• A data-driven model is proposed for urban-scale rapid pluvial flood prediction. The extrapolates to new catchments that were not included in the training data. Two options are compared process catchment areas of different sizes and shapes. Different parameters, including input kernel sizes, investigated. Data-driven machine learning models have recently received increasing interest resolve co...

Flash flooding affects a growing number of people and causes billions dollars in losses each year with the impact often falling disproportionally on underdeveloped regions. To inform post-flood mitigation efforts, it is crucial to determine flash extents, especially for extreme events. Unfortunately, flood hazard mapping has been limited by lack observations both high spatial temporal resolutio...

This study proposes a simple method to produce flood hazard assessment map in burned and urban areas, where primary data are scarce. The area is municipal unit of Nea Makri, coastal part the eastern Attica peninsula (central Greece), which has been strongly urbanized suffered damage from fires 2018. Six factors were considered as parameters most controlling runoff when it overdraws drainage sys...

Abstract Introduction After flood occurrences, remote sensing images provide crucial information for mapping inundation extent. Optical satellite can be utilized to generate flooded area maps when the areas are free from clouds. Materials and Methods In this study was calculated using a variety of water indices classification algorithms, on Landsat data. Pre-flood, during flood, post-flood data...

India witnessed increased flooding incidences during recent past especially in urban areas reportedly since Mumbai (2005) as a mega disaster. Other South Asian cities like Dhaka, Islamabad, Rawalpindi, besides many other cities in India, are also reportedly been affected by frequent floods. Flood risk in urban areas are attributed to hazards accelerated by growth in terms of population, housing...