Exposure assessment of rainstorm waterlogging on old-style residences in Shanghai based on scenario simulation

Waterlogging is one of the most serious hazards in China. Old-style residences in cities are prone to be damaged by waterlogging hazards. This paper describes our exposure assessment of old-style residences in Shanghai during rainstorm waterlogging. Two rainstorm scenarios of 20-year and 50-year return periods were simulated with the rainstorm simulation model from Shanghai Flood Risk Information Center. Each old-style residence was ranked according to its degree of exposure indicated by the inundation depth of that residence. An exposure assessment model was then built to integrate three ranks of exposure in order to reflect the total exposure features of a district and to compare disaster situation among different districts. Our research results reveal that Hongkou District and Huangpu District are the regions most necessary for the government to carry out safety defense in old-style residences, while rainstorms bring little effect on old-style residences in the districts of Putuo, Luwan, Changning, Zhabei, and Jing’an. These results provide important information for Shanghai Municipal Government to improve waterlogging management, and the method of exposure assessment can also be applied in other cities to provide guidance regarding flood risk control.     

Risk analysis of rainstorm waterlogging on residences in Shanghai based on scenario simulation

Due to special geographical location and climate, the waterlogging has always been one of the most serious hazards in Shanghai. Residences in the inner city are prone to be damaged by waterlogging hazards. This paper describes the risk analysis of rainstorm waterlogging on residences in Shanghai. First, a rainstorm scenario of 50-year return period was simulated with the rainstorm simulation model from Shanghai Flood Risk Information Center. Each residence was ranked according to its degree of exposure indicated by the inundation depth of that residence, and an exposure analysis model was then built. It is found from the exposure analysis that residences in the sub-districts like Linfen Road, Pengpu Village, Gonghe New Village, Hongqiao Road, Xianxia Road, Xinhua Road, and Zhenru Town are at high-exposure level. Whereas residences in other sub-districts like Gaojing Town, Siping Road, Huaihai Road, Yuyuan, Waitan, Caojiadu, Nanjing East Road, etc. are at low-exposure level. Second, given the characteristics of residences in waterlogging, the vulnerability of residences was expressed as the proportion of old-style residences to total residences. The results show that residences in Yuyuan, Xiaodongmen, Waitan, Nanjing East Road, Laoximen, Zhapu Road, North Station, and Tilanqiao are the most vulnerable ones, while there is no vulnerability in Fenglin Road, Kongjiang Road, Liangcheng New Village, Quyang Road, Siping Road, and Xianxia Road due to the absence of old-style residences. Finally, a model has been built from a systematic perspective and then waterlogging risk analysis was quantified by multiplying the exposure value with vulnerability value of residences. The results reveal that Laoximen, Tilanqiao, Dinghai Road, North Station, Tianping Road, Hongmei Road, Hunan Road, and Xiaodongmen are at high-risk level. The systemic risk model is a simple tool that can be used to assess the relative risk of waterlogging in different regions and the results of risk analysis are applicable to prevention and mitigation of waterlogging for Shanghai Municipal Government.     

Population vulnerability assessment based on scenario simulation of rainstorm-induced waterlogging: a case study of Xuhui District, Shanghai City

Waterlogging is one of the most serious hazards in cities. People are the core of the human social system and the main group affected by disasters. This research introduces a method of scenario simulation which provides a basis for the accurate measurement of exposure to waterlogging. Then based on the concept and structure of vulnerability, representative indicators are selected to develop an indicator system based on objective weights derived from principal components analysis. The method is then used to conduct a population vulnerability assessment in Xuhui District of Shanghai city based on scenario simulation of rainstorm-induced waterlogging over a 50-year period. The final assessment results show that the population vulnerability is greatest for Tianlin Street, Lingyun Street, Changqiao Street, Fenglin Street, and Caohejing Street, while Tianping Street, Xujiahui Street, and Xietulu Street have medium levels of vulnerability. Hongmei Road Street, Healthy Village Street, Longhua Street, and Hunan Road Street have low levels of vulnerability, and Huajing Town is the area with the lowest population vulnerability. The results provide both necessary information and guidance for the government to improve the flood management.     

