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.     

Rainstorm waterlogging risk assessment in central urban area of Shanghai based on multiple scenario simulation

With the acceleration of the urbanization process, waterlogging problems in coastal cities are becoming more and more serious due to climate change. However, up until now, the common procedures and programs for rainstorm waterlogging risk assessment in coastal cities still have not formed. Considering a series of impact factors of rainstorm waterlogging in coastal city, the present study established a paradigm for rainstorm waterlogging risk assessment through the combination of hydrological modeling and GIS spatial analysis, and took the residence in central urban area of Shanghai as an example. First, the simplified urban waterlogging model was applied to simulate the depth and extent of rainstorm waterlogging under six hypothetic scenarios. Second, the residence exposed to rainstorm waterlogging was extracted and analyzed supported by spatial analysis module of ArcGIS. Then, stage-damage curves were applied to analyze the loss rate of structure and contents of residential building. Finally, the waterlogging loss maps of residence in different scenarios, the annual average loss, and the risk curve were taken as the expression of waterlogging risk. The results show that the inundated water depth, vulnerability, and losses of residence all increase as the intensity of rainstorm increases. The old-style residence is most vulnerable to rainstorm waterlogging, followed by the new-style residence, and villa is less vulnerable to rainstorm waterlogging. The annual average loss of residence in Shanghai central urban area was about CNY 22.25 million. The results also indicate high risk in Yangpu and Putuo districts, Xuhui, Hongkou, Changning and Zhabei districts come under medium-risk zone, and Jing’an, Luwan and Huangpu districts come under low-risk zone. These results provide important information for the local government, and the methodology can be applied in other cities to provide guidance on waterlogging risk governance.     

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.     

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.     

基于暴雨衰减特性的上海市长历时综合暴雨公式

编制适用于不同历时的综合暴雨公式是协调城市管网排水与区域防洪治涝的重要基础。选用上海市代表雨量站徐家汇站65 a实测雨量资料,建立不同重现期暴雨强度与历时关系,解析暴雨衰减规律,编制单一重现期暴雨公式,结合雨力公式推求适用不同重现期的长历时综合暴雨公式,并推导出暴雨重现期公式。结果表明:不同重现期1~24 h历时暴雨强度均以0.74的衰减指数衰减,据此推求的长历时综合暴雨公式可计算1~24 h任意历时、2~100 a任意重现期的设计暴雨,且平均相对和平均绝对均方根误差分别为1.9%和0.009 mm/min,符合规范要求;暴雨重现期公式可估算1~24 h历时内任意场次暴雨的重现期,高效地服务于城市洪涝防治决策。成果已纳入上海市治涝地方标准,对其他城市具有参考价值。     

Risk assessment of rainstorm and flood disasters in China between 2004 and 2009 based on gray fixed weight cluster analysis

Rainstorm and flood disasters frequently occur in China, causing heavy losses for people’s lives and property and reducing the capability of sustainable development of the national and local economy. In this study, the risks of the rainstorm and flood disasters are assessed for the Chinese mainland, excluding Hong Kong, Macao, and Taiwan and also employ the historical data of seven indicators, including the affected area of crops, the affected population, the direct economic loss, and etc., from 2004 to 2009. Based on the large 1,302 historical sample data, the impact of rainstorm and flood disasters were analyzed using the methodology of gray fixed weight cluster analysis according to disaster losses, which were divided into the three gray classes of high, medium, and low. The regional differences of the risk assessment of the rainstorm and flood disasters are discussed, and the dynamical risk zoning map is conducted. The results show a consistent conclusion with the actual losses of rainstorm and flood disasters over each administrative district, which can provide more scientific evidence for the relevant departments of disaster prevention and mitigation.     

基于WCA2D与SWMM模型的城市暴雨洪涝快速模拟

为探讨计算高效的元胞自动机模型(WCA2D)与传统一维管网模型耦合的机制以及计算效果,尝试将WCA2D与SWMM模型耦合(SWMM/WCA2D),以广州市长湴片区为例探究一种暴雨洪涝快速二维模拟技术,对比实测积水数据以及SWMM/LISFLOOD-FP模拟,结果表明:SWMM/WCA2D模拟结果与"20180607"实测积水数据相近,表明模型精度良好;根据多指标评估结果,综合考虑主干渠道淤积以及建筑物阻挡情景的R_TPR、R_PPV、F₁值分别达到0.8、0.6、0.7,模拟精度最高,最能反映区域实际情况;通过与SWMM耦合,WCA2D和LISFLOOD-FP的模拟结果差异小(最大水深差值基本低于0.1 m)、相关性强(相关系数基本超过0.7),但前者计算效率是后者的3～5倍,表明WCA2D能够耦合SWMM且计算效率更高,为复杂城市化地区暴雨洪涝快速模拟提供了一种新方法。     

