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.     

Field investigation of deformation characteristics and stress mobilisation of a soil slope

Stress mobilisation and deformation of a slope are important for engineers to carry out reliable design of retaining systems. However, most case histories reported mainly on the response of pore water pressure (PWP), whereas knowledge about the stress deformation characteristics of slope is limited. In this study, a saprolitic soil slope was instrumented to monitor not only the responses of PWP but also horizontal stress and horizontal displacement. To assist in the interpretation of field data, a series of laboratory tests was conducted to characterise volume change behaviour of the soil taken from the site, under the effects of both net stress and suction. During a rainstorm event when positive PWP built up, a remarkably large displacement of 20 mm was recorded between 5.5- and 6-m depths, and the top 5 m of the slope exhibited translational downslope movement. This caused an increase in Bishop’s effective horizontal stress by 350 %, which reached a peak value close to 40 % of a Bishop’s effective passive stress. During the subsequent dry season when suction was recovered, an upslope rebound of 10 mm was recorded. Comparison of field and laboratory data reveals that the rebound was attributed to suction-induced soil shrinkage. This rebound led to a decrease in the Bishop’s effective horizontal stress previously built up during the storm event.     

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.     

Factors driving riverbed scouring and sedimentation in the Bayangaole to Toudaoguai reaches of the Upper Yellow River

The Inner Mongolia reaches of the Yellow River face problems of severe sedimentation caused by a variety of complex factors. The sedimentation process in those reaches has been characterized using the sediment balance method, and the key factors affecting the process have been analyzed using the correlation analysis method. The results show that during the period 1952–2012 the Bayangaole (Bayan Gol) to Toudaoguai reaches in Inner Mongolia have undergone successive processes of accumulative sedimentation, then relative balance, and then accumulative sedimentation once again. The total annual sedimentation is 12.0341×10⁸ m³, of which accumulations from July to October account for 95.1% and the reaches from Sanhuhekou to Toudaoguai account for 98.5%. The main factor affecting scouring and sedimentation of the Bayangaole to Sanhuhekou reaches is the combined water and sediment condition. The critical conditions for equilibrium are an incoming sediment coefficient < 0.007 kg·s·m^–6 and a flow discharge > 700 m³·s^–1. The main factor affecting scouring and sedimentation of the Sanhuhekou to Toudaoguai reaches is the incoming sediment from the tributaries on the south bank and the combined water and sediment condition of the main stream. The critical conditions of the main stream for maintaining equilibrium status are a flow discharge of the main stream exceeding 800 m³·s^–1 and a comprehensive incoming sediment coefficient < 0.005 kg·s·m^–6. The incoming sediment from the tributaries has little impact on the main stream when the annual sediment load is less than 0.1×10⁸ t. The incoming sediment coefficient of the main stream and the incoming sediment from the tributaries both play vital roles in the riverbed evolution of the Inner Mongolia reaches, but the latter contributes the most.     

Progress in China’s sustainable development research: Contribution of Chinese geographers

Sustainable development has always been a hotspot in Chinese geographical research. Herein, we conduct a systematic statistical analysis of the contribution of Chinese geographers to sustainable development research using bibliometric methods. Based on the review of a vast amount of literature, we identify the main research teams, research funding sources, journals, and key research fields. The findings are as follows: (1) the resources and environmental institutes of the Chinese Academy of Sciences have a significant influence on sustainable development research; (2) China’s central government foundations (the National Natural Science Foundation of China and National Social Sciences Fund) are the main research funding sources; (3) most of the highly cited articles are published in journals sponsored by the Geographical Society of China; and (4) sustainable development theory and its research areas are being constantly enriched and perfected. Based on the statistics of keywords, the theory, research methods, research regional scales, and key research areas are summarized and expounded.     

