Assessing risk to groundwater quality using an integrated risk framework

Source-water protection strategies are ideally focused where the greatest amount of harm reduction can occur. This process of risk management requires an assessment of the spatial variability of risk to water. The assessment methodology presented herein combines aquifer susceptibility with a hazard threat inventory and an analysis of the consequence of contamination to assess the risk to water quality. Aquifer susceptibility combines the intrinsic susceptibility of the physical system with anthropogenic features that locally increase susceptibility. Hazard threats are assessed based on the properties of the chemicals (toxicity and environmental fate), the potential magnitude (extent and quantity of release) and the likelihood of release. The consequence is herein considered as the financial costs of the loss of the resource, including the replacement of a water source and the economic loss where water intensive businesses are lost. A second scenario is included that analyses health issues related to pathogen sources as well as the financial impact to the community where people fall ill and present a financial burden to the public health care system. The risk assessment methodology is applied to the Township of Langley, in southwestern British Columbia, Canada. The results outline the most vulnerable areas as those where susceptible aquifers coexist with potential chemical and biological threats. The risk is greatest where these vulnerable areas coincide with those with the greatest potential for financial loss: within the capture zones of major municipal production wells and where private wells serve agricultural operations with high annual farm sales.     

滑坡易发性危险性风险评价例析

从易发性、危险性、风险的概念入手,依据国际上流行和通用的滑坡风险评价与管理理论,分析了易发性评价的内容,包括易发性评价到危险性评价需要增加的评价要素,以及从危险性评价到风险评价需要增加的评价要素,阐明了这三种评价之间的联系和区别。并通过延安宝塔区的滑坡易发性、危险性和风险的评价与区划具体说明三者的做法和结果。     

A statistical approach to landslide risk modelling at basin scale: from landslide susceptibility to quantitative risk assessment

A procedure for landslide risk assessment is presented. The underlying hypothesis is that statistical relationships between past landslide occurrences and conditioning variables can be used to develop landslide susceptibility, hazard and risk models. The latter require also data on past damages. Landslides occurred during the last 50 years and subsequent damages were analysed. Landslide susceptibility models were obtained by means of Spatial Data Analysis techniques and independently validated. Scenarios defined on the basis of past landslide frequency and magnitude were used to transform susceptibility into quantitative hazard models. To assess vulnerability, a detailed inventory of exposed elements (infrastructures, buildings, land resources) was carried out. Vulnerability values (0–1) were obtained by comparing damages experienced in the past by each type of element with its actual value. Quantitative risk models, with a monetary meaning, were obtained for each element by integrating landslide hazard and vulnerability models. Landslide risk models showing the expected losses for the next 50 years were thus obtained for the different scenarios. Risk values obtained are not precise predictions of future losses but rather a means to identify areas where damages are likely to be greater and require priority for mitigation actions.     

Population amount risk assessment of extreme precipitation-induced landslides based on integrated machine learning model and scenario simulation

In this study, the future landslide population amount risk (LPAR) is assessed based on integrated machine learning models (MLMs) and scenario simulation techniques in Shuicheng County, China. Firstly, multiple MLMs were selected and hyperparameters were optimized, and the generated 11 models were cross-integrated to select the best model to calculate landslide susceptibility; by calculating precipitation for different extreme precipitation recurrence periods and combining the susceptibility results to assess the landslide hazard. Using the town as the basic unit, the exposure and vulnerability of the future landslide population under different Shared Socioeconomic Pathways (SSPs) scenarios in each town were assessed, and then combined with the hazard to estimate the LPAR in 2050. The results showed that the integrated model with the optimized random forest model as the combination strategy had the best comprehensive performance in susceptibility assessment. The distribution of hazard classes is similar to susceptibility, and with an increase in precipitation, the low-hazard area and high-hazard decrease and shift to medium-hazard and very high-hazard classes. The high-risk areas for future landslide populations in Shuicheng County are mainly concentrated in the three southwestern towns with high vulnerability, whereas the northern towns of Baohua and Qinglin are at the lowest risk class. The LPAR increased with the intensity of extreme precipitation. The LPAR differs significantly among the SSPs scenarios, with the lowest in the “fossil-fueled development (SSP5)” scenario and the highest in the “regional rivalry (SSP3)” scenario. In summary, the landslide susceptibility model based on integrated machine learning proposed in this study has a high predictive capability. The results of future LPAR assessment can provide theoretical guidance for relevant departments to cope with future socioeconomic development challenges and make corresponding disaster prevention and mitigation plans to prevent landslide risks from a developmental perspective.     