中国城市洪涝致灾机理与风险评估研究进展

近年来，在全球气候变化和城市化快速发展的共同影响下，中国城市洪涝灾害日益严重，已经成为影响中国城市公共安全的突出问题，严重制约经济社会的持续健康发展。变化环境下城市洪涝致灾机理与风险评估研究是完善城市防洪除涝减灾体系、提升城市防洪除涝能力的重要依据。本文阐述了气候变化和城市化发展对城市洪涝灾害的影响机制，系统分析了城市洪涝灾害的驱动要素和致灾机理，梳理了城市洪涝灾害的风险评估和分区方法，并以济南市海绵城市示范区为例，对城市洪涝灾害风险分区方法进行了分析和对比。     

中国城市洪涝致灾机理与风险评估研究进展

近年来，在全球气候变化和城市化快速发展的共同影响下，中国城市洪涝灾害日益严重，已经成为影响中国城市公共安全的突出问题，严重制约经济社会的持续健康发展。变化环境下城市洪涝致灾机理与风险评估研究是完善城市防洪除涝减灾体系、提升城市防洪除涝能力的重要依据。本文阐述了气候变化和城市化发展对城市洪涝灾害的影响机制，系统分析了城市洪涝灾害的驱动要素和致灾机理，梳理了城市洪涝灾害的风险评估和分区方法，并以济南市海绵城市示范区为例，对城市洪涝灾害风险分区方法进行了分析和对比。     

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.     

广州东濠涌流域城市洪涝灾害情景模拟与风险评估

绘制直观与可靠的城市洪涝灾害风险区划图,为城市防洪排涝相关部门决策提供参考依据。以广州市东濠涌流域为研究区域,综合考虑城市降雨、径流、地形和排水系统特性,构建基于InfoWorks ICM的一维-二维耦合城市洪涝仿真模型,模拟暴雨重现期为1年、5年、50年情景下的洪涝过程并获取致灾因子数据。调研分析区域的孕灾环境、承灾体和防灾减灾能力概况,结合层次分析法、评价等级和阈值划分等进行洪涝灾害风险评估。结果表明:城市洪涝仿真模型在一维排水系统和二维地面淹没模拟上均有较好的精度和可靠性,保证了致灾因子数据的可靠性;风险区划图能较好地反映流域的风险分布;随着重现期增大,较高、高风险区的面积显著增加,为防洪排涝重点关注区域。     

Real-time identification of urban rainstorm waterlogging disasters based on Weibo big data

With the acceleration of urbanisation in China, preventing and reducing the economic losses and casualties caused by urban rainstorm waterlogging disasters have become a critical and difficult issue that the government is concerned about. As urban storms are sudden, clustered, continuous, and cause huge economic losses, it is difficult to conduct emergency management. Developing a more scientific method for real-time disaster identification will help prevent losses over time. Examining social media big data is a feasible method for obtaining on-site disaster data and carrying out disaster risk assessments. This paper presents a real-time identification method for urban-storm disasters using Weibo data. Taking the June 2016 heavy rainstorm in Nanjing as an example, the obtained Weibo data are divided into eight parts for the training data set and two parts for the testing data set. It then performs text pre-processing using the Jieba segmentation module for word segmentation. Then, the term frequency–inverse document frequency method is used to calculate the feature items weights and extract the features. Hashing algorithms are introduced for processing high-dimensional sparse vector matrices. Finally, the naive Bayes, support vector machine, and random forest text classification algorithms are used to train the model, and a test set sample is introduced for testing the model to select the optimal classification algorithm. The experiments showed that the naive Bayes algorithm had the highest macro-average accuracy.     

Geological risk assessment by a fracture measurement procedure in an urban area of Zacatecas,Mexico

Natural Hazards - Geological hazards represent medium- and long-term risks, when they affect urban infrastructure and residential areas as they become a source of danger for the population. In...     

