Spatiotemporal Analysis of Channel Morphometrics in the Ga-Selati River, Limpopo Province, South Africa

River channel morphometrics are critical indicators of geomorphic stability, flood susceptibility, and catchment health, yet quantitative spatiotemporal morphometric baselines remain scarce for many semi-arid tributaries in southern Africa. This study quantifies and evaluates changes in channel morphometrics along the Ga-Selati River, a tributary of the Olifants River in Limpopo Province, South Africa, between 2015 and 2025 to assess the influence of climate variability and land-use change on channel stability.

Annual dry-season Landsat 8 Collection 2 Level-2 Surface Reflectance imagery (2015–2025) was processed using Google Earth Engine and QGIS to extract channel planform characteristics, including channel width, bankline position, centreline geometry, and sinuosity. The Modified Normalised Difference Water Index (MNDWI) and Normalised Difference Vegetation Index (NDVI) were applied to delineate water bodies and riparian vegetation. A 30 m Shuttle Radar Topography Mission (SRTM) Digital Elevation Model was used to derive basin morphometric parameters, including drainage density, stream frequency, bifurcation ratio, relief ratio, elongation ratio, circularity ratio, and form factor, providing the geomorphic context for observed channel adjustments. Classification accuracy was evaluated using standard accuracy assessment metrics derived from reference data.

Preliminary results indicate that the Ga-Selati River maintained an overall stable planform during the study period, although measurable channel widening occurred in the upper reaches and downstream of instream dams, suggesting geomorphic adjustment associated with altered flow regimes and sediment dynamics. Basin morphometric characteristics indicate moderate erosion susceptibility within the catchment. Quantitative analyses of channel width, sinuosity, and basin morphometric indices will provide a baseline for evaluating channel stability and informing river management. The study demonstrates the value of integrating Google Earth Engine and QGIS for long-term river morphometric monitoring and provides the first remote sensing-derived morphometric baseline for the Ga-Selati River, supporting flood risk assessment, infrastructure planning, and sustainable catchment management in semi-arid river systems.