Storm surge prediction using an artificial neural network model and cluster analysis

In this study, an artificial neural network model was developed to predict storm surges in all Korean coastal regions, with a particular focus on regional extension. The cluster neural network model (CL-NN) assessed each cluster using a cluster analysis methodology. Agglomerative clustering was used to determine the optimal clustering of 21 stations, based on a centroid-linkage method of hierarchical clustering. Finally, CL-NN was used to predict storm surges in cluster regions. In order to validate model results, sea levels predicted by the CL-NN model were compared with results using conventional harmonic analysis and the artificial neural network model in each region (NN). The values predicted by the NN and CL-NN models were closer to observed data than values predicted using harmonic analysis. Data such as root mean square error and correlation coefficient varied only slightly between CL-NN and NN model results. These findings demonstrate that cluster analysis and the CL-NN model can be used to predict regional storm surges and may be used to develop a forecast system.     

Crustal and upper mantle S-wave velocity structure beneath the Bransfield Strait (West Antarctica) from regional surface wave tomography

Regional surface wave tomography in the sub-Antarctic Scotia Sea is helpful in revealing the nature of the crust and the S-wave seismic velocity profile beneath the Bransfield Strait. The joint use of our regional network, global seismographic network stations and local temporary arrays provide better lateral resolution than that obtained in our previous studies concerning the Scotia Sea region.Tomographic analysis of data obtained using 10 broad band seismic stations and more than 300 regional events, shows that the Bransfield Basin is characterised by a strong group velocity reduction of 8% with respect to the surrounding areas, in the period range from 15 s to 50 s.The crustal and upper mantle models of the eastern, central and western Bransfield Basin are obtained by joint inversion of Rayleigh and Love local dispersion curves from 15 s to 50 s. In addition our data set is expanded to a broader period interval (1–80 s), in central Bransfield Strait in order to better constrain the upper mantle and shallow crust.The main results can be summarized as follows: (a) the crust thins distinctly from W toward E; the variation is consistent with the type of volcanism, earthquake distribution and bathymetric observations, (b) low upper mantle velocities (soft lid) extend down to depths exceeding 70 km as a consequence of elevated temperatures, (c) the crust beneath the central Bransfield Basin displays continental characteristics with a gradually increasing S-wave velocity distribution versus depth analogous to the East African Rift structure of Kenya, (d) negative velocity gradients are present in the lower crust beneath the eastern Bransfield Basin; these could be interpreted as magmatic bodies originating from decompression melting of the mantle.     

Hydrogeodeformation monitoring: prospects of earthquake prediction

The regional hydrogeodeformatics, the new discipline dealing with regional deformation processes and based on hydrogeodeformation (HGD) monitoring methodology, was introduced in Russia in the early 1980s. During the last 30 years, the theoretical principles and HGD methodology were further developed and modified in Russia and some other countries. The HGD field is a combination of short-lived 3D deformation structures which are formed within the lithosphere and have a lifetime ranging from several days to several months. Monitoring of the HGD field within the study area provides a comprehensive picture of deformation changes and transformations occurring in real time. Some important HGD field features and parameters were described and discussed. A combined analysis of these parameters and seismic information was applied to the southwestern part of British Columbia (Canada). The results indicated that British Columbia was the area highly sensitive to global deformations and, as such, should be included in the international HGD monitoring network. Prior to establishing such a network, the existing provincial groundwater monitoring network in British Columbia could be utilized for HGD monitoring and predicting strong earthquakes in the province and the neighboring areas.     

Neural network-based methodology for inter-arrival times of earthquakes

In this paper, an artificial neural network (ANN)?Cbased methodology is proposed to determine the probability of inter-arrival time (IAT) of main shock of six broad seismic regions of India. Initially, classical methodology using exponential distribution is applied to IAT of earthquake events computed from earthquake catalog data. From the goodness-of-fit test results, it has been found that exponential distribution is not adequate. In this paper, a more efficient ANN-based methodology is proposed, and two ANN models are developed to determine the probability of IAT of earthquake events for a specified region, specified magnitude range or magnitude greater than the specified value. The performance of ANN models developed is validated with number of examples and found to predict the probability with minimal error compared to exponential distribution model. The methodology developed can be applied to any other region with the database of the respective regions.     

