Engineering geomorphological characterisation of the Vajont Slide,Italy, and a new interpretation of the chronology and evolution of the landslide

Although the 1963 Vajont Slide in Italy has been extensively studied for over 50 years, its regional geological and geomorphological context has been neglected. In this paper, we use field observations and remote sensing data to elucidate the interaction between endogenic and exogenic processes that brought the north slope of Monte Toc to failure. We present the first detailed pre- and post-failure engineering geomorphology maps of the slide area. The maps delineate two main landslide blocks, several sub-blocks, compressional and extensional zones, and secondary failures in the deposit. The maps provide new insights into the kinematics, dynamics and evolution of the slide. Finally, we discuss the origin of Vajont Gorge and a prehistoric failure that occurred at the same location as the 1963 slide. We propose, as part of a newly developed multi-stage landscape evolution sequence, that the prehistoric failure was a deep-seated gravitational slope deformation (sackung) that initiated during deglaciation and continued to slowly move until the catastrophic failure in 1963. We argue that the gorge was created by these deep-seated slow movements.     

A Comparative Analysis of Weights of Evidence,Evidential Belief Functions,and Fuzzy Logic for Mineral Potential Mapping Using Incomplete Data at the Scale of Investigation

Large amounts of digital data must be analyzed and integrated to generate mineral potential maps, which can be used for exploration targeting. The quality of the mineral potential maps is dependent on the quality of the data used as inputs, with higher quality inputs producing higher quality outputs. In mineral exploration, particularly in regions with little to no exploration history, datasets are often incomplete at the scale of investigation with data missing due to incomplete mapping or the unavailability of data over certain areas. It is not always clear that datasets are incomplete, and this study examines how mineral potential mapping results may differ in this context. Different methods of mineral potential mapping provide different ways of dealing with analyzing and integrating incomplete data. This study examines the weights of evidence (WofE), evidential belief function and fuzzy logic methods of mineral potential mapping using incomplete data from the Carajás mineral province, Brazil to target for orogenic gold mineralization. Results demonstrate that WofE is the best one able to predict the location of known mineralization within the study area when either complete or unacknowledged incomplete data are used. It is suggested that this is due to the use of Bayes’ rule, which can account for “missing data.” The results indicate the effectiveness of WofE for mineral potential mapping with incomplete data.     

Data-Driven Predictive Modeling of Mineral Prospectivity Using Random Forests: A Case Study in Catanduanes Island (Philippines)

The Random Forests (RF) algorithm is a machine learning method that has recently been demonstrated as a viable technique for data-driven predictive modeling of mineral prospectivity, and thus, it is instructive to further examine its usefulness in this particular field. A case study was carried out using data from Catanduanes Island (Philippines) to investigate further (a) if RF modeling can be used for data-driven modeling of mineral prospectivity in areas with few (i.e., <20) mineral occurrences and (b) if RF modeling can handle predictor variables with missing values. We found that RF modeling outperforms evidential belief (EB) modeling of prospectivity for hydrothermal Au–Cu deposits in Catanduanes Island, where 17 hydrothermal Au–Cu prospects are known to exist. Moreover, just like EB modeling, RF modeling allows analysis of the spatial relationships between known prospects and individual layers of predictor data. Furthermore, RF modeling can handle missing values in predictor data through an RF-based imputation technique whereas in EB modeling, missing values are simply represented by maximum uncertainty. Therefore, the RF algorithm is a potentially useful method for data-driven predictive modeling of mineral prospectivity in regions with few (i.e., <20) occurrences of mineral deposits of the type sought. However, further testing of the method in other regions with few mineral occurrences is warranted to fully determine its usefulness in data-driven predictive modeling of mineral prospectivity.     

