A transformative framework reshaping sustainable drought risk management through advanced early warning systems.

In light of the increasing vulnerability to drought occurrences and the heightened impact of drought-related disasters on numerous communities, it is imperative for drought-sensitive sectors to adopt proactive measures. This involves the implementation of early warning systems to effectively mitigate potential risks. Guided by Toulmin's model of argumentation, this research proposes a framework of eight interconnected modules introducing Fourth Industrial Revolution technologies to enhance drought early warning capabilities. The framework emphasizes the Internet of Things, drones, big data analytics, and deep learning for real-time monitoring and accurate drought forecasts. Another key component is the role of natural language processing in analyzing data from unstructured sources, such as social media, and reviews, essential for improving alerts, dissemination, and interoperability. While the framework optimizes resource use in agriculture, water, and the environment, overcoming impending limitations is crucial; hence, practical implementation and amendment of policies are necessary.