Rainfall thresholds for the triggering of landslides considering previous soil moisture conditions (Asturias,NW Spain)

Given its geological and climatic conditions and its rugged orography, Asturias is one of the most landslide prone areas in the North of Spain. Most of the landslides occur during intense rainfall episodes. Thus, precipitation is considered the main triggering factor in the study area, reaching average annual values of 960 mm. Two main precipitation patterns are frequent: (i) long-lasting periods of moderate rainfall during autumn and winter and (ii) heavy short rainfall episodes during spring and early summer. In the present work, soil moisture conditions in the locations of 84 landslides are analysed during two rainfall episodes, which represent the most common precipitation patterns: October–November 2008 and June 2010. Empirical data allowed the definition of available water capacity percentages of 99–100% as critical soil moisture conditions for the landslide triggering. Intensity-duration rainfall thresholds were calculated for each episode, considering the periods with sustained high soil moisture levels before the occurrence of each analysed landslide event. For this purpose, data from daily water balance models and weather stations were used. An inverse relationship between the duration of the precipitation and its intensity, consistent with published intensity-duration thresholds, was observed, showing relevant seasonal differences.     

Non-woven polypropylene fabric modified with carbon nanotubes and decorated with nanoakaganeite for arsenite removal

Due to its harmful impact on human health, the presence of heavy metals, metalloids and other toxic pollutants in drinking or irrigation water is a major concern. Recent studies have proved that nanosized adsorbents are significantly more effective than their microsized counterparts. Particular attention has been given to nanocomposites with nanoadsorbents embedded in matrixes that could provide stability to the material and contribute to eliminating problems that may appear when using conventional granular systems. This study presents the preparation of a novel hybrid filter from a commercially available polypropylene (PP) non-woven fabric matrix modified with multiwall carbon nanotubes (MWCNT) and iron oxy(hydroxide) nanoparticles, and its use in the removal of As(III). A Box–Behnken statistical experimental design has been chosen to explore relevant variables affecting the filter performance: (1) As(III) concentration, (2) pH and (3) sorbent dose. From an As(III) concentration of 10 mg L^?1, at pH 6.5 and with a sorbent dose of 5 g L^?1, the PP filter modified with MWCNT removes 10% of the initial metalloid concentration, reaching a capacity of 0.27 mg g^?1. After modification with iron oxy(hydroxide), the performance of the material is largely enhanced. The filter, under the same conditions, removes 90% of the initial As(III) concentration, reaching a capacity almost tenfold higher (2.54 mg g^?1). This work demonstrates that the developed hybrid filter is effective toward the removal of As(III) in a wide range of pHs. A cubic regression model to compute the removal of the filter as a function of pH and sorbent dose is provided.     

Toxic metals in a highly urbanized industry-impacted estuary (Bahia Blanca Estuary,Argentina): spatio-temporal analysis based on GIS

Cadmium, chromium, nickel, and lead were evaluated in the particulate fraction at one of the most industrialized estuaries at the Southwestern Atlantic Ocean, through Geographic Information System (GIS). Concentrations were analyzed at 21 stations during 2008–2010. The highest metal concentrations (Cd: 8,9; Cr: 256,49; Ni: 27,02; Pb: 78,43 µg g^??1 d. w.) were recorded at the stations located near industrial and urban discharges situated along the estuary. In addition, Pb presented a different seasonal and spatial behavior in comparison with Cd, Cr and Ni. Winter and spring presented the higher concentrations of Pb, and the inner stations presented the higher values. The estuary is considered a moderate to strongly polluted and significantly polluted according to the Index of geoaccumulation (I_geo) and the Enrichment Factor of Cd, respectively. The Multidimensional Scaling plot showed three groups of stations: the inner, associated to low levels of metals (G1), middle stations (G2) with intermediate levels and the outer (G3) with the highest ones. In addition, this work reveals the usefulness of the GIS-mapping techniques in the distribution of pollutants along an estuarine environment and the environmental quality assessment of estuarine systems.     

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.     

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.     

Automatic detection of earthquake-induced ground failure effects through Faster R-CNN deep learning-based object detection using satellite images

Natural Hazards - The seismically induced ground failure is defined as any earthquake-generated process that leads to deformations within a soil medium, which in turn results in permanent...     

Causes and consequences of long-term groundwater overabstraction in Jordan

Hydrogeology Journal - In 2017, a comprehensive review of groundwater resources in Jordan was carried out for the first time since 1995. The change in groundwater levels between 1995 and 2017 was...     

Morphosedimentary features and recent depositional architectural model of the Cantabrian continental margin

Multibeam bathymetry, high (sleeve airguns) and very high resolution (parametric system-TOPAS-) seismic records were used to define the morphosedimentary features and investigate the depositional architecture of the Cantabrian continental margin. The outer shelf (down to 180–245 m water depth) displays an intensively eroded seafloor surface that truncates consolidated ancient folded and fractured deposits. Recent deposits are only locally present as lowstand shelf-margin deposits and a transparent drape with bedforms. The continental slope is affected by sedimentary processes that have combined to create the morphosedimentary features seen today. The upper (down to 2000 m water depth) and lower (down to 3700–4600 m water depth) slopes are mostly subject to different types of slope failures, such as slides, mass-transport deposits (a mix of slumping and mass-flows), and turbidity currents. The upper slope is also subject to the action of bottom currents (the Mediterranean Water — MW) that interact with the Le Danois Bank favouring the reworking of the sediment and the sculpting of a contourite system. The continental rise is a bypass region of debris flows and turbidity currents where a complex channel-lobe transition zone (CLTZ) of the Cap Ferret Fan develops.The recent architecture depositional model is complex and results from the remaining structural template and the great variability of interconnected sedimentary systems and processes. This margin can be considered as starved due to the great sediment evacuation over a relatively steep entire depositional profile. Sediment is eroded mostly from the Cantabrian and also the Pyrenees mountains (source) and transported by small stream/river mountains to the sea. It bypasses the continental shelf and when sediment arrives at the slope it is transported through a major submarine drainage system (large submarine valleys and mass-movement processes) down to the continental rise and adjacent Biscay Abyssal Plain (sink). Factors controlling this architecture are tectonism and sediment source/dispersal, which are closely interrelated, whereas sea-level changes and oceanography have played a minor role (on a long-term scale).