Susceptibility and risk assessment of earthquake-induced landslides based on Landslide Response Units in the Subao River basin,China

Generally, pixels are the basic unit for assessment of landslide susceptibility. However, even if the results facilitate the comparison, a pixel-based analysis does not clearly illustrate the distribution relationships. To eliminate this deficiency, the concept of the Landslide Response Unit (LRU) is proposed in this study, for which adjacent pixels that have similar properties are combined as a basic unit for susceptibility assessment. The Subao River basin, seriously impacted by the Wenchuan Earthquake, was selected as the study area, and three factors including slope gradient, slope aspect, and slope shape, which have a significant impact on landslides, were chosen to divide the basin into 25,984 LRUs. Then topographic, geologic, and distance factors were applied for the landslide susceptibility evaluation. The logistic regression method was used to establish the susceptibility assessing model by analyzing 2,000 susceptible LRUs and 2,000 un-susceptible LRUs. The model accuracy was defined in terms of the ROC curve value and the κ value, 0.531 and 0.84, respectively. The susceptibility of landslides was divided into low, moderate, high, and very high in Subao River basin, and 73% of historical landslides and all four new landslides are in the highly susceptible zone and very highly susceptible zones. Finally, the LRUs with houses, farmlands, and roads prone to sliding and burial hazard were assessed separately. On the basis of considering the potential movement directions of the LRUs, the result found that 1,001 and 835 LRUs probably would be destroyed by slope sliding and landslide burial, respectively.     

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70％landslide pixels)and validation data(30％landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20％interval of landslide occurrence probability contained 89％of the historical landslides but only accounted for 10.3％of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices.     

考虑基质吸力作用的Newmark改进模型在地震滑坡风险评价中的应用

传统的Newmark模型常对地下水位以上由负孔隙水压力提供的部分抗剪强度忽略不计,这对于滑动面的主要部分处在地下水位以下时较为合理,但对地下水位很深或考虑出现浅层滑动的坡体,其计算结果过于保守。因此,文章将Newmark累积位移模型扩展至非饱和土力学领域,在考虑基质吸力作用的基础上,改进了Newmark模型计算公式。分别利用Newmark传统模型和改进模型对甘肃礼县幅区域内的地震滑坡进行易发性分区,并在此基础上分别开展50年超越概率10%情况下的地震滑坡危险性分区和风险评价,最后利用ROC曲线对评价结果进行验证和比较。结果表明:改进模型所得易发区和危险区的计算结果明显优于传统模型计算结果;改进的模型所得风险区的计算结果虽然改进效果不明显,但仍优于传统模型计算结果。由于考虑基质吸力作用的Newmark改进模型充分发挥了基质吸力的贡献,使得计算结果更为合理,研究成果可为相关地区开展地震滑坡易发性分区、危险性分析和风险评价提供新的参考。     

Mining geohazards susceptibility and risk mapping: The case of the Amyntaio open-pit coal mine,West Macedonia,Greece

During the last decades, numerous methodologies for the construction of both susceptibility and risk maps have been developed in order to identify and mitigate geohazards such as landslides and secondarily land subsidence phenomena caused by the collapse of natural or man-made underground cavities. According to literature review, the conducted research concerning the assessment of land subsidence risk due to the overexploitation of the aquifer is still at an early stage. This study focuses οn the land subsidence phenomenon due to the overexploitation of the aquifer occurring in the Amyntaio basin in West Macedonia, hosting the active Amyntaio open-pit coal mine. This phenomenon has caused significant damage to settlements, farmlands and infrastructure. In order to construct susceptibility and risk maps knowledge of the geological, geotechnical, hydrogeological and tectonic settings of the study area is required. The proposed methodology for the production of a susceptibility and a risk map of land subsidence was based on the semi-quantitative method Weighted Linear Combination (WLC). The results were evaluated with an extensive field survey action recording, besides the above-mentioned settings, the spatial distribution of surface ruptures. The excellent agreement between the produced maps and the findings of the field survey, proved the added value of the maps, assigning them as crucial tools for the management of land subsidence phenomena.     