岩溶浸没内涝灾害的物理(数学)模拟研究

红水河梯级水电站的百龙滩、岩滩等库区，由于岩溶地下河系统的存在，在水电站蓄水以前，每逢大雨，就会造成库区谷地的浸没内涝，在水库蓄水以后，由于地下河出口水位的提高，使得库区内涝灾害加重，为了研究库区洼地水库蓄水前、后浸没内涝灾害的规律，根据该地区的水文地质条件，组装了物理模型。采用物理（数学）模拟的方法对红水河百龙滩水电站库区的地苏地下河系统进行模拟计算。研究库区凤翔、镇兴、南江谷地在不同的大气降水、不同的地下河出口水位条件下，谷地的内涝水位的变化规律，建立起3个谷地的数学模型，同时，对可能出现的降雨类型进行模型预测。     

Risk assessment of groundwater pollution using sensitivity analysis and a worst-case scenario analysis

This paper illustrates how sensitivity analysis and a worst-case scenario analysis can be useful tools in risk assessment of groundwater pollution. The approach is applied to a study area in Hungary with several known groundwater pollution sources and nearby drinking water production wells. The main concern is whether the contamination sources threaten the drinking water wells of the area. A groundwater flow and transport model is set up to answer this question. Due to limited data availability, the results of this model are associated with large uncertainty. Sensitivity analysis and a worst-case scenario analysis are applied to estimate this uncertainty and build confidence in the model results.     

基于风险度的青海省暴雨洪涝灾害风险评估

基于自然灾害风险原理,结合青海省气象数据、地理信息数据、社会经济数据,并利用主成分分析法、GIS自然断点法对青海省暴雨洪涝灾害致灾因子危险度、承载体易损度评估模型以及暴雨洪涝灾害风险度进行评估,结果表明：青海省不同强度降水日数均呈增多趋势,新世纪以来中雨日数及强降水日数增加趋势尤为明显;暴雨洪涝灾害致灾因子危险度呈由东南向西北降低的趋势,承载体易损度为东北部地区最高,南部以及西部地区最低;暴雨洪涝风险较高的地区主要集中在东部地区,互助、湟中、大通、西宁为高风险区,东部大部地区、环青海湖地区为较高风险区,西部地区为低风险区。该评估结果可以在气象灾害风险管理业务中进行应用,可以加强对暴雨洪涝灾害风险的影响程度及影响区域的判定,为地方防灾减灾救灾工作提供科学依据。     

Risk mechanisms of large group emergency decision-making based on multi-agent simulation

Natural Hazards - There are many critical sources of risk in large group emergency decision-making. In this paper, we systematically identify individual and group sources of risk in large group...     

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.     

中国城市洪涝问题及成因分析

随着经济社会的发展,中国步入城镇化快速发展的阶段,城镇化率已由2000年的36.22%增加到2014年的54.77%。在全球气候变化与快速城镇化背景下,中国城市洪涝灾害日益严重。阐述了全球气候变化及城镇化对城市降水和极端暴雨的影响机制,并从流域产汇流角度分析了城镇化对洪水过程的影响,系统剖析了中国城市洪涝频发的主要原因。在成因分析的基础上,进一步提出了中国城市洪涝防治的应对策略,主要包括:①以低影响开发理念为指导,加强城市基础设施建设,建设海绵城市;②建立城市洪涝立体监测、预报预警和实时调度系统,强化城市洪涝科学决策能力;③健全和完善城市洪涝应急预案,强化应急管理能力,完善灾害救助和恢复机制。     

台风暴雨条件下滑坡稳定性影响因素分析

以实验数据为依据,通过数值模拟对台风暴雨条件下滑坡体稳定性的主要影响因素进行模拟研究。台风暴雨条件下滑坡体的主要影响因素为特殊降雨雨型：(1) 在相同雨强程度下,台风暴雨的单峰型降雨水文响应速度、稳定性破坏速度及程度均大于普通均匀型降雨,单峰型降雨导致边坡短时间内达到失稳状态,呈“即雨即滑”情况;(2) 强台风多峰型降雨下,经过第一个峰值强降雨后浅层土质边坡已处于不稳定状态,当第二个强峰值降雨来临时,坡体的稳定性较单峰型降低更为迅速。这些为福建省台风暴雨这一特殊降雨类型条件下滑坡的发生机理探索及预警预报提供了新的思路和科学依据。     

