{"title":"Enhancing compound flood simulation accuracy and efficiency in urbanized coastal areas using hybrid meshes and modified digital elevation model","authors":"Ebrahim Hamidi , Behzad Nazari , Hamed Moftakhari , Hamid Moradkhani","doi":"10.1016/j.scs.2025.106184","DOIUrl":null,"url":null,"abstract":"<div><div>Accurate flood simulation is crucial for comprehending its impacts, especially in urbanized coastal areas. Reliable flood modeling depends on precise input data, as errors can lead to inaccurate severity estimates. This research investigates the impact of Digital Elevation Model (DEM) modifications on hydrodynamic simulation results, particularly in densely populated urban regions where man-made features like roads and bridges significantly affect water movement. Findings reveal that integrating local survey data to modify DEMs not only significantly enhances result accuracy but also reduces computational costs. Additionally, comparing unstructured and hybrid meshes indicates that using hybrid meshes on a Modified DEM significantly improves accuracy and computational efficiency for flood inundation mapping. A case study of Hurricane Harvey in Houston, Texas, shows a 40 % improvement in flood estimate accuracy and a 34 % reduction in computation time with hybrid meshes on a modified DEM. Additionally, the study evaluates the impact of atmospheric forces and surge, revealing a 20 % improvement in results in the Bay area when atmospheric forces are included. This research underscores the importance of employing accurate DEMs, appropriate meshes tailored to domain features and proper boundary forces for precise flood simulations, helping decision-makers and city planners better assess community vulnerability.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"121 ","pages":"Article 106184"},"PeriodicalIF":10.5000,"publicationDate":"2025-02-01","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/S2210670725000629","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}
引用次数: 0
Abstract
Accurate flood simulation is crucial for comprehending its impacts, especially in urbanized coastal areas. Reliable flood modeling depends on precise input data, as errors can lead to inaccurate severity estimates. This research investigates the impact of Digital Elevation Model (DEM) modifications on hydrodynamic simulation results, particularly in densely populated urban regions where man-made features like roads and bridges significantly affect water movement. Findings reveal that integrating local survey data to modify DEMs not only significantly enhances result accuracy but also reduces computational costs. Additionally, comparing unstructured and hybrid meshes indicates that using hybrid meshes on a Modified DEM significantly improves accuracy and computational efficiency for flood inundation mapping. A case study of Hurricane Harvey in Houston, Texas, shows a 40 % improvement in flood estimate accuracy and a 34 % reduction in computation time with hybrid meshes on a modified DEM. Additionally, the study evaluates the impact of atmospheric forces and surge, revealing a 20 % improvement in results in the Bay area when atmospheric forces are included. This research underscores the importance of employing accurate DEMs, appropriate meshes tailored to domain features and proper boundary forces for precise flood simulations, helping decision-makers and city planners better assess community vulnerability.
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;