基于HHM-RFRM-EOC模型的洪水风险定量评估与结构化表达

洪水灾害是世界上最严重的自然灾害之一，对洪水风险分析是减轻灾害损失和影响的重要途径。现有洪水分析方法缺少体系化流程，导致洪水应急时间紧迫、信息匮乏。为此本文提出一种基于分层全息建模（hierarchical holographic modeling，HHM）与风险过滤、评级与管理（risk filtering，ranking and management framework , RFRM）和要素-对象-结果模型（element-object-consequence，EOC）的暴雨洪水灾害风险识别、筛选与表达方法。首先，构建暴雨洪水人力、设备、环境、应急管理、信息五个方面风险辨识框架，确定出暴雨洪水系统初始风险要素。其次，基于RFRM方法理论将初始要素情景按照约束条件过滤，形成主要风险情景。之后，结合贝叶斯定理对暴雨洪水灾害进行定性和定量化评级，筛选暴雨洪水灾害的高危风险情景。最后，将暴雨洪水高危风险情景基于EOC风险概念模型参数化，并采用Protégé软件结构化表达。研究结果可以为暴雨洪水灾害应急决策提供辅助支持，为优化暴雨洪水灾害抢险救灾和防灾体系建设提供科学依据。

Flood Risk Analysis and Expression Based on HHM-RFRM-EOC Model

Flood disaster is one of the most serious natural disasters in the world. And flood risk analysis is an important way to reduce disaster loss and impact. The existing flood analysis methods lack systematic process, which leads to the urgent flood emergency decision-making time and the scarce information. To this end, an identification, screening and expression method of rainstorm and flood disaster risk based on hierarchical holographic modeling (HHM), risk filtering, ranking and management framework (RFRM) and element-object-consequence (EOC) model is proposed. Firstly, the risk identification framework of rainstorm flood manpower, equipment, environment, emergency management and information are constructed to determine the initial risk factors of rainstorm flood system. Secondly, based on the theory of RFRM method, the initial element scenarios are filtered according to the constraints to form the main risk scenarios. Then the rainstorm flood disaster is qualitatively and quantitatively rated by Bayes theorem, and the high-risk risk scenarios of rainstorm flood disaster are screened out. Finally, the flood high-risk scenario is parameterized based on EOC risk conceptual model and expressed structurally by protégé software. The research results can provide auxiliary support for flood disaster emergency decision-making, and provide scientific basis for optimizing storm flood disaster rescue and disaster prevention system construction.