Engineering and Information Technology Collected Works - Research Publications

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    Future Water: Comparing and contrasting approaches to predicting water quality
    Guo, D ; Lintern, A ; Prodanovic, V ; Kuller, M ; Bach, PM ; Deletic, A ; Shi, B ; McCarthy, D ; Ryu, D ; Webb, JA ; Liu, S ; Western, AW (Modelling and Simulation Society of Australia and New Zealand, 2019-12-01)
    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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    Modelling the impact of land use and catchment characteristics on stream water quality using a Bayesian hierarchical modelling approach in the Great Barrier Reef catchments
    Liu, S ; Ryu, D ; Western, A ; Webb, JA ; Lintern, A ; Waters, D ; Thomson, B ; Syme, G ; Hatton MacDonald, D ; Fulton, B ; Piantadosi, J (Modelling and Simulation Society of Australia and New Zealand Inc., 2017)
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    Understanding the spatial variability in catchment dynamics: a case study of 107 stream catchments in Victoria
    Lintern, A ; Webb, J ; ryu, ; liu, S ; Bende-Michl, U ; Watson, M ; Waters, D ; Leahy, P ; Wilson, P ; Western, A ; Syme, G ; Hatton MacDonald, D ; Fulton, B ; Piantadosi, J (The Modelling and Simulation Society of Australia and New Zealand, 2018-12-03)
    Rivers and streams around the world are being affected by declining water quality. When designing remediation strategies, we must first understand the key factors affecting spatial and temporal variability in stream water quality. As such, the objective of this investigation was to investigate the relationships between in-stream constituent concentrations and streamflow and to understand how these relationships vary across space. We intend to use these findings to add a temporal component into existing statistical models of spatial variability in water quality. Monthly water quality data for total suspended solids (TSS), total phosphorus (TP), filterable reactive phosphorus (FRP), total Kjedahl nitrogen (TKN), nitrate-nitrite (NOx) and electrical conductivity (EC), in addition to streamflow collected between 1994 and 2014 from 107 water quality monitoring sites in Victoria were used for this study. Using these data, we characterized the interaction between constituent concentrations and streamflow in terms of (i) the ratio of the coefficient of variation (CV) of constituent concentrations to the CV of streamflow (CVC/CVQ) , and (ii) the slope of the linear regression between the log-transformed constituent concentrations and log-transformed streamflow (the C-Q slope). We then linked the spatial variations in CVC/CVQ and the C-Q slope to catchment characteristics (e.g., land use and climate). We found that the interaction between constituents and streamflow depends significantly on the reactivity of the constituent, and whether the constituent is in the dissolved or particulate state. TSS, TP, TKN, FRP and NOx demonstrated chemodynamic behavior, with the concentrations varying with streamflow (i.e., high CVC/CVQ and large absolute value in C-Q slope). On the other hand, EC demonstrated chemostatic behavior for the selected sites, with low CVC/CVQ values and C-Q slopes. The interaction between streamflow and constituents varied significantly across space. The variability in CVC/CVQ for TSS, nutrients and salts correlated positively with catchment characteristics such as mean catchment slope, average annual rainfall and woodland cover. This could be due to the weaker sources of TSS due to reduced erosion, nutrients due to zero or low application and salts due to high leaching in steeply sloping, vegetated and high rainfall catchments (as they tend to be less disturbed). Lower magnitude and less temporal consistency of constituent sources can lead to greater variability in constituent concentrations relative to streamflow. The spatial variability in C-Q slopes generally did not correlate strongly to catchment characteristics, likely due to the presence of major dams in approximately half of the water quality monitoring sites. However, once these sites were removed, we found that the TSS C-Q slope correlated strongly to average annual rainfall and the mean 7-day low flow. This suggests that there is a stronger positive linear relationship between TSS concentrations and streamflow in catchments with temporally consistent rainfall and streamflow. There were weak correlations between catchment characteristics and the C-Q slopes for nutrients regardless of the exclusion of the water quality monitoring sites with dams. This could be due to the reactive nature of these compounds, leading to less predictable interactions between streamflow and in-stream concentrations. The results of the analysis will be used to develop statistically-based predictive models of spatio-temporal variability in stream water quality.