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Seasonal Flood Forecasts and Warning Response Opportunities


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Produktinformationen
cover
cover
Artikel-Nr.:
     858A-9783031178238
Hersteller:
     Springer Verlag
Herst.-Nr.:
     9783031178238
EAN/GTIN:
     9783031178238
Suchbegriffe:
Geowissenschaften-Bücher
Geowissenschaftsbücher
geowissenschaftliche Bücher - engli...
geowissenschaften bücher
This book explores the feasibility of using El Niño-Southern Oscillation (ENSO)-based forecasts and early warning systems to prevent losses from floods and droughts in Bangladesh. Despite advances in short-range flood forecasting and information dissemination systems in Bangladesh, the present system is less than satisfactory. This is due to short lead-time products, outdated dissemination networks, and lack of direct feedback from the end-user. One viable solution is to produce long-lead seasonal forecasts--the demand for which is significantly increasing in Bangladesh-- and disseminate these products through appropriate channels. As observed in other regions, the success of seasonal forecasts, in contrast to short-term forecasts, depends on consensus among the participating institutions. Therefore, the primary objective of the book is to revisit and modify the framework of an ideal warning response system for issuance of consensus seasonal flood forecasts in Bangladesh. The book discusses issues related to the 5-stage Flood Forecasts, Warning, and Response System (FFWRS) and emphasizes the role of the seasonal 'Climate Outlook Forum (COF)' in Bangladesh. The book also identifies ways to improve forecasting and early warning systems by utilizing ENSO-based climate data and models, and discusses a comprehensive and participatory approach to seasonal flood hazard management in Bangladesh.
Weitere Informationen:
Author:
Md. Rashed Chowdhury
Verlag:
Springer International Publishing
Sprache:
eng
Weitere Suchbegriffe: Climate Variability and Change; early warning systems; Natural Disasters; Flood Forecasting, Bangladesh, Climate variability and change, early warning systems, flood forecasting, natural disasters
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