Comparison of the alternative models SOURCE and SWAT for predicting catchment streamflow, sediment and nutrient loads under the effect of land use changes
Date
2019
Authors
Nguyen, H.
Recknagel, F.
Meyer, W.
Frizenschaf, J.
Ying, H.
Gibbs, M.
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Journal article
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Science of the Total Environment, 2019; 662:254-265
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Hong Hanh Nguyen, Friedrich Recknagel, Wayne Meyer, Jacqueline Frizenschaf, He Ying, Matthew S. Gibbs
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Abstract
Quantifying the water quantity and quality variations resulting from human induced activities is important for policy makers in view of increasing water scarcity and water pollution. Simple models can be robust tools in estimating the runoff from catchments, but do they also sufficiently reflect complex physio-chemical processes required for spatially-explicit simulation of soil-water interactions, and the resulting pollutant responses in catchments? Do these models respond sensitive to the impacts of different land use change representations? These questions are considered by applying the semi-distributed process-based catchment models SWAT and SOURCE to the Sixth Creek catchment in South Australia. Both models used similar data whereas inputs for SOURCE were generated from land-use based Functional Units (FUs), while FUs for SWAT were based on land use, soil and slope combinations. After satisfying calibration of both models for the outlet station of the catchment, the simulated flow by SOURCE produced high goodness of fit metrics, while nutrient loads simulated by SWAT were more realistic. Both models benefitted from using locally available Potential Evapotranspiration data for calibrating the hydrology. Scenarios of intensified land uses by two models showed more credible results for sediment and nutrient loads with the static approach when simulating the linear rather than the non-linear land use changes. The study has shown that informing decisions on the hydrology at catchment scale is well suited to less-complex models, whereas decisions on impact of land use change on water quality in catchments are better suited by models with process descriptions for soil-water interactions.
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© 2019 Elsevier B.V. All rights reserved.