Abstract
Land use management plays a key role in mitigating urban river pollution. Past research has addressed how primary land uses influence river water and sediment quality, but has given limited attention to the subdivision of primary land uses to a secondary level, limiting the accurate identification of potential sources of pollutants. The current study, using Bayesian Networks, investigated how the hierarchical structure of land use can be employed to accurately characterise the pollution of sediments in two rivers in China and Australia. It was found that the primary land uses are a weak determinant of potential sources of metals, nutrients, and organochlorine pesticides (OCPs). However, secondary land uses provide higher accuracy in determining pollutant sources. The study highlighted that the lack of data to enable the subdivision of land uses can constrain informed decision making for the mitigation of urban water pollution.
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