Enhancing hydrological modeling with transformers: a case study for 24-h streamflow prediction
In this paper, we address the critical task of 24-h streamflow forecasting using advanced
deep-learning models, with a primary focus on the transformer architecture which has seen …
deep-learning models, with a primary focus on the transformer architecture which has seen …
DiffREE: feature-conditioned diffusion model for radar echo extrapolation
W Qi-liang, W **ng, Z Tong, M Zi-shu… - The Journal of …, 2025 - Springer
In recent years, deep learning has become integral to short-term precipitation forecasting
through radar echo extrapolation. However, as the extrapolation time increases, radar echo …
through radar echo extrapolation. However, as the extrapolation time increases, radar echo …
Spatial downscaling of streamflow data with attention based spatio-temporal graph convolutional networks
Accurate streamflow data is vital for various climate modeling applications, including flood
forecasting. However, many streams lack sufficient monitoring due to the high operational …
forecasting. However, many streams lack sufficient monitoring due to the high operational …
An Integrated Flood Impact Assessment Framework for Mitigation and Decision Support Systems
Y Alabbad - 2023 - search.proquest.com
Flooding is one of the most prevalent types of natural disasters affecting communities
worldwide. It is expected to persist with increasing magnitude and frequency due to climate …
worldwide. It is expected to persist with increasing magnitude and frequency due to climate …