Probabilistic disaggregation of a spatial portfolio of exposure for natural hazard risk assessment

In natural hazard risk assessment situations are encountered where information on the portfolio of exposure is only available in a spatially aggregated form, hindering a precise risk assessment. Recourse might be found in the spatial disaggregation of the portfolio of exposure to the resolution of the hazard model. Given the uncertainty inherent to any disaggregation, it is argued that the disaggregation should be performed probabilistically. In this paper, a methodology for probabilistic disaggregation of spatially aggregated values is presented. The methodology is exemplified with the disaggregation of a portfolio of buildings in two communes in Switzerland and the results are compared to sample observations. The relevance of probabilistic disaggregation uncertainty in natural hazard risk assessment is illustrated with the example of a simple flood risk assessment.     

Factors influencing determination of shale classification indices and their correlation to mechanical properties

The influence of sample preparation procedure on the measured classification indices such as clay-size fraction, liquid limit, and plastic limit of shales was investigated. Shale samples covering a wide range of composition and plasticity were tested using standard and modified preparation procedures to yield quantitative data required for this investigation. The study specifies the range of shale plasticity in which the measured values of clay-size fraction and liquid limit are sensitive to hydrometer specimen size and rehydration time, respectively. The study also revealed that the degree of shale particle disaggregation has an important influence on the measured clay-size fraction and liquid limit. This influence is maximized for shales with intermediate plasticity and can be interpreted in terms of particle size and shape. Correlations were established between classification indices derived from standard and modified sample preparation procedures. It is recommended to use these correlations to adjust shale classification indices derived from standard sample preparation procedures usually utilized by commercial laboratories. Such correlations help in creating a universally followed procedure for better estimation of shale engineering properties and reliable interpretation of case histories involving shale formations.     

Missing data estimation in tyrannosaurid dinosaurs: Can diameter take the place of circumference?

Missing data, due to taphonomic deformation, inaccessibility of specimens, or human error in collecting, cataloguing and measuring features, is a formidable problem in current palaeontological studies. Missing values within a data set can undermine confidence in analyses, skew results in promoting analyses of small portions of a population, not necessarily representative of the entire data set, and drastically decrease sample sizes. Missing data estimation methods, however, may reduce the effects of these missing values and potentially boost sample sizes for palaeontological studies. Here, six missing data estimation models for the prediction of femoral circumferences in tyrannosaurids were statistically tested and their predictive success measured against true circumferences, and other models. The statistical analyses suggest that estimation models based on anteroposterior diameter values of tyrannosaurid femora were poor predictors of circumference, whereas those based on mediolateral diameters were much more successful. Three out of the six models, were presented as viable alternatives to missing measured circumferences and may be used to boost tyrannosaurid samples with significant levels of missing data.     

在中国建立注册地质师制度的探讨

在我国建立与风险投资相关的制度和法规，吸引民间多元资本与商业性地质勘查项目的投资，首先要对项目进行风险分析，评估，做出权威认定。为此，要实行地质学家职业资格制度，对地质师进行注册管理。接受注册管理的地质师在执业中以中立的，客观的，公正的态度独立地行使技术权利，为投资人和筹资人服务。章提出了建立注册地质师制度的必要性，可行性和可操作性。     

Climate change risks for severe storms in developing countries in the context of poverty and inequality in Cambodia

Least developed countries are generally regarded as particularly sensitive to climate change due to among other vulnerable locations and low adaptation capabilities. In the present study, we address climate change hazards in least developed countries by presenting a methodological framework, which is suitable for the estimation damage costs as a function of risk aversion, equality, income distribution and climate scenario using state-of-the-art climate model projections. As a case study, the methodology is applied to study severe storms in Cambodia based on two future climate scenarios and data on historical damages from storm events, which are used as a proxy in performing a sensitivity analysis on all input parameters. For the assumptions and parameter ranges used here, the study shows a high sensitivity to the income distribution (reflected by discount rates) and risk aversion and smaller effects from equality measures and extreme wind climate scenario. We emphasize that the assumptions on risk aversion reflecting consumption smoothing possibilities of low-income households clearly depicts that climate risks can be particularly high as a consequence of poverty and therefore recommend that context-specific vulnerabilities and equity concerns in climate risk studies should be included when making assessments for least developed countries.     