区域斜坡不稳定空间预测

将场地斜坡稳定随机模拟分析结果与区域斜坡空间不稳定性预测结合起来,基于层次分析建立了区域斜坡空间破坏概率的多层模糊稳定分析方法,实现了场地斜坡稳定非确定性模型评价结果与区域稳定性研究相结合,借助这一关系模型可以实现空间点评价向空间面评价的过渡．以川南经济开发区区域斜坡空间破坏概率预测为例进行了方法验证,结果显示这种方法可以克服区域斜坡不稳定性评价中的定量化困难,物理意义更加明确．     

区域地壳稳定性研究现状与趋势

回顾了区域地壳稳定性发展历史及现状。区域稳定评价应和工程实际要求紧密结合 ,逐步实现由场地评价场地利用地质工程设计的转变 ;在理论上紧密结合岩石圈动力学 ,大陆动力学等当代地球科学发展前沿 ;在分析评价上 ,考虑内外地球动力作用的耦合 ,将地球内外动力地质灾害统一起来分析 ,建立统一地质灾害动力学模型 ,最终实现区域地壳稳定性研究的系统化和定量化     

Flood risk assessment using regional regression analysis

This study aimed to create a flood risk map for ungauged regions, which have limited flood damage data and other relevant data. The fact that there is a shortage of data that are critical for the establishment of a flood assessment and mitigation plan is not surprising even in developed countries like South Korea. To address this problem, the regional regression concept in statistical hydrology was introduced to the flood risk assessment field in this study, and it was framed with a series of two regression functions: flood damage and regional coefficients. As the second regression function utilizes the local socioeconomic variables, the resulting flood risk map can reflect the spatial characteristics well. The proposed methodology was applied to create flood risk maps for the three metropolitan areas in South Korea. The comparison of the proposed methodology with the existing methods revealed that only the proposed methodology can produce a statistically meaningful flood risk map based on a recent major flood in 2001.     

Use of hierarchical cluster analysis to assess the representativeness of a baseline groundwater quality monitoring network: comparison of New Zealand’s national and regional groundwater monitoring programs

Baseline monitoring of groundwater quality aims to characterize the ambient condition of the resource and identify spatial or temporal trends. Sites comprising any baseline monitoring network must be selected to provide a representative perspective of groundwater quality across the aquifer(s) of interest. Hierarchical cluster analysis (HCA) has been used as a means of assessing the representativeness of a groundwater quality monitoring network, using example datasets from New Zealand. HCA allows New Zealand??s national and regional monitoring networks to be compared in terms of the number of water-quality categories identified in each network, the hydrochemistry at the centroids of these water-quality categories, the proportions of monitoring sites assigned to each water-quality category, and the range of concentrations for each analyte within each water-quality category. Through the HCA approach, the National Groundwater Monitoring Programme (117 sites) is shown to provide a highly representative perspective of groundwater quality across New Zealand, relative to the amalgamated regional monitoring networks operated by 15 different regional authorities (680 sites have sufficient data for inclusion in HCA). This methodology can be applied to evaluate the representativeness of any subset of monitoring sites taken from a larger network.     

Rainfall thresholds for the forecasting of landslide occurrence at regional scale

This paper concerns a regional scale warning system for landslides that relies on a decisional algorithm based on the comparison between rainfall recordings and statistically defined thresholds. The latter were based on the total amount of rainfall, which was cumulated considering different time intervals: 1-, 2- and 3-day cumulates took into account the critical rainfall influencing shallow movements, whilst a variable time interval cumulate (up to 240 days) was used to consider the triggering of deep-seated landslides in low permeability terrains. A prototypal version of the model was initially set up to define statistical thresholds. Then, thresholds were calibrated using a database of past georegistered and dated landslides. A validation procedure showed that the calibration highly improves the results and therefore the model was integrated in the regional warning system of Emilia Romagna (Italy) for civil protection purposes. The proposed methodology could be easily implemented in other similar regions and countries where a sufficiently organised meteorological network is present.     

