Location: Water Management and Systems ResearchTitle: Modeling water quality in freshwater systems: From here to the next generation
|FU, BAIHUA - Australian National University|
|HORSBURGH, JEFFERY - Utah State University|
|JAKEMAN, ANTHONY - Australian National University|
|GUALTIERI, CARLO - University Of Napoli|
|ARNOLD, THORSTEN - University Of Hohenheim|
|MARSHALL, LUCY - University Of New South Wales|
|QUINN, NIGEL - Lawrence Berkeley National Laboratory|
|VOLK, MARTIN - Helmholtz Centre For Environmental Research|
|HUNT, RANDALL - Us Geological Survey (USGS)|
|VEZZARO, LUCA - Technical University Of Denmark|
|CROKE, BARRY - Australian National University|
|JAKEMAN, JOHN - Sandia National Laboratory|
|SNOW, VALERIE - Agresearch|
|RASHLEIGH, BRENDA - Us Environmental Protection Agency (EPA)|
Submitted to: Water Resources Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/24/2020
Publication Date: 10/29/2020
Citation: Fu, B., Horsburgh, J.S., Jakeman, A., Gualtieri, C., Arnold, T., Marshall, L., Green, T.R., Quinn, N.W., Volk, M., Hunt, R.J., Vezzaro, L., Croke, B., Jakeman, J., Snow, V., Rashleigh, B. 2020. Modeling water quality in freshwater systems: From here to the next generation. Water Resources Research. 56(11). Article e2020WR027721. https://doi.org/10.1029/2020WR027721.
Interpretive Summary: In this paper, we assess four knowledge gaps in water quality simulation, including environmental interfaces, in-stream processes, soil and urban areas. Challenges include data quality control, calibration, uncertainty management, scale mismatches and model tool provision. We conclude that model developers and specialists need to strengthen connections with experimentalists and stakeholders to cultivate knowledge for modeling processes.
Technical Abstract: In this synthesis, we assess present research and anticipate future development needs in modeling water quality in freshwater systems. We first discuss five four knowledge gaps in the representation of freshwater systems pertaining to water quality, including representation of environmental interfaces, in-stream water quality and process interactions, soil health and land management, and urban areas. In addition, we provide insights into the contemporary challenges in the practices of water quality modeling, including quality control of monitoring data, model parameterization and calibration, uncertainty management, scale mismatches and provisioning of modeling tools. Finally, we make three recommendations to provide a path forward for improving water quality modeling science, infrastructure and practices. These include building stronger collaborations between experimentalists and modelers, bridging gaps between modelers and stakeholders, and cultivating and applying procedural knowledge to better govern and support water quality modeling processes within organizations.