23 Apr 2021

23 Apr 2021

Review status: a revised version of this preprint is currently under review for the journal NHESS.

Flash Flood warning in context: combining local knowledge and large-scale hydro-meteorological patterns

Agathe Bucherie1,2,3, Micha Werner2, Marc van den Homberg3, and Simon Tembo4 Agathe Bucherie et al.
  • 1The International Research Institute for Climate and Society (IRI), Columbia University, New York, 10964, USA
  • 2IHE Delft Institute for Water Education, Delft, 2611AX, The Netherlands
  • 3510, an initiative of The Netherlands Red Cross, The Hague, 2593 HT, The Netherlands
  • 4Malawi Red Cross Society, Lilongwe, 30096, Malawi

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, 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 corroborates this knowledge, and that combining local and scientific knowledge provides improved understanding of flash flood processes within the local context. We highlight the potential in linking large-scale global datasets with local knowledge to improve the usability of flash flood warnings.

Agathe Bucherie et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-107', Anonymous Referee #1, 27 May 2021
    • AC1: 'Reply on RC1', Agathe Bucherie, 24 Aug 2021
  • RC2: 'Comment on nhess-2021-107', Anonymous Referee #2, 14 Jul 2021
    • AC2: 'Reply on RC2', Agathe Bucherie, 24 Aug 2021

Agathe Bucherie et al.

Agathe Bucherie et al.


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Short summary
Local communities in North Malawi have a well-developed knowledge of the conditions leading to flash flood, spatially and temporally. Scientific analysis of catchment geomorphology and global re-analysis datasets corroborates this local knowledge, underlining the potential of these large scale scientific datasets. Combining local knowledge with contemporary scientific datasets provides a common understanding of flash flood events, contributing to a more people-centred warning to flash floods.