Land use/land cover dynamics and soil erosion in the Umzintlava catchment (T32E), Eastern Cape, South Africa

Abstract

Land use/land cover (LULC) change is often recognised as one of the most sensitive indicators of the interaction between humans and the natural environment contributing to soil erosion. Assessing the impact of LULC dynamics on soil erosion is imperative for soil conservation planning. Against this background, the primary aim of this paper is to assess the impact of LULC change on soil erosion in the Umzintlava catchment during the period 1989–2017. To achieve this, multi-temporal Landsat data, together with the Revised Universal Soil Loss Equation (RUSLE) were used. Six LULC classes – water bodies, badlands, bare soil and built-up area, agriculture, grassland, and forest – were derived for the years 1989, 2001, and 2017, based on the Normalised Difference Vegetation Index (NDVI) classification. A post-classification change detection analysis showed that water bodies, agriculture, and grassland decreased by 0.038%, 1.796%, and 13.417%, respectively, whereas the areas covered by forest, badlands, and bare soil and built-up area increased by 9.741%, 3.7338%, and 1.778%, respectively. Results further showed that all other LULC classes, except badlands, experienced increased rates of soil loss. The proportion of the catchment area experiencing moderate (12–25t ha^-1year^-1) to extremely high (>150t ha^-1year^-1) erosion risk consistently increased. This study provides relevant information on the relationship between LULC dynamics and soil erosion risk, highlighting the necessity and importance of integrating remote sensing and empirical erosion models in spatio-temporal soil erosion assessment at the catchment level.

Keywords:

• land use/land cover dynamics
• soil erosion
• Revised Universal Soil Loss Equation (RUSLE)
• multi-temporal remote sensing
• Umzintlava

ACKNOWLEDGEMENTS

The authors wish to thank the South African Weather Services (SAWS) for providing rainfall data and the United States Geological Survey (USGS) for availing Landsat images and Digital Elevation Model (DEM) at no cost.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

ORCID

Kwanele Phinzi http://orcid.org/0000-0003-1865-7011

Additional information

Funding

This work was supported by the National Research Foundation (NRF) of South Africa (grant 107329).