Atmosphere (Nov 2020)

Water Constraints and Flood-Recession Agriculture in the Senegal River Valley

  • Mamadou Sall,
  • Jean-Christophe Poussin,
  • Aymar Yaovi Bossa,
  • Ramatoulaye Ndiaye,
  • Madiama Cissé,
  • Didier Martin,
  • Jean-Claude Bader,
  • Benjamin Sultan,
  • Andrew Ogilvie

DOI
https://doi.org/10.3390/atmos11111192
Journal volume & issue
Vol. 11, no. 11
p. 1192

Abstract

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Flood recession farming practiced in flood-prone areas and on the banks of rivers and lakes in arid or semi-arid environments essentially depends on the soil water stock after the flood has receded. During these last few decades, this coveted agriculture is increasingly challenged by severe water constraints, due to increased hydrological hazards and development projects aimed at controlling floods. These challenges are difficult to anticipate, and are the subject of a great deal of uncertainty regarding the sustainability of development projects in the concerned areas. In this study, recent hydraulic data of the Senegal River were analyzed to understand the constraints related to the river management in flood-prone areas. Satellite imagery analysis techniques were used to estimate flooded areas and establish relationships with the river regime. Agricultural practices implemented by farmers were also analyzed to evaluate the resilience of this cropping system to the risk of water stress. The results confirmed many constraints of different importance related to the objectives assigned to the management of dams under multiple water use context. It clearly came out that the water resource management rules relegate flood-recession agriculture to the lowest priorities. In addition, there are safety issues related to unexpected effects of flooding on the water structures and in the nearby inhabited localities of flood-prone areas. Knowing some characteristics of the flooding and of the river’s levels and their relationships can be useful within the framework of an organized climate service that would help farmers and communities to better anticipate constraints.

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