A comparison of selected global disaster risk assessment results

We compare country risk rankings derived from two recently published global disaster risk analyses. One set of country rankings is based on the Disaster Risk Index (DRI) developed by the United Nations Environment Program (UNEP) Division of Early Warning and Assessment Global Resource Information Database project under a contract to the United Nations Development Program (UNDP). The other is based on an index of disaster mortality risk developed by the Global Natural Disaster Risk Hotspots project implemented by Columbia University, the World Bank and associated partners. We convert data from these sources into two comparable indexes of disaster mortality risk and rank countries according to the resulting values for a set of natural hazards common to both studies. The country rankings are moderately correlated, ranging from .41 to .56 for individual hazards to .31 for multi-hazard mortality risks. We identify the top 25 countries according to the mortality risk values we recomputed from each study’s results to show the degree to which countries are highly ranked in common. The numbers of countries common to both lists for individual hazards range from 7 to 16 out of 25. The correspondence among the top 25 ranked countries is lowest for earthquakes and floods. Only 6 out of 25 countries are common to both lists in the multi-hazard case. We suggest that while the convergence in the results for some hazards is encouraging, more work is needed to improve data and methods, particularly with respect to assessing the role of vulnerability in the creation of risk and the calculation of multi-hazard risks. The views expressed are the authors’ and do not necessarily reflect those of SM2 Consulting Multi-Hazards and Risk Holistic Solutions or the United Nations Development Program.     

Global landslide and avalanche hotspots

Allocating resources for natural hazard risk management has high priority in development banks and international agencies working in developing countries. Global hazard and risk maps for landslides and avalanches were developed to identify the most exposed countries. Based on the global datasets of climate, lithology, earthquake activity, and topography, areas with the highest hazard, or “hotspots”, were identified. The applied model was based on classed values of all input data. The model output is a landslide and avalanche hazard index, which is globally scaled into nine levels. The model results were calibrated and validated in selected areas where good data on slide events exist. The results from the landslide and avalanche hazard model together with global population data were then used as input for the risk assessment. Regions with the highest risk can be found in Colombia, Tajikistan, India, and Nepal where the estimated number of people killed per year per 100 km² was found to be greater than one. The model made a reasonable prediction of the landslide hazard in 240 of 249 countries. More and better input data could improve the model further. Future work will focus on selected areas to study the applicability of the model on national and regional scales.     

Estimation of components of variance for partially cross-classified data in a factorial arrangement of treatments

A procedure is presented for obtaining estimates of components of variance for the main effects and interaction in a two-way factorial arrangement of treatments with only partially cross-classified data (sometimes referred to as unbalanced data in a two-way crossed classification model with interaction). The procedure entails the use of two hierarchical analyses of variance in which each main effect is first treated as classes and then as subclasses. The estimation of the variance component for each main effect results from the solution of two simultaneous equations with values used obtained directly from the hierarchical analyses. The interaction component of variance can be obtained from the variance components for main effects. An example is presented for the purpose of illustrating the procedure. Interpretation of the interaction variance component estimated by the method is limited due to the absence of some of the subclasses.     

Long-term spatio-temporal social vulnerability variation considering health-related climate change parameters particularly affecting elderly

For assessing the social dimension of vulnerability, population exposure mapping is usually considered the essential starting point. Integration of social structure then further differentiates situation-specific vulnerability patterns on a local scale. Census data available in heterogeneous spatial reference units are still considered the standard information input for assessing potentially affected people, for example, in case of an emergency. There is a strong demand for population data in homogeneous spatial units that are independent from administrative areas. Raster representations meet this demand but are not yet available for all European countries. In this paper, we present an approach of spatial disaggregation of population data for a European transect referring to current population statistics and anticipated future prospects. Recently published data providing the degree of soil sealing are applied as basic proxy for population density in the spatial disaggregation model. In order to assess future patterns of climate change-related vulnerability, results of a European regional climate model are considered for projecting the situation in the 2030s. “Heat wave frequency” is accounted for as climate variable featuring conditions regarded as especially strenuous for elderly or physically weak persons. Integrated analysis of the population and climate prospects enables identification of hot spots in the European transect examined, that is, regions of particularly demanding projected climatic patterns as well as high population density and case-specific vulnerable structure (elderly people). Integrated and consistent spatial analyses on European scale are essential for decision support in the context of climate change impact mitigation as well as for risk communication and future safety and security considerations.     

Practical Research on Fuzzy Risk of Water Resources in Jinhua City,China

A fuzzy expected value of the possibility-probability distribution is a set with _boxclose(x)\underline{E}_{\alpha}(x) and [`(E)]<sub>a</sub>(x)\overline{E}_{\alpha}(x) as its boundaries. The fuzzy expected values E<sub>a</sub>(x)\underline{E}_{\alpha}(x) and [`(E)]_a(x)\overline{E}_{\alpha}(x) of a possibility-probability distribution represent the fuzzy risk values being calculated. Using these values under a given α level, three risk values can be calculated: a conservative risk value, a venture risk value, and a maximum probability risk value. Calculation of the fuzzy expected value of Jinhua City’s water resource risk has been performed based on the interior-exterior set model. This model is first used to evaluate the risk of water resources in Jinhua City: it not only solves an imprecise probability estimation, which results from small samples and unclear risk relationship, but it also explores the implicit risk information of the raw data as much as possible. Both of these achievements can make analyses more objective and comprehensive, which makes it easy to regulate options for policy-makers. Hence, the fuzzy risk analysis provides a new way to assess water resources.     

