Linear discriminant analysis to describe the relationship between rainfall and landslides in Bogotá, Colombia

Bogotá is located in the central Andean region of Colombia, which is frequently affected by landslide processes. These processes are mostly triggered during the rainy season in the city. This fact remarks the importance of determining what rain-derived parameters (e.g. intensity, antecedent rain, daily rain) are better related with the occurrence of landslides. For this purpose, the linear discriminant analysis (LDA), a technique derived from multivariate statistics, was used. The application of this type of analysis led to obtain simple mathematical functions that represent the probability of occurrence of landslides in Bogotá. The functions also allow to identify the most relevant variables derived from records of rainfall linked to the generation of landslides. A proof of concept using the proposed methodology was done using historic rainfall data from a 9-km² area of homogenous climatology and geomorphology in the south part of Bogotá. Landslides needed to be grouped for the LDA. Each one of these grouping categories represents landslides that occurred in similar geomorphologic conditions. Another set of events with no landslides was generated synthetically. Results of the proof of concept show that rainfall parameters such as normalized rainfall intensity I _MAP, normalized daily rainfall R _MAP and rainy-days normal RDN have the best statistical correlation with the landslides observed in the zone of analysis.     

High-dimensional geostatistical history matching

Hydrocarbon reservoir modelling and characterisation is a challenging subject within the oil and gas industry due to the lack of well data and the natural heterogeneities of the Earth’s subsurface. Integrating historical production data into the geo-modelling workflow, commonly designated by history matching, allows better reservoir characterisation and the possibility of predicting the reservoir behaviour. We present herein a geostatistical-based multi-objective history matching methodology. It starts with the generation of an initial ensemble of the subsurface petrophysical property of interest through stochastic sequential simulation. Each model is then ranked according the match between its dynamic response, after fluid flow simulation, and the observed available historical production data. This enables building regionalised Pareto fronts and the definition of a large ensemble of optimal subsurface Earth models that fit all the observed production data without compromising the exploration of the uncertainty space. The proposed geostatistical multi-objective history matching technique is successfully implemented in a benchmark synthetic reservoir dataset, the PUNQ-S3, where 12 objectives are targeted.     

Three-dimensional numerical and analytical study of horizontal group of square anchor plates in sand

In this paper, numerical and analytical methods are used to evaluate the ultimate pullout capacity of a group of square anchor plates in row or square configurations, installed horizontally in dense sand. The elasto-plastic numerical study of square anchor plates is carried out using three-dimensional finite element analysis. The soil is modeled by an elasto-plastic model with a Mohr–Coulomb yield criterion. An analytical method based on a simplified three-dimensional failure mechanism is developed in this study. The interference effect is evaluated by group efficiency η, defined as the ratio of the ultimate pullout capacity of group of N anchor plates to that of a single isolated plate multiplied by number of plates. The variation of the group efficiency η was computed with respect to change in the spacing between plates. Results of the analyses show that the spacing between the plates, the internal friction angle of soil and the installation depth are the most important parameters influencing the group efficiency. New equations are developed in this study to evaluate the group efficiency of square anchor plates embedded horizontally in sand at shallow depth (H = 4B). The results obtained by numerical and analytical solutions are in excellent agreement.     

Classify-normalize-classify

Changing atmospheric conditions often result in a data distribution shift in remote sensing images for different dates and locations making it difficult to discriminate between various classes of interest. To alleviate this data shift issue, we introduce a novel supervised classification framework, called Classify-Normalize-Classify (CNC). The proposed scheme uses a two classifier approach where the first classifier performs a rough segmentation of the class of interest (COI) in the input image. Then, the median signal of the estimated COI regions is subtracted from all image pixels values to normalize them. Finally, the second classifier is applied to the normalized image to produce the refined COI segmentation. The proposed methodology was tested to detect deforestation using bitemporal Landsat 8 OLI images over the Amazon rainforest. The CNC framework compared favorably to benchmark masks of the PRODES program and state-of-the-art classifiers run on surface reflectance images provided by USGS.     

