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Are African irrigation dam projects for large-scale agribusiness or small-scale farmers?

Domaine:

agriculturegeospatial
Créateur:
MokPao
Éditeur:
IOP
Hôte:
Abstract The economic development of rural economies across the global south is often related to access to water and the development of water infrastructure. It has been argued that the construction of new dams would unleash the agricultural potential of African nations that are exposed to seasonal water scarcity, strong interannual rainfall variability, and associated uncertainties in water availability. While water security is often presented as the pathway to poverty alleviation and invoked to justify large dam projects for irrigation, it is still unclear to what extent small holders will benefit from them. Are large dams built to the benefit of subsistence farmers or of large-scale commercial agriculture? Here we use remote sensing imagery in conjunction with advanced machine learning algorithms to map the irrigated areas (or ‘command areas’) that have appeared in the surroundings of 18 major dams built across the African continent between 2000 and 2015. We quantify the expansion of irrigation afforded by those dams, the associated changes in population density, forest cover, and farm size. We find that, while in the case of nine dams in the year 2000 there were no detectable farming patterns, in 2015 a substantial fraction of the command area (ranging between 8.5% and 96.7%) was taken by large-scale farms (i.e., parcels >200 ha). Seven of the remaining 9 dams showed a significant increase in average farm size and number of farms between 2000 and 2015, with large-scale farming accounting for anywhere between 5.2% and 76.7% of the command area. Collectively, these results indicate that many recent dam projects in Africa are associated either with the establishment of large-scale farming or a transition from small-scale to mid-to-large scale agriculture.

Visit

doi.org

Licenses

http://creativecommons.org/licenses/by/4.0/https://iopscience.iop.org/info/page/text-and-data-mining

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