大數據驅動的城市洪澇災害風險感知與預警決策研究范式

王慧敏 黃晶 劉高峰 佟金萍 曾慶彬

摘 要：城市洪澇災害防控是國家防洪安全的重大需求，更是城市公共安全管理的重要內容。如何利用大數據實現全信息融合、全過程管控、全社會參與的城市洪澇災害預警與全景式決策是國內外關注的前沿熱點和重點領域。本文從“跨界關聯、粒度縮放、全局視圖”視角出發，提出了大數據驅動的城市洪澇災害風險感知與預警決策研究范式，包括：利用天空地網多源異構數據信息，基于“數據驅動”的關聯關系挖掘與“模型驅動”的因果解析方法，感知暴雨洪澇情景態勢;建立基于暴雨洪澇情景的空間動態網絡風險研判模型，構建“觀測-感知-辨析”的城市洪澇災害動態預警模式;創建以數據為中心的扁平化城市洪澇災害管理框架，提出全景式災害應急合作響應與風險控制策略。

關鍵詞：大數據;城市洪澇;風險感知;預警;決策

中圖分類號：C93 文獻標識碼：A 文章編號：2097-0145（2022）01-0035-07 doi：10.11847/fj.41.1.35

Abstract：Urban flood disaster prevention and control is a major demand for national flood control and is also an important part of urban public safety management. How to use big data to achieve full information fusion， whole process control and participation of the whole society in urban flood disaster warning and panoramic decision-making is the frontier hotspot and key area of concern at home and abroad. From the perspective of “cross-border association， granularity scaling and global view”， this study proposes a research paradigm of big data driven urban flood disaster risk perception， early warning， and decision. Based on “data-driven” association mining and “model-driven” causality analysis method， multi-source heterogeneous data information of sky and earth network is used to perceive rainstorm and flood scenarios. The spatial dynamic network risk analysis model based on rainstorm and flood scenarios is established， and the “observation-perception-discrimination” urban flood disaster dynamic warning model is constructed. A data-centered flattened urban flood disaster management framework is established， and a panoramic disaster emergency cooperative response and risk control strategy is proposed.

Key words：big data; urban flood; risk perception; early warning; decision

1 引言

城市化、工業化的快速發展及人類生產生活方式的轉變，加劇了水資源壓力，顯著改變了降雨徑流、匯流路徑和方式等水文過程，水循環多過程的非一致性特征凸現[1，2]，表現為城市“雨島效應”凸顯、極端暴雨頻發，城市內澇升級，“逢雨必澇”、“城市看海”已成常態。北京“7.21”暴雨、武漢、深圳以及鄭州“720”特大暴雨，嚴重威脅了人民生命財產安全。據《中國水旱災害公報》數據顯示，近20年全國洪澇災害直接經濟損失年均1500多億元，占GDP的1.5%～2%;近10年年均損失高達2300多億元，災害損失呈顯著增長趨勢。……