风沙灾害风险评估研究进展

风沙灾害是气象灾害的重要组成部分,具有影响范围大、季节性强、灾害损失大等特点,已成为中国北方沙区的生态灾难,严重影响人居环境和社会经济的可持续发展。为了评估风沙灾害对中国社会经济的影响,已有学者对中国风沙灾害问题进行了长期研究,但对区域风沙灾害风险系统评估研究相对较少,尚未建立系统的风沙灾害风险评价体系。在综合分析近30年相关文献的基础上,借鉴其他自然灾害评估方法,从风沙灾害风险评估理论内涵、评估指标及评估方法等方面对相关研究进行了全面的分析,指出目前风沙灾害风险评估还存在理论不完善、评估模型不合理、孕灾环境指标量化不细致和指标体系繁杂、风险评估方法单一、指标分级和权重计算的主观性强、社会经济数据不能空间化等问题。因此,未来在风沙灾害评估研究时需借鉴、引入和融合其他自然灾害风险评估理论和技术方法,综合近年来在风沙物理学、风沙地貌学、防沙治沙工程学、沙漠化遥感技术和理论等方面的成果,建立多指标的综合风沙灾害评估模型,为预防区域风沙灾害、降低风沙灾害损失和保障"一带一路"经济发展提供理论依据。     

多灾种综合风险评估软层次模型

在复杂的灾害风险系统中,风险并非简单相加,但目前的研究成果基本是单一灾种简单相加得到的综合风险,缺乏可靠性。因此,此研究基于灾害风险系统理论,引入模糊信息粒化方法和模糊转化函数,利用模糊近似推理理论和方法,建立一个多灾种综合风险评估软层次模型。研究表明该模型的优势：1）不仅考虑了灾害风险系统中的确定性,而且还包括了随机不确定性和模糊不确定性;2）利用模糊信息粒化方法不仅减少了数据的不确定性,而且还包括了一些主观信息,使得评估结果更加接近实际,理论与实际紧密结合,更有利于风险管理者和决策者为减少损失规避风险提供依据;3）通过模糊转化函数将不同灾种得到的不同量纲的量转化同一量纲的量,以便于综合分析和模糊近似推理,获得多灾种综合风险。以云南省丽江地区（市）的地震－洪水灾害为例,验证多灾种综合风险评估软层次模型的实用性,并将其结果与世界银行灾害管理中心和哥伦比亚大学灾害和风险研究中心所建议的风险评估模型（HMU－CHRR模型）的结果进行比较分析,讨论了本研究所建模型在多灾种综合风险评估中的特点。     

沿海区域水灾脆弱性及风险的的初步分析

在理清自然灾害风险系统构成的基础上,总结其风险评估的三种方法:基于历史数据、指标体系和情景模拟。文章采用由果及因的演绎思路,据历史灾情参考全球尺度灾害风险评估国际计划做脆弱性的评估,探讨水灾脆弱性的区域分异规律,并分析其社会经济因素。由于历史数据局限,引入信息扩散的模糊数学方法,对沿海各省区的受灾率进行风险评估,并将区域风险与脆弱性的次序进行对比,表明:脆弱性是风险的重要组分,减少脆弱性可有效降低风险,但探寻灾害发生规律、降低人类社会的暴露性,也是减少灾害风险的必要环节。     

基于信息扩散理论的气象灾害风险评估方法

基于信息扩散理论提出直接估计低温冷害、干旱和洪涝的风险评估方法,以低温冷害为例,将计算结果与风险指数法和主观频率法做比较.直接估计灾害风险具有:(1)计算过程简单,所需资料少;(2)可对灾害不同级别进行风险评估,利于进行灾害风险评价和区划;(3)此方法可触类旁通,应用到其它自然灾害风险评估;(4)此方法需要的资料年限短等优点,对开展乡(镇)级小区域自然灾害风险评估有借鉴作用.     