Application of Discriminant Analysis and Support Vector Machine in Mapping Gold Potential Areas for Further Drilling in the Sari-Gunay Gold Deposit,NW Iran

In this contribution, we used discriminant analysis (DA) and support vector machine (SVM) to model subsurface gold mineralization by using a combination of the surface soil geochemical anomalies and earlier bore data for further drilling at the Sari-Gunay gold deposit, NW Iran. Seventy percent of the data were used as the training data and the remaining 30 % were used as the testing data. Sum of the block grades, obtained by kriging, above the cutoff grade (0.5 g/t) was multiplied by the thickness of the blocks and used as productivity index (PI). Then, the PI variable was classified into three classes of background, medium, and high by using fractal method. Four classification functions of SVM and DA methods were calculated by the training soil geochemical data. Also, by using all the geochemical data and classification functions, the general extension of the gold mineralized zones was predicted. The mineral prediction models at the Sari-Gunay hill were used to locate high and moderate potential areas for further infill systematic and reconnaissance drilling, respectively. These models at Agh-Dagh hill and the area between Sari-Gunay and Agh-Dagh hills were used to define the moderate and high potential areas for further reconnaissance drilling. The results showed that the nu-SVM method with 73.8 % accuracy and c-SVM with 72.3 % accuracy worked better than DA methods.     

Testing optically stimulated luminescence dating on sand-sized quartz of deltaic deposits from the Sperchios delta plain,central Greece

This study reports on the first investigation into the potential of luminescence dating to establish a chronological framework for the depositional sequences of the Sperchios delta plain, central Greece. A series of three borehole cores(20 m deep) and two shallow cores(4 m deep), from across the delta plain, were extracted, and samples were collected for luminescence dating. The luminescence ages of sand-sized quartz grains were obtained from small aliquots of quartz, using the Single-Aliquot Regenerative-dose(SAR) protocol.The equivalent dose determination included a series of tests and the selection of the Minimum Age Model(MAM) as the most appropriate statistical model. This made it possible to confirm the applicability of quartz Optically Stimulated Luminescence(OSL) dating to establish absolute chronology for deltaic sediments from the Sperchios delta plain.Testing age results of the five cores showed that the deltaic sediments were deposited during the Holocene.A relatively rapid deposition is implied for the top ~14 m possibly as a result of the deceleration in the rate of the sea-level rise and the transition to terrestrial conditions, while on the deeper parts, the reduced sedimentation rate may indicate a lagoonal or coastal environment.     

A method of alternating characteristics with application to advection-dominated environmental systems

We present a numerical method for solving a class of systems of partial differential equations (PDEs) that arises in modeling environmental processes undergoing advection and biogeochemical reactions. The salient feature of these PDEs is that all partial derivatives appear in linear expressions. As a result, the system can be viewed as a set of ordinary differential equations (ODEs), albeit each one along a different characteristic. The method then consists of alternating between equations and integrating each one step-wise along its own characteristic, thus creating a customized grid on which solutions are computed. Since the solutions of such PDEs are generally smoother along their characteristics, the method offers the potential of using larger time steps while maintaining accuracy and reducing numerical dispersion. The advantages in efficiency and accuracy of the proposed method are demonstrated in two illustrative examples that simulate depth-resolved reactive transport and soil carbon cycling.     

Perspectives on lithospheric evolution through tectonomagmatic processes: a volume in honour of Jaroslav Dostal—an introduction

International Journal of Earth Sciences -     

Characterising the vertical separation of shale-gas source rocks and aquifers across England and Wales (UK)

Shale gas is considered by many to have the potential to provide the UK with greater energy security, economic growth and jobs. However, development of a shale gas industry is highly contentious due to environmental concerns including the risk of groundwater pollution. Evidence suggests that the vertical separation between exploited shale units and aquifers is an important factor in the risk to groundwater from shale gas exploitation. A methodology is presented to assess the vertical separation between different pairs of aquifers and shales that are present across England and Wales. The application of the method is then demonstrated for two of these pairs—the Cretaceous Chalk Group aquifer and the Upper Jurassic Kimmeridge Clay Formation, and the Triassic sandstone aquifer and the Carboniferous Bowland Shale Formation. Challenges in defining what might be considered criteria for ‘safe separation’ between a shale gas formation and an overlying aquifer are discussed, in particular with respect to uncertainties in geological properties, aquifer extents and determination of socially acceptable risk levels. Modelled vertical separations suggest that the risk of aquifer contamination from shale exploration will vary greatly between shale–aquifer pairs and between regions and this will need to be considered carefully as part of the risk assessment and management for any shale gas development.