Building level flood exposure analysis using a hydrodynamic model

Bertsch, Robert; Glenis, Vassilis; Kilsby, Chris

doi:10.1016/j.envsoft.2022.105490

Cited by 18 publications

(15 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The approach taken here to validation of the models is to estimate the flood exposure of each building and compare it with flooding in areal observed event. In a recent study by Bertsch et al (2022), a new tool was developed to assess exposure of buildings to flooding and validate against a real flood event in Newcastle upon Tyne, UK. The ‘ Building Hole ’ approach was used for the representation of buildings and the model successfully predicted between 68% and 75% of the surveyed buildings that suffered from flooding.…”

Section: Resultsmentioning

confidence: 99%

“…The BH approach represents buildings as void space where the cells within the building are removed from the computational grid. The surface water cannot flow into the building voids, so the water flows around the building boundary (Bertsch, 2019). In addition, reduction of the simulation time from a smaller number of computational cells is an advantage, especially for dense built-up areas.…”

Section: Aims Of This Studymentioning

confidence: 99%

“…In contrast, with the SB approach the flood water flows over the building, generating unrealistic flowpaths. T A B L E 1 Classification scheme for calculating flood exposure likelihood for buildings (Bertsch, 2019;Bertsch et al, 2022).…”

Section: Velocity Comparisonmentioning

confidence: 99%

“…Building outlines from OS (MasterMap, 2020; Ordnance Survey, 2020) were used to estimate the flood risk to buildings by analysing each model's maximum flood depth output in a one-cell wide buffer around the building outline. Buildings were classified as flooded if the flood water is above a typical property threshold of 30 cm (Bertsch, 2019;Bertsch et al, 2022;Environment Agency, 2021; Table 1).…”

Section: Flood Exposure Analysismentioning

confidence: 99%

See 3 more Smart Citations

Representing buildings and urban features in hydrodynamic flood models

Iliadis,

Glenis,

Kilsby

2023

J Flood Risk Management

Self Cite

View full text Add to dashboard Cite

Flood risk in cities and built‐up areas is a major threat which is likely to grow due to increased urbanisation and climate change. It is a priority for urban planning, civil defence and insurance to accurately represent buildings and urban features in hydrodynamic models to assess flood risk to people, properties, assets and infrastructure in an uncertain future. The correct representation of urban features in models is currently blocked by the lack of detailed and accurate techniques and has become a priority for the improvement of urban flood modelling now that better data and computational resources are available. This study has reviewed the available approaches for the representation of buildings and urban features and implemented the widely used ‘stubby building’ approximation as well as a more realistic and innovative ‘building hole’ approach using the hydrodynamic model CityCAT. The city centre of Newcastle upon Tyne, UK, was used as a case study, allowing independent validation of the methods and direct, systematic comparison of performance. Shortcomings of the approximate method are described, and guidance given on limits to its reliable application and scope for improvement.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Aims Of This Studymentioning

confidence: 99%

Section: Velocity Comparisonmentioning

confidence: 99%

Section: Flood Exposure Analysismentioning

confidence: 99%

See 2 more Smart Citations

Representing buildings and urban features in hydrodynamic flood models

Iliadis,

Glenis,

Kilsby

2023

J Flood Risk Management

Self Cite

View full text Add to dashboard Cite

show abstract

“…Further research extends to the influence of flooding on equity in urban regions (Thaler, 2021). The application of social media data has paved the way for high‐precision calculations, such as population density and urban functionality at the building scale, improving the spatiotemporal resolution of vulnerability assessments (Bertsch et al., 2022; Deng et al., 2022).…”

Section: Introductionmentioning

confidence: 99%

Evaluating the effect of urban flooding on spatial accessibility to emergency shelters based on social sensing data

Zhu,

Jiang,

Zhang

et al. 2023

Transactions in GIS

View full text Add to dashboard Cite

Urban flooding is a growing source of natural hazards, significantly threatening the safety of sustainable development in cities. The distribution of flood risks is heterogeneous, so it is crucial to allocate emergency resources reasonably. This article develops an analytical framework to evaluate the effect of urban flooding on emergency responses based on social sensing data. Initially, we designed a Weibo search pattern and used natural language processing technologies to get high‐risk flood points. Then, assuming that such high‐risk flood points can disrupt traffic, we assessed urban emergency shelter accessibility after flooding events. Finally, we carried out an evaluation of spatial fairness between population and emergency shelter accessibility through spatial correlation analysis. We analyzed the urban area of Nanjing as a case study, extracting 37 high‐risk flood points from the past 5 years. The results highlight that existing emergency shelters fall short in accommodating the needs of urban residents under disaster conditions. This disparity is notably amplified in high‐risk flood points. By measuring the impact of flooding quantitatively, we expect to promote a more comprehensive management on urban flood risks.

show abstract

Newcastle upon Tyne, United Kingdom

Chang,

Ross

2024

Climate Change, Urbanization, and Water Resources

View full text Add to dashboard Cite

Building level flood exposure analysis using a hydrodynamic model

Cited by 18 publications

References 20 publications

Representing buildings and urban features in hydrodynamic flood models

Representing buildings and urban features in hydrodynamic flood models

Evaluating the effect of urban flooding on spatial accessibility to emergency shelters based on social sensing data

Newcastle upon Tyne, United Kingdom

Contact Info

Product

Resources

About