| 摘要: |
| 针对滨海城市雨洪灾害“孕灾机制复
杂、风险暴露度高、承载体脆弱”等典型特征，
应用多源数据与智能分析的雨洪灾害智慧识别
技术，提出了多尺度规划协同的韧性防灾布局的
规划思路，建构了应对滨海城市雨洪灾害的“宏
观—中观—微观”多尺度智慧—韧性海绵城市
规划方法。结合闽三角城市群—厦门市—杏林
湾片区三个典型尺度，进行规划应用探索，包括
流域—城市群层面的孕灾环境与承载体脆弱性
解析、区域生态海绵系统格局建构，城市层面的
雨洪脆弱性评价、承洪韧性空间结构布局、土
地利用规划与避灾场所布局，街区层面的分单元
差异化承洪韧性规划设计及雨洪风险智慧监测
与导控，为滨海城市雨洪灾害的智慧识别与韧性
防控提供系统化的理论方法及实践应用支持。 |
| 关键词: 滨海城市 雨洪灾害 智慧识别 韧性防控 多尺度 |
| DOI：10.13791/j.cnki.hsfwest.20220610 |
| 分类号: |
| 基金项目:国家自然科学基金项目(52078330)；天津大学自主创
新基金项目（2021XSC-0129）；中国博士后科学基金
（ 2022M722403）；天津市哲学社会科学规划项目
（TJGL21-013） |
|
| Planning Method of Coastal City Rain Flood Disaster Prevention and Control Based on the Concept of Intelligence-Resilience |
|
TIAN Jian,ZENG Suiping,ZENG Jian,DING Siyuan,WANG Qianwen
|
| Abstract: |
| In view of the typical characteristics of coastal city rain flood damage, such as
“complex mechanism of disaster formation, high risk exposure and fragile carrier”, this paper
proposes the intelligent identification technology of rain flood damage by introducing multisource data and intelligent analysis, and the planning idea of resilient disaster prevention layout
based on sponge city. The intelligent identification technology of flood damage in coastal
cities includes the collection and processing of flood damage data based on multi-source data,
the calculation and feature induction of flood risk based on intelligent analysis. The first is to
collect and process the flood damage data of coastal cities based on multi-source data. Through
DEM data, hydrologic data and other comprehensive calculation, the catchment area is divided.
Combined with soil underlying surface database and coastal rainfall and flood meteorological
database, the database of catchment area and hydrological response unit including disastercausing factors, disaster-inducing environment and carrier characteristics was constructed
comprehensively. Then based on the intelligent analysis technology, the storm flood risk of
coastal cities is calculated and the spatial distribution characteristics are summarized. Multifactor data such as land surface, topography, hydrology, meteorology, water source, social
economic value and ecological service value were superimposed and analyzed. After unified
data grid and colinear detection, machine learning were used to train and calculate the risk
value of urban rain flood damage and the contribution rate of rain flood risk factors, so as to
analyze the spatial characteristics and cause laws of coastal city rain flood risk based on GIS
platform.
The resilience prevention and control of coastal city flood damage mainly includes three
aspects. The first is to construct the ecological security pattern of “mountain-water-sea-city”,
strengthen the ecological conservation of the upper reaches, improve the urban blue-green
ecological network, and reduce the oppression of urban construction land on the coastal zone.
The second is to improve the stormwater storage capacity of the inner space of the city through
semi-natural treatment, such as grass ditches, rain gardens, sunken green spaces and roof
greening. The third is to improve the design standard of urban drainage system and improve
the drainage capacity of local areas. In addition, it also includes the construction of information
platform to support sponge city management and risk monitoring. At the same time, thecoordination of multi-scale planning should be strengthened to construct a “macro-meso-micro” multi-scale intelligent and resilient planning method
to deal with coastal cities’ flood damage. On the one hand, macro scale measures such as climate regulation, watershed ecological conservation and
coastal zone ecological security pattern construction should be taken to reduce the impact force of storm floods. On the other hand, based on the
differences of disaster risk identification accuracy and corresponding spatial planning level at different mesoscale and micro scales, the targeted
contents of flood risk identification and resilience planning were formed respectively. Through multi-scale collaborative governance, coastal cities
will be enhanced in the prevention and control of rain and flood damage.
Combined with the three typical scales of Fujian Triangle urban agglomeration-Xiamen City-Xinglinwan area, the application of planning
practice is explored. At the macro level, the vulnerability of disaster-bearing environment and carrier of watersheds and urban agglomerations in
Fujian Triangle was analyzed, and the pattern of regional ecological sponge system was constructed. By utilizing the ecological function of coastal
natural sponge space, and strengthening ecological conservation and landscape restoration projects, the storm flood regulation function of watershed
and urban agglomeration ecosystem will be brought into full play. At the middle level, the vulnerability of urban rain flood was evaluated in Xiamen
City, the first-level disaster prevention zones were delineated, and the spatial layout of lifeline of urban rain flood disaster prevention was proposed.
On this basis, urban storm flood resilience disaster prevention spatial structure is formed, which provides support for urban ecological sponge spatial
layout and shelter system layout. At the micro level, differentiated planning strategies for low impact flood resilience of different catchment units in
Xinglinwan District were developed. For example, the standard of roof greening and permeable pavement transformation should be strengthened
in old communities, the construction standard of sunken green space and rainwater garden should be improved in new communities, and the
construction standard of biological retention layer in waterfront open space is relatively higher. At the same time, the intelligent information system
of flood damage in urban area is established.
In conclusion, the research results integrate multi-source data and intelligent analysis technology in the intelligent identification of rain flood
damage, providing support for solving the coupling problem of complex risk types in the simulation of rain flood damage, and making the risk
identification more comprehensive and systematic. In the aspect of resilience prevention and control of rain and flood damage, the planning method
of concept indexing-index spatialization-spatial systematization-system construction and implementation is put forward, which is closely combined
with spatial planning. Through the “macro-meso-micro” multi-scale resilience planning coordination, coastal cities can effectively reduce the risk of
flood damage, and provide systematic theoretical methods and practical application support for the intelligent identification and resilience prevention
and control of flood damage in coastal cities. |
| Key words: Coastal Cities Flood Damage Intelligent Identification Resilience Prevention Multi-Scale |
