四川旱涝震灾害的人工神经网络外推预测

选取旱、涝、震灾害之间的一步转移概率作为Ｂ－Ｐ人工神经网络训练样本的输入信息，建立了四川旱、涝、震的人工神经网络灾型预测模型。Ｂ－Ｐ网络模型应用于实例预测结果与用主分量分析法的趋势预测结果精度接近。     

1951-2008年辽宁冰雹的时空分布特征

选取1951-2008年辽宁省56个站气象资料和中国气象灾害大典等资料,对冰雹时空分布进行了统计分析。结果表明：辽宁冰雹日数以山地为最多,丘陵次之,平原和沿海最少。移动路径基本与山脉、河流、海岸线等地形走向一致。冰雹具有明显的季节变化,主要出现在4-10月。5-6月为冰雹多发期,6月为最多,5月次之。近30a辽宁省年冰雹日数呈减少趋势。冰雹发生主要集中在中午至傍晚。辽西走廊、辽宁中部平原及辽东半岛南部大连地区为冰雹灾害重点防御区。产生冰雹的天气系统按高空形势分类主要有4种：冷涡、冷涡后部横槽、高空槽和槽后西北气流,对应地面形势多为低压冷锋。     

2010年凌云县干旱灾害成因分析及抗旱措施

从气候、地形等方面分析了凌云县2009年秋至2010年干旱灾害的成因,并提出了相应的抗旱措施,尽可能减少干旱灾害造成的损失。     

Social and structural vulnerabilities: Associations with disaster readiness

The ability to plan for a disaster is associated with a range of contextual factors and often traverses several sites of inequities, including sociodemographic and institutional disparities. While multiple studies have investigated the relationship of housing insecurity with adverse outcomes after a disaster, fewer studies have examined how housing insecurity is associated with disaster preparedness. This paper hypothesizes social and structural vulnerabilities to be directly associated with preparedness. Housing insecurity is posited to have both direct and multiplicative effects with social vulnerability on the dependent variable. We use nationally representative data from the 2017 American Housing Survey. The final weighted study sample consisted of 29,070 housing units, with 52% male and 48% female householders. Fifty-seven percent of the population was not prepared with food, water, emergency funds, and transportation. Housing security and quality emerged as important conditions for households to be better prepared. Further, housing insecurity moderated the relationship between some social vulnerability factors and preparedness. The study helps identify where resources and research funds should be targeted to reduce multidimensional vulnerabilities before a disaster. Safe and affordable housing is central to climate and environmental justice; centering disaster readiness, response, and climate action across policy agendas is vital.     

Resilience to disaster: Evidence from American wellbeing data

As the severity and frequency of extreme weather events become more pronounced with climate change and the increased habitation of at-risk areas, it is important to understand people’s resilience to them. We quantify resilience by estimating how disasters in the US impacted individual wellbeing in the initial weeks and months post-disaster, and whether the effect sizes differed by individual- and county-level factors. The methodological approach contrasts changes in wellbeing in counties affected by disasters with that of residents in unaffected counties of the same state. We find that people’s hedonic wellbeing is reduced by approximately 6% of a standard deviation in the first two weeks following the event, with the effect diminishing rapidly thereafter. The negative effects are driven by White, older, and economically advantaged sub-populations, who exhibit less resilience. We find no evidence that existing indices of community resilience moderate impacts. Our conclusion is that most people in the US have a resilient response to extreme weather events.     

2021年、2022年中国大陆地震灾害损失述评

基于2021年、2022年中国5.0级及以上地震目录,结合应急管理部、有关省(自治区、直辖市)地震局的地震灾害评估报告和相关资料,对中国大陆地震灾害情况、主要地震灾害事件及其特点进行了总结和分析。此外,按省份总结了各省地震灾害事件及地震灾害特点。其中,云南省中强震多、强震少,震区房屋抗震能力较高,人员伤亡较小; 四川省中强震少、强震多,次生灾害较为发育,造成严重人员伤亡; 青海省虽然震级高、破坏性强、致灾范围广,但震区地广人稀,房屋抗震设防等级较高,人员伤亡少。最后,结合历史震害统计数据,分析对比近2年中国大陆地震灾害致灾特点。     

四川九寨沟7.0级地震后社交媒体多层次信息沟通功能分析

本文以“社交媒体多层次信息流”为概念框架,分析了四川九寨沟7.0级地震发生后,个人、当地的组织、宏观层面的主流媒体使用社交媒体所发挥的作用。通过对微博的数据进行挖掘分析,总结出地震灾害发生后社交媒体所具有的5项功能:人际之间的交流,地方政府、本土组织以及当地媒体的传播渠道,大众传媒信息发布的渠道,信息的收集和分享,微观、中观以及宏观各主体间沟通的渠道。在强震发生后社交媒体有巨大的传播潜力,本文的研究成果对未来大震发生后如何利用社交媒体来应对灾害有一定的借鉴意义。     

震后典型建筑物倒塌分类及救援特点分析

震后建筑物倒塌造成人员埋压,快速的搜索与营救是有效减少伤亡的重要途径之一。本文通过研究震后典型建筑物倒塌类型,从建筑物垂直和水平破坏角度出发,提出一套三级分类体系,并对每类倒塌建筑物的受力及生存空间进行讨论。同时结合大量文献及汶川地震救援案例资料,重点分析总结各类建筑物救援时的路线选择、救援通道建立、被困人员施救等技术特点。     

基于12322平台的江苏省地震应急灾情速报系统的设计与应用

通过分析地震应急救援工作中对灾情信息的需求,提出了“地震应急灾情”的概念,设计了基于12322平台的江苏省地震应急灾情速报系统。本文详细介绍了该系统的设计框架、基本功能和应用效果。系统主要包括短信和微信两大模块,短信模块主要面向非地震系统人员,通过手机短信形式向社会灾情速报员发送灾情邀请短信,灾情速报员只需简单回复灾情代码“1”—“4”即可。微信模块主要面向地震系统工作人员,通过微信企业号“苏震12322”自动推送地震信息并完成灾情收集工作。经过近1年的试运行,系统能够在震后迅速完成灾情信息的收发与数据处理工作,并以“天地图”为地理底图实时直观地展示已上报的灾情信息。     

基于微信平台的水情报汛共享体系设计与实现

随着信息化技术的快速发展,传统的电话及网页人工报汛手段无法满足水文行业信息化发展的要求。结合移动互联网的发展趋势,将微信公众号平台与传统水情报汛相结合,通过微信平台实现了无层级、扁平化、可反馈的信息传输交流模式,并在用户体验、私人定制、可移动性、容错性、实时反馈等方面做了充分设计和优化,切实保障了水情报汛信息传输的"零中断",提升了水情报汛效率和精度,减少了报汛工作的时空限制,真正实现了"互联网+水情报汛"和高效、安全、个性化共享体系的建立。