Small dams/reservoirs site location analysis in a semi-arid region of Mozambique

António dos Anjos Luís, Pedro Cabral

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
187 Downloads (Pure)

Abstract

The water crisis is one of the biggest human problems in developing countries, especially in semi-arid regions where it can form an obstacle to irrigation and cultivation, cattle raising and people's survival. The construction of small dams/reservoirs are a possible solution to remediate this problem. These infrastructures must be located in suitable areas to be successful. This study aimed to find the most suitable locations for small dams/reservoirs in the Tete province region, Mozambique, which has a pronounced water deficit. A Geographical Information System (GIS) based approach was used to implement a multi-criteria evaluation (MCE) analysis through an Analytic Hierarchical Process (AHP), which included local experts’ consultation. Three main categories of suitability were identified: “Not suitable” (15% of total area), “Modestly suitable” (78%), and “Suitable” (7%). We found that 35 of the 38 (92%) abandoned small dams/reservoirs were in areas classified as “Modestly suitable” confirming the robustness of our model. We also found that most of the dams/reservoirs currently operating (78%) and planned (73%) are in modestly suitable areas. This finding suggests that the decision to construct dams/reservoirs may not have considered the most critical suitability factors identified in this study. More data and/or additional criteria are required for the full understanding of finding out why so many dams/reservoirs failed before building new ones to address the population's water needs in the region.

Original languageEnglish
Pages (from-to)381-393
Number of pages13
JournalInternational Soil and Water Conservation Research
Volume9
Issue number3
Early online date27 Feb 2021
DOIs
Publication statusPublished - 1 Sep 2021

Keywords

  • Geographic information systems
  • Mozambique
  • Multi-criteria evaluation
  • Remote sensing
  • Water scarcity

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