Research Work #1

Droughts pose significant challenges to economies and societies, leading to water shortages, crop failures, and wildfires. This study aims to develop a deep learning system capable of predicting drought severity at least 90 days into the future. Using historical data, specific deep learning algorithms were trained to identify drought-associated patterns for accurate future drought condition predictions. The proposed system incorporates a new index, Standardized Precipitation Index Daily (SPID), enhancing the model’s ability to assess drought severity. The model achieved a test loss of 0.0291 and a training loss of 0.0639, demonstrating its effectiveness in predicting droughts. Future research could further improve the model’s performance by including more data and incorporating information from other cities. The findings from this study offer valuable insights for decision-makers in water resource management, drought mitigation planning, and community preparedness for drought conditions.