Efficacy of laser cleaning in the removal of biological patina on the volcanic scoria of the rock-hewn churches of Lalibela,Ethiopia

The Lalibela rock-hewn churches are one of the most important religious pilgrimage sites in Ethiopia. These churches are carved from the scoriaceous basalt rock substrate, which has been exposed to attack by biological agents with significant loss of surface material. Particularly, the widespread growth of lichens and other microorganisms on the carved surfaces of the churches has proven to represent a substantial threat for the preservation of the site. In this study, laboratory tests have been conducted to assess the feasibility of using laser technology as an efficient cleaning method of biological patina from polymineralic stone substrates. Multi-analytical techniques were applied for the characterization of the stone samples collected from two of the Lalibela churches: Bete Giyorgis and Bete Amanuel. Stone samples artificially inoculated with bacteria, yeast, fungi isolates, and lichen-encrusted samples were laser cleaned using UV and IR laser wavelengths. The high content of Fe and Ti oxides and the high porosity have made the stone surfaces easily susceptible to low-energy laser treatment. Results indicate that laser cleaning can be applied to polymineralic lithotypes and UV irradiation can successfully remove lichen colonies. Further studies need to be conducted to optimize the laser procedure in polymineralic, high porosity stones.     

Analysis of physical factors of climate and bioclimate and their effects on almonds production to increase the economy in Hebron area of Palestine

For the 1993–2009 period, we analyzed the relationship between almond yield and three climatic variables (mean annual temperature, soil water reserve, and precipitation), and four bioclimatic variables (annual ombrothermic index, water deficit, simple continentality index, and compensated thermicity index), for one major Hebron crop (soft and hard almonds). Moreover, we obtained data almond production from the Palestinian Central Bureau of Statistics, while the climate data from the Palestinian meteorological station during the study period from 1993 to 2009, and analysis is it by using bioclimatic classification of the Earth of Salvador Rivas-Martinez to study the relationship between the almond yield and climate and bioclimate factors (variables). The climatic and bioclimate variables of greatest importance to almond were used to develop regressions analysis relating yield to climatic conditions. Hebron was positively affected by annual ombrothermic index, simple continentality index, precipitation, water soil reserve, and mean annual temperature, but negatively affected by water deficit, with a large proportion of the variance explained by axis F1 (72.48%), F2 (22.38%), and axes F1and F2 (94. 86%). However, in order to produce a high amount of almonds and quality, it can be grown in the regions of the mesomediterranean region, with the value of annual ombrothemic index more than 3, compensated thermicity index between 220/220 to 350/350, simple continentality index between 14 and 20, and in areas where the average annual temperature is between 15 and 20 °C.     

The P-y Response of Laterally Loaded Flexible Piles in Residual Soil

This paper describes the main features related to lateral displacements with depth after successive lateral loading–unloading cycles applied to the top of reinforced-concrete flexible bored piles embedded in naturally bonded residual soil. The bored piles under study have a cylindrical shape, with 0.40-m in diameter and 8.0-m in length. Both bored piles types (P1 and P2) include an embedded steel pipe section in their center as longitudinal steel reinforcements: pile type P1 has another 16 steel rods as steel reinforcement to concrete while pile type P2 has no further steel reinforcement. Pile type P1 has three times as much stiffness (EI) and four and a half times the plastic moment (M_y) than pile type P2. A similar load–displacement performance was observed at initial loads as for small displacements of both piles. At this initial loading stage, the response of the reinforced concrete piles is a function of the soil characteristics and of a linear elastic pile deformation. During this stage, piles can even be understood as probes for evaluating soil reactions. For larger horizontal displacements, after the concrete section starts undergoing large deformations, approaching the ultimate bending moment, pile behavior and consequently the load–displacement relation starts to diverge for both piles. For pile P1 the values of relevant lateral displacements are extended to about 2.5-m in depth, while for pile P2 lateral displacements are mostly constrained to about 2.0-m in depth. Measurements of horizontal displacements of pile P1 against depth recorded with a slope indicator show that, after unloading, lateral loads at distinct stages (small and near failure loads), exhibits a much higher elastic phase of the system response. An analytical fitting model of soil reaction is proposed based on the measured displacements from slope indicator. The integration of a continuous model proposed for the soil reaction agrees fairly well with the measured displacements up to moments close to plastic limit. Results of load–displacement show that the stiffer pile (P1) was able to mobilize twice as much lateral load compared to pile P2 for a service limit displacement of about 20 mm. The paper shows results that enable the isolation of the structural variable through real scale pile load tests, thus granting understanding of its importance and enabling its quantitative visualization in examples of piles embedded in residual soil sites.