Influence of the sediment delivery ratio index on the analysis of silting and break risk in the Plasencia reservoir (Central System,Spain)

The random forest method was used to generate susceptibility maps for debris flows, rock slides, and active layer detachment slides in the Donjek River area within the Yukon Alaska Highway Corridor, based on an inventory of landslides compiled by the Geological Survey of Canada in collaboration with the Yukon Geological Survey. The aim of this study is to develop data-driven landslide susceptibility models which can provide information on risk assessment to existing and planned infrastructure. The factors contributing to slope failure used in the models include slope angle, slope aspect, plan and profile curvatures, bedrock geology, surficial geology, proximity to faults, permafrost distribution, vegetation distribution, wetness index, and proximity to drainage system. A total of 83 debris flow deposits, 181 active layer detachment slides, and 104 rock slides were compiled in the landslide inventory. The samples representing the landslide free zones were randomly selected. The ratio of landslide/landslide free zones was set to 1:1 and 1:2 to examine the results of different sample ratios on the classification. Two-thirds of the samples for each landslide type were used in the classification, and the remaining 1/3 were used to evaluate the results. In addition to the classification maps, probability maps were also created, which served as the susceptibility maps for debris flows, rock slides, and active layer detachment slides. Success and prediction rate curves created to evaluate the performance of the resulting models indicate a high performance of the random forest in landslide susceptibility modelling.     

Landslide risk analysis and its application in regional planning: an example from the highlands of the Outer Western Carpathians, Czech Republic

Using detailed field mapping, an analysis of landslide risk has been undertaken in the flysch highlands of the Outer Western Carpathians. The standardized Czech methodology of expert derived susceptibility zonation widely used for land development planning purposes and deterministic modeling of shallow landslides was used to separately assess the susceptibility of different landslide types. The two susceptibility zonation maps were used to define landslide hazard using information about landslide reactivation and the return periods of precipitation that triggered the respective landslide types. A risk matrix was then used to qualitatively analyze the landslide risk to selected assets. The monetary value of these assets, according to actual market prices, was calculated and analyzed with respect to the risk classification. Since the study area is an important residential and recreational area, the practical application of the derived results was checked through a series of interviews conducted with personnel of the local government planning and construction office. This demonstrated a willingness to apply the landslide hazard maps as well as restraints of its successful application. The main one is the absence of legally binding regulations to enforce the spatial planers to use this information.     

Integration of statistical and heuristic approaches for landslide risk analysis: a case of volcanic mountains in West Java Province,Indonesia

Owing to fragile geo-morphology, extreme climatic conditions, and densely populated settlements and rapid development activities, West Java Province is the most landslide hazardous area in Indonesia. So, a landslide risk map for this province bears a great importance such as for land-use planning. It is however widely accepted that landslide risk analysis is often difficult because of the difficulties involved in landslide hazard assessment and estimation of consequences of future landslide events. For instance, lack of multi-temporal inventory map or records of triggering events is often a major problem in landslide hazard mapping. In this study, we propose a simple technique for converting a landslide susceptibility map into a landslide hazard map, which we have employed for landslide risk analysis in one ideally hazardous part of volcanic mountains in West Java Province. The susceptibility analysis was carried out through correlation between past landslides and eight spatial parameters related to instability, i.e. slope, aspect, relative relief, distance to river, geological units, soil type, land use and distance to road. The obtained susceptibility map was validated using cross-time technique, and was collaborated with the frequency-area statistics to respond to ‘when landslide will occur’ and ‘how large it will be’. As for the judgment of the consequences of future landslides, expert opinion was used considering available literature and characteristic of the study area. We have only considered economic loss in terms of physical damage of buildings, roads and agricultural lands for the landslide risk analysis. From this study, we understand the following: (1) the hazard map obtained from conversion of the susceptibility map gives spatial probability and the area of an expected landslide will be greater than 500m² in the next 2 years, (2) the landslide risk map shows that 24% of the total area is in high risk; 30% in moderate risk; 45% in low risk and no risk covers only 1% of the total area, and (3) the loss will be high in agricultural lands, while it will be low in the road structures and buildings.     

