Development of stochastically reconstructed 3D porous media micromodels using additive manufacturing: numerical and experimental validation.

We propose an integrated methodology for the design and fabrication of 3D micromodels that are suitable for the pore-scale study of transport processes in macroporous materials. The micromodels, that bear the pore-scale characteristics of sandstone, such as porosity, mean pore size, etc, are designed following a stochastic reconstruction algorithm that allows for fine-tuning the porosity and the correlation length of the spatial distribution of the solid material. We then construct a series of 3D micromodels at very fine resolution (i.

Combining Geostatistics and Remote Sensing Data to Improve Spatiotemporal Analysis of Precipitation.

The wide availability of satellite data from many distributors in different domains of science has provided the opportunity for the development of new and improved methodologies to aid the analysis of environmental problems and to support more reliable estimations and forecasts. Moreover, the rapid development of specialized technologies in satellite instruments provides the opportunity to obtain a wide spectrum of various measurements. The purpose of this research is to use publicly available remote sensing product data computed from geostationary, polar and near-polar satellites and radar to improve space-time modeling and prediction of precipitation on Crete island in Greece.

Characterisation of the dynamics of past droughts.

Drought is a complex natural phenomenon. The description of the way in which drought changes (moves) in space may help to acquire knowledge on its drivers and processes to improve its monitoring and prediction. This research presents the application of an approach to characterise the dynamics of drought.

Geostatistical analysis of precipitation in the island of Crete (Greece) based on a sparse monitoring network.

Based on the predictions of General Circulation Models, significant reduction of precipitation in Mediterranean areas is a possible scenario. Hence, better understanding of the spatial and temporal precipitation patterns is necessary in order to quantify desertification risks and design suitable mitigation measures. This study uses monthly precipitation measurements from a sparse network of 54 monitoring stations on the Mediterranean island of Crete (Greece).

Environmental drivers of the distribution of nitrogen functional genes at a watershed scale.

To date only few studies have dealt with the biogeography of microbial communities at large spatial scales, despite the importance of such information to understand and simulate ecosystem functioning. Herein, we describe the biogeographic patterns of microorganisms involved in nitrogen (N)-cycling (diazotrophs, ammonia oxidizers, denitrifiers) as well as the environmental factors shaping these patterns across the Koiliaris Critical Zone Observatory, a typical Mediterranean watershed. Our findings revealed that a proportion of variance ranging from 40 to 80% of functional genes abundance could be explained by the environmental variables monitored, with pH, soil texture, total organic carbon and potential nitrification rate being identified as the most important drivers.

Environmental drivers of soil microbial community distribution at the Koiliaris Critical Zone Observatory.

Data on soil microbial community distribution at large scales are limited despite the important information that could be drawn with regard to their function and the influence of environmental factors on nutrient cycling and ecosystem services. This study investigates the distribution of Archaea, Bacteria and Fungi as well as the dominant bacterial phyla (Acidobacteria, Actinobacteria, Bacteroidetes, Firmicutes), and classes of Proteobacteria (Alpha- and Betaproteobacteria) across the Koiliaris watershed by qPCR and associate them with environmental variables. Predictive maps of microorganisms distribution at watershed scale were generated by co-kriging, using the most significant predictors.