Oral Presentation World Lake Conference 2025

Use of process-based wetland modelling as a guide to contribute to water quality improvements (#59)

Natnael Shiferaw Legesse 1 , Liliana Pagliero 1 , David Hamilton 1 , Tony Weber 2 , Ha Nguyen 3 , Nathan Waltham 4 , Felix Egger 2 , Joel Rahman 5 , Melanie Roberts 1 , Mohammad Hassan Ranjbar 1
  1. Australian Rivers Institute, School of Environment and Science, Griffith University, Brisbane, QLD, Australia
  2. Alluvium Consulting, Brisbane, QLD, Australia
  3. Alluvium Consulting, Sydney, NSW, Australia
  4. Centre of Tropical Water and Aquatic Ecosystem Research, College of Science and Engineering, James Cook University, Townsville, Australia
  5. Flow Matters Pty Ltd, Canberra, ACT, Australia

 

Wetlands are important ecosystems that depend on fresh water and support a wide range of aquatic and terrestrial plants and animals. They provide ecosystem services and, therefore, support economic, social, and environmental outcomes. The interplay of hydrodynamic and biogeochemical processes determines the level of ecosystem services provided by individual wetlands. Wetlands are commonly referred to as natural sponges as they play a significant role in attenuating peak flows and sediments due to their long hydraulic residence time (Seifollahi-Aghmiuni et al., 2019). They also remove nutrients through biogeochemical processes such as denitrification, sedimentation, plant uptake and mineralisation (Kadlec & Wallace, 2009). Wetlands are a nature-based solution that helps improve the resilience of catchments to climate change and extreme events. Modelling is a critical tool to support wetland design by quantifying the performance and optimising the restorative role of wetlands in the landscape. Consequently, detailed modelling of their internal processes is required to ensure that constructed and rehabilitated wetlands perform as intended.
In this research, we model a constructed wetland, Bakers Creek wetland, in Mackay, north Queensland, Australia, using the processes-based one-dimensional (1D) General Lake Model coupled with the Aquatic Eco-Dynamics model (GLM-AED). The model was calibrated against the observed data from Dec 2019 to Apr 2020, and the performance of the model was assessed using mean absolute error and root mean square error. To better understand and model the complex processes within the wetland, we divided the wetland into distinct zones (open water, submerged vegetation, emergent vegetation, and standing vegetation zones) and explicitly quantified the biogeochemical and hydrological dynamics of each zone. This approach allowed us to identify the dominant processes by simulating different wetland zones and optimise design and management strategies. Our results showed that macrophytes and vegetation in different zones of a wetland play a crucial role in biogeochemical processes and enhance nutrient removal efficiency. Additionally, longer water retention times were found to promote biogeochemical reactions that can attenuate nutrients. We demonstrate that by incorporating zoning into a 1D wetland model, we improve our ability to capture the spatial variability of biogeochemical interactions and can provide a strategic framework for optimising wetland-based nutrient removal.

  1. 1. Kadlec, R., & Wallace, S. (2009). Treatment Wetlands 2nd Edition CRC Press. In: Lewis Publishers: New York. 2. Seifollahi-Aghmiuni, S., Nockrach, M., & Kalantari, Z. (2019). The potential of wetlands in achieving the sustainable development goals of the 2030 Agenda. Water, 11(3), 609.