Thermal thickness of the Earth’s lithosphere: a numerical model

A technique is suggested and the thermal thickness of the lithosphere is calculated, as well as the temperature distribution in the lithosphere on the basis of data on topography, the age of the oceanic bottom, crustal composition and structure, gravity anomalies, and mean annual surface temperatures. The bottom of the lithosphere is determined as the 1300°C isotherm. The calculation resolution is 0.5°×0.5°. All first-order tectonic structures, such as mid-ocean ridges and plume areas in oceans, continental rifts, cratons, and orogenic belts, are expressed in the computed thermal thickness. The comparative analysis of the thermal thickness of oceanic and continental lithosphere, lithosphere of cratons and young platforms, ancient and young orogens, remnant oceanic basins and adjacent continental areas can be used in geodynamical analysis of the corresponding regions.     

Constructing a truly global model of Earth’s dynamics: basic principles

This is a snapshot of the today’s views of the Earth with its geospheres, and terrestrial and extraterrestrial triggers of its dynamics and energy sources. Along with the presented brief historic outline of the planetary evolution, these data can make basis for creating in the future a truly global model of the Earth’s dynamics and evolution.     

Pareto’s law and sample size: a case study of China’s urban system 1984–2008

While Pareto’s law has been widely supported by empirical evidence in urban studies, past studies have focused on finding best fits for city rank-size distribution. A main concern with Pareto’s law is the truncation of sample selection, for which few studies have examined it directly. This study tests three existing threshold methods (number threshold, size threshold, and urban population percentage threshold) using China’s city system as a case study. In addition, this study proposes a new method based upon the percentage threshold of the total number of cities. A systematic analysis is applied to examine the relationship between Pareto exponent and sample size using different threshold methods. The results show that Pareto exponent is sensitive to sample size and the truncation point. Including only large cities is problematic because a slight change in the truncation point will yield quite different results of Pareto exponent. In addition, the new method, the percentage threshold of the total number of cities method, presents an advantage over previous methods, in that this method yields a consistent set of results over a wide range of thresholds. Finally, when using this new method with China’s city system, the Pareto exponent presents a turning point in 1996, representing China’s transition from a planned economy to a more market oriented economy during that period.     

An examination on the feed-in tariff policy for renewable electricity: Taiwan’s case example

Taiwan’s feed-in tariff (FIT) policy, revised in 2009, sets a goal to increase the installation capacity 6,500–10,000 MW (megawatts) of renewable power systems in 20 years. The purpose of this paper is to examine whether the goal can be achieved or not. This paper presents an overview of FIT policies implemented in some leading countries and their performance of renewable electricity installed capacity and generation. This paper presents two outlook scenarios for Taiwan’s renewable power installation capacity by using Germany as a benchmark after a detailed analysis and discussion on Taiwan’s historical evolution of renewable energies. The Moderate Scenario projects that total cumulative capacity of renewable power systems increases from 5,813.8 MW in 2010 to 7,245.99 MW in 2030, while the Optimistic Scenario estimates the total renewable power capacity will be 11,977.14 MW in 2030. The total increase in the new installation capacity attain to 1,432.19 and 6,163.64 MW for the two scenarios, respectively.     

Geospatial data: a key ingredient for Swiss Re’s underwriting and service tools

As a leading global reinsurer, Swiss Re deals with many hazards and risks for which geospatial data are crucial in order to obtain reliable assessments of expected insured losses or large losses from catastrophes. Typically, such data are used in combination with insurance data either in pricing tools to calculate premiums, tail risks and more, or in mapping tools. In natural perils pricing applications—the most important group of tools—geospatial data are usually “not visible” but are instead used to create probabilistic event sets. For example, a flood event set may define spatially if and how frequently a given location is flooded. Mapping tools, such as Swiss Re’s CatNet^® (www.swissre.com/catnet), visualize the data in the form of maps which include many useful attributes per geographic location.

