Land cover models to predict non-point nutrient inputs for selected biomes in South Africa

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