrotra, Grégoire Mariethoz, Julien Straubhaar, more

Stochastic Environmental Research and Risk Assessment > 2018 > 32 > 2 > 321-340

Daily rainfall is a complex signal exhibiting alternation of dry and wet states, seasonal fluctuations and an irregular behavior at multiple scales that cannot be preserved by stationary stochastic simulation models. In this paper, we try to investigate some of the strategies devoted to preserve these features by comparing two recent algorithms for stochastic rainfall simulation: the first one is...

article

Missing data simulation inside flow rate time-series using multiple-point statistics

Fabio Oriani, Andrea Borghi, Julien Straubhaar, Grégoire Mariethoz, more

Environmental Modelling & Software > 2016 > 86 > C > 264-276

The direct sampling (DS) multiple-point statistical technique is proposed as a non-parametric missing data simulator for hydrological flow rate time-series. The algorithm makes use of the patterns contained inside a training data set to reproduce the complexity of the missing data. The proposed setup is tested in the reconstruction of a flow rate time-series while considering several missing data...

article

Improving radar rainfall estimation by merging point rainfall measurements within a model combination framework

Mohammad Mahadi Hasan, Ashish Sharma, Gregoire Mariethoz, Fiona Johnson, more

Advances in Water Resources > 2016 > 97 > C > 205-218

While the value of correcting raw radar rainfall estimates using simultaneous ground rainfall observations is well known, approaches that use the complete record of both gauge and radar measurements to provide improved rainfall estimates are much less common. We present here two new approaches for estimating radar rainfall that are designed to address known limitations in radar rainfall products by...

article

Utilizing spatial association analysis to determine the number of multiple grids for multiple-point statistics

Hexiang Bai, Yong Ge, Gregoire Mariethoz

Spatial Statistics > 2016 > 17 > C > 83-104

Scale selection is a fundamental issue of spatial analysis. Based on spatial association analysis, this paper proposes a quantitative method for estimating the scale, which is represented using the minimal number of multiple grids in a single normal equation simulation. First, the largest scale structural information that a data template can consider for the finest grid is computed using the distance...

article

Improving in situ data acquisition using training images and a Bayesian mixture model

Mohammad Javad Abdollahifard, Gregoire Mariethoz, Mohammadreza Pourfard

Computers & Geosciences > 2016 > 91 > C > 49-63

Estimating the spatial distribution of physical processes using a minimum number of samples is of vital importance in earth science applications where sampling is costly. In recent years, training image-based methods have received a lot of attention for interpolation and simulation. However, training images have never been employed to optimize spatial sampling process. In this paper, a sequential...

article

Influence of Alluvial Morphology on Upscaled Hydraulic Conductivity

Sanjeev Kumar Jha, Gregoire Mariethoz, George Mathews, John Vial, more

Groundwater > 54 > 3 > 384 - 393

The hydraulic conductivity of aquifers is a key parameter controlling the interactions between resource exploitation activities, such as unconventional gas production and natural groundwater systems. Furthermore, this parameter is often poorly constrained by typical data used for regional groundwater modeling and calibration studies performed as part of impact assessments. In this study, a systematic...

article

Conditioning multiple-point statistics simulations to block data

Julien Straubhaar, Philippe Renard, Grégoire Mariethoz

Spatial Statistics > 2016 > 16 > C > 53-71

Multiple-points statistics (MPS) allows to generate random fields reproducing spatial statistics derived from a training image. MPS methods consist in borrowing patterns from the training set. Therefore, the simulation domain is assumed to be at the same resolution as the conceptual model, although geometrical deformations can be handled by such techniques. Whereas punctual conditioning data corresponding...

article

Application of 1D paleo‐fluvial process modelling at a basin scale to augment sparse borehole data: example of a Permian formation in the Galilee Basin, Australia

Zhenjiao Jiang, Gregoire Mariethoz, Matthias Raiber, Wendy Timms, more

Hydrological Processes > 30 > 10 > 1624 - 1636

The heterogeneous hydraulic conductivity (K) in water‐bearing formations controls subsurface flow and solute transport processes. Geostatistical techniques are often employed to characterize the K distribution in space based on the correlation between K measurements. However, at the basin scale, there are often insufficient measurements for inferring the spatial correlation. This is a widespread problem...

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INFONA - science communication portal

Search results for: Grégoire Mariethoz

Snow cover persistence as a useful predictor of alpine plant distributions

Influence of microclimate and geomorphological factors on alpine vegetation in the Western Swiss Alps

Reconstructing the climatic niche breadth of land use for animal production during the African Holocene

Quantitative evaluation of multiple-point simulations using image segmentation and texture descriptors

MPS-APO: a rapid and automatic parameter optimizer for multiple-point geostatistics

Fast and Interactive Editing Tools for Spatial Models

Numerical investigation on the implications of spring temperature and discharge rate with respect to the geothermal background in a fault zone

Accelerating Sequential Gaussian Simulation with a constant path

Nurturing a growing field: Computers & Geosciences

Erratum to: Which Path to Choose in Sequential Gaussian Simulation

Which Path to Choose in Sequential Gaussian Simulation

A Fast Approximation for Seismic Inverse Modeling: Adaptive Spatial Resampling

Simulating rainfall time-series: how to account for statistical variability at multiple scales?

Missing data simulation inside flow rate time-series using multiple-point statistics

Improving radar rainfall estimation by merging point rainfall measurements within a model combination framework

Utilizing spatial association analysis to determine the number of multiple grids for multiple-point statistics

Improving in situ data acquisition using training images and a Bayesian mixture model

Influence of Alluvial Morphology on Upscaled Hydraulic Conductivity

Conditioning multiple-point statistics simulations to block data

Application of 1D paleo‐fluvial process modelling at a basin scale to augment sparse borehole data: example of a Permian formation in the Galilee Basin, Australia

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