     

A correlation model for oscillations of the Earth’s pole with parametric perturbations

A differential correlation model for oscillations of the Earth’s pole is constructed. The model has gravitational-tidal, additive and parametric, slowly varying, harmonic (at the Chandler frequency and double this frequency), and random Gaussian, broadband perturbations. Special attention is paid to the analysis of trends and the amplitude-frequency characteristics of stochastic oscillations of the Earth’s pole. Numerical simulations show that first-approximation equations can be used to estimate the correlation characteristics of oscillations of the Earth’s pole to within 10%. The results of the model are compared with the results of statistical modeling of oscillations at the Chandler frequency. The model represents a base of informational resources for analytical modeling of the motion of the Earth’s pole over intervals of three to five years.     

The Swedish Geotechnical Society’s methodology for risk management: a tool for engineers in their everyday work

The Swedish Geotechnical Society has adopted a general methodology for risk management in geotechnical engineering projects to reduce the costs related to negative outcomes of geotechnical risks. This technical note highlights the main features of the methodology and strives to inspire the international geotechnical community to apply sensible risk management methods. In the authors’ opinion, a successful geotechnical risk management needs to be structured, be tailored to the project, and permeate the engineers’ everyday work. Then, sufficient quality can be achieved in the project with larger probability.     

Application of a Weighted-Averaging Method for Determining Paleosalinity: A Tool for Restoration of South Florida’s Estuaries

A molluscan analogue dataset is presented in conjunction with a weighted-averaging technique as a tool for estimating past salinity patterns in south Florida’s estuaries and developing targets for restoration based on these reconstructions. The method, here referred to as cumulative weighted percent (CWP), was tested using modern surficial samples collected in Florida Bay from sites located near fixed water monitoring stations that record salinity. The results were calibrated using species weighting factors derived from examining species occurrence patterns. A comparison of the resulting calibrated species-weighted CWP (SW-CWP) to the observed salinity at the water monitoring stations averaged over a 3-year time period indicates, on average, the SW-CWP comes within less than two salinity units of estimating the observed salinity. The SW-CWP reconstructions were conducted on a core from near the mouth of Taylor Slough to illustrate the application of the method.     

Determining proper strategies for Iran’s dimensional stone mines: a SWOT–AHP analysis

Iran has very high potential for production and export of dimension stone (rock quarried to size and shape specifications); nevertheless, in spite of growing mine production during the past decade, in many instances this potential has been overlooked. Construction, decorative, and facing stones of Iran are among the highest-quality products in the world. In this paper, Iran’s dimensional stone mines are analyzed using strengths, weaknesses, opportunities and threats (SWOT) analysis in combination with analytic hierarchy process (AHP). SWOT analysis is a tool commonly used for analyzing both the internal and external environments in order to attain a systematic approach and support for a decision situation. Conventionally, SWOT analysis is qualitative and does not quantify the effect of the factors. Consequently, it is not effective in priority setting. To overcome this limitation, SWOT analysis has been used in combination with other quantitative multi-criteria decision making methods especially the AHP. In this study, first an environment analysis was performed by an expert team familiar with these mines. In this way, the SWOT factors were identified and the subfactors which had very significant effects on the success of these mines were determined. Using the SWOT subfactors, the SWOT matrix and alternative strategies based on these subfactors were developed. Subsequently, the strategies were prioritized and the best strategies for Iran’s dimensional stone mines were determined.     

Multi-agent distributed data mining approach for classifying meteorology data: case study on Iran’s synoptic weather stations

Today’s organizations, industries and research centers are geographically distributed in different sites. To achieve true knowledge of business, mining massive amounts of data is necessary. In earth-related sciences such as meteorology, the date obtained from the various types of sensors is huge because of the high-frequency rate of data acquisition process and also the geographical distribution of weather stations. Therefore, the data mining and knowledge discovery process of this big and distributed data is a challenging work. In this paper, we propose a new distributed data mining approach called multi-agent hierarchical data mining to classify meteorology data, which has been collected from different sites widely distributed around the country (Iran). Our method utilizes a modified version of REPTree algorithm, which has been optimized to work in multi-agent system. To evaluate the proposed approach, it is implemented on 20 million of meteorology data record. Experimental results show that multi-agent hierarchical data mining approach can achieve significant performance improvement over centralized and parallel methods for knowledge discovery in large amounts of data.     