区域突发公共事件风险综合评估的多源数据PHV集成模型构建与应用

测度区域突发公共事件风险的综合特征及分区是当前乃至今后中国应急管理提高预判性与可操作性面临的重大课题。基于区域灾害系统理论和风险概念,集成可能性、危害性、脆弱性等风险要素,尝试构建了用于区域风险综合评估的PHV集成模型（Possibility, harmfulness, vulnerability integrated model）,同时,依评价指标引导,构建“新闻+空间+统计”的多源数据接口,在公里网格尺度,测算了多灾种叠加的风险可能性、危害性、脆弱性和综合风险水平,并以内蒙古阿拉善盟为案例检验。结果显示：(1)模型以灾害事件发生概率做灾害事件综合的权重,将风险损失纳入危害性指数测算,识别风险易发地并纳入可能性指数测算,克服了以往研究权重设置不合理、灾害影响程度量化途径单一的“瓶颈”;(2) PHV模型和多源数据的方法,可以实现大尺度区域灾害数据缺失情况下的多灾种综合风险评估,具有一定的应用推广价值。     

基于多智能体的自然灾害动态风险评估模型

将多智能体建模方法引入灾害风险评估领域,以期为灾害风险评估开拓新的研究思路.区别于一般静态评估模型,基于多智能体的风险评估模型自下而上,从微观上建立灾害系统各要素之间的相互关系,在多风险情景下,仿真模拟灾害系统状态的变化,以实现动态的风险评估.在理解多智能体建模的一般原理的基础上,设计了基于多智能体的自然灾害动态风险评估的总体模型和主要智能体的结构,并总结了多智能建模在风险评估方面的优势.     

自然灾害风险评估与分级方法论探研——以山西省地震灾害风险为例

自然灾害发生的可能损失一直是灾害风险评估上的难题.本研究以自然灾害风险评估经典模型为基础,提出了新的自然灾害风险评估与风险等级划分方法,利用历史灾情和孕灾环境解决风险评价中致灾因子破坏力与灾害发生的可能,并以山西省地震灾害风险为例进行了定量化评估研究.主要改进在于:确定灾害损失率和环境参数以建立地震灾害可能损失计算模型...     

基于小尺度的城市暴雨内涝灾害情景模拟与风险评估

自然灾害情景模拟与风险评估是灾害研究的核心内容和热点问题之一,但城市自然灾害风险评估至今却缺乏统一的程序与范式。本文选择了城市频发的暴雨内涝灾害为研究对象,结合上海市静安区实证研究,提出了一套基于小尺度的城市暴雨内涝灾害风险评估的思路与方法。基于灾害风险的基本理念,从致灾因子分析、脆弱性分析和暴露分析三方面入手,探讨不同情景下的小尺度城市暴雨内涝灾害情景模拟与风险表达方式;提出了小尺度城市暴雨内涝灾害风险评估宜采用情景模拟和综合分析方法,充分考虑城市的内部地形特征、降水、径流和排水等因素,创建一个基于GIS栅格的城市内涝模型,并基于多种重现期灾害情景,更客观地模拟内涝积水深度和淹没面积;采用多次实地调查获得的内涝损失数据,拟合出居民房屋和室内财产的灾损曲线;利用灾损曲线评估脆弱性、暴露要素和损失,建立超越概率-损失曲线,创建了基于GIS栅格城市暴雨内涝灾害的风险评估模型与范式,为制订城市暴雨内涝灾害风险管理和规划奠定了基础。这亦为进一步开展小尺度城市自然灾害情景模拟和风险评估研究提供了一种新探索。     

