Effects of land-cover - land-use on water quality within the kuils - Eerste River Catchment
The most significant human impacts on the hydrological system are due to land-use change. The conversion of land to agricultural, mining, industrial, or residential uses significantly alters the hydrological characteristics of the land surface and modifies pathways and rates of water flow. If this occurs over large or critical areas of a catchment, it can have significant short and long-term impacts, on the quality of water. While there are methods available to quantify the pollutants in surface water, methods of linking non-point source pollution to water quality at catchment scale are lacking. Therefore, the research presented in this thesis investigated modelling techniques to estimate the effect of land-cover type on water quality. The main goal of the study was to contribute towards improving the understanding of how different landcovers in an urbanizing catchment affect surface water quality. The aim of the research presented in this thesis was to explain how the quality of surface runoff varies on different land-cover types and to provide guidelines for minimizing water pollution that may be occurring in the Kuils-Eerste River catchment. The research objectives were; (1) to establish types and spatial distribution of land-cover types within the Kuils-Eerste River catchment, (2) to establish water quality characteristics of surface runoff from specific land-cover types at the experimental plot level, (3) to establish the contribution of each land-cover type to pollutant loads at the catchment scale. Land-cover characteristics and water quality were investigated using GIS and Remote Sensing tools. The application of these tools resulted in the development of a landcover map with 36 land classifications covering the whole catchment. Land-cover in the catchment is predominantly agricultural with vineyards and grassland covering the northern section of the catchment. Vineyards occupy over 35% of the total area followed by fynbos (indigenous vegetation) (12.5 %), open hard rock area (5.8 %), riparian forest (5.2 %), mountain forest (5 %), dense scrub (4.4 %), and improved grassland (3.6 %). The residential area covers about 14 %. Roads cover 3.4 % of the total area. Surface runoff is responsible for the transportation of large quantities of pollutants that affect the quality of water in the Kuils-Eerste River catchment. The different land-cover types and the distribution and concentration levels of the pollutants are not uniform. Experimental work was conducted at plot scale to understand whether landcover types differed in their contributions to the concentration of water quality attributes emerging from them. Four plots each with a length of 10 m to 12 m and 5 m width were set up. Plot I was set up on open grassland, Plot II represented the neyards, Plot III covered the mountain forests, and Plot IV represented the fynbos landcover. Soil samples analyzed from the experimental plots fell in the category of sandy soil (Sa) with the top layer of Plot IV (fynbos) having loamy sand (LmSa). The soil particle sizes range between fine sand (59.1 % and 78.9 %) to coarse sand (between 7 % and 22 %). The content of clay and silt was between 0.2 % and 2.4 %. Medium sand was between 10.7 % and 17.6 %. In terms of vertical distribution of the particle sizes, a general decrease with respect to the size of particles was noted from the top layer (15 cm) to the bottom layer (30 cm) for all categories of the particle sizes. There was variation in particle size with depth and location within the experimental plots. Two primary methods of collecting water samples were used; grab sampling and composite sampling. The quality of water as represented by the samples collected during storm events during the rainfall season of 2006 and 2007 was used to establish water quality characteristics for the different land-cover types. The concentration of total average suspended solids was highest in the following land-cover types, cemeteries (5.06 mg L-1), arterial roads/main roads (3.94 mg L-1), low density residential informal squatter camps (3.21 mg L-1) and medium density residential informal townships (3.21 mg L-1). Chloride concentrations were high on the following land-cover types, recreation grass/ golf course (2.61 mg L-1), open area/barren land (1.59 mg L- 1), and improved grassland/vegetation crop (1.57 mg L-1). The event mean concentration (EMC) values for NO3-N were high on commercial mercantile (6 mg L-1) and water channel (5 mg L-1). The total phosphorus concentration mean values recorded high values on improved grassland/vegetation crop (3.78 mg L-1), medium density residential informal townships (3mgL-1) and low density residential informal squatter camps (3 mg L-1). Surface runoff may also contribute soil particles into rivers during rainfall events, particularly from areas of disturbed soil, for example areas where market gardening is taking place. The study found that different land cover types contributed differently to nonpoint source pollution. GIS model was used to estimate the diffuse pollution of five pollutants (chloride, phosphorus, TSS, nitrogen and NO3-N) in response to land cover variation using water quality data. The GIS model linked land cover information to diffuse nutrient signatures in response to surface runoff using the Curve Number method and EMC data were developed. Two models (RINSPE and N-SPECT) were used to estimate nonpoint source pollution using various GIS databases. The outputs from the GIS-based model were compared with recommended water quality standards. It was found that the RINSPE model gave accurate results in cases where NPS pollution dominate the total pollutant inputs over a given land cover type. However, the N-SPECT model simulations were too uncertain in cases where there were large numbers of land cover types with diverse NPS pollution load. All land-cover types with concentration values above the recommended national water quality standard were considered as areas that needed measures to mitigate the adverse effects of nonpoint pollution. The expansion of urban areas and agricultural land has a direct effect on land cover types within the catchment. The land cover changes have adverse effect which has a potential to contribute to pollution.