Informing equitable water and food policies through accurate spatial information on irrigated areas in smallholder farming systems
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...
| Main Authors: | , , , , , |
|---|---|
| Format: | Journal Article |
| Language: | Inglés |
| Published: |
MDPI
2021
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/117599 |
| _version_ | 1855518765339377664 |
|---|---|
| author | Magidi, J. van Koppen, Barbara Nhamo, L. Mpandeli, S. Slotow, R. Mabhaudhi, Tafadzwanashe |
| author_browse | Mabhaudhi, Tafadzwanashe Magidi, J. Mpandeli, S. Nhamo, L. Slotow, R. van Koppen, Barbara |
| author_facet | Magidi, J. van Koppen, Barbara Nhamo, L. Mpandeli, S. Slotow, R. Mabhaudhi, Tafadzwanashe |
| author_sort | Magidi, J. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | 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. |
| format | Journal Article |
| id | CGSpace117599 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI |
| publisherStr | MDPI |
| record_format | dspace |
| spelling | CGSpace1175992024-06-26T10:09:15Z Informing equitable water and food policies through accurate spatial information on irrigated areas in smallholder farming systems Magidi, J. van Koppen, Barbara Nhamo, L. Mpandeli, S. Slotow, R. Mabhaudhi, Tafadzwanashe smallholders farming systems irrigated farming water policies food policies food security water security spatial distribution rainfed farming irrigated land cultivated land catchment areas crop production farmers sustainable development datasets normalized difference vegetation index biochemistry 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. 2021-12-16 2022-01-20T07:02:56Z 2022-01-20T07:02:56Z Journal Article https://hdl.handle.net/10568/117599 en Open Access MDPI Magidi, J.; van Koppen, Barbara; Nhamo, L.; Mpandeli, S.; Slotow, R.; Mabhaudhi, Tafadzwanashe. 2021. Informing equitable water and food policies through accurate spatial information on irrigated areas in smallholder farming systems. Water, 13(24):3627. [doi: https://doi.org/10.3390/w13243627] |
| spellingShingle | smallholders farming systems irrigated farming water policies food policies food security water security spatial distribution rainfed farming irrigated land cultivated land catchment areas crop production farmers sustainable development datasets normalized difference vegetation index biochemistry Magidi, J. van Koppen, Barbara Nhamo, L. Mpandeli, S. Slotow, R. Mabhaudhi, Tafadzwanashe Informing equitable water and food policies through accurate spatial information on irrigated areas in smallholder farming systems |
| title | Informing equitable water and food policies through accurate spatial information on irrigated areas in smallholder farming systems |
| title_full | Informing equitable water and food policies through accurate spatial information on irrigated areas in smallholder farming systems |
| title_fullStr | Informing equitable water and food policies through accurate spatial information on irrigated areas in smallholder farming systems |
| title_full_unstemmed | Informing equitable water and food policies through accurate spatial information on irrigated areas in smallholder farming systems |
| title_short | Informing equitable water and food policies through accurate spatial information on irrigated areas in smallholder farming systems |
| title_sort | informing equitable water and food policies through accurate spatial information on irrigated areas in smallholder farming systems |
| topic | smallholders farming systems irrigated farming water policies food policies food security water security spatial distribution rainfed farming irrigated land cultivated land catchment areas crop production farmers sustainable development datasets normalized difference vegetation index biochemistry |
| url | https://hdl.handle.net/10568/117599 |
| work_keys_str_mv | AT magidij informingequitablewaterandfoodpoliciesthroughaccuratespatialinformationonirrigatedareasinsmallholderfarmingsystems AT vankoppenbarbara informingequitablewaterandfoodpoliciesthroughaccuratespatialinformationonirrigatedareasinsmallholderfarmingsystems AT nhamol informingequitablewaterandfoodpoliciesthroughaccuratespatialinformationonirrigatedareasinsmallholderfarmingsystems AT mpandelis informingequitablewaterandfoodpoliciesthroughaccuratespatialinformationonirrigatedareasinsmallholderfarmingsystems AT slotowr informingequitablewaterandfoodpoliciesthroughaccuratespatialinformationonirrigatedareasinsmallholderfarmingsystems AT mabhaudhitafadzwanashe informingequitablewaterandfoodpoliciesthroughaccuratespatialinformationonirrigatedareasinsmallholderfarmingsystems |