Abstract
Abstract. The small spatial and temporal scales at which flash floods occur make predicting events challenging, particularly in data-poor environments where high-resolution weather models may not be available. Additionally, the uptake of warnings may be hampered by difficulties in translating the scientific information to the local context and experiences. Here we use social science methods to characterise local knowledge of flash flooding among vulnerable communities along the flat Lake Malawi shoreline in the district of Karonga, northern Malawi. This is then used to guide a scientific analysis of the factors that contribute to flash floods in the area using contemporary global datasets, including geomorphology, soil and land-use characteristics, and hydro-meteorological conditions. Our results show that communities interviewed have detailed knowledge of the impacts and drivers of flash floods (deforestation and sedimentation), early warning signs (changes in clouds, wind direction, and rainfall patterns), and distinct hydro-meteorological processes that lead to flash flood events at the beginning and end of the wet season. Our analysis shows that the scientific data corroborate this knowledge and that combining local and scientific knowledge provides improved understanding of flash flood processes within the local context. We highlight the potential of linking large-scale global datasets with local knowledge to improve the usability of flash flood warnings.
Highlights
Weather-related hazards are responsible for 78 % of the economic losses and 38 % of the fatalities related to disasters worldwide, with a drastic increase in the number of events in the last 35 years attributed to global climate change
The risk knowledge established in the themes about the (ii) occurrence of flash flood events and (iii) impact of flash floods is based on the integration and corroboration of the focus group discussions (FGDs) and key informant interviews (KIIs) with the flash flood occurrence and impact analysis derived from the secondary data
Shorter-duration and more localised flash flood events are reported to occur in January, while longer-duration floods affecting larger areas are observed in April (Table 2)
Summary
Weather-related hazards are responsible for 78 % of the economic losses and 38 % of the fatalities related to disasters worldwide, with a drastic increase in the number of events in the last 35 years attributed to global climate change. Hydrological events show the highest increase globally with a rise of a factor of 4, while meteorological catastrophes have increased by a factor of 3 (Hoeppe, 2015). These events affect the entire globe, exposure to hydrological events and vulnerability of those affected are not uniformly distributed, and climate risk disproportionately affects the world’s poorest (Byers et al, 2018). Aiming at reducing the global impacts of natural hazards, the Sendai Framework for Disaster Risk Reduction (UNISDR, 2015) calls for the increased adoption of multihazard early warning systems
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