Abstract
The correlation between water quality and land use and land cover change plays a significant role in the quality of the rivers. These changes directly impact the water’s physical, biological, and chemical composition. Remote sensing and geographical information system tools have been widely used to measure the relationship between land use and land cover change and water quality parameters. This approach depends on collecting field data, historical data, land use and land cover data. Seasonal field samplings were conducted for a period of two years to determine the temporal and spatial variation in the Klip River. This study analysed the historical land use and land cover data from the years 2003, 2008, 2013, 2018 and 2023 and some historical water quality data to determine the correlation. Supervised classification with a maximum likelihood classifier was applied to generate LULC maps for the selected periods. A correlation model statistical method was used to determine the relationship between LULC change and water quality variables and to develop a sustainable urban ecological restoration model.
The water quality parameter results generally showed poor conditions and exceeded the target limits for some parameters. Medium sand dominated the sites, and upstream sites were strongly correlated with E. coli and faecal coliform bacteria. In contrast, the downstream sites were strongly associated with nitrate, nitrite, phosphorus and chlorophyll-a. Metals were more detectable in the sediment samples, with some present in high concentrations above the limit. Organic compounds were also more detectable in sediment samples with SVOCs and phenols in high concentrations. Moreover, little variations were observed between seasons. Macroinvertebrates results showed a poor abundance of macroinvertebrates with low SASS scores and ASPT values. The results of LULC change from 2003 to 2023 revealed an increase in the residential area (13.83%), bare soil (12.66%), mine (0.7%); meanwhile, forest (-27.1%) and waterbody (-0.09%) recorded a decreasing trend. The LULC change correlated positively and negatively with water quality parameters, implying that LULC change impacts water quality.
The Klip River, transversing diverse land uses, suffers from poor water quality, highlighting the urgent need for an urban ecological restoration approach. In response to the “UN Decade on Ecosystem Restoration” (2021-2030) initiative, this study proposed a sustainable urban ecological restoration model based on comprehensive water quality and land use and cover (LULC) data. The conceptual framework derived from this model incorporates five components: drivers, pressures,
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state, impacts, and responses. The conceptual framework supported by regular river cleanup, holistic community engagements, and constant monitoring are effective strategies that can be implemented to improve water quality in the Klip River.
Keywords: Water pollution, heavy metals, SVOCs, Landsat images, macroinvertebrates, remote sensing, Conceptual framework.