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Expression of Interest are invited for Drought Forecasting and Early Warning Tool for Afghanistan Afghanistan is highly vulnerable to intense and recurring natural hazards that further risk growth and stability. Since 2000, natural disasters (i.e., droughts, earthquakes, epidemics, extreme temperature, floods, landslides, storms) have affected close to 19 million people in the country, resulting in 10,656 total deaths and US$173.11 million in total damages. Of these hazards, droughts have the most widespread impact and affect a larger population. The 5 significant drought events, occurring in 2000, 2006, 2008, 2011/12, and 2017/18, have affected over 17 million people with estimated damages totaling US$142.05 million. With its diverse topography, isolation of many vulnerable communities, and limited coping mechanisms, hazard events in Afghanistan, regardless of security factors, are ever more likely to turn into disasters with significant humanitarian and economic consequences. The World Bank, through the AF-ECLIM Enhancing Hydromet Early Warning and Climate Services for Resilience Project (P168141), aims to strengthen the delivery of hydromet, climate, and early warning services to relevant stakeholders and strengthen the knowledge of climate risk management and resilience building practices in Afghanistan. The project support enhanced dissemination of weather forecasts, hydrological forecasts, and impact-based information by improving their production, translation, and communication. It also aims to deliver services to stakeholders and end-users, particularly in priority sectors such as public safety and the economy, while fostering regional collaboration to enhance the quality of information. Ultimately, the project aims to empower proactive decision-making to effectively mitigate the adverse impacts of natural hazards on life, livelihoods, and property. The primary objective of this consultancy is to develop a robust prototype of Drought Forecasting and Early Warning Tool focusing on the geographic area of Afghanistan, leveraging Earth Observation (EO) data and machine learning (ML) techniques, that enables the Bank to better understand the drought situation in the country and inform the design and prioritization of future operations. Specific objectives of this assignment include: Develop a comprehensive understanding of historical drought patterns in Afghanistan. Integrate EO datasets and ML techniques to produce seasonal drought forecasts, including meteorological and agricultural droughts. Establish a prototype of the drought forecasting and early warning tool tool to help access and interpret drought forecasts and associated datasets. Facilitate effective utilization of the tool. Tender Link : https://wbgeprocure-rfxnow.worldbank.org/rfxnow/public/advertisement/index.html
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