An assessment of the risk associated with urban development in the Thiaroye area (Senegal)

Water quality data from 56 wells, aquifer characteristics, soil types and land use in the city suburb of Dakar were compared to assess the effects of land use on the Thiaroye groundwater quality. The study area encompassed an unsewered densely populated zone, agricultural land, low density villages, and undeveloped land located in the sand dunes. A method similar to GIS technologies was applied to evaluate the degree of vulnerability of the different parts of the aquifer in relation to urban development, land use and aquifer characteristics. The aquifer parameters (hydraulic conductivity, groundwater level depth, recharge, soil type) were re-evaluated qualitatively into three class rankings (high, moderate and low), depending on the likelihood for contaminants reaching the water table, then combined using the two matrix Boolean logic based approaches to identify the nine classes of vulnerability assessed in the aquifer domain. An attempt was made to explain the distribution of nitrate concentration with the assessed vulnerability. In the area assessed, in the densely populated zone running from Pikine, to Thiaroye and Yeumbeul, very high nitrate concentrations correspond with the highest vulnerability index (H1). Nitrate contamination in this area is a consequence of point-source seepage from individual septic systems improperly built in this area. In the eastern part of the aquifer, high nitrate concentrations at Deni B. Ndao, Mbawane and Golam localities coincide with a moderate vulnerability assessment. The major source of nitrate in these areas is induced by agricultural activities.     

城市地面塌陷灾害风险评估研究

随着城市化进程不断加快,城市地下空间安全问题引起广泛关注。本文以影响地下空间安全的典型灾害-地面塌陷为例,开展可能性风险评估研究,为降低地面塌陷灾害损失提供理论支撑。城市地面塌陷成因复杂,为了保证评价过程和结果的客观全面,通过调研对塌陷引发因素进行了总结,从管道因素、病害体因素、环境因素三个方面建立风险发生可能性评价指标体系,并使用AHP-熵权法-灰色关联法组合评价,建立地面塌陷风险评价模型。将该模型应用于郑州市典型地下空洞工程案例进行评估分析,结果表明:地面塌陷风险评价结果与实测结果相符,证明了评估模型的科学性,同时为城市地面塌陷预防提供了决策参考。     

基于三维遥感系统的泥石流土石量计算及影响范围模拟

结合三维遥感影像解译提出一种定量的泥石流土石量计算方法。在泥石流汇水区内对地形进行0次谷与1次谷划分,按可搬运的物质总量和一次降雨所能搬运的物质总量两种方式进行分析,使计算结果更加精细化;以数字高程模型(DEM)与降雨所搬运的土石总量作为影响范围模拟的基础,利用GIS空间分析功能分析泥石流汇水区的横截面面积及区域平面面积等地形参数,判别土石产出量与地形参数关系,实现泥石流影响范围的模拟。分析结果可为潜在泥石流危险区域评价预测提供参考。     

滇中姚安地区土壤重（类）金属来源分析及生态风险评价

为了解滇中姚安地区表层土壤重（类）金属的污染特征、来源及生态风险状况,在研究区共采集表层土壤样品428件,对其中As、Cd、Cr、Cu、Hg、Ni、Pb和Zn元素的含量进行测试分析。通过数据统计分析和地球化学图说明了这些重（类）金属元素的含量分布特征和空间分布特征。运用相关性分析、主成分分析和聚类分析方法探究了重（类）金属的来源。运用地累积指数法、富集系数法和潜在生态危害指数法对研究区土壤重（类）金属污染程度及潜在生态风险进行了评价。研究结果表明,As、Cu、Pb和Zn受自然背景与矿产开采共同影响;Cr、Ni主要来源于成土母质;而Cd受矿产开采和农业施肥的影响较大;Hg则受周边工厂以及煤炭燃烧的影响。地累积指数和富集系数分析表明,研究区污染程度普遍不高,但局部地区有重（类）金属元素的污染富集,代表元素为Cd和Hg。而潜在生态危害指数法分析结果也表明Cd和Hg是研究区最主要的风险元素,但以轻度和中度生态危害为主,强生态危害分布面积较小,研究区生态风险整体较低,风险可控。本研究对滇中地区的土壤重（类）金属的污染评价和土地利用发展规划有一定的参考作用。     

