Abstract

AbstractWith urbanization is on the rise, it wreaks havoc on the hydrological processes within a catchment, resulting in a deteriorating water environment. Floods can greatly raise the cost of mitigation efforts due to their damaging consequences. The natural water balance is disrupted by an increase in impermeable areas. As runoff rises, so do flood peaks and volumes even in short, low‐intensity showers. Urban flooding is a significant impact of urbanization that has drawn the attention of experts. Currently, there are techniques based on distributed hydrologic modeling and Geographic Information Systems (GIS) used to assess the influence of land use for urbanization on the environment. Deep learning techniques with their immense performance in Computer Vision and Image Processing fields have been extended to the problem of urban floods by integrating them with a GIS‐based methodology. This study outlines multiple techniques that have been used to address urban floods.

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