Open access
Oct 2026
Leveraging Causality to Enhance Drought Forecasting With Deep Learning Models
This study aims to improve the interpretability and efficacy of drought forecasting by integrating causality into the Long Short‐Term Memory (LSTM) structure. The proposed causal‐LSTM structure dynamically adjusts input weights based on identified causal relationships, tailored to the diverse climatic regions of Paki...
Muhammad Waseem, A. H. Jaffry, Jia-Qing Xiao et al.
· Hydrological Processes · 0 citations