北京城市洪涝问题与成因分析

利用社会经济统计数据和水文气象资料,探讨城市化背景下北京城市洪涝特征、形成机制及影响因素。近50年来城市内涝逐渐成为北京洪涝灾害的主要类型,随着城市化迅猛发展,城市内涝积水点数量在时间上表现为显著增加趋势,在空间上呈现出由内环逐步向外环扩张趋势,与城市化发展空间格局关系密切。从水循环的角度分析城市洪涝形成机制,指出区域气候变化和城市化发展改变了城市降水格局,汛期降水量和极端降水事件呈现下降趋势,但城区短历时强降水事件呈现增加态势;城市化发展改变了区域下垫面条件、城市流域产汇流特性和城市排水格局,进而影响了区域水循环过程和水量分配,在一定程度上增加了城市洪涝灾害风险;同时城市基础设施建设水平不足、排水排涝标准偏低、应急管理能力不足等因素,导致城市洪涝发生风险增加,降低了城市洪涝综合应对能力。     

上海轨道交通沉降风险评估

轨道交通沉降的风险评估和监测预警研究对轨道交通安全和城市规划建设具有重要意义。文章从上海轨道交通运营的地质环境出发,在总结工程地质条件和区域地面沉降特征的基础上,以3条轨道交通线路为例,分析了这3条线路地铁隧道运营期间的沉降规律特征。通过分析影响地铁隧道沉降的各风险因素与沉降变形之间的关系特征,建立了包括地质条件、区域地面沉降、周边工程建设、轨道交通结构差异、轨道交通沉降特征在内的轨道交通沉降风险评估指标体系,并以此为基础对3条线路进行了沉降风险评估。     

碳酸盐岩储集层模型数值模拟与分析

碳酸盐岩储层作为油气勘探领域中的重要研究目标,其波场特征变化极为复杂,为提高对该类储集层多波地震资料的认知度,高精度数值模拟是行之有效的方法之一。这里在各向同性弹性波方程基础上,推导了纵波、横波分离方程,运用高阶交错网格有限差分技术与PML边界吸收技术,高精度模拟地震波在碳酸盐岩储层中的传播,得到了该类储层模型中的弹性波全波场,也分离出纵波信息和转换波波场信息,并保留了各自能量信息。同时结合AVO技术分析了弹性波在碳酸盐岩储层中AVO响应特征,并通过对储层理论模型进行试算,分析研究该类储层中的波场响应特征及传播规律,为碳酸盐岩储层的识别与预测提供参考依据,更能满足复杂油气田勘探开发的实际需要。     

基于物理模拟试验的岩质滑坡地表位移分析

三段式岩质滑坡是一种典型的斜坡变形破坏模式,运用二维地质力学加载系统对其变形破坏全过程进行物理模拟试验研究,采用激光位移计对坡顶和坡脚位置进行位移监测。结果表明:位移监测曲线总体上表现为锁固段经历长时间的能量积累与应力调整后的突发脆性破坏;由于软弱夹层具有蠕滑特性,前缘蠕滑阶段呈现出与土质滑坡相似的初始变形→等速变形→加速变形特征;后缘拉裂阶段作为最短暂的变形阶段,其位移监测曲线表现为“减-增-减-增”的“W”型变化趋势;锁固段是三段式岩质边坡维持稳定的关键所在,其受剪变形的顺序为先上后下,损伤变形由端部向中部递进,最终锁固段剪断形成突发脆性破坏,滑坡高速启动。     

Efficient system reliability analysis of rock slopes based on Subset simulation

How to efficiently assess the system reliability of rock slopes is still challenging. This is because when the probability of failure is low, a large number of deterministic slope stability analyses are required. Based on Subset simulation, this paper proposes an efficient approach for the system reliability analysis of rock slopes. The correlations among multiple potential failure modes are properly accounted for with the aid of the “max” and “min” functions. A benchmark rock slope and a real engineered rock slope with multiple correlated failure modes are used to demonstrate the effectiveness of the proposed approach.