Deep learning has emerged as a powerful tool for streamflow forecasting and its
applications have garnered significant interest in the hydrological community. Despite the …

River floods are listed among the natural disasters that can directly influence different
aspects of life, ranging from human lives, to economy, infrastructure, agriculture, etc …

Real-time streamflow forecasting is essential to manage water resources effectively in a
reservoir-regulated basin. However, forecasting becomes challenging without weather and …

Accurate and timely mapping of wildfire burned areas is crucial for post-fire management,
planning, and next subsequent actions. The monitoring and mapping of the burned area by …

Flood risk assessment is a key step in flood management and mitigation, and flood risk
maps provide a quantitative measure of flood risk. Therefore, integration of deep learning …

Abstract This study addresses Hydrologic Engineering Center Hydrologic Modeling System
(HEC-HMS) model simulation issues in web environments and identifies key model …

Robust streamflow simulation at glacial basins is essential for the improvement of water
sustainability assessment, water security evaluation, and water resource management …

Rainfall-runoff (RR) modelling is a challenging task in hydrology, especially at the regional
scale. This work presents an approach to simultaneously predict daily streamflow in 86 …

The crucial element of community engagement has been recognised as a success factor in
the conception and dispensing of climate solutions, but consists in itself of complex factors to …

Due to a small proportion of observations, reliable and accurate flood forecasts for large
floods present a fundamental challenge to artificial neural network models, especially when …