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Investing in sustainable intensification for smallholders: quantifying large-scale costs and benefits in Uganda

L. Piemontese,R. Kamugisha,J. Barron,J. Tukahirwa,Nicole Harari,F. Jaramillo

Published 2022 in Environmental Research Letters

ABSTRACT

In Uganda, upgrading smallholder agriculture is a necessary step to achieve the interlinked sustainable development goals of hunger eradication, poverty reduction and land degradation neutrality. However, targeting the right restoration practices and estimate their cost-benefit at the national scale is difficult given the highly contextual nature of restoration practices and the diversity of small-scale interventions to be adopted. By analysing the context-specific outcomes of 82 successful case studies on different sustainable land and water management (SLWM) in Uganda, we estimated that out-scaling of existing successful practices to 75% of agricultural land would require a one-time investment of US$ 4.4 billion from smallholders. Our results show that, besides the many social and environmental benefit commonly associated to SLWM, a wide outscale of SLWM could generate US$ 4.7 billion every year, once the practices are fully operational. Our context-specific estimates highlight the profitability of investing in smallholder farming to achieve the sustainable development goals in Uganda, with geographical differences coming from specific social-ecological conditions. This study can guide sustainable intensification development by targeting the most suitable SLWM practices and plan for adequate financial support from government, investors and international development aids to smallholder farming.

PUBLICATION RECORD

  • Publication year

    2022

  • Venue

    Environmental Research Letters

  • Publication date

    2022-03-04

  • Fields of study

    Agricultural and Food Sciences, Physics, Economics, Environmental Science

  • Identifiers
    DOI 10.1088/1748-9326/ac5ae0
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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