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Assessment of Flood Losses with Household Responses: Agent-Based Simulation in an Urban Catchment Area

机译:利用家庭响应评估洪灾损失:城市集水区基于代理的模拟

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Densely populated coastal urban areas are often exposed to multiple hazards, in particular floods and storms. Flood defenses and other engineering measures contribute to the mitigation of flood hazards, but a holistic approach to flood risk management should consider other interventions from the human side, including warning information, adaptive behavior, people/property evacuation, and the multilateral relief in local communities. There are few simulation approaches to consider these factors, and these typically focus on collective human actions. This paper presents an agent-based model that simulates flood response preferences and actions taken within individual households to reduce flood losses. The model implements a human response framework in which agents assess different flood scenarios according to warning information and decide whether and how much they invest in response measures to reduce potential inundation damages. A case study has been carried out in the Ng Tung River basin, an urbanized watershed in northern Hong Kong. Adopting a digital elevation model (DEM) as the modeling environment and a building map of household locations in the case area, the model considers the characteristics of households and the flood response behavior of their occupants. We found that property value, warning information, and storm conditions all influence household losses, with downstream and high density areas being particularly vulnerable. Results further indicate (i) that a flood warning system, which provides timely, accurate, and broad coverage rainstorm warning, can reduce flood losses by 30-40%; and (ii) to reduce losses, it is more effective and cheaper to invest early in response measures than late actions. This dynamic agent-based modeling approach is an innovative attempt to quantify and model the role of human responses in flood loss assessments. The model is demonstrated being useful for analyzing household scale flood losses and responses and it has the potential to contribute to flood emergency planning resource allocation in pluvial flood incidents.
机译:人口稠密的沿海城市地区经常遭受多重危害,特别是洪水和暴风雨。防洪措施和其他工程措施有助于减轻洪灾危害,但整体的洪灾风险管理方法应考虑人为方面的其他干预措施,包括预警信息,适应性行为,人员/财产疏散以及当地社区的多边救济。很少有模拟方法来考虑这些因素,并且这些方法通常关注于人类的集体行动。本文提出了一种基于主体的模型,该模型可模拟洪水响应偏好和单个家庭在减少洪水损失方面采取的行动。该模型实施了一个人为应对框架,在该框架中,特工根据警告信息评估不同的洪水情境,并决定他们是否投资以及投入了多少资金来减少潜在的淹没破坏。在香港北部的城市化分水岭吴洞流域进行了案例研究。采用数字高程模型(DEM)作为建模环境和案例区域中住户位置的建筑图,该模型考虑了住户的特征及其居住者的洪水响应行为。我们发现财产价值,警告信息和暴风雨条件都会影响家庭损失,下游和高密度地区尤其容易受到伤害。结果进一步表明:(i)提供及时,准确和广泛覆盖的暴雨预警的洪水预警系统可以减少30%至40%的洪水损失; (ii)为减少损失,尽早投资于应对措施要比后期行动更为有效和廉价。这种基于代理的动态建模方法是一种创新的尝试,可以量化和建模人类响应在洪水损失评估中的作用。该模型被证明对分析家庭规模的洪水损失和响应非常有用,并且有可能有助于在洪灾事件中分配洪水应急计划资源。

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