浅谈我国的地质灾害风险评估

针对我国地质灾害风险评估研究现状,着重讨论了对我国地质灾害风险评估的理解,提出了中国地质灾害风险评估为灾害体易发性、承灾体的易损性、这两者耦合关系评估的结构组成及结构公式,并根据其研究对象、内容、目的等方面情况提出了地质灾害风险评估的完整概念。     

国际滑坡风险评估与管理指南研究综述

总结了国际主流滑坡风险评估与管理技术指南的进展和现状,综述了滑坡风险管理范畴中包含的理论和技术框架,研究精度和层次,滑坡编录、易发性、危险性和风险分区研究的技术方法;指出了滑坡风险分区成果的误差来源和可靠性验证方法;基于滑坡风险分区的研究成果,提出了土地利用规划中风险控制措施的建议。总结了主流国家和地区滑坡风险管理的发展历程和经验,结合中国地质灾害防灾减灾的现状,强调了出版滑坡风险评估与管理指南的紧迫性,并展望了滑坡等突发地质灾害风险评估与管理的发展前景。     

陕北黄土崩塌灾害风险评价指标体系构建

在滑坡的易发性、危险性和风险评价中,评价指标的选取和定量化是非常关键的。目前国内外采取的主要方法是利用GIS工具提取地形、岩性、距河流或断层带的距离、土地类型、植被、降雨、河流密度等因子进行分析和计算。这些指标在滑坡易发性和危险性区划中得到了广泛应用并取得了丰硕的成果,但也有一些局限性,具体表现在3个方面:一是不能针对不同的滑坡类型提供不同的评价指标体系;二是提取的这些因子中在区域上有些是共性因子,如岩性、降雨等;三是尚未建立一个完整的风险评价指标体系。本次研究专门针对陕西北部地区广泛发育的一种称之为"黄土崩塌"的滑坡类型,运用国际上流行的滑坡风险管理理论,确定其风险评价总体指标体系;基于大量野外调查数据的统计规律,分析了黄土崩塌危险性的主要来源和影响危害性的主要因素,从失稳可能性评价指标、崩塌强度评价指标、承灾体评价指标和易损性评价指标4个方面共确定了16大类36个评价指标。该指标体系的构建可为进一步的陕北黄土地区斜坡单元崩塌灾害风险评价提供基础。     

基于信息量法的地质灾害气象风险预警模型:以甘肃省陇南地区为例

地质灾害气象风险预警是目前地质灾害防治研究领域的难点和热点。陇南地区是中国地质灾害造成人员财产损失和受灾害威胁最严重的区域之一,为精细化和准确化预报陇南地区地质灾害风险,在ArcGIS平台将研究区划分为250 m×250 m的栅格单元,使用信息量法选取9个影响因素进行地质环境敏感性评价,结合有效降雨量构建地质灾害气象风险预警模型;该模型通过6次历史降雨事件引发的156起地质灾害验证,预报准确率为83.42%,提高了研究区内地质灾害风险预警精度。该研究基于信息量法的地质环境敏感性分区客观合理,综合考虑下垫面和气象要素的第二代预警模型在类似地区的应用,有较高的准确性和适用性。     

基于组合赋权-未确知测度理论的滑坡危险性评价

危险性评价与预测是滑坡灾害预防与减灾工作首要解决的重要内容。以西藏隆子县研究区内发育的滑坡为例,据其特有的地质环境条件,选取滑坡发育高程、坡度等13项影响因素作为滑坡危险性评价的指标,并建立分级标准将滑坡危险性划分为高度、中度和低度三级。采用组合赋权-未确知测度理论耦合评价模型,构建了评价指标未确知测度函数、评价指标组合赋权值、置信度判别准则,对研究区内20个滑坡进行了危险性评价,获得了每个滑坡危险性等级,并与模糊物元和突变理论评价结果及实测结果对比,评价结果基本符合实际情况,证明该方法科学合理,可为滑坡危险性预测提供新思路。     

Debris-flow risk analysis in south Gargano watersheds (Southern-Italy)

