Application of machine learning-based surrogate models for urban flood depth modeling in Ho Chi Minh City, Vietnam

Applied Soft Computing, Год журнала: 2023, Номер 150, С. 111031 - 111031

Опубликована: Ноя. 10, 2023

Язык: Английский

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Machine learning-based surrogate modelling of a robust, sustainable development goal (SDG)-compliant land-use future for Australia at high spatial resolution

Journal of Environmental Management, Год журнала: 2024, Номер 363, С. 121296 - 121296

Опубликована: Июнь 5, 2024

Язык: Английский

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Risk prediction based on oversampling technology and ensemble model optimized by tree-structured parzed estimator

International Journal of Disaster Risk Reduction, Год журнала: 2024, Номер 111, С. 104753 - 104753

Опубликована: Авг. 12, 2024

Язык: Английский

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On the accuracy requirement of surrogate models for adequate global sensitivity analysis of urban low-impact development model

Journal of Hydrology, Год журнала: 2025, Номер unknown, С. 133102 - 133102

Опубликована: Март 1, 2025

Язык: Английский

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An intelligent SWMM calibration method and identification of urban runoff generation patterns

Frontiers in Environmental Science, Год журнала: 2025, Номер 13

Опубликована: Апрель 4, 2025

The accuracy of urban runoff simulation using the Storm Water Management Model (SWMM) largely depends on parameter calibration. This study proposes a universal and effective method to enhance model by optimizing value ranges through an unsupervised intelligent clustering algorithm. Simulation scenarios with varying proportions pervious impervious areas are established, sensitivity analysis is conducted rank key parameters identify dominant generation patterns. results show that when area less than 10%, most sensitive Zero.Imperv, N.Imperv, Dstore-Imperv, indicating primarily originates from surfaces. As increases, shifts areas, where Unit Hydrograph Model, fewer simpler calibration process, leads higher accuracy. These findings improve reliability SWMM provide reference for setting requirements under different surface conditions.

Язык: Английский

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Enhancing 2D hydrodynamic flood models through machine learning and urban drainage integration

Journal of Hydrology, Год журнала: 2025, Номер 659, С. 133258 - 133258

Опубликована: Апрель 10, 2025

Язык: Английский

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Quantifying the impact of river levels on urban drainage capacity

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Апрель 15, 2025

When river flooding and urban waterlogging occur simultaneously, the rising water level could reduce drainage capacity of pipe network, thereby exacerbating risk. This study quantitatively analyzed impact fluctuations on network. A 1D network model was coupled with a 2D hydrodynamic to simulate different combination scenarios, based which flow coefficient formula fitted. The results indicate that is closely related outflow conditions. Under free conditions, remains largely unaffected by external levels. However, when 1 2 times (in term diameter outlet) higher than bottom outlet, phenomenon inundation begins emerge, progressively weakening capacity. exceeds twice diminishes rapidly zero, backflow may occur. Taking Beijing Sub-center as case study, findings reveal during normal levels, operates effectively, ensuring proper drainage. under high becomes limited or even ineffective. During recession phase, river's influence diminishes, leading partial recovery drainage, although it cannot be fully restored. These provide important reference for combined scheduling floods waterlogging.

Язык: Английский

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Unravelling the impact of land use transformation on thermal environment across seasons: A comprehensive study of rapidly urbanizing Patna Planning Area, India

Environmental Science and Pollution Research, Год журнала: 2025, Номер unknown

Опубликована: Май 29, 2025

Язык: Английский

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Toward Improved Urban Building Energy Modeling Using a Place-Based Approach

Energies, Год журнала: 2023, Номер 16(9), С. 3944 - 3944

Опубликована: Май 7, 2023

Urban building energy models present a valuable tool for promoting efficiency in design and control, as well managing urban systems. However, the current often overlook importance of site-specific characteristics, spatial attributes variations within specific area city. This methodological paper moves beyond state-of-the-art modeling urban-scale by incorporating an improved place-based approach to address this research gap. allows more in-depth understanding interactions behind patterns increase number quality energy-related variables. The outlines detailed description steps required create presents sample application results each model. pre-modeling phase is highlighted critical step which geo-database used collected, corrected, integrated. We also discuss use auto-correlation geo-database, introduces new spatial-temporal relationships that describe territorial clusters complex environment study identifies redefines three primary types modeling, including process-driven, data-driven, hybrid models, context approaches. challenges associated with type are highlighted, emphasis on data requirements availability concerns. concludes crucial achieving self-sufficiency districts or cities energy-modeling studies.

Язык: Английский

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A novel and efficient method for real-time simulating spatial and temporal evolution of coastal urban pluvial flood without drainage network

Environmental Modelling & Software, Год журнала: 2023, Номер 172, С. 105888 - 105888

Опубликована: Ноя. 22, 2023

Язык: Английский

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