Transportation Research Part D Transport and Environment, Journal Year: 2024, Volume and Issue: unknown, P. 104479 - 104479
Published: Oct. 1, 2024
Language: Английский
Transportation Research Part D Transport and Environment, Journal Year: 2024, Volume and Issue: unknown, P. 104479 - 104479
Published: Oct. 1, 2024
Language: Английский
Land Use Policy, Journal Year: 2025, Volume and Issue: 151, P. 107494 - 107494
Published: Feb. 5, 2025
Language: Английский
Citations
5Tunnelling and Underground Space Technology, Journal Year: 2025, Volume and Issue: 157, P. 106353 - 106353
Published: Jan. 2, 2025
Language: Английский
Citations
2Cities, Journal Year: 2025, Volume and Issue: 159, P. 105794 - 105794
Published: Feb. 10, 2025
Language: Английский
Citations
0International Journal of Digital Earth, Journal Year: 2025, Volume and Issue: 18(1)
Published: Feb. 23, 2025
Language: Английский
Citations
0Developments in the Built Environment, Journal Year: 2025, Volume and Issue: unknown, P. 100637 - 100637
Published: March 1, 2025
Language: Английский
Citations
0Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106276 - 106276
Published: March 1, 2025
Language: Английский
Citations
0Environmental Impact Assessment Review, Journal Year: 2025, Volume and Issue: 114, P. 107925 - 107925
Published: March 26, 2025
Language: Английский
Citations
0Water, Journal Year: 2025, Volume and Issue: 17(7), P. 964 - 964
Published: March 26, 2025
Under the context of global climate change, floods are one major challenges facing urban development. Based on resilience theory, this study proposed an evaluation method to accurately assess flooding prevention and control systems (FPCs), integrating both attribute (AR) functional (FR). First, organized FPC attributes from perspective waterlogging generation elimination processes using foundational data area, it established a indicator system. The Entropy Weight Method (EWM) was applied calculate weights, Technique for Order Preference by Similarity Ideal Solution (TOPSIS) used values, ultimately deriving (AR). Subsequently, performance during actual operations evaluated scenario simulation based hydrodynamic model results, FR determined. Finally, spatial correlation analysis AR conducted identify areas with weak resilience. This developed that considers system central area Beijing as case flood results indicated most influential factors affecting green space percentage (GSP), average slope, drainage capacity (DC), their weights calculated 0.17, 0.137, 0.205, respectively. Among resistance, absorption, recovery, absorption had greatest influence, weight 0.447. Moran’s I indices were 0.66 0.49, respectively, indicating clustering, although clustering locations differed. There between FR, enabling more precise identification high low However, trends not entirely consistent across different types sub-districts due differences in methods influence various indicators.
Language: Английский
Citations
0Journal of Safety Science and Resilience, Journal Year: 2025, Volume and Issue: unknown
Published: March 1, 2025
Language: Английский
Citations
0Water, Journal Year: 2025, Volume and Issue: 17(7), P. 1084 - 1084
Published: April 5, 2025
In recent years, heavy rainfall-induced flood incidents have occurred frequently in subway stations worldwide. Flooding complex underground facilities, such as stations, can result significant casualties and property damage. Therefore, it is crucial to determine risk management levels within stations. This study proposes a comprehensive management-level evaluation method based on spatial network importance, functional risk, focusing the relationship between structure of risk. The research integrates theory hydrodynamic simulation techniques construct model assessing importance index each subspace network. Simultaneously, calculated through quantitative analysis different functions. Additionally, Volume Fluid (VOF) used simulate distribution, obtaining for subspace. By applying entropy weight analysis, various areas station are determined. results indicate that among all indicators, assigned highest weight, accounting 50%. Specifically, S6 hall, S11 connecting corridors S1–S6 S11–S6 exceeds 0.48, with these constituting 75% total space. highlights their central role crowd flow connectivity. found level five occupy 11.43% space, indicating prioritizing prevention measures critical essential enhancing station’s resilience. provides both theoretical support practical references spaces.
Language: Английский
Citations
0