GIS及模糊优选理论在尾矿坝选址中的应用

为了克服传统尾矿库选址方法的局限性,针对尾矿库选址过程中诸多因素与地理空间信息有关,部分决策指标又为不确定的模糊量的特点,研究了运用地理信息系统(GIS)获取若干待选坝址的样本集的可行性,并结合模糊综合优选理论,从定性到定量排序确定各选址决策指标和样本数据的优越度,实现了尾矿坝址方案的空间模糊优选.工程实例表明,该方法提高了尾矿库选址的综合决策量化水平和可视化程度.     

基于GIS的城市重大危险源选址研究

近年来,城市重大危险源的安全问题日益突出,对城市的健康安全发展构成了极大威胁,因此,如何进行城市重大危险源选址成为现代社会研究的重要内容。利用GIS空间分析技术,对影响重大危险源选址布局的空间信息进行处理,将道路图、土地利用规划图、城市遥感影像、城市基础设施等与城市区划图相结合,以获取适宜选址的可行域。利用模糊综合评价理论,选出影响选址的因素集和评语集,通过模糊运算评判可行域,并由实例验证了该选址方法,最终得出城市重大危险源最优选址方案。因此,进行城市重大危险源的选址研究具有现实可行的意义,有助于提高城市的整体安全水平。     

基于区间数信息的区域应急物资储备库选址多目标决策模型

应急物资储备库选址决策是区域应急物资储备体系建设中的重要问题之一。该文研究了基于区间数的区域应急物资储备库选址问题的模糊多目标决策方法,给出了区间数的概念和排序规则,构建了约束条件中含有区间数的区域应急物资储备库选址问题的模糊多目标规划模型,提出了求模型满意解的算法,最后通过算例分析说明该方法的有效性。     

突发事件下大规模人员临时应急避难所的选址研究

近年来突发事件时有发生,人员紧急疏散显得日益重要。本文研究了突发事件下人员临时应急避难所的选址问题,基于单一指派约束和容量约束的设施选址问题(SSCFLP)研究基础,假设疏散时间随机和选址网络随机,考虑一个星期和一天中不同时间段疏散人员数量不同的现时情况,建立临时应急避难所选址模型,并采用启发式算法进行求解,确定临时应急避难所的数量和位置,并通过实例验证模型的可靠性。将人群聚集在临时应急避难所等待救援,可以节约救援车辆等资源,大幅减少疏散时间,提高人员应急疏散效率。     

多约束多目标的灾害避难所选址优化研究——以海南省文昌市为例

地震灾害避难所优化选址是灾害管理的一个重要内容,也是个难点。以最小化总疏散距离和最小化避难所总面积为目标,同时在满足距离约束和容量约束的条件下,建立地震灾害避难所选址多目标模型,采用改进的粒子群算法对模型进行解算,并以海南省文昌市为例进行实证分析。结果表明:距离约束在多目标模型的空间分配结果中起主导作用,容量约束则会显著影响多目标模型及其算法在高维复杂问题中的空间搜索能力和解的质量。优化结果可为灾害避难所区位的确定及疏散方案的制定提供科学依据,为震后应急疏散提供决策支持。     

基于博弈论的突发性水污染事件治污决策模型

针对当前严重的水污染问题,采用博弈论对突发性水污染事件治污决策进行了研究,为事件应急管理提供理论支撑与决策支持。基于经典博弈论构建了信息不对称下突发性水污染事件中管理部门与企业之间的信号博弈模型,对信号发送方企业的类型空间、信号空间和信号接收方管理部门的行动空间进行假设,求得了模型的精炼贝叶斯均衡解,并对不同参数取值下的均衡解进行了分析。基于有限理性建立了企业群治污决策进化博弈模型,通过求解模型复制动态方程得到了不同参数取值下的进化稳定策略,并对模型进化趋势进行了分析。结果表明:对突发性水污染事件进行治污决策时,通过公开企业信息与信誉,提高对企业是否采取治污策略的奖惩力度,采用现代先进信息技术降低企业治污与管理部门检查的成本等方式有助于企业采取治污策略。     

城市防灾减灾设施的层级选址问题建模

提出了城市防灾减灾设施的层级选址问题,并对其进行了分类.针对高低级设施相对独立和相互从属的层级选址问题进行了建模.依据城市防灾减灾设施选址问题的特点,提出了两阶段的层级选址过程:(1)使用位置集合覆盖模型确定能覆盖全部需求点所必需的最少设施数量和位置,作为基本等级设施的选址;(2)对独立型层级选址问题,使用最大覆盖准则确定高级设施的位置,对从属型层级选址问题,使用极小和准则确定高级设施的位置.对层级选址问题模型的应用进行了讨论.     

