Future Water: Comparing and contrasting approaches to predicting water quality
AuthorGuo, D; Lintern, A; Prodanovic, V; Kuller, M; Bach, PM; Deletic, A; Shi, B; McCarthy, D; Ryu, D; Webb, JA; ...
Source TitleProceedings of 23rd International Congress on Modelling and Simulation
PublisherModelling and Simulation Society of Australia and New Zealand
University of Melbourne Author/sWestern, Andrew; Ryu, Dongryeol; Guo, Danlu; Webb, James; Liu, Shuci; Lintern, Anna
Document TypeConference Paper
CitationsGuo, D., Lintern, A., Prodanovic, V., Kuller, M., Bach, P. M., Deletic, A., Shi, B., McCarthy, D., Ryu, D., Webb, J. A., Liu, S. & Western, A. W. (2019). Future Water: Comparing and contrasting approaches to predicting water quality. Proceedings of 23rd International Congress on Modelling and Simulation, pp.1112-1118. Modelling and Simulation Society of Australia and New Zealand. https://doi.org/10.36334/modsim.2019.k15.guo.
Access StatusOpen Access
Open Access URLhttps://doi.org/10.36334/modsim.2019.K15.guo
ARC Grant codeARC/LP140100495
Globally, surface water quality deterioration is an important issue exacerbated by increasing urbanisation, intensified agricultural activities and climate change. To mitigate this increase in waterway pollution there is a strong need for effective catchment management strategies. However, this is currently limited by: (1) our lack of understanding of the key processes and mechanisms driving water quality change in waterways, and (2) our inability to predict future water quality change. To address these, we need to improve our ability to understand and model water quality. This improved capacity will enable us to better identify important water quality changes under various land use, land management and climate scenarios. These improvements could thus assist waterway managers to better prioritise regions which require special management attention, as well as better assess the benefits of different management interventions and preventative actions to reduce pollution levels.
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