Real-time control (RTC) of stormwater control systems can now enable release or storage of stormwater from tanks, ponds or wetlands in response to a variety of water management goals, such as reducing flooding and erosion downstream, providing an alternative water supply, and boosting water flow during dry periods to support downstream ecosystems. The effectiveness of water released from storages depends on how it translates downstream and how it interacts with instream physical habitat along the way. In turn, an understanding of those processes needs to be built back into RTC algorithms. This project will investigate hydrodynamic effects of stormwater releases on downstream environments, including their interaction with physical habitat and stream geomorphology, and will develop new ways to consider those processes in design and operation of RTC stormwater systems. The project will include the case study of the Monbulk Creek smart water network, but ideally will generalise findings beyond that study area using modelling approaches.

The project may include a combination of the following sub-topics, depending on the candidate’s interests:

1. Investigations of flow routing effects from stormwater release sites to target reaches, including effects of release size, streamflow, seasonality. Aim: understand the potential extent and intensity of influence of stormwater releases on downstream ecosystems. Techniques: physically-based hydrodynamic models, signal processing algorithms.
2. Development and testing of geomorphic objectives for real-time control of urban stormwater. Assess integrated effects of distributed RTC storages on erosion potential in streams (of different types, and with different substrate compositions), and investigate methods to scale instream erosion protection objectives to building-scale RTC objectives/rules. Tools: sediment transport models, flow frequency analysis, tank water balance modelling.
3. Simulations of RTC algorithm performance incorporating new objectives or rules to account for habitat and geomorphic objectives and flow routing effects between storages and targets.

The candidate will require excellent numeric and data analysis skills, and strong written and verbal communication skills. An understanding of surface hydrology, stream hydraulics and fluvial geomorphic processes is essential. Experience in the following areas is favourable:

• Hydrodynamic modelling in software such as TUFLOW, HEC-RAS 
• Hydrologic time-series data analysis 
• Sediment transport modelling
• Programming and data analysis in Python and R.

The PhD comes with a tax-free scholarship of $39,500 per year (and a small supplement may also be possible).