Multi‐scale constraints of sediment source to sink systems in frontier basins: a forward stratigraphic modelling case study of the Levant region

Recent scientific work has highlighted the presence of an up to 12 km thick Cenozoic siliclastic and carbonate infill in the Levant Basin. Since the Late Eocene, several regional geodynamic events affecting Afro‐Arabia and Eurasia (collision and strike slip deformation) induced marginal uplifts. The initiation of local and long‐lived regional drainage systems in the Oligo‐Miocene period (e.g., Lebanon, Arabia and Nile) provoked a change in the depositional pattern along the Levant region from carbonate‐dominated to mixed clastic‐rich systems. Herein, we explore the importance of multi‐scale constraints (i.e., seismic, well and field data) in the quantification of subsidence history, sediment transport and deposition of a Middle to Upper Miocene “multi‐source” to sink system along the northern Levant frontier region. Through a comprehensive 4D forward stratigraphic modelling workflow, we suggest that the contribution to basin infill is split between proximal and more distal clastic sources as well as in situ carbonate and hemipelagic deposition. The results show that single‐source scenarios could not reasonably satisfy the basin‐scale constraints. The worldwide application of such new multi‐disciplinary workflows in frontier regions highlights the additional data constraints that are needed to de‐risk highly uncertain geological models in the hydrocarbon exploration phase.     

Projecting future drought in Mediterranean forests: bias correction of climate models matters!

Global and regional climate models (GCM and RCM) are generally biased and cannot be used as forcing variables in ecological impact models without some form of prior bias correction. In this study, we investigated the influence of the bias correction method on drought projections in Mediterranean forests in southern France for the end of the twenty-first century (2071–2100). We used a water balance model with two different atmospheric climate forcings built from the same RCM simulations but using two different correction methods (quantile mapping or anomaly method). Drought, defined here as periods when vegetation functioning is affected by water deficit, was described in terms of intensity, duration and timing. Our results showed that the choice of the bias correction method had little effects on temperature and global radiation projections. However, although both methods led to similar predictions of precipitation amount, they induced strong differences in their temporal distribution, especially during summer. These differences were amplified when the climatic data were used to force the water balance model. On average, the choice of bias correction leads to 45 % uncertainty in the predicted anomalies in drought intensity along with discrepancies in the spatial pattern of the predicted changes and changes in the year-to-year variability in drought characteristics. We conclude that the choice of a bias correction method might have a significant impact on the projections of forest response to climate change.     

Origine des eaux des émergences karstiques chlorurées du Languedoc-Roussillon

The origin of chloride-rich karstic spring waters representative of the Languedoc-Roussillon region has been investigated with a hydrochemical approach. To this end, the major and trace elements most often used in the study of saline environments have been considered (Cl, SO₄, Br, B, Li). This study allowed distinguishing the different end-members of the various chloride-rich karstic spring waters (evaporitic, marine, geothermal). Associated with the Cl, Br and B contents, the Li/SO₄ ratio appeared as a relevant tracer for the determination of the origin of lithium and by extension of the considered waters. To cite this article: O. Hébrard et al., C. R. Geoscience 338 (2006).     

Modeling the risk of robbery in the city of Tshwane,South Africa

ABSTRACT

In this study, we model the risk of robbery in the City of Tshwane in South Africa. We use the collective knowledge of two prominent spatial theories of crime (social disorganization theory, and crime pattern theory) to guide the selection of data and employ rudimentary geospatial techniques to create a crude model that identifies the risk of future robbery incidents in the city. The model is validated using actual robbery incidences recorded for the city. Overall the model performs reasonably well with approximately 70% of future robbery incidences accurately identified within a small subset of the overall model. Developing countries such as South Africa are in dire need of crime risk intensity models that are simple, and not data intensive to allocate scarce crime prevention resources in a more optimal fashion. It is anticipated that this model is a first step in this regard.