Indicators of the Anthropocene: is there a case for conservation?

The Earth's atmosphere, biosphere and lithosphere are increasingly being modified by human activity. Given this anthropogenic influence on the natural environment, the case for recognizing an Anthropocene Epoch has recently been made and there is ongoing debate as to whether, and how, to formally characterize and define such an epoch. As a contribution to this debate, this article explores whether or not the landscapes, deposits, landforms and key marker horizons that may be used to characterize and define an Anthropocene Epoch could, and should, be identified and conserved in the same manner as other parts of the geological succession. Anthropogenic features pose a conservation challenge, however, as they often cross cut existing conservation frameworks which tend to focus on the natural, historic or cultural environment. Developing a coherent approach to the conservation of the indicators of an Anthropocene Epoch would, therefore, require an integrated system of describing, auditing and designating features for conservation. A major benefit of such an approach would be the opportunities for interdisciplinary collaboration between the wide range of researchers interested or involved in studying and conserving the record of anthropogenic activity.     

Forecasting flood-prone areas using Shannon’s entropy model

With regard to the lack of quality information and data in watersheds, it is of high importance to present a new method for evaluating flood potential. Shannon’s entropy model is a new model in evaluating dangers and it has not yet been used to evaluate flood potential. Therefore, being a new model in determining flood potential, it requires evaluation and investigation in different regions and this study is going to deal with this issue. For to this purpose, 70 flooding areas were recognized and their distribution map was provided by ArcGIS10.2 software in the study area. Information layers of altitude, slope angle, slope aspect, plan curvature, drainage density, distance from the river, topographic wetness index (TWI), lithology, soil type, and land use were recognized as factors affecting flooding and the mentioned maps were provided and digitized by GIS environment. Then, flood susceptibility forecasting map was provided and model accuracy evaluation was conducted using ROC curve and 30% flooding areas express good precision of the model (73.5%) for the study area.     

Fairness of China’s provincial energy environment efficiency evaluation: empirical analysis using a three-stage data envelopment analysis model

China has become the world’s largest carbon emitter since 2007; thus, reducing future emission has become an arduous task. Calculating energy efficiency fairly is paramount for formulating energy policies, given the different development levels of provinces. This study employed a three-stage data envelopment analysis model that considered environmental constraints to evaluate the energy efficiency of China’s 30 provinces in 2015 and redefined traditional energy efficiency as energy environment efficiency which calculated under environmental constraints. Different factors, such as urban development level and industrial structure in relation to energy environment efficiency, were analyzed. Three main results were obtained. First, the average energy environment efficiency in 2015 was only 0.73, which showed that China has roughly 30% capacity for improvement in the future. Second, stochastic frontier analysis demonstrated that the industrial structure, energy consumption structure, and central heating systems exerted negative impacts, and the level of city design and the degree of openness exerted positive effects on energy environment efficiency. Third, capital, manpower, and the extent of industrial concentration in central and western regions should be increased to improve China’s energy environment efficiency.

     

Influence of Shannon’s entropy on landslide-causing parameters for vulnerability study and zonation—a case study in Sikkim, India

Landslide is a common hazard in the hilly regions, which causes heavy losses to life and properties every year. Since 1980, various researches and analyses have been carried out in the geographic information systems (GIS) environment to identify factors responsible for causing landslides. The important conditioning factors identified by the researchers are slope, geological, geomorphologic structures, and land use coupled with triggering factors like rainfall and a few of the anthropogenic activities. Almost all landslides vulnerability studies carried out so far used parameters of landslide events of the past as essential inputs and advanced methods like information value, regression analysis, fuzzy logic, etc. The present research is an attempt to investigate the landslide vulnerabilities in different slope areas with simple and realistic method of assignments of weights to the parameters based on experts?? opinion and generic logic, without using the parameters of past landslide events as inputs. The identified factors were assigned appropriate weights based on experts?? opinion and these weights were further balanced with respect to the Shannon??s entropy of their occurrences within the study area. The study area was finally classified into three zones namely least vulnerable zone, moderately vulnerable zone, and most vulnerable zone. When compared with the actual landslide history of the past, it was found that Shannon??s entropy applied zonation model matched to real landslide events with higher value of landslide density as compared to the model developed without Shannon??s entropy.     