This article describes a methodology to analyse debris-flow risk in the torrential watersheds of the southern hillside of Gargano (Puglia—Italy). The approach integrates a stability model that identifies the areas of potential shallow landslides in different meteorological conditions with a two-dimensional flood routing model that allows hazard mapping and GIS interface. The results were combined with a susceptibility map that was defined by analyzing the vulnerability conditions and the exposure of the alluvial fan. The models were calibrated on the 1972, July catastrophic event for which the distribution of rainstorm intensity was available. The geo-mechanical properties of the debris were studied by field surveys and laboratory tests while the sediment source areas and the shape of the alluvial cone were obtained using photo-aerial interpretation. The risk conditions of the areas under consideration were also investigated in order to plan and guide measures aimed at limiting the damage such hazards may cause.     

Assessment of disaster resilience capacity of hillslope communities with high risk for geological hazards

This study presents a novel preparedness assessment method for assessing hazard mitigation and environmental planning of hillslope communities. A professional questionnaire was utilized to weight each indicator. Communities in Hsinchu, Taichung and Nantou counties with debris flow hazards were taken as study samples. Debris flow risk and landslide susceptibility for each community were determined using Geographic Information System (GIS) technology and logistic regression analysis. Thus, a novel risk assessment method for evaluating disaster resilience capacity of hillslope communities was established. This method was then applied to assess casualties caused by Typhoon Herb in 1996 and Typhoon Mindulle in 2004. Additionally, the analytical results generated by this assessment method were discussed with the aim of developing references for implementation of risk analysis, increasing the effectiveness of disaster mitigation, and reducing future loss of life and property.     

Integrated risk assessment of multi-hazards in China

Maps of population exposure, vulnerability and risk to natural hazards are useful tools for designing and implementing disaster risk mitigation programs in China. The ranking of provinces by relative risk to natural hazards would provide a metric for prioritizing risk management strategies. Using provinces as our study unit, from the perspectives of hazard exposure, susceptibility, coping capacity and adaptive capacity, this study first constructed China’s disaster risk index for five types of major natural hazards: earthquakes, floods, droughts, low temperatures/snow and gale/hail. Then, the relative risk level at the provincial scale in China was assessed. Finally, the hotspots with the highest hazard exposure, vulnerability and risk were identified. The results showed that high exposure was a significant risk driver in China, whereas high vulnerability, especially social vulnerability, amplified the risk levels. Similar to the population exposure to disasters, the relative risk levels in the southwestern, central and northeastern regions of China were significantly higher than those in the eastern, northern and western regions. The high-risk regions or hotspots of multi-hazards were concentrated in southern China (less-developed regions), while the low-risk regions were mainly distributed in the eastern coastal areas (well-developed regions). Furthermore, a nonlinear relationship existed between the disaster risk level and poverty incidence as well as per capita GDP, demonstrating that disaster losses in middle-income areas are likely to increase if economic policies are not modified to account for the rising disaster risk. These findings further indicated that research on disaster risk should focus not only on hazards and exposure but also on the vulnerability to natural disasters. Thus, reducing vulnerability and population exposure to natural hazards would be an effective measure in mitigating the disaster risk at hotspots in China.     

Landslide risk analysis in the area North of Lisbon (Portugal): evaluation of direct and indirect costs resulting from a motorway disruption by slope movements

A risk analysis is developed for a test site located in the area north of Lisbon using a scenario of a temporary interruption of the motorway A9 due to a landslide of rotational or translational type. Landslide susceptibility is assessed at the regional scale independently for rotational and translational slides, comparing the landslide distribution with a set of assumed independent landslide predisposing factors. Susceptibility models are validated and classified through the computation of prediction rate curves based on the temporal partition of the landslide data sets. Landslide hazard maps are based on a scenario of future landslide occurrence for the next 27 years. These maps allow the definition of two critical areas on the motorway A9 with regards to landslide susceptibility. Direct costs associated with both critical spots are assessed taking into account the probable affected area of the motorway, and the reconstruction costs. Indirect costs derived from the traffic interruption are evaluated considering the alternatives paths to the motorway, and include costs resulting from: (1) additional fuel consumption; (2) decrease in tollgate income; and (3) loss of productive time. Results show that indirect costs may be 24 to 43 times higher than direct costs, assuming a temporary interruption of the motorway for 6 months.