The Importance of Prehistoric Data and Variability of Hazard Regimes in Natural Hazard Risk Assessment – Examples from Australia

Natural hazards are normally viewed as events that occur randomly overtime. This precept usually forms the basis for the development of the hazardmagnitude-recurrence interval relationship used in risk assessments. However,hazard variability does not always conform to this relationship especially overlonger time intervals. Non-stationarity can be common with some hazards andthose periods where the variability and/or mean (magnitude/frequency) remainconstant are referred to here as hazard regimes. Shifts from one regime to anotheroccur at a variety of time scales from centuries to millennia. Regime shifts areoften only discernible by examining longer-term records which usually includeprehistoric data. Risk assessments frequently ignore these regime shifts andestimates of the risks associated with tropical cyclones, tsunami, terrestrialfloods and landslides in Australia have been both under-estimated and exaggeratedwhen such assessments have been based solely upon short historical records.Examples of these regime shifts and their significance for natural hazard riskassessment are presented here.     

Documentary proxies and interdisciplinary research on historic geomorphologic hazards: a discussion of the current state from a central European perspective

During the last two decades, documentary data (written and iconographic sources) have been increasingly employed in geomorphologic research aiming at reconstruction of territorial distribution, temporal occurrence and social and economic impacts of various geomorphologic hazards. The goal of this paper is to broaden the previous discussion (Glade et al. The use of historical data in natural hazard assessments. Kluwer, Dordrecht, 2001) of the methodological constraints on the use of documentary data for geomorphologic hazard research. Using the interdisciplinary approach of geomorphology, historiography and medial studies, we firstly summarise the major finding of papers that have employed various types of documentary data sources to study geomorphologic hazards in different regions. In the second section, we present case studies from the Czech Republic resulting from the ongoing research project that is devoted to the assessment of the potential of documentary data to reconstruct past occurrences of and mitigation strategies for geomorphologic hazards. Finally, we discuss three main methodological issues emerging from our research: (a) problems emerging from the positivist approach to documentary data sources and the necessity for critical analyses of documentary data sources based on modern historiographic approaches, (b) constraints arising from the combination of documentary data from different spatiotemporal scales and (c) lacks in the use of documentary data to study local-based adaptation strategies to cope with geomorphologic hazards.     

A framework for the probabilistic analysis of meteotsunamis

A probabilistic technique is developed to assess the hazard from meteotsunamis. Meteotsunamis are unusual sea-level events, generated when the speed of an atmospheric pressure or wind disturbance is comparable to the phase speed of long waves in the ocean. A general aggregation equation is proposed for the probabilistic analysis, based on previous frameworks established for both tsunamis and storm surges, incorporating different sources and source parameters of meteotsunamis. Parameterization of atmospheric disturbances and numerical modeling is performed for the computation of maximum meteotsunami wave amplitudes near the coast. A historical record of pressure disturbances is used to establish a continuous analytic distribution of each parameter as well as the overall Poisson rate of occurrence. A demonstration study is presented for the northeast U.S. in which only isolated atmospheric pressure disturbances from squall lines and derechos are considered. For this study, Automated Surface Observing System stations are used to determine the historical parameters of squall lines from 2000 to 2013. The probabilistic equations are implemented using a Monte Carlo scheme, where a synthetic catalog of squall lines is compiled by sampling the parameter distributions. For each entry in the catalog, ocean wave amplitudes are computed using a numerical hydrodynamic model. Aggregation of the results from the Monte Carlo scheme results in a meteotsunami hazard curve that plots the annualized rate of exceedance with respect to maximum event amplitude for a particular location along the coast. Results from using multiple synthetic catalogs, resampled from the parent parameter distributions, yield mean and quantile hazard curves. Further refinements and improvements for probabilistic analysis of meteotsunamis are discussed.     

Probabilistic Analysis of Tsunami Hazards*

Determining the likelihood of a disaster is a key component of any comprehensive hazard assessment. This is particularly true for tsunamis, even though most tsunami hazard assessments have in the past relied on scenario or deterministic type models. We discuss probabilistic tsunami hazard analysis (PTHA) from the standpoint of integrating computational methods with empirical analysis of past tsunami runup. PTHA is derived from probabilistic seismic hazard analysis (PSHA), with the main difference being that PTHA must account for far-field sources. The computational methods rely on numerical tsunami propagation models rather than empirical attenuation relationships as in PSHA in determining ground motions. Because a number of source parameters affect local tsunami runup height, PTHA can become complex and computationally intensive. Empirical analysis can function in one of two ways, depending on the length and completeness of the tsunami catalog. For site-specific studies where there is sufficient tsunami runup data available, hazard curves can primarily be derived from empirical analysis, with computational methods used to highlight deficiencies in the tsunami catalog. For region-wide analyses and sites where there are little to no tsunami data, a computationally based method such as Monte Carlo simulation is the primary method to establish tsunami hazards. Two case studies that describe how computational and empirical methods can be integrated are presented for Acapulco, Mexico (site-specific) and the U.S. Pacific Northwest coastline (region-wide analysis). * The U.S. Government’s right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged.     