Identifying China’s leading world city: a network approach

This paper reports our research on China’s world cities. Formal network analysis of air passenger linkages for recent years among China’s most populous cities and among many of the world’s largest cities allows us to identify the country’s leading world city from among the leading Mainland candidates, Beijing, Shanghai and Guangzhou. We theorize our findings about China’s world cities in relation to both global forces (and China’s increasing entanglement with them) and the policies and actions of the national state. We examine the national and global urban network through a longitudinal, two-level analysis of airline passenger travel for four time points between about 1990 and 2005. We show that Beijing was China’s leading world city at the beginning of the time period, a status it lost nationally in as early as 1995, and then globally 10 years later. On the other hand Shanghai became China’s leading world city, and it acquired this status first nationally in 2000, and then globally in 2005. The changing status of the Chinese capital corresponds to the country’s increasing involvement with the capitalist world economy. Shanghai’s ascendance as the leading world city in China may indicate that global forces have come to play an increasingly important role relative to that of the developmental state.

Evaluation of EDI derived from the exponential evapotranspiration model for monitoring China’s surface drought

Drought has become the most severe natural disaster in many provinces of China. In this paper, evaporative drought index (EDI) has been used to monitor China’s surface dryness conditions based on the exponential evapotranspiration (ET) model and Hargreaves equation from JAXA-MODIS Insolation products, GEWEX, NCEP-2 and MODIS NDVI data. The exponential ET model based on the surface net radiation, vegetation index, mean air temperature and diurnal air temperature range (DTaR) has been developed to estimate surface ET of China and has been independently validated using ground-measured data collected from two sites (Arou and Miyun) in China, indicating that the bias varies from −5.96 to 5.02 W/m². The good agreement between daily estimated and ground-measured ET using ground observation data collected from all 22 sites further supports the validity of the exponential ET model for regional ET estimation. Moreover, EDI is closely correlated to the average soil moisture at 0–10 cm soil depth of the Yongning site with coefficient of determination of R ² = 0.52. The spatio-temporal patterns of monthly ET and EDI from April to September of 2004 over China are explored and the result indicates EDI is accordant with the precipitation by comparing the 15-day smoothed EDI with precipitation over six representative sites. The EDI based on the exponential ET model by integrating energy fluxes in response to soil moisture stress has demonstrated its validity for monitoring China’s surface drought events.     

Exploring the magnitude–frequency distribution: a cellular automata model for landslides

Landslide magnitude–frequency curves allow for the probabilistic characterization of regional landslide hazard. There is evidence that landslides exhibit self-organized criticality including the tendency to follow a power law over part of the magnitude–frequency distribution. Landslide distributions, however, also typically exhibit poor agreement with the power law at smaller sizes in a flattening of the slope known as rollover. Understanding the basis for this difference is critical if we are to accurately predict landslide hazard, risk or landscape denudation over large areas. One possible argument is that the magnitude–frequency distribution is dominated by physiographic controls whereby landslides tend to a larger size, and larger landslides are landscape limited according to a power law. We explore the physiographic argument using first a simple deterministic model and then a cellular automata model for watersheds in coastal British Columbia. The results compare favorably to actual landslide data: modeled landslides bifurcate at local elevation highs, deposit mass preferentially where the local slopes decrease, find routes in confined valley or channel networks, and, when sufficiently large, overwhelm the local topography. The magnitude–frequency distribution of both the actual landslides and the cellular automata model follow a power law for magnitudes higher than 10,000–20,000 m² and show a flattening of the slope for smaller magnitudes. Based on the results of both models, we argue that magnitude–frequency distributions, including both the rollover and the power law components, are a result of actual physiographic limitations related to slope, slope distance, and the distribution of mass within landslides. The cellular automata model uses simple empirically based rules that can be gathered for regions worldwide.