Université de Neuchâtel

Simulating Small-Scale Rainfall Fields Conditioned by Weather State and Elevation : A Data-Driven Approach Based on Rainfall Radar Images

Oriani, F ; Ohana-Levi, N ; Marra, F ; Straubhaar, J ; Mariethoz, Gregoire ; Renard, Philippe ; Karnieli, A ; Morin, E

In: Water Resources Research, 2017, vol. 53, p. 8512-8532

The quantification of spatial rainfall is critical for distributed hydrological modeling. Rainfall spatial patterns generated by similar weather conditions can be extremely diverse. This variability can have a significant impact on hydrological processes. Stochastic simulation allows generating multiple realizations of spatial rainfall or filling missing data. The simulated data can then be used...

Université de Neuchâtel

Conditioning multiple-point statistics simulations to block data

Straubhaar, J ; Renard, Philippe ; Mariethoz, Gregoire

In: Spatial Statistics, 2016, vol. 16, p. 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...

Université de Neuchâtel

Analog-based meandering channel simulation

Mariethoz, Gregoire ; Comunian, Alessandro ; Irarrazaval, Inigo ; Renard, Philippe

In: Water Resources Research, 2014, vol. 50, no. 2, p. 836–854

Characterizing the complex geometries and the heterogeneity of the deposits in meandering river systems is a long-standing issue for the 3-D modeling of alluvial formations. Such deposits are important sources of accessible groundwater in alluvial aquifers throughout the world and also play a major role as hydrocarbons reservoirs. In this paper, we present a method to generate meandering river...

Université de Neuchâtel

Spatiotemporal reconstruction of gaps in multivariate fields using the direct sampling approach

Mariethoz, Gregoire ; McCabe, Matthew F ; Renard, Philippe

In: Water Resources Research, 2012, vol. 48, p. W10507

The development of spatially continuous fields from sparse observing networks is an outstanding problem in the environmental and Earth sciences. Here we explore an approach to produce spatially continuous fields from discontinuous data that focuses on reconstructing gaps routinely present in satellite-based Earth observations. To assess the utility of the approach, we use synthetic imagery...

Université de Neuchâtel

A practical guide to performing multiple-point statistical simulations with the Direct Sampling algorithm

Meerschman, Eef ; Pirot, Guillaume ; Mariethoz, Gregoire ; Straubhaar, Julien ; Van Meirvenne, Marc ; Renard, Philippe

In: Computers & Geosciences, 2013, vol. 52, p. 307-324

The Direct Sampling (DS) algorithm is a recently developed multiple-point statistical simulation technique. It directly scans the training image (TI) for a given data event instead of storing the training probability values in a catalogue prior to simulation. By using distances between the given data events and the TI patterns, DS allows to simulate categorical, continuous and multivariate...

Université de Neuchâtel

Reducing the impact of a desalination plant using stochastic modeling and optimization techniques

Alcolea, Andres ; Renard, Philippe ; Mariethoz, Gregoire ; Bertone, François

In: Journal of Hydrology, 2009, vol. 365, no. 3-4, p. 275-288

Water is critical for economic growth in coastal areas. In this context, desalination has become an increasingly important technology over the last five decades. It often has environmental side effects, especially when the input water is pumped directly from the sea via intake pipelines. However, it is generally more efficient and cheaper to desalt brackish groundwater from beach wells rather...