上海地区地质灾害危险性评估关键技术问题研究

"建设项目地质灾害危险性评估技术规程"即将成为上海市工程建设规范。该规程总结了以往评估实践,细化和完善了具体技术细则,强化了指导性和可操作性。介绍了上海地区确定的地面沉降、地基变形、边坡失稳、砂土液化、水土突涌、岸带冲淤、浅层天然气害、水土污染等8个评估灾种的界定、地质环境条件复杂程度的分类要素及划分标准、建设项目重要性的具体划分、评估范围的确定、地质灾害危险性分级分区原则、拟建场地建设适宜性评价准则等灾评实践及规程编制中的关键技术问题。     

Potential assessment of CO2 geological storage based on injection scenario simulation: A case study in eastern Junggar Basin

Carbon Capture and Storage (CCS) is one of the effective means to deal with global warming, and saline aquifer storage is considered to be the most promising storage method. Junggar Basin, located in the northern part of Xinjiang and with a large distribution area of saline aquifer, is an effective carbon storage site. Based on well logging data and 2D seismic data, a 3D heterogeneous geological model of the Cretaceous Donggou Formation reservoir near D7 well was constructed, and dynamic simulations under two scenarios of single-well injection and multi-well injection were carried out to explore the storage potential and CO₂ storage mechanism of deep saline aquifer with real geological conditions in this study. The results show that within 100 km² of the saline aquifer of Donggou Formation in the vicinity of D7 well, the theoretical static CO₂ storage is 71.967 × 10⁶ tons (P50)^①, and the maximum dynamic CO₂ storage is 145.295 × 10⁶ tons (Case2). The heterogeneity of saline aquifer has a great influence on the spatial distribution of CO₂ in the reservoir. The multi-well injection scenario is conducive to the efficient utilization of reservoir space and safer for storage. Based on the results from theoretical static calculation and the dynamic simulation, the effective coefficient of CO₂ storage in deep saline aquifer in the eastern part of Xinjiang is recommended to be 4.9%. This study can be applied to the engineering practice of CO₂ sequestration in the deep saline aquifer in Xinjiang.     

Economic benefit risk assessment of controlling land subsidence in Shanghai

Land subsidence, a major and well-known geological hazard in Shanghai, has caused serious losses. Based on past studies, the cost and benefit of the Shanghai's land subsidence hazard control were assessed and forecasted by risk assessment. An economic benefit-risk assessment was taken in order to control completely land subsidence and make rational safety elevations of the flood control wall. The result of risk assessment shows that the present 6.9-m elevation of the floodwall is not sufficient for the standard of occurring only once in a thousand years. After 200 years, the spring tide hazardous risk losses caused by land subsidence would amount to 49.73 million yuan per year. The proportion of expense in thoroughly controlling land subsidence to the economic benefit is 1:41.44; to construct the flood control wall to an elevation that would prevent inundation from a flood event, to reach the standard of occurring only once in a thousand years, and to avoid tide losses, the ratio of the investment of reducing tide hazard to the economic benefit should be 1:53.24.     

北方集中供热系统气象风险评估初探

供热管网爆裂、跑冒滴漏是北方集中供热城市面临的常见问题,供热管网出现大型故障往往是在室外寒冷的隆冬时节,如果间断或限额供热时间过长,将会造成严重的社会和经济影响。同时在极端低温情况下,可能会造成热源供应不足,出现限额供热现象,不能保证室内舒适度,影响人们的正常生活。本文提出了能源供应气象风险评估和热网维修寒冷风险评估方法,并进行了案例评估,以期为未来进行相关风险评估提供参考。