Hydrodynamic and Water Quality Modelling

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Our team is currently engaged in several hydrodynamic and reservoir water quality modelling studies. One-dimensional General Lake Model (GLM), two/three-dimensional TUFLOW FV and ‘Aquatic Ecodynamics’ (AED2) water quality modelling software are used for these purposes and are currently accessible (licenced) at Trop Water. Our in-house expert knowledge and understanding of both modelling and reservoir limnology provide an extra advantage for our clients, particularly in reservoir management, future planning and decision-making processes.

Surface-water Modelling System (SMS) software is used as supportive software to build conceptual models by constructing model mesh/grid using GIS objects: points, arcs and polygons. In addition, we use SMS to visualise and analyse model results and to visualise bathymetry data and develop hypsographic curves.

Our expert staff are capable of handling big data and use numerous software/programming languages such as MATLAB, QGIS, Python, Excel, Excel Macro, SURFER, PRIMER to support their data visualisation, analysis and interpretation processes. 

In addition, our scientists and engineers have experience in rainfall-runoff modelling and stormwater management system assessment (e.g., sizing, water quality performances) using software such as SWMM (open source), MUSIC and MIKE URBAN. Software licences for MUSIC or MIKE URBAN are subject to Client requirements. 

Expertise engagement in modelling;
Trop Water has an extensive network of highly skilled modelling colleagues both nationally and internationally, and believes that knowledge sharing is a key aspect of successful project deliveries, and ultimately contributes to the body of scientific knowledge. The Australian Rivers Institute at Griffith University, GLM-AED modelling team in University of Western Australia are two of our major knowledge sharing partners. Recently, Trop Water actively engaged with the Australian Rivers Institute to develop best practice guidelines for lake modelling to inform quantitative microbial risk assessment.