Abstract
WQSAM is a practical water quality model for use in guiding southern African water quality management. However, the estimation of non-point nutrient inputs within WQSAM is uncertain, as it is achieved through a combination of calibration and expert knowledge. Non-point source loads can be correlated to particular land cover types. Although observed water quality data through which non-point source loads can be estimated are scarce, land cover databases exist covering the entire area of South Africa. To reduce the uncertainty associated with estimating non-point source loads, this study describes a formal model to link the nutrient signatures of incremental flow to land cover. Study catchments incorporating the fynbos, grassland, savanna and thicket biomes were identified. Instream nutrients of 25 sites were modelled using WQSAM and calibrated against observed data. Multiple regression was used to investigate the relationships between the calibrated nutrient signatures of incremental flow from WQSAM and land cover within study sites. The regression models reflected greater non-point loads from cultivation- and urban-related land cover categories. The nutrient signatures of incremental flow obtained through the multiple regressions were consistent with those obtained through calibration of the WQSAM model at higher signature values, whereas discrepancies were evident at lower values. It is argued that this formal modelling approach for linking land cover to nutrient signatures of incremental flow can be implemented for situations where it is known that there are strong non-point inputs of nutrients into a river reach. The statistical model presented in the current study could potentially be applied as an alternative to the water quality model as a relatively simple method to estimate non-point source loads of nutrients from tributary catchments in South Africa. Keywords: land cover, non-point inputs, nutrients, southern Africa, Water Quality Systems Assessment Model
Highlights
The continual degradation of water quality of freshwater resources is a global problem (Zimmerman et al, 2008)
Water quality modelling in South Africa is constrained by a lack of observed data, technical modelling expertise and funding, and there is a rich history of hydrological modelling and systems modelling for flow, water quality research and modelling is relatively undeveloped
The Water Quality Systems Assessment Model (WQSAM) (Hughes and Slaughter, 2016; Slaughter et al, 2015) was designed to use the available observed water quality data and to simulate water quality data that are useful for water resource management in South Africa, in that WQSAM takes as input, flow data generated by routinely used systems models, and water quality data are simulated in a form that is able to provide an estimate of risks associated with management decisions
Summary
The continual degradation of water quality of freshwater resources is a global problem (Zimmerman et al, 2008). The application of existing internationally developed water quality models to South African catchments is hindered by the aforementioned constraints on observed data and modelling expertise. Within this context, the Water Quality Systems Assessment Model (WQSAM) (Hughes and Slaughter, 2016; Slaughter et al, 2015) was designed to use the available observed water quality data and to simulate water quality data that are useful for water resource management in South Africa, in that WQSAM takes as input, flow data generated by routinely used systems models, and water quality data are simulated in a form that is able to provide an estimate of risks associated with management decisions. WQSAM has initially focused on simulating nutrients, as eutrophication is arguably currently the most pressing water quality issue within freshwater resources in South Africa
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