Fast simulation and prediction of urban pluvial floods using a deep convolutional neural network model

Journal of Hydrology, Journal Year: 2023, Volume and Issue: 624, P. 129945 - 129945

Published: July 18, 2023

Language: Английский

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Simulation Performance Evaluation and Uncertainty Analysis on a Coupled Inundation Model Combining SWMM and WCA2D

International Journal of Disaster Risk Science, Journal Year: 2022, Volume and Issue: 13(3), P. 448 - 464

Published: June 1, 2022

Abstract Urban floods are becoming increasingly more frequent, which has led to tremendous economic losses. The application of inundation modeling predict and simulate urban flooding is an effective approach for disaster prevention risk reduction, while also addressing the uncertainty problem in model always a challenging task. In this study, cellular automaton (CA)-based combining storm water management (SWMM) weighted automata 2D was applied physical-based (LISFLOOD-FP) coupled with SWMM comparison. simulation performance factors were systematically discussed. results show that CA-based can achieve sufficient accuracy higher computational efficiency than model. resolution terrain rainstorm data had strong influence on model, simulations would be less creditable when using input lower 15 m recorded interval rainfall greater 30 min. roughness value type showed limited impacts change depth occurrence peak area. Generally, demonstrated laudable applicability recommended fast flood episodes. This study provide references implications reducing constructing

Language: Английский

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Assessing runoff control of low impact development in Hong Kong's dense community with reliable SWMM setup and calibration

Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 345, P. 118599 - 118599

Published: July 7, 2023

Language: Английский

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First flush stormwater pollution in urban catchments: A review of its characterization and quantification towards optimization of control measures

Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 340, P. 117976 - 117976

Published: April 28, 2023

Language: Английский

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Developing sustainable strategies by LID optimization in response to annual climate change impacts

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 416, P. 137931 - 137931

Published: June 28, 2023

Language: Английский

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Interpretable machine learning for predicting urban flash flood hotspots using intertwined land and built-environment features

Computers Environment and Urban Systems, Journal Year: 2024, Volume and Issue: 110, P. 102096 - 102096

Published: March 13, 2024

Language: Английский

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Impact and analysis of urban water system connectivity project on regional water environment based on Storm Water Management Model (SWMM)

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 423, P. 138840 - 138840

Published: Sept. 13, 2023

Language: Английский

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A Framework on Fast Mapping of Urban Flood Based on a Multi-Objective Random Forest Model

International Journal of Disaster Risk Science, Journal Year: 2023, Volume and Issue: 14(2), P. 253 - 268

Published: April 1, 2023

Abstract Fast and accurate prediction of urban flood is considerable practical importance to mitigate the effects frequent disasters in advance. To improve efficiency accuracy, we proposed a framework for fast mapping flood: coupled model based on physical mechanisms was first constructed, rainfall-inundation database generated, hybrid finally using multi-objective random forest (MORF) method. The results show that had good reliability modelling flood, 48 scenarios were then specified. MORF also demonstrated performance predicting inundated depth under observed scenario rainfall events. spatial depths predicted by close those model, with differences typically less than 0.1 m an average correlation coefficient reaching 0.951. however, achieved computational speed 200 times faster model. overall better k-nearest neighbor Our research provides novel approach rapid early warning.

Language: Английский

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Capacity Optimization of Rainwater Harvesting Systems Based on a Cost–Benefit Analysis: A Financial Support Program Review and Parametric Sensitivity Analysis

Water, Journal Year: 2023, Volume and Issue: 15(1), P. 186 - 186

Published: Jan. 2, 2023

Water risk has been continuously rising due to climate change and ownership disputes of water resources. Dam construction secure resources may lead environmental problems upstream immersion. On the other hand, rainwater harvesting systems can effectively supply at a low cost, although economic efficiency these is still debatable. This study evaluates financial support programs promote installation systems, increasing feasibility. Based on cost–benefit analysis, capacity optimization methods are further suggested. A sensitivity analysis performed determine relative importance among uncertain parameters such as inflation discount rates. In doing so, priority factors consider in design ultimately identified. net present value, it sensitive rate, shown be more appropriate estimate system, compared typical ratio. Because high future value overestimates feasibility proper rates should applied. All all, funding program significantly increases benefits. Thus, national policies recommended ensure systems.

Language: Английский

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A tight coupling model for urban flood simulation based on SWMM and TELEMAC-2D and the uncertainty analysis

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 114, P. 105794 - 105794

Published: Sept. 2, 2024

Language: Английский

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