An integrated model to predict and prevent hypoxia in floodplain-river systems

Area of Science:

• Environmental Science
• Hydrology
• Water Quality Management

Background:

• Floodplain rewetting can lead to hypoxia, impacting aquatic ecosystems and biogeochemical cycles.
• Managed inundations, often at lower flow rates, can exacerbate hypoxic "blackwater" events compared to natural floods.
• Understanding the interplay between hydrology, floodplain inundation, and water quality is crucial for effective management.

Purpose of the Study:

• To develop a model for simulating dissolved organic carbon (DOC) and dissolved oxygen (DO) dynamics during floodplain inundation.
• To provide a tool for risk mitigation strategies related to managed inundation events.
• To integrate complex water quality processes into hydrological modeling software.

Main Methods:

• Development of the "DODOC plugin" for the Source hydrological modelling software.
• Incorporation of key processes: spatial variability of litter, DOC leaching, microbial DO consumption, and reaeration.
• Parameterization of the model using data from the River Murray, South Australia, distinguishing between labile and refractory DOC components.

Main Results:

• The DODOC plugin successfully simulated DOC (R² = 0.84–0.93) and DO (R² = 0.74–0.92) dynamics.
• Model simulations demonstrated parameter sensitivity and informed hypothetical operational scenarios.
• The model can represent inundation impacts at various scales, from single floodplains to multiple river reaches.

Conclusions:

• The DODOC plugin effectively integrates complex water quality processes into hydrological models.
• This tool can represent the cumulative impacts of floodplain inundation events.
• The model aids in minimizing the risk of hypoxia associated with managed inundations.