Researchers in Pakistan used advanced deep learning models to predict drought risk across different climate zones, finding that droughts in semi-arid and desert regions are growing longer and more intense. The CNN-LSTM model outperformed traditional methods for long-range forecasts, offering a practical tool for early warning systems and water management decisions.
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Drought intensity and duration are increasing rapidly in Pakistan's semi-arid and coastal desert regions, based on multi-scale rainfall index analysis across 1, 3, 6, 9, and 12-month timescales.
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The CNN-LSTM hybrid deep learning model outperformed traditional methods (SVM and Penman-Monteith) for long-term drought forecasting, while BiLSTM was most accurate for short-term predictions.
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Long-term drought trends were best captured by 9- and 12-month standardized precipitation indices, suggesting sustained moisture deficits rather than brief dry spells are the dominant pattern.
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