Assessing rockfall susceptibility in steep and overhanging slopes using three-dimensional analysis of failure mechanisms

Rockfalls strongly influence the evolution of steep rocky landscapes and represent a significant hazard in mountainous areas. Defining the most probable future rockfall source areas is of primary importance for both geomorphological investigations and hazard assessment. Thus, a need exists to understand which areas of a steep cliff are more likely to be affected by a rockfall. An important analytical gap exists between regional rockfall susceptibility studies and block-specific geomechanical calculations. Here we present methods for quantifying rockfall susceptibility at the cliff scale, which is suitable for sub-regional hazard assessment (hundreds to thousands of square meters). Our methods use three-dimensional point clouds acquired by terrestrial laser scanning to quantify the fracture patterns and compute failure mechanisms for planar, wedge, and toppling failures on vertical and overhanging rock walls. As a part of this work, we developed a rockfall susceptibility index for each type of failure mechanism according to the interaction between the discontinuities and the local cliff orientation. The susceptibility for slope parallel exfoliation-type failures, which are generally hard to identify, is partly captured by planar and toppling susceptibility indexes. We tested the methods for detecting the most susceptible rockfall source areas on two famously steep landscapes, Yosemite Valley (California, USA) and the Drus in the Mont-Blanc massif (France). Our rockfall susceptibility models show good correspondence with active rockfall sources. The methods offer new tools for investigating rockfall hazard and improving our understanding of rockfall processes.     

Subduction-related mafic to felsic magmatism in the Malayer–Boroujerd plutonic complex,western Iran

The Malayer–Boroujerd plutonic complex (MBPC) in western Iran, consists of a portion of a magmatic arc built by the northeast verging subduction of the Neo-Tethys plate beneath the Central Iranian Microcontinent (CIMC). Middle Jurassic-aged felsic magmatic activity in MBPC is manifested by I-type and S-type granites. The mafic rocks include gabbroic intrusions and dykes and intermediate rocks are dioritic dykes and minor intrusions, as well as mafic microgranular enclaves (MMEs). MBPC Jurassic-aged rocks exhibit arc-like geochemical signatures, as they are LILE- and LREE-enriched and HFSE- and HREE-depleted and display negative Nb–Ta anomalies. The gabbro dykes and intrusions originated from metasomatically enriched garnet-spinel lherzolite [Degree of melting (f_mel) ~ 15%] and exhibit negative Nd and positive to slightly negative ε_Hf(T) (+ 3.0 to ? 1.6). The data reveal that evolution of Middle Jurassic magmatism occurred in two stages: (1) deep mantle-crust interplay zone and (2) the shallow level upper crustal magma chamber. The geochemical and isotopic data, as well as trace element modeling, indicate the parent magma for the MBPC S-type granites are products of upper crustal greywacke (f_mel: 0.2), while I-type granites formed by partial melting of amphibolitic lower crust (f_mel: 0.25) and mixing with upper crustal greywacke melt in a shallow level magma chamber [Degree of mixing (f_mix): 0.3]. Mixing between andesitic melt leaving behind a refractory dense cumulates during partial crystallization of mantle-derived magma and lower crustal partial melt most likely produced MMEs (f_mix: 0.2). However, enriched and moderately variable ε_Nd(T) (? 3.21 to ? 4.33) and high (⁸⁷Sr/⁸⁶Sr)_i (0.7085–0.7092) in dioritic intrusions indicate that these magmas are likely experienced assimilation of upper crustal materials. The interpretations of magmatic activity in the MBPC is consistent with the role considered for mantle-derived magma as heat and mass supplier for initiation and evolution of magmatism in continental arc setting, elsewhere.     

Assessment of the acid drainage neutralization capacity and the toxic metals lixiviation of tailing from Guanajuato mining district,Mexico

In Mexico, many environmental problems are generated by large mining activities taking place in several mining districts. These mining activities produce great quantities of residues; large majorities of these have high sulfur content, which could generate acid drainage due to their interaction with the oxygen in the environment. The study area was located in the Mining District of Guanajuato, Mexico with abandoned tailings generated mainly by the gold and silver production. Two areas, called as Monte de San Nicolás (SN) and Peregrina (P) were selected for this study. The results study shows that there was no risk of production of acid drainage, since these tailings contained high amount of carbonates, which neutralized the generation of acidity and consequently decreased the possibility of leaching of some elements. However, not all elements leach in acid pH, as arsenic bound to oxyhydroxides, which is in a basic environment and its increased release by increasing the pH.     

Exploratory Factor Analysis of Wireline Logs Using a Float-Encoded Genetic Algorithm

In the paper, a novel inversion approach is used for the solution of the problem of factor analysis. The float-encoded genetic algorithm as a global optimization method is implemented to extract factor variables using open-hole logging data. The suggested statistical workflow is used to give a reliable estimate for not only the factors but also the related petrophysical properties in hydrocarbon formations. In the first step, the factor loadings and scores are estimated by Jöreskog’s fast approximate method, which are gradually improved by the genetic algorithm. The forward problem is solved to calculate wireline logs directly from the factor scores. In each generation, the observed and calculated well logs are compared to update the factor population. During the genetic algorithm run, the average fitness of factor populations is maximized to give the best fit between the observed and theoretical data. By using the empirical relation between the first factor and formation shaliness, the shale volume is estimated along the borehole. Permeability as a derived quantity also correlates with the first factor, which allows its determination from an independent source. The estimation results agree well with those of independent deterministic modeling and core measurements. Case studies from Hungary and the USA demonstrate the feasibility of the global optimization based factor analysis, which provides a useful tool for improved reservoir characterization.     

