地球信息科学学报 ›› 2020, Vol. 22 ›› Issue (2): 187-197.doi: 10.12082/dqxxkx.2020.190604

• 地球信息科学理论与方法 • 上一篇    下一篇

台风风暴潮情景构建与时空推演

饶文利1, 罗年学2,*()   

  1. 1. 北京辰安科技股份有限公司,武汉 430000
    2. 武汉大学测绘学院,武汉 430079
  • 收稿日期:2019-10-15 修回日期:2019-11-20 出版日期:2020-02-25 发布日期:2020-04-13
  • 通讯作者: 罗年学 E-mail:nxluo@sgg.whu.edu.cn
  • 作者简介:饶文利(1990— ),女,湖北武汉人,硕士,主要从事GIS产品研发。E-mail: 1194721378@qq.com
  • 基金资助:
    国家重点研发计划课题(2017YFC1405300)

Scenarios Construction and Spatial-temporal Deduction of Typhoon Storm Surge

RAO Wenli1, LUO Nianxue2,*()   

  1. 1. Beijing Global Safety Technology Company Limited, Wuhan 430000, China
    2. School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
  • Received:2019-10-15 Revised:2019-11-20 Online:2020-02-25 Published:2020-04-13
  • Contact: LUO Nianxue E-mail:nxluo@sgg.whu.edu.cn
  • Supported by:
    National Key Research and Development Project of China(2017YFC1405300)

摘要:

因台风风暴潮的突发性、情景演变时间的连续性和路径的不确定性,导致应急决策者在应急救援中难以做出正确决策,针对这一现状,将“情景—应对”应用在台风风暴潮应急决策中。本文在分析台风风暴潮情景、情景要素的概念模型基础上,首先通过资料搜集、属性识别等方法提取关键情景要素,采用框架表示法构建情景;然后分析台风风暴潮情景演变规律及演变路径;其次通过动态贝叶斯网络法构建台风风暴潮动态情景网络;最后利用先验概率与条件概率计算情景状态概率,实现了台风风暴潮的关键情景推演。本文以2018年9月16日11时至17时山竹台风对广东省沿海城市影响为例,演示了台风风暴潮的情景推演流程及关键技术。实证分析结果表明,溃堤、海水倒灌、洪水、滑坡发生的概率分别为85%、81%、74%、54%,验证了情景推演在风暴潮中应用的合理性。

关键词: 台风风暴潮, 情景要素, 框架表示法, 情景演变, 演变路径, 动态贝叶斯网络, 情景推演, 应急决策

Abstract:

Due to abruptness of typhoon storm surge, continuity of the evolution time and uncertainty of the path, it is hard for emergency decision-makers to make correct decisions in emergency rescue. To solve this problem, this article applies "scenario-response" to the typhoon storm surge. Firstly, based on the analysis of the typhoon storm surge scenarios and the conceptual model of the scenario elements, we extract the key scenario elements by means of data collection and attribute recognition. Then, we construct the dynamic scenario network of the typhoon storm surge by the method of frame representation. Secondly, we analysis the evolution and path of typhoon storm surge. Thirdly, we construct dynamic scenario network of typhoon storm surge with the dynamic Bayesian network method. Finally, we calculate the state probability of scenarios with the prior state probability and conditional probability and realize the key scenario deduction of the typhoon storm surge. In the end of the essay, we simulated an experiment for the influence of typhoon on the coastal cities of Guangdong Province from 11 to 17 on September 16 in 2018. The experiment results show that the probability of dykes, seawater inversion, floods and landslides respectively are 85%, 81%, 74%, 54%. The conclusion is drawn as follows: (1) The structure and content of each scenario element in the scenario construction process are different and interactional. Frame representation can reasonably characterize complex heterogeneous scenario elements data. (2) The evolution path of the situation is determined by many factors such as the situation itself, the disaster-bearing body, and emergency management. Decision makers need to comprehensively consider the emergency team and the rational use of resources when making decisions. (3) From the construction of the storm surge scenario to the deduction, the whole process has clear ideas and intuitive results, which is conducive to the promotion and application in marine disasters. The tentative application of "scenario-response" in storm surge events provides new emergency ideas and solutions for storm surge control.

Key words: typhoon storm surge, scenario elements, frame representation, scenario evolution, evolution path, dynamic Bayesian network, scenario deduction, emergency decision