Bayesian Spatial Modelling of Gamma Ray Count Data

Gamma ray logging is a method routinely employed by geophysicists and environmental engineers in site geology evaluations. Modelling of gamma ray data from individual boreholes assists in the local identification of major lithological changes; modelling these data from a network of boreholes assists with lithological mapping and spatial stratigraphic correlation. In this paper we employ Bayesian spatial partition models to analyse gamma ray data spatially. In particular, a spatial partition is defined via a Voronoi tessellation and the mean intensity is assumed constant in each cell of the partition. The number of vertices generating the tessellation as well as the locations of vertices are assumed unknown, and uncertainty about these quantities is described via a hierarchical prior distribution. We describe the advantages of the spatial partition modelling approach in the context of smoothing gamma ray count data and describe an implementation that may be extended to the fitting of a more general model than a constant mean within each cell of the partition. As an illustration of the methodology we consider a data set collected from a network of eight boreholes, which is part of a geophysical study to assist in mapping the lithology of a site. Gamma ray logs are linked with geological information from cores and the spatial analysis of log data assists with predicting the lithology at unsampled locations.     

用远震接收函数研究渤海盆地的沉积覆盖

本研究收集了华北地震台网近6年的远震数据,提取有效接收函数12000余条,对同一台站的接收函数进行了叠加;用固定值域模拟搜索技术,获得了台站下方覆盖层(沉积覆盖)的厚度和Vp/Vs比,有效数据点27个,合理地覆盖了研究区。计算结果显示,上覆地层厚度受到北东向构造影响,由北西至东南渐次增厚;Vp/Vs与上覆地层厚度和P波延时成正比,上覆地层厚度大致与Vp/Vs比成正比;上覆地层厚度与S波速度成反比,与地层的松散度成正比。研究显示,上述结果为场地条件和工程领域的研究提供了约束参数;同时,我们认为,本研究为油气勘探和油气储量计算提供了新的技术和思路。     

Point Cumulative Semivariogram for Identification of Heterogeneities in Regional Seismicity of Turkey

Geological events are neither isotropic nor homogeneous in their occurrences. These two properties present difficulties for spatial modeling of regionalized variables. This paper presents a point cumulative semivariogram (PCSV) technique for quantifying the heterogeneity characteristics of the phenomenon concerned. The basis of the methodology is to obtain experimental PCSVs for each measurement point which led to estimation of radius of influence around each site. In addition, the experimental PCSVs provide basic information about the heterogeneity of the geological variable in the region, and furthermore many useful interpretations can be made concerning the regional variability of the variable. It provides the measure of cumulative similarity of a regional variable around any measurement site. Because PCSV is a means of measuring total similarity, maps at fixed similarity levels are provided in order to document the regional heterogeneity. Identification of heterogeneities depends on the comparison of fixed PCSV values at a multitude of irregularly scattered sites. The PCSV methodology has been applied to the regional seismic data of Turkey.     

Estimation of volcanic hazards based on Cox stochastic processes

Assessments of the probability and the consequences of future volcanic activity can be critical aspects when evaluating the safety of the population and of industrial plants. A new methodology has been developed for the probabilistic modelling of volcanic hazards based on regional volcanic data that facilitates the production of probabilistic hazard maps for various volcanic scenarios (lava flows, tephra). The stochastic model is based on Cox processes and allows account to be taken of the observed temporal and spatial correlation inherent in volcanic eruptions. The model is applied to the Quaternary field of the Osteifel region where the forecast number of future eruptions and the probabilities related to the different scenarios are estimated using a Monte Carlo approach. The obtained hazard maps of future volcanic events are part of a comprehensive hazard analysis and serve as a major input for the risk analysis that will determine the consequences of forecast volcanic activity at the site.     