供水管网水质监测点选址风险研究

饮用水足否安全，是近年来社会各界普遍关注的问题之一。供水管网的水质监测是保证供水安全、降低水污染风险的重要环节。然而，如何合理选择水质监测点，至今尚无科学的方法。往定义供水管网水质监测点选址风险度的基础上，结合某供水管网，利用二进制编码的微粒群算法埘供水管网水质监测点选址的风险问题进行了研究，可以帮助决策者科学地选择优化的水质监测点。     

基于理想点的已知部分属性权重信息中心避难场所选址方法研究

从场所用地安全性、场所规模和防救灾设施3个方面归纳了城镇中心避难场所选址9个评价指标,并给出了各项指标的评价标准。提出了基于理想点的已知部分属性权重信息的中心避难场所选址单目标最优化模型,该模型遵循悲观准则,降低了决策风险且求解简单。最后,以某市中心避难场所选址为例,验证了模型的适用性。     

应急避难场所选址最大准备度覆盖模型及其算法

应急避难场所的选址是应急规划的关键职能。当前的应急规划往往是依据现有的公园、绿地、广场等来选择应急避难场所,难以满足实际应急疏散的需要。目前不少学者在最大覆盖选址模型的基础上提出了应急设施选址问题的相关模型。将准备度指标引入最大覆盖应急设施选址问题,综合考虑需求量、与设施的距离和距离决定的权重,对每个社区的应急服务覆盖程度进行量化,从而保证将应急避难场所设置在合理的位置。为了求解该模型,构建了多智能体进化算法。案例研究表明,该算法可以高效地求解最大准备度覆盖模型。     

Exploring the administrative mechanism of China's Paired Assistance to Disaster Affected Areas programme

The Paired Assistance to Disaster Affected Areas (PADAA) programme is a mutual aid initiative with Chinese characteristics, which speeded up the process of restoring and reconstructing regions affected by the Wenchuan earthquake on 12 May 2008. 1 The PADAA is an efficient instrument for catastrophe recovery, yet it remains a mysterious mechanism to many members of disaster management communities. This paper aims to lift the veil on it by assessing its origins and evolution. It draws on the multi‐level moderated competition model to explain how the PADAA functions within the Chinese administrative system. The country's top‐down political system allows the central authority to mandate provincial and local governments from more economically developed regions to assist devastated areas with post‐disaster reconstruction. The practices of local accountability complement vertical control by giving leaders from donor regions strong incentives to accomplish assigned reconstruction tasks, resulting in intense competition between them.     

Lessons from a microfinance recapitalisation programme

Following a major disaster, microfinance institutions (MFIs) often face high levels of bad debt, which may require the institutions to be recapitalised. This paper describes a recapitalisation programme implemented by the SANASA movement of Sri Lanka in 390 microfinance societies following the December 2004 tsunami, and highlights lessons for other similar programmes. MFI recapitalisation is a good use of funds in post‐disaster situations. To create successful programmes, donors should expect to relax some of their usual project requirements and MFIs should focus on maintaining credit discipline.     

Insuring against earthquakes: simulating the cost‐effectiveness of disaster preparedness

Ex‐ante measures to improve risk preparedness for natural disasters are generally considered to be more effective than ex‐post measures. Nevertheless, most resources are allocated after an event in geographical areas that are vulnerable to natural disasters. This paper analyses the cost‐effectiveness of ex‐ante adaptation measures in the wake of earthquakes and provides an assessment of the future role of private and public agencies in disaster risk management. The study uses a simulation model approach to evaluate consumption losses after earthquakes under different scenarios of intervention. Particular attention is given to the role of activity diversification measures in enhancing disaster preparedness and the contributions of (targeted) microcredit and education programmes for reconstruction following a disaster. Whereas the former measures are far more cost‐effective, missing markets and perverse incentives tend to make ex‐post measures a preferred option, thus occasioning underinvestment in ex‐ante adaptation initiatives.     

Cyclone preparedness and response: an analysis of lessons identified using an adapted military planning framework

The United Kingdom uses the Defence Lines of Development (DLOD) framework to analyse and understand the key components and costs of a military capability. Rooted in the Resource Based View (RBV) of a firm, an adapted DLOD approach is employed to explore, analyse and discuss the preparedness, planning and response strategies of two markedly different countries (Australia and Bangladesh) when faced with a major cyclone event of a comparable size. Given the numerous similarities in the challenges facing military forces in a complex emergency and humanitarian agencies in a natural disaster, the paper demonstrates the applicability of the DLOD framework as an analysis and planning tool in the cyclone preparedness planning and response phases, and more broadly within the disaster management area. In addition, the paper highlights the benefit to disaster managers, policymakers and researchers of exploiting comparative cross-learning opportunities from disaster events, drawn from different sectors and countries.     

Learning from the rubble: the case of Christchurch,New Zealand,after the 2010 and 2011 earthquakes

Learning after a disaster is crucial in creating more resilient places. However, many societies are repeatedly overwhelmed by disasters. This can be because of missed opportunities to learn in post‐disaster settings or because of actions implemented that seem to be highly relevant to recovery in the short term, but potentially constrain aspirations in the longer term. This paper assesses learning processes among state and non‐state actors and the ways in which these are bridged and scaled up to wider improvements in governance. Aiming to enrich understanding of post‐disaster learning, it explores different actors’ response actions after the earthquakes in Christchurch, New Zealand, in 2010 and 2011. On the one hand, ‘learning by doing’ is occurring, yet, on the other hand, systemic learning is hindered by mismatches between top‐down steering and bottom‐up initiatives. The study concludes that better linking and synergising of learning processes among different levels is vital for enhancing resilience in post‐disaster societies.     