基于随机森林模型的山区铁路线暴雨洪灾风险评估——以朔黄铁路原平段为例

随机森林决策树分裂易受数据集不平衡性及变异性的影响,导致权重分配和预测结果出现偏差。山区洪灾风险评估影响因素众多、数据差异性大,如何降低数据不平衡性以及变异性的影响,直接关系各因素重要性的科学排序以及评价结果的准确性。该文依据流域灾害系统理论,从致灾因子和孕灾环境选取9个风险指标,构建山区铁路洪灾风险评估数据集,在此基础上,分别采用基于Gini指数和Sigmoid函数两种分裂方式的随机森林模型进行对比分析,之后采用最优模型对朔黄铁路原平段沿线洪灾风险进行预测,并利用实地调研结果对预测结果进行验证。研究发现：地形要素(高程、坡度、坡向)与洪灾风险密切相关,孕灾环境作为产生暴雨洪灾风险的内因,在山区铁路洪灾风险评估中起决定性作用;基于Sigmoid函数分裂方式的随机森林模型在分裂过程中可以降低信息不纯度和数据变异性对结果的影响,精度更优,预测结果与实际吻合度较高,方法适用性较强。研究成果可为山区铁路暴雨洪灾风险评估提供方法参考。     

灾害链风险评估的概念模型——以汶川5·12特大地震为例

大量事实表明,每发生一种重大灾害总会诱发一系列次生灾害,形成破坏力远超单一灾种的灾害链现象.要有效防范灾害链风险,理清其形成过程、构建其评估模型是前提.在梳理国内外链式风险评估概念模型的基础上,结合“5·12”汶川特大地震灾害链案例,初步提出灾害链风险评估的概念模型.①孕灾环境敏感性是致灾因子链发的重要影响因素,决定灾害链风险的链发概率,确定影响孕灾环境敏感性的因素及定量关系是评估关键;②灾害链中承灾体重复受灾导致脆弱性增大,脆弱性变化评估的引入将提高灾害链风险评估结果的精度.本文旨在为完善区域灾害系统理论,进一步推动灾害链风险防范提供依据.     

Spatial Characteristics of Regional Wildfire Frequencies in Intermountain West Grass-Dominated Communities

Understanding the environmental factors that influence spatial patterns of rangeland wildfires facilitates both fire and land management decisions. I used discriminant analysis to examine ignition frequency of lightning-initiated fires in grass-dominated communities in the Intermountain West between 1980 and 1994, then mapped regional fire frequencies to illustrate spatial patterns. Two canonical discriminant functions effectively separate groups of high, medium, and low ignition frequencies, based on climate conditions and fuel characteristics. Regions of highest frequency tend to have large elevational differences, more mesic climates, and less annual grass cover. Spatial patterns of ignition frequencies tend to reflect local topography, with higher frequencies west of 119° W. Expansion of exotic annual grasses throughout the region may be reducing differences in ignition frequency between regions of highest and lowest frequency.     

Spatial Characteristics of Regional Wildfire Frequencies in Intermountain West Grass-Dominated Communities

Understanding the environmental factors that influence spatial patterns of rangeland wildfires facilitates both fire and land management decisions. I used discriminant analysis to examine ignition frequency of lightning-initiated fires in grass-dominated communities in the Intermountain West between 1980 and 1994, then mapped regional fire frequencies to illustrate spatial patterns. Two canonical discriminant functions effectively separate groups of high, medium, and low ignition frequencies, based on climate conditions and fuel characteristics. Regions of highest frequency tend to have large elevational differences, more mesic climates, and less annual grass cover. Spatial patterns of ignition frequencies tend to reflect local topography, with higher frequencies west of 119° W. Expansion of exotic annual grasses throughout the region may be reducing differences in ignition frequency between regions of highest and lowest frequency.     

