广饶县海(咸)水入侵灾害防治的水文地质环境研究

广饶县咸水入侵灾害的发生在于自然环境的脆弱性和社会经济环境的严峻性。本文分析了引起海(咸)水入侵的基本矛盾, 制定了防治咸水入侵灾害的对策和措施──水文地质环境调整方案。     

汶川震区文家沟泥石流成灾机理与特征

文家沟位于绵竹市清平乡,属于 5 ·12 汶川Ms8.0级地震极重灾区。地震发生后的3个汛期内,文家沟曾先后发生5次典型泥石流灾害,其中以2010年8月13日泥石流灾害最为严重,规模与灾情巨大,社会影响深远。在对文家沟泥石流跟踪调查的基础上,探讨了泥石流的成灾机理和特征。研究表明:(1)文家沟泥石流是地震和强降雨共同作用的结果,其成因可归纳为震因与物源以及雨因与水源两个方面,在整个泥石流形成和发生的过程中,呈现出洪流-侵蚀下切-崩滑-席卷-进一步侵蚀下切-进一步崩滑-增大泥石流规模—……的"滚雪球式"循环过程; (2)泥石流发生所需的雨量、雨强条件和水动力条件都显著降低,泥石流规模和雨量之间呈现出明显幂函数关系; (3)发生过程呈现出持续时间长、运动距离远的特征; (4)成灾过程呈现出明显的链式效应,危害形式多样; (5)泥石流频率呈现出高发性,规模呈现出放大性。最后提出了文家沟泥石流研究与防治的建议。     

Equilibrium in natural catastrophe insurance market under disaster-resistant technologies,financial innovations and government interventions

Natural disasters increase in number and severity. Studies have shown the failure of the catastrophe insurance market by listing many causes or through developing economic models (Charpentier and Le Maux, 2014; Kousky and Cooke, 2012; Ibragimov et al., 2009). However, they have not considered the effect of the following factors on market equilibrium: advanced disaster-resistant technologies used by insureds, alternative financial innovations employed by insurers, and various disaster policies that are implemented by governments. To fill this gap, this study examines how these three factors affect the market equilibrium by changing the supply of, and demand for insurance and determines which factor(s) contributes to the market equilibrium. Furthermore, we derive the formula of position size which gives criteria for selecting index-based contracts. Overall annual numbers and insured losses of catastrophes are collected by peril type and by occurrence region listed in Sigma, which is issued by Swiss Re annually. The comparative static equilibrium analysis demonstrates that the improvement of market equilibrium is significant at low level of loss correlation in all cases. The empirical findings give insurers good references for business and geographical diversification in portfolio of catastrophe insurance policies.     

The N-policy of a discrete time Geo/G/1 queue with disasters and its application to wireless sensor networks

We analyze an N-policy of a discrete time Geo/G/1 queue with disasters. We obtain the probability generating functions of the queue length, the sojourn time, and regeneration cycles such as the idle period and the busy period. We apply the queue to a power saving scheme in wireless sensor networks under unreliable network connections where data packets are lost by external attacks or shocks. We present various numerical experiments for application to power consumption control in wireless sensor networks. We investigate the characteristics of the optimal N-policy that minimizes power consumption and derive practical insights on the operation of the N-policy in wireless sensor networks.     

The impact of disaster on the strategic interaction between company and government

A company allocates a resource between safety effort and production. The government earns taxes on production. The disaster probability is modeled as a contest between the disaster magnitude and the two players’ safety efforts. The model illustrates that safety efforts are strategic substitutes and inverse U shaped in the disaster magnitude. The company’s safety effort increases, and the government’s safety effort decreases, in taxation. Taxation can ameliorate companies’ free riding on governments’ safety efforts. With sufficiently large production, the government prefers, and the company does not prefer, raising taxation above 0%. For the government, an upper limit usually exists above which taxation cannot be profitably increased. The model shows how both or no players exert safety efforts when the disaster magnitude is small and large respectively, and how they free ride on each other’s safety efforts when the disaster magnitude is intermediate. The company free rides when the unit production cost is low so that the large profits outweigh the negative impact of the disaster. With endogenized taxation determined by the government, the tax rate decreases in the disaster magnitude, the unit production cost, the government’s unit cost of safety effort, and how the company is negatively affected by the disaster. The tax rate increases in the company’s resource and how the government is negatively affected by the disaster. The tax rate is weakly U shaped in the company’s unit safety effort. The model is illustrated with numerical examples and with the oil spill disasters by BP in 2010 and by Exxon Valdez in 1989.     

