Machine learning (ML) is increasingly used in environmental research to process large data
sets and decipher complex relationships between system variables. However, due to the …

Recently, there has been a notable tendency towards employing ensemble learning
methodologies in assorted areas of engineering, such as hydrology, for simulation and …

Feature selection becomes prominent, especially in the data sets with many variables and
features. It will eliminate unimportant variables and improve the accuracy as well as the …

Flood hazard map** (FHM) has undergone significant development in terms of approach
and capacity of the result to meet the target of policymakers for accurate prediction and …

With the growth of cities, urban flooding has increasingly become an issue for regional and
national governments. The destructive effects of floods are magnified in cities. Accurate …

Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …

Historical exploration of flash flood events and producing flash-flood susceptibility maps are
crucial steps for decision makers in disaster management. In this article, classification and …

Floods are one of the most widespread natural hazards occurring across the globe. The
main objective of this study was to produce flood susceptibility maps for the province of …

In recent years, the number of floods around the world has increased. As a result, Flood
Susceptibility Maps (FSMs) became vital for flood prevention, risk mitigation, and decision …

Increase in urban flood hazards has become a major threat to cities, causing considerable
losses of life and in the economy. To improve pre-disaster strategies and to mitigate …