Method of predicting tremors on the basis of seismicemission registered in exploitation workings

A method of tremor risk estimation on the basis of seismic emission registered in mining exploitation zones is presented in this paper. A considerable part of the emission registered in these conditions, is generated by mechanical devices used in the mine (miner transporters etc.). Therefore, it is not possible to evaluate the risk of mining rock-bursts properly on the basis of interpretation of emission using known theories and models describing rock mass fracturing. In a new approach presented in this paper, the tremor risk is determined on the basis of time variation of a parameter describing the attenuation of seismic vibrations of the rock medium. The attenuation is assessed from the analysis of seismic emission registered in the frequency range from 30 Hz to 1000 Hz. Information about this parameter is encapsulated in the seismic emission regardless of the means of its generation. The method of estimating the temporal variations of attenuation is based on the analysis of signal envelopes of the microseismic emission. Attenuation trends can be interpreted in a straightforward way. As the stress values keep increasing, the following processes take place in the rock mass: compaction (hardening), dilatancy (softening), and then possibly tremors. At the compaction stage attenuation values are lower, while they increase at the dilatancy stage. This mechanism has been proven in practice. Our results can be used for monitoring tremor risk.     

Some guidelines for economic evaluation of geochemical engineering projects

Most geochemical engineering projects aim at commercial application. The proper economical analysis during the initial stages of the engineering process are of the utmost importance for the successful realisation of such projects. Many of the costs are committed at this stage. Important issues are: the scale of the project, the product quality and the choice of raw materials. For chemical plants, the Zevnik/Buchanan method is often used to make a rough estimation of the economic viability in an early stage. After the preliminary design of a geochemical process or other application has been completed, a more accurate estimation can be made by means of an economic balance. Guidelines for various costs are given in this article. Generally two criteria are used by companies to make a decision about further commercial realisation. One is the return on investment (R.O.I.), the annual profit divided by the total investment. The other is the pay-out time, the inverse of the R.O.I., the time needed to earn back the invested sum. This article provides geochemical engineers with some basic tools, that can be used to make an estimation of the economic potential of new geochemical engineering methods.     

Physically based dynamic run-out modelling for quantitative debris flow risk assessment: a case study in Tresenda,northern Italy

Quantitative landslide risk assessment requires information about the temporal, spatial and intensity probability of hazardous processes both regarding their initiation as well as their run-out. This is followed by an estimation of the physical consequences inflicted by the hazard, preferentially quantified in monetary values. For that purpose, deterministic hazard modelling has to be coupled with information about the value of the elements at risk and their vulnerability. Dynamic run-out models for debris flows are able to determine physical outputs (extension, depths, velocities, impact pressures) and to determine the zones where the elements at risk can suffer an impact. These results can then be applied for vulnerability and risk calculations. Debris flow risk has been assessed in the area of Tresenda in the Valtellina Valley (Lombardy Region, northern Italy). Three quantitative hazard scenarios for different return periods were prepared using available rainfall and geotechnical data. The numerical model FLO-2D was applied for the simulation of the debris flow propagation. The modelled hazard scenarios were consequently overlaid with the elements at risk, represented as building footprints. The expected physical damage to the buildings was estimated using vulnerability functions based on flow depth and impact pressure. A qualitative correlation between physical vulnerability and human losses was also proposed. To assess the uncertainties inherent in the analysis, six risk curves were obtained based on the maximum, average and minimum values and direct economic losses to the buildings were estimated, in the range of 0.25–7.7 million €, depending on the hazard scenario and vulnerability curve used.     

Maize yield forecasting for Zimbabwe farming sectors using satellite rainfall estimates

Southern Africa rainfall station network is suffering from an unfortunate serious decline while climate-related food insecurity is worsening. In the current work, we demonstrate the possibility of exploiting the complementary roles that remote sensing, modeling, and geospatial data analysis can play in forecasting maize yield using data for the growing seasons from 1996/1997 to 2003/2004. Satellite-derived point-specific rainfall estimates were input into a crop water balance model to calculate the Water Requirement Satisfaction Index (WRSI). When these WRSI values were regressed with historical yield data, the results showed that relatively high skill yield forecasts can be made even when the crops are at their early stages of growth and in areas with sparse or without any ground rainfall measurements. Inferences about the yield at national level and small-scale commercial farming sector (SSCF) sector can be made at confidence levels above 99% from the second dekad of February. However, the most unstable models are those for the communal farming sectors whose inferences for yield forecast can only be made above the 95% confidence level from the end of February, after having recovered from a state of complete breakdown two dekads earlier. The large-scale commercial farming (LSCF) sector has generally the weakest fitting, but it is usable from the first dekad of February to the end of the rainy season. Validation of the national yield models using independent data set shows that an early estimation of maize yield is quite feasible by the use of the WRSI.     

