Informing Equitable Water and Food Policies through Accurate Spatial Information on Irrigated Areas in Smallholder Farming Systems

James Magidi; Barbara van Koppen; Luxon Nhamo; Sylvester Mpandeli; Rob Slotow; Tafadzwanashe Mabhaudhi

doi:10.3390/w13243627

Informing Equitable Water and Food Policies through Accurate Spatial Information on Irrigated Areas in Smallholder Farming Systems

Water (Basel). 2021 Dec 16;13(24):3627. doi: 10.3390/w13243627.

Authors

James Magidi¹, Barbara van Koppen², Luxon Nhamo³, Sylvester Mpandeli^{3

4}, Rob Slotow^{5

6}, Tafadzwanashe Mabhaudhi^{7

8}

Affiliations

¹ Geomatics Department, Tshwane University of Technology, Pretoria 0001, South Africa.
² International Water Management Institute (IWMI), Southern Africa Office, Pretoria 0184, South Africa.
³ Water Research Commission of South Africa (WRC), Pretoria 0081, South Africa.
⁴ Faculty of Science, Engineering and Agriculture, University of Venda, Thohoyandou 0950, South Africa.
⁵ Centre for Transformative Agricultural and Food Systems (CTAFS), School of Life Sciences, University of KwaZulu-Natal, Scottsville, Pietermaritzburg 3209, South Africa.
⁶ Department of Genetics, School of Genetics, Evolution & Environment, University College, London WC1E 6BT, UK.
⁷ Centre for Transformative Agricultural and Food Systems (CTAFS), School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Scottsville, Pietermaritzburg 3209, South Africa.
⁸ International Water Management Institute (IWMI-GH), West Africa Office, Accra GA015, Ghana.

Abstract

Accurate information on irrigated areas' spatial distribution and extent are crucial in enhancing agricultural water productivity, water resources management, and formulating strategic policies that enhance water and food security and ecologically sustainable development. However, data are typically limited for smallholder irrigated areas, which is key to achieving social equity and equal distribution of financial resources. This study addressed this gap by delineating disaggregated smallholder and commercial irrigated areas through the random forest algorithm, a non-parametric machine learning classifier. Location within or outside former apartheid "homelands" was taken as a proxy for smallholder, and commercial irrigation. Being in a medium rainfall area, the huge irrigation potential of the Inkomati-Usuthu Water Management Area (UWMA) is already well developed for commercial crop production outside former homelands. However, information about the spatial distribution and extent of irrigated areas within former homelands, which is largely informal, was missing. Therefore, we first classified cultivated lands in 2019 and 2020 as a baseline, from where the Normalised Difference Vegetation Index (NDVI) was used to distinguish irrigated from rainfed, focusing on the dry winter period when crops are predominately irrigated. The mapping accuracy of 84.9% improved the efficacy in defining the actual spatial extent of current irrigated areas at both smallholder and commercial spatial scales. The proportion of irrigated areas was high for both commercial (92.5%) and smallholder (96.2%) irrigation. Moreover, smallholder irrigation increased by over 19% between 2019 and 2020, compared to slightly over 7% in the commercial sector. Such information is critical for policy formulation regarding equitable and inclusive water allocation, irrigation expansion, land reform, and food and water security in smallholder farming systems.

Keywords: South Africa; informal irrigation; irrigated areas; sustainable development smallholder farmers; vegetation indices; water security.

Grants and funding

201790/WT_/Wellcome Trust/United Kingdom