Natural hazards in Central Java Province,Indonesia: an overview

Central Java Province, Indonesia, suffers from natural hazard processes such as land subsidence, coastal inundation, flood, volcanic eruption, earthquake, tsunami, and landslide. The occurrence of each kind of natural hazard is varied according to the intensity of geo-processes. It is necessary to learn from the historical record of coastal inundation, flood, volcanic eruption, earthquake, tsunami, and landslide hazards in Central Java Province to address issues of comprehensive hazard mitigation and management action. Through the understanding about the nature and spatial distribution of natural hazards, treatments can be done to reduce the risks. This paper presents the natural hazard phenomena in Central Java Province and provides critical information for hazard mitigation and reduction.     

Scale-invariance of soil moisture variability and its implications for the frequency-size distribution of landslides

Power spectral analyses of soil moisture variability are carried out from scales of 100 m to 10 km on the microwave remotely-sensed data from the Washita experimental watershed during 1992. The power spectrum S(k) has an approximate power-law dependence on wave number k with the exponent −1.8. This behavior is consistent with the behavior of a stochastic differential equation for soil moisture at a point, and it has important consequences for the frequency-size distribution of landslides. We present the cumulative frequency-size distributions of landslides induced by precipitation in Japan and Bolivia as well as landslides triggered by the 1994 Northridge, California earthquake. Large landslides in these regions, despite being triggered by different mechanisms, have a cumulative frequency-size distribution with a power-law dependence on area with an exponent ranging from −1.5 to −2. We use a soil moisture field with the above statistics in conjunction with a slope stability analysis to model the frequency-size distribution of landslides. In our model, landslides occur when a threshold shear stress dependent on cohesion, pore pressure, internal friction and slope angle is exceeded. This implies a threshold dependence on soil moisture and slope angle since cohesion, pore pressure and internal friction are primarily dependent on soil moisture. The cumulative frequency-size distribution of domains of shear stress greater than a threshold value with soil moisture modeled as above and topography modeled as a Brownian walk is a power-law function of area with an exponent of −1.8 for large landslide areas. This distribution is similar to that observed for landslides. The effect of strong ground motion from earthquakes lowers the shear stress necessary for failure, but does not change the frequency-size distribution of failed areas. This is consistent with observations. This work suggests that remote sensing of soil moisture can be of great importance in monitoring landslide hazards and proposes a specific quantitative model for landslide hazard assessment.     

Bayesian techniques for seismic hazard assessment using imprecise data

Some Bayesian methods of dealing with inaccurate or vague data are introduced in the framework of seismic hazard assessment. Inaccurate data affected by heterogeneous errors are modeled by a probability distribution instead of the usual value plus a random error representation; these data are generically called imprecise. The earthquake size and the number of events in a certain time are modeled as imprecise data. Imprecise data allow us to introduce into the estimation procedures the uncertainty inherent in the inaccuracy and heterogeneity of the measuring systems from which the data were obtained. The problem of estimating the parameter of a Poisson process is shown to be feasible by the use of Bayesian techniques and imprecise data. This background technique can be applied to a general problem of seismic hazard estimation. Initially, data in a regional earthquake catalog are assumed imprecise both in size and location (i.e errors in the epicenter or spreading over a given source). By means of scattered attenuation laws, the regional catalog can be translated into a so-called site catalog of imprecise events. The site catalog is then used to estimate return periods or occurrence probabilities, taking into account all sources of uncertainty. Special attention is paid to priors in the Bayesian estimation. They can be used to introduce additional information as well as scattered frequency-size laws for local events. A simple example is presented to illustrate the capabilities of this methodology.     