Using the Viable System Model (VSM) to structure information processing complexity in disaster response

Earthquakes, hurricanes, flooding and terrorist attacks continue to threaten our society and, when the worst happens, lives depend on different agencies to manage the response. The literature shows that there is significant potential for operational research (OR) to aid disaster management and that, whilst some of this potential has been delivered, there is more that OR can contribute. In particular, OR can provide detailed support to analysing the complexity of information processing – an essential topic as failure could cause response agencies to act on low quality information or act too slowly – putting responders and victims at risk. However, there is a gap in methods for analysing information processing whilst delivering rapid response. This paper explores how OR can fill this gap through taking a Viable System Model (VSM) approach to analyse information processing. It contributes to the OR literature by showing how VSM can support the analysis of information processing as well as how the OR modelling technique can be further strengthened to facilitate the task.     

Review of recent developments in OR/MS research in disaster operations management

Potential consequences of disasters involve overwhelming economic losses, large affected populations and serious environmental damages. Given these devastating effects, there is an increasing interest in developing measures in order to diminish the possible impact of disasters, which gave rise to the field of disaster operations management (DOM). In this paper we review recent OR/MS research in DOM. Our work is a continuation of a previous review from Altay and Green (2006). Our purpose is to evaluate how OR/MS research in DOM has evolved in the last years and to what extent the gaps identified by Altay and Green (2006) have been covered. Our findings show no drastic changes or developments in the field of OR/MS in DOM since the publication of Altay and Green (2006). Additionally to our comparative analysis, we present an original evaluation about the most common assumptions in recent OR/MS literature in DOM. Based on our findings we provide future research directions in order to make improvements in the areas where lack of research is detected.     

准连续调制激光吸收谱测量封闭室内O2浓度的研究

在开采煤矿的生产活动中,遇到煤矿爆炸或地震、地质等自然灾害,会导致坍塌、掩埋、堆积等情形,进而形成复杂的封闭环境。如果发生人员被困等突发情况,破灾救援、挽救生命工作显得至关重要。封闭环境中O₂的浓度随时间的变化直接威胁到被困人员的生命安全,及时掌握被困人员所处环境的O₂浓度变化对破灾救援机器人作业实施有着非常重要的指导意义。为准确测量O₂的浓度,以封闭室内O₂为研究对象,综合应用可调谐二极管激光吸收光谱(TDLAS)技术和波长调制光谱(WMS)技术,设计了一套准连续调制激光吸收谱实验测量O₂浓度系统,对24 h封闭室内O₂的浓度随时间变化情况进行测量研究。实验结果表明,封闭室内O₂的浓度受到室内人员活动的影响,准连续调制激光吸收谱测量方法可以准确测量封闭室内的氧气变化。     

On the principle of maximum entropy and the risk analysis of disaster loss

Disasters that occur everywhere in the most disordered way indicate that disaster entropy has reached the maximum value. Under given constraint conditions, when disaster entropy is the maximum value, the disaster loss series should follow P-III distribution. The occurrence interval of disaster loss refers to the average time interval that disaster loss of certain degree happens in the future. We could, according to the field disaster data and using P-III distribution function, calculate the value of future disaster loss with certain recurrence interval. Explicit in concept and easy to use, such a method has significant meaning in practice.     

Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods

The logistical deployment of resources to provide relief to disaster victims and the appropriate planning of these activities are critical to reduce the suffering caused. Disaster management attracts many organisations working alongside each other and sharing resources to cope with an emergency. Consequently, successful operations rely heavily on the collaboration of different organisations. Despite this, there is little research considering the appropriate management of resources from multiple organisations, and none optimising the number of actors required to avoid shortages or convergence.This research introduces a disaster preparedness system based on a combination of multi-objective optimisation and geographical information systems to aid multi-organisational decision-making. A cartographic model is used to avoid the selection of floodable facilities, informing a bi-objective optimisation model used to determine the location of emergency facilities, stock prepositioning, resource allocation and relief distribution, along with the number of actors required to perform these activities.The real conditions of the flood of 2013 in Acapulco, Mexico, provided evidence of the inability of any single organisation to cope with the situation independently. Moreover, data collected showed the unavailability of enough resources to manage a disaster of that magnitude at the time. The results highlighted that the number of government organisations deployed to handle the situation was excessive, leading to high cost without achieving the best possible level of satisfaction. The system proposed showed the potential to achieve better performance in terms of cost and level of service than the approach currently employed by the authorities.