Australian Geodynamics Cooperative Research Centre's integrated research program delivers a new minerals exploration strategy for industry

The Australian Geodynamics Cooperative Research Centre was an unincorporated joint venture between government organisations, universities and industry with financial support from the Commonwealth Government. Its Mission was to develop, in partnership with the minerals exploration industry, a geodynamic framework of the Australian continent, which would enhance industry's capacity to discover new world‐class deposits. The Centre has now closed after completing 7 years of integrated and innovative research. Prominent among the research outcomes are new geological, geophysical and geochronological data for key regions of Australia and new enabling technologies to collect better data or to better analyse existing data. In addition, it developed a systematic and objective methodology for synthesising data into possible exploration models that could be tested by computer analyses that simulate the geodynamic evolution of the proposed geology. If the computer simulation reproduced the same characteristics as are known to occur in a mineral deposit then the input data and exploration model are considered to be valid. They can then be used to predict whether other, as yet undiscovered deposits, occur within that area and their likely location, structure, ore grade and tonnage. This new exploration strategy can be used to reduce exploration risk and increase the rate of discovery of major new deposits.     

Geological similarity byQ analysis

Mineral resource assessment using areal, or unit regional, value approach estimates the variety of commodities likely to occur in a region by comparing its geology with that of regions already well developed and known to produce a variety of commodities. It is, therefore, essential to be able to discern regions which are similar in geology. The data used for this purpose are derived by point-counting geological maps of the regions to be evaluated; one aspect of this data is the presence-absence (i.e., 0–1 data)of 65 standardized rocktypes. It is then necessary to compare geological data from both the developed and undeveloped regions to determine which of the regions are geologically similar. The initial data consists of a matrix (A)of Cregions by Rrock types and all relations (λ)among Cand Rmay be expressed as λ ? C × R.We may then use Atkin's Qanalysis to determine the structure of these relations. Postmultiplying Aby its transpose and subtracting a suitably dimensioned unit matrix yields an output matrix K_C (R; λ)which expresses the relations among regions in terms of their rock types. This output matrix comprises qconnectivities among regions; its diagonal elements (denoted \(\hat q\) )are the number of rock types, minus one, in each region. The offdiagonal elements ( \(\check{q} \) )are the number of rock types (minus one)which are common to each pair. Similarities of regions in terms of their rock types are then found by using tables of equivalences in which the values of \(\hat q\) are the dimensions of simplicies representing each region; the rock types are the apicies of the simplicies and similarities are the shared edges and faces of the simplicies. The largest number of shared apicies equals \(\check{q} \) .Examples of the application of Qanalysis to a comparison of the geology of the 10 counties in New Hampshire and the 50 states of the U.S.A. and Puerto Rico illustrate the procedure. Qanalysis supplies an algebraic language and an equivalent geometry to express the relations among regions in terms of their rock types.     

The Water Framework Directive: Can more information be extracted from groundwater data? A case study of Seewinkel,Burgenland, eastern Austria

Water protection is one of the most important goals in environmental protection. The Clean Water Act in the USA and the Water Framework Directive (WFD) in Europe are the legal frameworks to facilitate the achievement of this goal. The question is raised of whether more information can be extracted from WFD-related groundwater data. To answer it, a methodology has been developed that is easy to use and could be implemented into official practice. A case study is presented in which the groundwater data of a sodic area in Austria (Seewinkel) is assessed. Eighteen parameters in groundwater sampled from 23 wells (1991–2011) were analyzed. With basic statistics, trend-, cluster-, Wilks’ λ and spatial sampling density analysis, local phosphorus and boron phenomena were described, along with the determining role of sulphate, groundwater flow, and the oxygen gradient in the area. As a final step, the spatial sampling density was determined. Regarding the current set of parameters, all the sampling sites are necessary and only in the case of certain parameters (Ca²⁺, Mg²⁺, K⁺, NO₃ ^?, pH) could one sampling site be abandoned. The methodology applied brings a new perspective to exploring groundwater data collected according to the requirements of the WFD.     