Bayesian estimation of seismic hazard for two sites in Switzerland

Seismic hazard analysis is based on data and models, which both are imprecise and uncertain. Especially the interpretation of historical information into earthquake parameters, e.g. earthquake size and location, yields ambiguous and imprecise data. Models based on probability distributions have been developed in order to quantify and represent these uncertainties. Nevertheless, the majority of the procedures applied in seismic hazard assessment do not take into account these uncertainties, nor do they show the variance of the results. Therefore, a procedure based on Bayesian statistics was developed to estimate return periods for different ground motion intensities (MSK scale).Bayesian techniques provide a mathematical model to estimate the distribution of random variables in presence of uncertainties. The developed method estimates the probability distribution of the number of occurrences in a Poisson process described by the parameter . The input data are the historical occurrences of intensities for a particular site, represented by a discrete probability distribution for each earthquake. The calculation of these historical occurrences requires a careful preparation of all input parameters, i.e. a modelling of their uncertainties. The obtained results show that the variance of the recurrence rate is smaller in regions with higher seismic activity than in less active regions. It can also be demonstrated that long return periods cannot be estimated with confidence, because the time period of observation is too short. This indicates that the long return periods obtained by seismic source methods only reflects the delineated seismic sources and the chosen earthquake size distribution law.     

Database of geo-hydrological disasters for civil protection purposes

This paper presents the results of a research concerning available historical information about natural hazards (landslides and floods) and consequent disasters in the Consortium of Mountain Municipalities of Valtellina di Tirano, in Northern Italy. A geo-referenced database, collecting information till 2008, was designed with the aim of using available data of historical events for hazard estimation and the definition of risk scenarios as a basis for Civil Protection planning and emergency management purposes. This database and related statistics about landslides and floods are shown, and a brief overview of historical disasters caused by natural hazards in the study area is presented. A case study showing how useful the database can be to define a simple but realistic scenario is described. Information availability and reliability is discussed and possible uncertainties are underlined. The study shows that collecting and making use of historical information for the definition of hypothetical scenarios and the evaluation of territorial threats is a fundamental source of knowledge to deal with future emergencies.     

Spatial-temporal variability of seismic hazard in peninsular India

This paper examines the variability of seismic activity observed in the case of different geological zones of peninsular India (10°N–26°N; 68°E–90°E) based on earthquake catalog between the period 1842 and 2002 and estimates earthquake hazard for the region. With compilation of earthquake catalog in terms of moment magnitude and establishing broad completeness criteria, we derive the seismicity parameters for each geologic zone of peninsular India using maximum likelihood procedure. The estimated parameters provide the basis for understanding the historical seismicity associated with different geological zones of peninsular India and also provide important inputs for future seismic hazard estimation studies in the region. Based on present investigation, it is clear that earthquake recurrence activity in various geologic zones of peninsular India is distinct and varies considerably between its cratonic and rifting zones. The study identifies the likely hazards due to the possibility of moderate to large earthquakes in peninsular India and also presents the influence of spatial rate variation in the seismic activity of this region. This paper presents the influence of source zone characterization and recurrence rate variation pattern on the maximum earthquake magnitude estimation. The results presented in the paper provide a useful basis for probabilistic seismic hazard studies and microzonation studies in peninsular India.     

Community-based disaster risk and vulnerability models of a coastal municipality in Bangladesh

Bangladesh is one of the most natural hazard-prone countries in the world with the greatest negative consequences being associated with cyclones, devastating floods, riverbank erosion, drought, earthquake, and arsenic contamination, etc. One way or other, these natural hazards engulfed every corner of Bangladesh. The main aim of this research paper is to carry out a multi-hazards risk and vulnerability assessment for the coastal Matlab municipality in Bangladesh and to recommend possible mitigation measures. To this aim, hazards are prioritized by integrating SMUG and FEMA models, and a participation process is implemented so as to involve community both in the risk assessment and in the identification of adaptation strategies. The Matlab municipality is highly vulnerable to several natural hazards such as cyclones, floods, and riverbank erosion. The SMUG is a qualitative assessment, while FEMA is a quantitative assessment of hazards. The FEMA model suggests a threshold of highest 100 points. All hazards that total more than 100 points may receive higher priority in emergency preparedness and mitigation measures. The FEMA model, because it judges each hazard individually in a numerical manner, may provide more satisfying results than the SMUG system. The spatial distributions of hazard, risk, social institutions, land use, and other resources indicate that the flood disaster is the top environmental problem of Matlab municipality. Hazard-specific probable mitigation measures are recommended with the discussion of local community. Finally, this study tries to provide insights into the way field research combining scientific assessments tools such as SMUG and FEMA could feed evidence-based decision-making processes for mitigation in vulnerable communities.     

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.     

A temporal model for landslide risk based on historical precipitation

Of the recognized nonsteady-state factors that influence slope stability, probably most critical in many field situations is the character of precipitation and infiltration activity. A groundwater response model used in conjunction with precipitation records can provide a historical catalog of estimated maximum groundwater levels in a particular study area. An extreme-value statistical analysis of this catalog is linked with geotechnical slope stability analyses to provide a landslide hazard model for estimating the probability of slope failure within a given time. This modeling approach can provide meaningful input to risk assessments for landslide mitigation programs and to decision analyses and cost-benefit studies important for land-use planning and resource management.This paper was presented at Emerging Concepts, MGUS 87 Conference, Redwood City, California, 13–15 April 1987.     

