Enhancing flood risk assessment in urban areas by integrating hydrodynamic models and machine learning techniques

Alireza Khoshkonesh; Rouzbeh Nazari; Mohammad Reza Nikoo; Maryam Karimi

doi:10.1016/j.scitotenv.2024.175859

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Enhancing flood risk assessment in urban areas by integrating hydrodynamic models and machine learning techniques

Alireza Khoshkonesh Rouzbeh Nazari Mohammad Reza Nikoo Maryam Karimi

Year: 2024 Journal: The Science of The Total Environment Vol: 952 Pages: 175859-175859 Publisher: Elsevier BV

DOI: 10.1016/j.scitotenv.2024.175859

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Keywords:

Flood myth Reliability (semiconductor) Flood risk assessment Lidar Principal component analysis Computer science Predictive modelling Environmental science Machine learning Artificial intelligence Geography Remote sensing

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Topics

Flood Risk Assessment and Management

Physical Sciences → Environmental Science → Global and Planetary Change

Hydrology and Drought Analysis

Physical Sciences → Environmental Science → Global and Planetary Change

Hydrology and Watershed Management Studies

Physical Sciences → Environmental Science → Water Science and Technology

Enhancing flood risk assessment in urban areas by integrating hydrodynamic models and machine learning techniques

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Citation History

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