L. Gao, Limin Zhang, Yang Hong, Hong-Xin Chen, Shijin Feng
{"title":"Flood hazards in urban environment","authors":"L. Gao, Limin Zhang, Yang Hong, Hong-Xin Chen, Shijin Feng","doi":"10.1080/17499518.2023.2201266","DOIUrl":null,"url":null,"abstract":"ABSTRACT Apart from the estimation of magnitudes of precipitation, floods and storm surges, modelling of storm water flows in a densely populated urban area is required for designing coping strategies and making decisions. Incorporating surface runoff and conduit flow modelling capabilities has enabled the prediction of urban flood hazards. This study synthesises methodologies for simulating flood processes and evaluating flood hazards in urban environment. Existing models and their associated uncertainties are summarised, and state-of-the-art techniques to build up a numerical model for simulating urban floods and the applications to specific cases are illustrated. A schematic framework for urban flood hazard prediction is proposed, within which multi-source observation retrieval, physics-based modelling, parameter optimisation, uncertainty estimation, model-observation fusion, evaluation of compound effects of multiple factors and digital twin techniques are included. The major challenges and uncertainties in flood process modelling originate from input data, model structures, validation processes and compounding effects. Multidisciplinary techniques for estimating the input data and enhancing the efficiency and accuracy of the flood evaluation should be developed. Great efforts are needed in understanding the process-dependent indicators, coupled modelling and data-model assimilation. Determining the probability of compound floods and understanding the driving factors are also essential for evaluating flood risks.","PeriodicalId":48524,"journal":{"name":"Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards","volume":"17 1","pages":"241 - 261"},"PeriodicalIF":6.5000,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/17499518.2023.2201266","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, GEOLOGICAL","Score":null,"Total":0}
引用次数: 3
Abstract
ABSTRACT Apart from the estimation of magnitudes of precipitation, floods and storm surges, modelling of storm water flows in a densely populated urban area is required for designing coping strategies and making decisions. Incorporating surface runoff and conduit flow modelling capabilities has enabled the prediction of urban flood hazards. This study synthesises methodologies for simulating flood processes and evaluating flood hazards in urban environment. Existing models and their associated uncertainties are summarised, and state-of-the-art techniques to build up a numerical model for simulating urban floods and the applications to specific cases are illustrated. A schematic framework for urban flood hazard prediction is proposed, within which multi-source observation retrieval, physics-based modelling, parameter optimisation, uncertainty estimation, model-observation fusion, evaluation of compound effects of multiple factors and digital twin techniques are included. The major challenges and uncertainties in flood process modelling originate from input data, model structures, validation processes and compounding effects. Multidisciplinary techniques for estimating the input data and enhancing the efficiency and accuracy of the flood evaluation should be developed. Great efforts are needed in understanding the process-dependent indicators, coupled modelling and data-model assimilation. Determining the probability of compound floods and understanding the driving factors are also essential for evaluating flood risks.
期刊介绍:
Georisk covers many diversified but interlinked areas of active research and practice, such as geohazards (earthquakes, landslides, avalanches, rockfalls, tsunamis, etc.), safety of engineered systems (dams, buildings, offshore structures, lifelines, etc.), environmental risk, seismic risk, reliability-based design and code calibration, geostatistics, decision analyses, structural reliability, maintenance and life cycle performance, risk and vulnerability, hazard mapping, loss assessment (economic, social, environmental, etc.), GIS databases, remote sensing, and many other related disciplines. The underlying theme is that uncertainties associated with geomaterials (soils, rocks), geologic processes, and possible subsequent treatments, are usually large and complex and these uncertainties play an indispensable role in the risk assessment and management of engineered and natural systems. Significant theoretical and practical challenges remain on quantifying these uncertainties and developing defensible risk management methodologies that are acceptable to decision makers and stakeholders. Many opportunities to leverage on the rapid advancement in Bayesian analysis, machine learning, artificial intelligence, and other data-driven methods also exist, which can greatly enhance our decision-making abilities. The basic goal of this international peer-reviewed journal is to provide a multi-disciplinary scientific forum for cross fertilization of ideas between interested parties working on various aspects of georisk to advance the state-of-the-art and the state-of-the-practice.