基于GIS的北京市延庆县地质灾害易发性区域划分

随着灾害科学研究的深入，区域地质灾害已成为其重要的研究领域。文章利用遥感技术及GPS工具获取地质灾害的特征信息，在对地质灾害的成因背景分析基础上，运用GIS空间分析功能和地质灾害危险性评价、评估理论构建了地质灾害发育度模型。以北京市延庆县为实验区，采用ArcEngine＆．NET进行易发性分区程序的编写，计算研究区域内单元网格的发育度值。为了克服调查数据的局限性和人为因素，在计算发育度时引入修正系数，从延庆县DEM数据中提取单元格网内的地形坡度值，根据坡度值区间确定修正系数。将发育度计算结果按照一定规律、原则聚类。进行地质灾害易发性区域划分，取得了与实际情况较为一致的结果。基于“3S”技术及灾害地质条件，采用地质灾害发育度模型，可以较好地用于区域地质灾害易发性区域的划分，并能为防灾、减灾提供重要信息。     

香丽高速公路边坡地质灾害发育特征与易发性区划

针对香丽高速公路边坡地质灾害,在详细的道路工程勘察设计文件的基础上,结合现场踏勘调查,系统地研究了其边坡地质灾害的主要类型、发育特征和分布规律;提出高速公路等线性工程边坡灾害的基本地质条件、自然诱发因素、人类工程活动和灾害历史记录等完整信息评价指标。采用层次分析法、专家评分法与因素累积法相结合的研究方法,建立了线性工程边坡地质灾害易发性评价模型,并基于GIS平台完成了香丽高速公路边坡地质灾害的易发性区划。为指导香丽高速公路地质灾害的危险性评价及科学防治提供了重要依据,对类似山区道路等线性工程边坡地质灾害危险性评价研究与实践具有一定的示范作用和参考价值。     

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.     

全球主要火山灾害及其分布特征

本文研究了火山灾害各种致灾因子的物理过程和灾害特点,根据文献中记载的全球火山灾害,在进行火山灾害分区研究的基础上,研究了全球火山灾害分布特征.全球主要的火山灾害分布在8个主要区域.有记载的火山灾害在热带占73%,远高于火山喷发分布于热带区的比例.全球两个最强烈的火山灾害分布区都是围绕着位于板块结合部表现为复杂构造结的班达海和加勒比海,而且每一个灾害区都有3条分支.热带区第3个灾害区为中非区,地幔上隆是这里主要的动力学背景.本文还研究了1700年以来火山灾害时间分布特征,以及1993年以来各种火山灾害发生频次.     

Three-parameter generalized exponential distribution in earthquake recurrence interval estimation

The purpose of this article is to study the three-parameter (scale, shape, and location) generalized exponential (GE) distribution and examine its suitability in probabilistic earthquake recurrence modeling. The GE distribution shares many physical properties of the gamma and Weibull distributions. This distribution, unlike the exponential distribution, overcomes the burden of memoryless property. For shape parameter  β> 1, the GE distribution offers increasing hazard function, which is in accordance with the elastic rebound theory of earthquake generation. In the present study, we consider a real, complete, and homogeneous earthquake catalog of 20 events with magnitude above 7.0 (Yadav et al. in Pure Appl Geophys 167:1331–1342, 2010) from northeast India and its adjacent regions (20°–32°N and 87°–100°E) to analyze earthquake inter-occurrence time from the GE distribution. We apply the modified maximum likelihood estimation method to estimate model parameters. We then perform a number of goodness-of-fit tests to evaluate the suitability of the GE model to other competitive models, such as the gamma and Weibull models. It is observed that for the present data set, the GE distribution has a better and more economical representation than the gamma and Weibull distributions. Finally, a few conditional probability curves (hazard curves) are presented to demonstrate the significance of the GE distribution in probabilistic assessment of earthquake hazards.     

Seismicity of the northern Barents Sea in area of the Franz Victoria and Orla troughs

The results of seismic monitoring in the area of the Franz Victoria and Orla trenches in 2011–2013 are discussed in the paper. A seismic catalog of recorded earthquakes with calculated source parameters is given, and the spatial distribution of these earthquakes is characterized. The results of monitoring are compared with the data on historical earthquakes. A cumulative graph of recurrence has been constructed.