Analysis of the contribution of multiple factors to the recent decrease in discharge and sediment yield in the Yellow River Basin,China

The Yellow River basin is well known for its high sediment yield. However, this sediment yield has clearly decreased since the 1980s, especially after the year 2000. The annual average sediment yield was 1.2 billion tons before 2000, but has significantly decreased to 0.3 billion tons over the last 10 years. Changes in discharge and sediment yield for the Yellow River have attracted the attention of both the Central Government and local communities. This study aimed to identify the individual contributions of changes in precipitation and human activities (e.g. water conservancy projects, terracing, silt dams, socio-economic and needs, and soil and water conservation measures) to the decrease in discharge and sediment yield of the Yellow River. The study used both improved the hydrological method and the soil and water conservation method. The study focused on discharge analysis for the upper reaches and the investigation of sediments for the middle reaches of the river. The results showed that discharge and sediment yield have both presented significant decreasing trends over the past 50 years. Precipitation showed an insignificant decreasing trend over the same period. The annual average discharge decreased by 5.68 billion m³ above Lanzhou reach of the Yellow River from 2000 to 2012; human activities (e.g. socio-economic water use) contributed 43.4% of the total reduction, whereas natural factors (e.g. evaporation from lakes, wetlands and reservoirs) accounted for 56.6%. The decrease in annual discharge and sediment yield of the section between Hekouzhen station and Tongguan station were 12.4 billion m³ and 1.24 billion tons, respectively. Human activities contributed 76.5% and 72.2% of the total reduction in discharge and sediment yield, respectively, and were therefore the dominant factors in the changes in discharge and sediment yield of the Yellow River.     

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.     

Metallic Mineral Resources in the Twenty-First Century. I. Historical Extraction Trends and Expected Demand

Industrial, technological, and economic developments depend on the availability of metallic raw materials. As a greater fraction of the Earth’s population has become part of developed economies and as developed societies have become more affluent, the demand on metallic mineral resources has increased. Yet metallic minerals are non-renewable natural resources, the supply of which, even if unknown and potentially large, is finite. An analysis of historical extraction trends for eighteen metals, going back to the year 1900, demonstrates that demand of metallic raw materials has increased as a result of both increase in world population and increase in per-capita consumption. These eighteen metals can be arranged into four distinct groups, for each of which it is possible to identify a consistent pattern of per-capita demand as a function of time. These patterns can, in turn, be explained in terms of the industrial and technological applications, and in some cases conventional uses as well, of the metals in each group. Under the assumption that these patterns will continue into the future, and that world population will grow by no more than about 50% by the year 2100, one can estimate the amount of metallic raw materials that will be required to sustain the world’s economy throughout the twenty-first century. From the present until the year 2100, the world can be expected to require about one order of magnitude more metal than the total amount of metal that fueled technological and economic growth between the age of steam and the present day. For most of the metals considered here, this corresponds to 5–10 times the amount of metal contained in proven ore reserves. The two chief driving factors of this expected demand are growth in per-capita consumption and present-day absolute population numbers. World population is already so large that additional population growth makes only a small contribution to the expected future demand of metallic raw materials. It is not known whether or not the amount of metal required to sustain the world’s economy throughout this century exists in exploitable mineral resources. In the accompanying paper, I show that it is nevertheless possible to make statistical inferences about the size distribution of the mineral deposits that will need to be discovered and developed in order to satisfy the expected demand. Those results neither prove nor disprove that the needed resources exist but can be used to improve our understanding of the challenges facing future supply of metallic raw materials.     

Practical Incorporation of Multivariate Parameter Uncertainty in Geostatistical Resource Modeling

There is a need to bridge theory and practice for incorporating parameter uncertainty in geostatistical simulation modeling workflows. Simulation workflows are a standard practice in natural resource and recovery modeling, but the incorporation of multivariate parameter uncertainty into those workflows is challenging. However, the objectives can be met without considerable extra effort and programming. The sampling distributions of statistics comprise the core theoretical notion with the addition of the spatial degrees of freedom to account for the redundancy in the spatially correlated data. Prior parameter uncertainty is estimated from multivariate spatial resampling. Simulation-based transfer of prior parameter uncertainty results in posterior distributions which are updated by data conditioning and the model domain extents and configuration. The results are theoretically tractable and practical to achieve, providing realistic assessments of uncertainty by accounting for large-scale parameter uncertainty, which is often the most important component impacting a project. A simulation-based multivariate workflow demonstrates joint modeling of intrinsic shale properties and uncertainty in estimated ultimate recovery in a shale gas project. The multivariate workflow accounts for joint prior parameter uncertainty given the current well locations and results in posterior estimates on global distributions of all modeled properties. This is achieved by transferring the joint prior parameter uncertainty through conditional simulations.