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Summary
The flood prone Gandaki river landscape, in the eastern Indian state of Bihar, produces inequities and uncertainties in equal measure. People’s knowledge of forecasting floods has historically evolved through complexities and politics of caste, class, and gender along with the ecological flux inherent to waterscapes. Interestingly, though, very little attention has been paid in literature on disaster risk reduction to local knowledge of flood forecasting and other meteorological phenomena. That local communities are not just consumers but also producers of information on weather and climate seems to have gone mostly unnoticed.
The present study attempts to address that gap in literature, by documenting various, sophisticated methods deployed by local communities to forecast floods and heavy rainfall in the Gandaki River basin. It makes a point that strengthening such local knowledge systems will effectively counterbalance the pitfalls of centralized and mechanized early flood warning systems as much as ensure their recognition and continuation.
This research also seeks to clarify its definition of local knowledge in an effort to move away from the interchangeable use of traditional/indigenous/local knowledge, a flexibility that has created ontological problems.
By documenting the complex interaction between local-knowledge based forecasting and official early warning systems, the study points out (a) a high degree of gender blindness embedded in official early flood warning systems, (b) at knowledge innovation practised by local communities that convert obtuse flood- related information to practical use through a complex process of triangulation, and (c) the change to local knowledge asymmetries being brought in through the rapid proliferation of mobile phones. Finally, it advocates knowledge co-production between local and scientific communities, which would only serve to strengthen one another.