Honglin Xiao , Jinping Zhang , Fuqiang Wang , Lingli Kong
{"title":"基于内涝风险角的城市内涝风险预警分类新框架","authors":"Honglin Xiao , Jinping Zhang , Fuqiang Wang , Lingli Kong","doi":"10.1016/j.scs.2025.106460","DOIUrl":null,"url":null,"abstract":"<div><div>Early-warning classification of urban waterlogging risk is the main prevention and control measure to improve urban sustainable water security and effectively reduce waterlogging disasters. The concept of waterlogging risk angle (WRA) is proposed and applied to determine the early-warning classification of urban waterlogging risk combing with the constructed InfoWorks ICM model. The results show that (1) with the increase of rainfall duration, the WRA value gradually decreases. And the WRA value of front-peak rainstorm (FPR) tends to be larger, which makes waterlogging disasters easier to occur. (2) The early-warning time of urban waterlogging risk (EWTUWR) in the same duration of level I and level II of FPR is all less than that of behind-peak rainstorm (BPR). Moreover, the average EWTUWR increases with the rainfall duration, with 1 h rainfall duration corresponding to the smallest average EWTUWR. (3) There has a compactly relations between EWTUWRs and rainstorm characteristics in different rainfall durations. The early-warning time is shortened by the increase of front-peak rainstorm intensity (FPRI) and total rainfall volume (TRV). (4) The theoretical verification and practical verification prove that the proposed early-warning time is available and applicable. This study provides a new method for studying the early-warning of urban waterlogging risk in other cities.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"127 ","pages":"Article 106460"},"PeriodicalIF":10.5000,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new framework for early-warning classification of urban waterlogging risk based on waterlogging risk angle\",\"authors\":\"Honglin Xiao , Jinping Zhang , Fuqiang Wang , Lingli Kong\",\"doi\":\"10.1016/j.scs.2025.106460\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Early-warning classification of urban waterlogging risk is the main prevention and control measure to improve urban sustainable water security and effectively reduce waterlogging disasters. The concept of waterlogging risk angle (WRA) is proposed and applied to determine the early-warning classification of urban waterlogging risk combing with the constructed InfoWorks ICM model. The results show that (1) with the increase of rainfall duration, the WRA value gradually decreases. And the WRA value of front-peak rainstorm (FPR) tends to be larger, which makes waterlogging disasters easier to occur. (2) The early-warning time of urban waterlogging risk (EWTUWR) in the same duration of level I and level II of FPR is all less than that of behind-peak rainstorm (BPR). Moreover, the average EWTUWR increases with the rainfall duration, with 1 h rainfall duration corresponding to the smallest average EWTUWR. (3) There has a compactly relations between EWTUWRs and rainstorm characteristics in different rainfall durations. The early-warning time is shortened by the increase of front-peak rainstorm intensity (FPRI) and total rainfall volume (TRV). (4) The theoretical verification and practical verification prove that the proposed early-warning time is available and applicable. This study provides a new method for studying the early-warning of urban waterlogging risk in other cities.</div></div>\",\"PeriodicalId\":48659,\"journal\":{\"name\":\"Sustainable Cities and Society\",\"volume\":\"127 \",\"pages\":\"Article 106460\"},\"PeriodicalIF\":10.5000,\"publicationDate\":\"2025-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sustainable Cities and Society\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2210670725003361\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CONSTRUCTION & BUILDING TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Cities and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210670725003361","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
A new framework for early-warning classification of urban waterlogging risk based on waterlogging risk angle
Early-warning classification of urban waterlogging risk is the main prevention and control measure to improve urban sustainable water security and effectively reduce waterlogging disasters. The concept of waterlogging risk angle (WRA) is proposed and applied to determine the early-warning classification of urban waterlogging risk combing with the constructed InfoWorks ICM model. The results show that (1) with the increase of rainfall duration, the WRA value gradually decreases. And the WRA value of front-peak rainstorm (FPR) tends to be larger, which makes waterlogging disasters easier to occur. (2) The early-warning time of urban waterlogging risk (EWTUWR) in the same duration of level I and level II of FPR is all less than that of behind-peak rainstorm (BPR). Moreover, the average EWTUWR increases with the rainfall duration, with 1 h rainfall duration corresponding to the smallest average EWTUWR. (3) There has a compactly relations between EWTUWRs and rainstorm characteristics in different rainfall durations. The early-warning time is shortened by the increase of front-peak rainstorm intensity (FPRI) and total rainfall volume (TRV). (4) The theoretical verification and practical verification prove that the proposed early-warning time is available and applicable. This study provides a new method for studying the early-warning of urban waterlogging risk in other cities.
期刊介绍:
Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including:
1. Smart cities and resilient environments;
2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management;
3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management);
4. Energy efficient, low/zero carbon, and green buildings/communities;
5. Climate change mitigation and adaptation in urban environments;
6. Green infrastructure and BMPs;
7. Environmental Footprint accounting and management;
8. Urban agriculture and forestry;
9. ICT, smart grid and intelligent infrastructure;
10. Urban design/planning, regulations, legislation, certification, economics, and policy;
11. Social aspects, impacts and resiliency of cities;
12. Behavior monitoring, analysis and change within urban communities;
13. Health monitoring and improvement;
14. Nexus issues related to sustainable cities and societies;
15. Smart city governance;
16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society;
17. Big data, machine learning, and artificial intelligence applications and case studies;
18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems.
19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management;
20. Waste reduction and recycling;
21. Wastewater collection, treatment and recycling;
22. Smart, clean and healthy transportation systems and infrastructure;