Remote sensing of surface water quality in relation to catchment condition in Zimbabwe

Abstract

The degradation of river catchments is one of the most important contemporary environmental problems affecting water quality in tropical countries. In this study, we used remotely sensed Normalised Difference Vegetation Index (NDVI) to assess how catchment condition varies within and across river catchments in Zimbabwe. We then used non-linear regression to test whether catchment condition assessed using the NDVI is significantly (α = 0.05) related with levels of Total Suspended Solids (TSS) measured at different sampling points in thirty-two sub-catchments in Zimbabwe. The results showed a consistent negative curvilinear relationship between Landsat 8 derived NDVI and TSS measured across the catchments under study. In the drier catchments of the country, 98% of the variation in TSS is explained by NDVI, while in wetter catchments, 64% of the variation in TSS is explained by NDVI. Our results suggest that NDVI derived from free and readily available multispectral Landsat series data (Landsat 8) is a potential valuable tool for the rapid assessment of physical water quality in data poor catchments. Overall, the finding of this study underscores the usefulness of readily available satellite data for near-real time monitoring of the physical water quality at river catchment scale, especially in resource-constrained areas, such as the sub-Saharan Africa.