Building community resilience: business preparedness lessons in the case of Adapazarı, Turkey

The lack of attention paid to businesses in disaster management systems from the standpoint of state policies hampers efforts to build community resilience. This paper examines, therefore, the extent of business preparedness for disasters. Empirical research was conducted in Adapazarı, Turkey, 13 years after the İzmit earthquake, which struck the northwest of the country on 17 August 1999, claiming the lives of some 17,000 people. For the study, 232 firms were selected to inquire about their preparedness before and after the event. It is hypothesised that business preparedness is influenced by the following set of variables: business size; business sector; business age; financial condition prior to the disaster; occupancy tenure; market range; education level; and previous disaster experience. In line with the findings of the research, a policy framework is constructed to rationalise the allocation of resources for building resilience at the aggregate level by facilitating business preparedness.     

西藏古乡沟泥石流模型试验研究

通过模型试验，研究不同类型（粘性、稀性、水石流）和不同规模（Ｐ＝２％、４％）的泥石流在古乡沟堆积扇上的运动和冲淤规律，同时进行防治工程模型试验研究，结合野外调查和资料对比，选择合理的防治工程方案，为工程设计提供可靠的依据和数据。本文结论对川藏公路与古乡沟类似灾害的整治有一定的参考价值     

Assessing the impact of household participation on satisfaction and safe design in humanitarian shelter projects

Participation has long been considered important for post‐disaster recovery. Establishing what constitutes participation in post‐disaster shelter projects, however, has remained elusive, and the links between different types of participation and shelter programme outcomes are not well understood. Furthermore, recent case studies suggest that misguided participation strategies may be to blame for failures. This study analysed 19 shelter projects implemented in the Philippines following Typhoon Haiyan in November 2013 to identify the forms of participation employed. Using fuzzy‐set qualitative comparative analysis, it assessed how household participation in the planning, design, and construction phases of shelter reconstruction led to outcomes of household satisfaction and safe shelter design. Participation was operationalised via eight central project tasks, revealing that the involvement of households in the early planning stages of projects and in construction activities were important for satisfaction and design outcomes, whereas engagement during the design phase of projects had little impact on the selected outcomes.     

Temporary disaster debris management site identification using binomial cluster analysis and GIS

An essential component of disaster planning and preparation is the identification and selection of temporary disaster debris management sites (DMS). However, since DMS identification is a complex process involving numerous variable constraints, many regional, county and municipal jurisdictions initiate this process during the post‐disaster response and recovery phases, typically a period of severely stressed resources. Hence, a pre‐disaster approach in identifying the most likely sites based on the number of locational constraints would significantly contribute to disaster debris management planning. As disasters vary in their nature, location and extent, an effective approach must facilitate scalability, flexibility and adaptability to variable local requirements, while also being generalisable to other regions and geographical extents. This study demonstrates the use of binomial cluster analysis in potential DMS identification in a case study conducted in Hamilton County, Indiana.     

Understanding recovery of small enterprises from natural disaster

This study, carried out among 251 small-scale firm owners by means of a cross-sectional survey, attempted to identify the factors affecting business recovery from disaster in a flood-prone area of Bangladesh. We selected the participants by using a convenience sampling technique, taking into consideration the characteristics of the firms, and the various enabling- and disaster-impact factors needed to identify those factors significant to business recovery from natural disaster. Results demonstrated that more than three-quarters (87.3%) of owners recovered their firms after disaster. Multivariate logistic regression analyses revealed that a total of six variables had a significant impact on business recovery: two variables pertaining to the firms’ characteristics, namely, retail firms (OR?=?0.147, P?<?0.05) and the number of employees >4 (OR?=?0.094, P?<?0.01); two variables pertaining to enabling factors, namely, receiving loans (OR?=?0.232, P?<?0.01) and the perception of recovery (OR?=?16.178, P?<?0.01); and two variables pertaining to disaster-impact factors, namely, an income loss amounting to >BDT 2000 (OR?=?7.395, P?<?0.05) and permanent or temporary relocation of the market (OR?=?9.252, P?<?0.001). Results further demonstrated that almost equally half of the owners recovered their firms immediately or within 7 days after disaster (50.9%); the remaining 49.1% took longer. Multivariate analyses, on the other hand, significantly identified three characteristics, namely, 6–10 years of business operation (OR?=?0.267, P?<?0.01), 2–4 employees (OR?=?0.1.822, P?<?0.01), and a monthly income of BDT 5001–7500 (OR?=?4.167, P?<?0.01); two enabling factors, namely, institutional education (OR?=?0.400, P?<?0.05) and awareness of disaster assistance (OR?=?0.607, P?<?0.05); and two disaster-impact factors, namely, loss of human resources (OR?=?6.293, P?<?0.05) and interrupted supply of raw materials (OR?=?4.741, P?<?0.05). We concluded the study with discussions of a few policy implications.