Social,Institutional, and Psychological Factors Affecting Wildfire Incident Decision Making

Managing wildland fire incidents can be fraught with complexity and uncertainty. Myriad human factors can exert significant influence on incident decision making, and can contribute additional uncertainty regarding programmatic evaluations of wildfire management and attainment of policy goals. This article develops a framework within which human sources of uncertainty in wildfire management can be classified and managed, specifically identifying social, institutional, and psychological factors that can affect wildland fire incident decision making. These factors are reviewed in the context of wildland fire incident management and the literature regarding fire manager decision making. I then provide specific recommendations for addressing these issues, with a focus on improving incident decision processes. Extending this framework to consider a broader set of human factors and to consider how human factors affect the broader wildfire management spectrum could lead to improved fire management outcomes.     

Earth,Wind, and Fire: Wildfire Risk Perceptions in a Hurricane-Prone Environment

Wildfire is one of several potential disturbances that could have extraordinary impacts on individuals and communities in fire-prone areas. In this article we describe disturbance risk perceptions from interviews with residents in three Florida communities that face significant wildfire and hurricane risk. Although they live in areas characterized by emergency managers as having high wildfire risk and many participants have direct experience with wildfire, residents tended to share high hurricane and low wildfire risk perceptions. The different perceptions of risk seem linked to several factors: direct hurricane experience, different scales of impact, the local “hurricane culture,” effectiveness of local ordinances and development patterns, perceived predictability of the event, and perceived ability to control the event. This study shows that residents may perceive and act to reduce risk for one disturbance in relation to their perceptions, concern, and actions for another.     

Wildfire mitigation behavior on single family residential properties near Balcones Canyonlands Preserve wildlands in Austin,Texas

Wildfires have become an increasingly important issue in central Texas as more people move to the wildland-urban interface. Although mitigation can reduce the risk of damage from wildfire, not all homeowners choose to mitigate. Using the area surrounding the Balcones Canyonlands Preserve wildlands in Austin, Texas as a case study, this research examined the factors that lead to homeowners' decisions to or not to mitigate for wildfires. In particular, this study examined the difference between behavioral intention and behavior relating to wildfire mitigation.Study methods included a mail survey of residents living in subdivisions adjacent to the Balcones Canyonlands Preserve wildlands. This study adopted the Theory of Planned Behavior (TPB) as the conceptual framework to explain homeowners' behaviors and intentions. Statistical analysis was performed on survey responses relating to the conceptual variables in the TPB model. The Intention model indicated that Attitude was the most important variable (40.6% of total variance) relating to Intention, followed by Subjective Norm (10.1%), and Behavioral Control (1.3%). Risk Perception and Residency explained an additional 2.2% of the total variance.The Behavior models indicated that only Intention and Subjective Norm were predictors for Mitigation Behavior 1 (keeping gutters and roof free of leaves, needles, and branches), only Intention and Behavioral Control were predictors for Mitigation Behavior 2 (keeping tree limbs pruned at least 10 feet from the roof), and only Intention was a predictor for Mitigation Behavior 3 (keeping dead vegetation cleared within 30 feet of the house). The models explained 52.4% of the variance in performance of Mitigation Behavior 1, 38.9% in Mitigation Behavior 2, and 42.2% in Mitigation Behavior 3. The models were better at predicting respondents who did perform mitigation behaviors compared with those who did not.     

Thinking about Fuel Management: The Potential of Integrative Complexity Theory to Inform Design of Communication about Fuel Management Used To Reduce Wildfire Risk

Multiple studies have examined ‘what’ people think about fuel management (perceptions); fewer have examined ‘how’ people think about it (structure of thoughts). In an Australian study, we used Integrative Complexity Theory (ICT) to explore the relationship between how complexly people thought about, and how acceptable they found, three fuel management strategies: prescribed burning, mechanical thinning and livestock grazing. Integrative complexity (IC) was associated with the direction of acceptability of the most familiar practice - prescribed burning, but trust in organizations was associated with acceptability of all strategies. IC was associated with the extremity of acceptability, with higher IC associated with more moderate attitudes. Our findings support the argument that targeting communication to (i) match current IC and (ii) encourage growth in complexity of thinking has potential to encourage more moderate and stable attitudes about fuel management.