Multilayer-exposure maps as a basis for a regional vulnerability assessment for landslides: applied in Waidhofen/Ybbs,Austria

Assessments of natural hazards and risks are beneficial for sustainable planning and natural hazard risk management. On a regional scale, quantitative hazard and risk assessments are data intensive and methods developed are difficult to transfer to other regions and to analyse different periods in a given region. Such transfers could be beneficial regarding factors of global change influencing the patterns of natural hazard and risk. The aim of this study was to show the landslide exposure of different elements at risk in one map, e.g. residential buildings and critical infrastructure, as a solid basis for an in-depth analysis of vulnerability and consequent risk. This enables to overcome the data intensive assessments on a regional scale and highlights the potential hotspots for risk analysis. The study area is located in the alpine foreland in Lower Austria and comprises around 112 km². The results show the different levels of exposure, as well as how many layers of elements at risk are affected. Several exposure hotspots can be delineated throughout the study area. This allows a decision on in-depth analysis of hotspots not only by indicated locations but also by a rank resulting from the different layers of incorporated elements at risk.     

Assessment of the hurricane-induced power outages from a demographic,socioeconomic, and transportation perspective

Natural disasters have devastating effects on the infrastructure and disrupt every aspect of daily life in the regions they hit. To alleviate problems caused by these disasters, first an impact assessment is needed. As such, this paper focuses on a two-step methodology to identify the impact of Hurricane Hermine on the City of Tallahassee, the capital of Florida. The regional and socioeconomic variations in the Hermine’s impact were studied via spatially and statistically analyzing power outages. First step includes a spatial analysis to illustrate the magnitude of customers affected by power outages together with a clustering analysis. This step aims to determine whether the customers affected from outages are clustered or not. Second step involves a Bayesian spatial autoregressive model in order to identify the effects of several demographic-, socioeconomic-, and transportation-related variables on the magnitude of customers affected by power outages. Results showed that customers affected by outages are spatially clustered at particular regions rather than being dispersed. This indicates the need to pinpoint such vulnerable locations and develop strategies to reduce hurricane-induced disruptions. Furthermore, the increase in the magnitude of affected customers was found to be associated with several variables such as the power network and total generated trips as well as the demographic factors. The information gained from the findings of this study can assist emergency officials in identifying critical and/or less resilient regions, and determining those demographic and socioeconomic groups which were relatively more affected by the consequences of hurricanes than others.     

Regional rating curve models of suspended sediment transport for Turkey

Estimations of annual suspended sediment loads are required for various types of water resources studies. Often estimation of the sediment load is needed for ungauged watersheds. Regionalization methods provide a practical solution to solve such problems. The purpose of this study is to classify suspended sediment yields in watersheds into homogeneous regions in order to identify their regional sediment rating curves. This study has been carried out for suspended sediment stations on 26 main basins of Turkey. Long term-scale suspended sediment rating curves of 115 gauging stations in Turkey were classified using cluster analysis on the basis of hydrological homogeneity. An agglomerative hierarchical clustering algorithm is used so that stations from different geographical locations are considered in the same cluster independently of their geographical location. 115 gauging stations were clustered into 4 different homogenous regions and the regional suspended sediment rating curve was developed for each region. The performance efficiencies of the developed regional rating curves were evaluated for 8 test stations and compared to the performances of rating curves in test sites. A regionalization model is developed for estimating suspended sediment rating curves for ungauged sites in Turkey. The developed regional rating curve models result in very close performances to those of their corresponding site rating curves.     

Seismic hazard analysis for the Philippines

Two sample probabilistic hazard maps for the Philippine Region are compiled. In these are shown various levels of expected horizontal ground acceleration for some given annual probability of exceedence, namely, for 0.1% a.p.e. and for 0.01% a.p.e. Such hazard maps are needed by structural engineers for compiling seismic zoning maps. The hazard maps are derived from source-zone or seismogenic maps, which, in turn, are compiled from seismographic, geologic, and geotectonic data. Much weight is put on geotectonic data rather than on seismographic data. The former lends support to extrapolating to much longer periods of exposure time or longer periods of recurrence.