Neo-rural populations and their relations with local decision makers in rural Québec: collaboration or conflict?

The socio-demographic recomposition of the countryside is affecting local interactions and power relations. Understanding these relationships remains a challenge, as the studies to date are often limited to conflicts between neo-rural populations (newcomers) and long-time country residents over partial issues, without including decision makers. To go beyond this conflictual and fragmentary perspective, the objective of this article is to present an overall picture of both cooperative and oppositional relations between four groups, namely, newcomers, long-time rural residents, leaders of local organizations and municipal officials, in regard to all the issues that concern them. The data are based on interviews with these various actors in two contrasting rural areas of Québec (Canada). After looking at the newcomers’ mixed assessment of their participation in community life, we concentrate on areas of collaboration and/or conflict between all the actors regarding demographic, economic, sociocultural, political, environmental and agricultural issues. Three main trends emerge, revealing unexpected ways of interacting, complex power relations and antagonistic conceptions of rural spaces and their future development.     

Effect of climatic oscillations on flood occurrence on Papaloapan River,México,during the 1550–2000 period

This study presents a chronology of historical and measured flood events in the Papaloapan River basin of Mexico during 450 years. Twenty-eight historical floods were recorded during the period 1550–1948 on this river and one flood event (1969) in the instrumental era (1949–2000), of which 14 were extraordinary floods and only 15 were catastrophic ones. There were several flood-rich decades during 1860–1870, 1880–1890, 1920–1930 and 1940–1950. Wavelet analysis found a significant flooding periodicity of 58 years. The wavelet coherence analysis found that flooding had an in-phase relationship with the Atlantic Multidecadal Oscillation and also with the Pacific Decadal Oscillation. Logistic regression corroborated that there exists a positive relationship between floods events and these two natural climatic oscillations. The logistic regression model predicted correctly 92% of flood events.     

Assessing the performance of WRF model in predicting high-impact weather conditions over Central and Western Africa: an ensemble-based approach

Natural Hazards - For numerical weather prediction over a particular region, it is important to know the best combination of physical parameterizations available in the considered modelling frame...     

Influence of the sediment delivery ratio index on the analysis of silting and break risk in the Plasencia reservoir (Central System,Spain)

The random forest method was used to generate susceptibility maps for debris flows, rock slides, and active layer detachment slides in the Donjek River area within the Yukon Alaska Highway Corridor, based on an inventory of landslides compiled by the Geological Survey of Canada in collaboration with the Yukon Geological Survey. The aim of this study is to develop data-driven landslide susceptibility models which can provide information on risk assessment to existing and planned infrastructure. The factors contributing to slope failure used in the models include slope angle, slope aspect, plan and profile curvatures, bedrock geology, surficial geology, proximity to faults, permafrost distribution, vegetation distribution, wetness index, and proximity to drainage system. A total of 83 debris flow deposits, 181 active layer detachment slides, and 104 rock slides were compiled in the landslide inventory. The samples representing the landslide free zones were randomly selected. The ratio of landslide/landslide free zones was set to 1:1 and 1:2 to examine the results of different sample ratios on the classification. Two-thirds of the samples for each landslide type were used in the classification, and the remaining 1/3 were used to evaluate the results. In addition to the classification maps, probability maps were also created, which served as the susceptibility maps for debris flows, rock slides, and active layer detachment slides. Success and prediction rate curves created to evaluate the performance of the resulting models indicate a high performance of the random forest in landslide susceptibility modelling.     

Mapping fractional landscape soils and vegetation components from Hyperion satellite imagery using an unsupervised machine-learning workflow

An unsupervised machine-learning workflow is proposed for estimating fractional landscape soils and vegetation components from remotely sensed hyperspectral imagery. The workflow is applied to EO-1 Hyperion satellite imagery collected near Ibirací, Minas Gerais, Brazil. The proposed workflow includes subset feature selection, learning, and estimation algorithms. Network training with landscape feature class realizations provide a hypersurface from which to estimate mixtures of soil (e.g. 0.5 exceedance for pixels: 75% clay-rich Nitisols, 15% iron-rich Latosols, and 1% quartz-rich Arenosols) and vegetation (e.g. 0.5 exceedance for pixels: 4% Aspen-like trees, 7% Blackberry-like trees, 0% live grass, and 2% dead grass). The process correctly maps forests and iron-rich Latosols as being coincident with existing drainages, and correctly classifies the clay-rich Nitisols and grasses on the intervening hills. These classifications are independently corroborated visually (Google Earth) and quantitatively (random soil samples and crossplots of field spectra). Some mapping challenges are the underestimation of forest fractions and overestimation of soil fractions where steep valley shadows exist, and the under representation of classified grass in some dry areas of the Hyperion image. These preliminary results provide impetus for future hyperspectral studies involving airborne and satellite sensors with higher signal-to-noise and smaller footprints.