The flood processes and control methods in narrow-valley cities exhibit significant
differences compared to other regions. Therefore, precise modeling and simulation of their …

We utilized the random forest (RF) machine learning algorithm, along with nine
topographical/morphological factors, namely aspect, slope, geomorphons, plan curvature …

Flood is one of the most devastating natural hazards. Employing machine learning models
to construct flood susceptibility maps has become a pivotal step for decision-makers in …

Urban flood risks have intensified due to climate change and dense infrastructural
development, necessitating innovative assessment approaches. This study aimed to …

The assessment of flood hazard in semi-arid region under the scare data situation is a
challenging task under the changing climatic situation. Therefore, the present research is …

Due to the complex interaction of urban and mountainous floods, assessing flood
susceptibility in mountainous urban areas presents a challenging task in environmental …

Abstract Study region Poldokhtar City is located on the bank of the Kashkan river in Iran.
Study focus This study presents a probabilistic modeling framework for flood risk …

Flood modeling is essential to determine and protect vulnerable areas. However, due to
complexity of flooding, it is challenging to model floods with a high level of sensitivity. While …

The dams and reservoirs built in the valleys play a key role in water management and
contribute to a society's quality of life. But they are also a potential risk, with often tragic …

Topographic conditions represented by the Digital Elevation Model (DEM) are essential in
flood inundation models. The DEM, which is categorised as a Digital Surface Model (DSM) …