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Water- and weather-related disasters result in the loss of life and billions of dollars annually, a problem that demands an all-hands-on-deck approach from the broad hydrological and meteorological scientific community in partnership with water and disaster management communities. Collaboration across disciplines is essential in order to develop impactful solutions that support national and local authorities in providing adequate early warning to communities and helping their resilience and recovery in the face of disaster events. In all cases, national and local decision makers are charged with the responsibility of committing resources before, during, and after, and must rely on actionable information to make the best possible decisions.
ICIMOD, Kathmandu, Nepal
22 October 2019 to
23 October 2019
SERVIR seeks to disseminate such information through its different hubs. It connects space to village by helping developing countries use satellite data to address challenges in food security, water resources, weather and climate, land use, and natural disasters. A partnership of the National Aeronautics and Space Administration (NASA), the United States Agency for International Development (USAID), and leading technical organizations, SERVIR develops innovative solutions to improve livelihoods and foster self-reliance in Asia, Africa, and the Americas. The International Centre for Integrated Mountain Development (ICIMOD) implements the SERVIR Hindu Kush Himalaya (SERVIR-HKH) Initiative – one of five regional hubs of the SERVIR network – in its regional member countries, prioritizing activities in Afghanistan, Bangladesh, Myanmar, Nepal, and Pakistan.
Work carried out by SERVIR with the Applied Science Teams has demonstrated that current flood forecasts can be enhanced by integrating global satellite and modelled data with regional and local forecasts. This supports the work of hydromet agencies and their goal of providing access to timely and relevant information for decision makers. It has produced ongoing medium-range forecasts for every river stretch and accompanying retrospective hindcasts – historical simulations that put the forecasts in context and provide surrogate observational datasets to support and strengthen existing national systems.