Interpreting sustainable yield of an aquifer using a fuzzy framework

Reliable estimates for how much water can be safely withdrawn from aquifers without harming the environment is crucial for identifying new water supply sources and fostering sustainable growth. Methodologies to estimate groundwater availability that are rooted in science and yet accomplishable with minimal data are particularly useful for effectual aquifer management. Also, as groundwater management is increasingly becoming a participatory process, these methodologies must be transparent and easily understood by a wide range of audiences. In addition, proposed approaches must also reconcile imprecision and uncertainties arising from lack of data, differences in stakeholders’ perceptions and limitations associated with incomplete aquifer characterization. In this study, the fundamental concept of water balance is coupled with fuzzy regression to develop a scheme for assessing regional-scale groundwater availability. Using the mass-balance approach, anthropogenic water demands (municipal, industrial and agricultural) and ecological demands (baseflows to rivers) can be incorporated into the availability estimation process. The use of fuzzy regression enables the specification of decision makers’ preferences to the adopted procedure and renders the parameter estimation to be more robust in the presence of extreme values. The methodology is illustrated by using it to estimate groundwater availability in the Gulf coast aquifer, underlying Refugio County, TX, USA.     

National-scale Assessment of Current and Future Flood Risk in England and Wales

In recent years, through the availability of remotely sensed data and other national datasets, it has become possible to conduct national-scale flood risk assessment in England and Wales. The results of this type of risk analysis can be used to inform policy-making and prioritisation of resources for flood management. It can form the starting point for more detailed strategic and local-scale flood risk assessments. The national-scale risk assessment methodology outlined in this paper makes use of information on the location, standard of protection and condition of flood defences in England and Wales, together with datasets of floodplain extent, topography, occupancy and asset values. The flood risk assessment was applied to all of England and Wales in 2002 at which point the expected annual damage from flooding was estimated to be approximately £1 billion. This figure is comparable with records of recent flood damage. The methodology has subsequently been applied to examine the effects of climate and socio-economic change 50 and 80 years in the future. The analysis predicts increasing flood risk unless current flood management policies, practices and investment levels are changed – up to 20-fold increase in real terms economic risk by the 2080s in the scenario with highest economic growth. The increase is attributable primarily to a combination of climate change (in particular sea level rise and increasing precipitation in parts of the UK) and increasing economic vulnerability.     

Geochemical dispersion of lead and zinc around a gossan in a carbonate environment at Heure (Belgium)

Samples of a brecciated sulphide vein (marcasite, sphalerite and scarce galena, in a calcite gangue), and its gossan, were collectet from bore holes. The gossan consists dominantly of goethite alternating with lepidocrocite and hydrohematite in a type of boxwork structure. Lead and manganese oxides are present. The gossan contains about 0.6% zinc and 0.2% lead. Sequential selective extractions and electron microprobe analyses were carried out. Soils with anomalous values in lead and zinc lying adjacent to the gossan contain fragments of ferruginous material which possess dimensions ranging from hundreds of microns to several centimeters. The textures, mineralogy and trace element contents of the fragments resemble those of limonites from the gossan. Mineralogical and selective analyses on the gossan and the soil materials show mineralogical and geochemical analogies. Lead and zinc anomalies can be explained partly by the occurrence of limonitic microfragments in the anomalous soils. The origin of these fragments is related to the disaggregation of the gossan. Already evoked by others authors for mainly non-carbonate environments, the results weight to the hypothesis that the dispersion of lead and zinc is partly mechanical.     

3D numerical modeling of landslide-generated tsunamis around a conical island

This paper presents numerical computations of tsunamis generated by landslides falling along the flank of a conical island. The model used is the fully three-dimensional commercial code FLOW-3D, based on the VOF technique for the treatment of the free surface. The model results are compared against available experimental data that allow validation of the model, evaluation of its accuracy, and estimation of the computational costs. The main conclusion of this research is that the model is applicable at reasonable costs for a few accurate simulations that may be used for preparing precomputed inundation maps of coasts prone to the risk of tsunamis inundation.     

工业废水和城市综合污水的环境风险管理

综述了国内外工业废水与城市综合废水的监控和环境风险管理进展。与发达国家比较,化学监测法是目前我国工业废水和城市综合污水监控的唯一手段,而且主要有赖于COD等极少参数,并不能有效监控复合有毒有机污染物的排放。采用生态毒性检测法,可弥补这一缺陷,满足环境风险管理要求。毒性鉴别评价鉴别出导致废水/污水生态毒性的关键有机毒物,是降低其环境风险的核心。还对生态毒性检测法应用于我国废水/污水排放的监控和环境风险管理前景做了评述。