Queensland Water Modelling Network Programs and Projects
2020 QWMN Forum, 26–27 February, Brisbane.
Registrations close Monday 17 February 2020 at 5.00pm.
QWMN External Engagement Program
The QWMN has initiated an External Engagement Program (EEP) to help build the capacity of water modelling and user expertise in Queensland, facilitate engagement across the full range of actors in the Queensland water-modelling ecosystem, and stimulate innovation in all aspects of water modelling and use. A consortium, led by the International Water Centre, is delivering a program of work that complements QWMN activities and investments to facilitate greater collaboration among water modellers, users and decision makers across Queensland, creating a community of water modelling excellence.
A key initiative is the QWMN Innovation Program where Innovation Associates register for PhD degrees then work directly with industry partners in local and state government and the private sector, to develop practical solutions to state, regional and local economic, environmental and social challenges.
Other activities include the annual QWMN Forum, a state-wide skills and knowledge audit to guide investment in education, training and workforce capability growth, a Hack, and a mentoring program to nurture and guide students into water modelling as a career path. A dedicated water modelling website has also been developed to showcase the program.
Consortium members are the Australian Institute of Marine Science, Griffith University, the International Water Centre, Queensland Cyber Infrastructure Foundation, Queensland University of Technology, The University of Queensland, and the University of Southern Queensland.
(New) Strategic review of Queensland water models
Increasing demands for higher quality model outputs in shorter timeframes can result in ‘stretching’ a model beyond the conceptual limits it was originally designed to meet. This project involves a strategic review of Queensland’s water models and their functions, led by BMT Commercial Australia in collaboration with The University of Queensland and The University of Western Australia. A key output will include an assessment framework to help modellers and decision-makers identify opportunities for improvement, integration, or transition to a different model or approach altogether. A final report will be provided to the QWMN to guide future strategic investment in Queensland’s water models.
(New) Review of the science used in the MEDLI model
The Model for Effluent Disposal using Land Irrigation (MEDLI) was first released in 1996, and is used to inform regulation and approvals associated with land-based disposal of effluent. MEDLI Version 2 was released in 2015 to allow the model to run on modern operating systems, however the science underpinning the model remained unchanged. This project includes input from four experts reviewing the Nitrogen, Phosphorus and Hydrology components of the Pond and Soil modules within MEDLI. A synthesis document with a set of recommendations will be provided to the QWMN to inform the next update of the MEDLI.
(New) Gully Erosion Framework to underpin rehabilitation and catchment modelling for Queensland
This project will develop a standardised framework and guidelines for collecting data on erosion gullies within Queensland. The Precision Erosion and Sediment Management Research Group (PrESM) at Griffith University is leading the project in collaboration with the Queensland Government (Departments of Environment and Science and Natural Resources, Mines and Energy). The framework will refine the gully characterisation framework developed by Griffith University under National Environmental Science Program (NESP) Tropical Water Quality hub; standardise data collection protocols for gullies in Queensland; improve data for catchment modelling; and, consider the associated database structure. This will inform the storage of erosion gully data across Queensland.
Stream bank erosion in the Great Barrier Reef catchments
This project will investigate the feasibility of applying alternative approaches to model stream bank erosion rates in the Great Barrier Reef catchments. Alluvium is leading the project with support from Griffith University, Reef Catchments, Fitzroy Basin Association and Wildland Hydrology. Improving stream bank erosion rate prediction in Great Barrier Reef catchments would deliver a better understanding of the key drivers of water quality, informing targeted mitigation strategies to improve water quality in Queensland. The project has undertaken a review of existing bank erosion models and research gaps, recommending a stream-type based approach and multi-temporal analysis as a way forward.
Visualisation of coupled economic and Queensland water quality models
This project will develop a cloud-based platform to couple water quality and economic models to assess natural resource management investment options for the Great Barrier Reef region. Truii Pty Ltd (in collaboration with the Office of the Great Barrier Reef) are developing this platform based on two existing custom tools: the Great Barrier Reef Foundation Reef Planning Investment Tool and the Seqwater Catchment Investment Decision Support System. The platform will use data management functionality to enable revision and updating of the latest available water quality and economic modelling data.
Model data portal to deliver catchment modelling data to end users
Successful modelling programs receive constant requests from end users for model results. These requests often require intensive processing. Truii Pty Ltd, in collaboration with the Office of the Great Barrier Reef, will develop a web-based model data portal to enable the delivery of catchment modelling results from the Paddock to Reef program. Data requesters will be able to create and record data queries which will generate data summaries for visualisation and download.
Addressing uncertainty in coupled water models using machine learning techniques
Linking models of varying complexity and scope can lead to uncertainties from each individual model, magnifying the uncertainty of final predictions. Data driven models and ensemble machine learning techniques can be used to improve predictions of water quality model outputs. BMT are leading this project in partnership with the University of Western Australia and Healthy Land and Water. The outcome is to develop capability hybridising process-based and data driven water models to improve predictions of model outputs in the context of a south-east Queensland catchment. Read the project proposal Addressing cumulative uncertainty in linked catchment and receiving water models using machine learning techniques .
Prediction of daily rainfall and runoff peak rates to inform hillslope erosion prediction and improve water quality modelling
This project will provide data improvements and estimation techniques that might allow hillslope erosion predictions of the Paddock to Reef catchment modelling for Reef Plan (for grazing lands) to be more sensitive to cover and management improvements. Delivered by Griffith University, this project will include data products for predictions of runoff depth and the peak runoff rate, at time and spatial scales for improved P2R Catchment modelling for Reef Plan.
Queensland Water Modelling Network (QWMN) Fellow
Based at the Australian Rivers Institute, Griffith University, the QWMN Fellow will undertake research that improves model functionality and capability between the catchment and its receiving water environments, having consideration for the influence of land use/land management, climate change and policy interventions to sustain the Great Barrier Reef. The work is initially focusing on the riverine and estuarine environment, building on knowledge, capacity and models that have been developed for the Great Barrier Reef to establish strategic estuarine, gully and streambank modelling capability.
- Effects of temporal variation in sediment reduction following improved land management practices on end-of-system delivery: a modelling investigation of a grazed catchment in Queensland, Australia
- Tropical Coastal Wetlands Ameliorate Nitrogen Export During Floods
Supporting regional groundwater supply security assessments in Queensland
Groundwater is a common water supply source for many rural and urban communities within Queensland, with many towns either wholly or partly dependent on groundwater. However, evaluation of this resource is often difficult, making risk assessment and management challenging. Piloted in Monto and Biggenden but with potential statewide relevance, the project will deliver a shared understanding of the capability of a community’s water supply system to meet current and forecast future urban water demand, and the associated water supply security risks.
Critical review of climate change and water modelling in Queensland
This project assessed Queensland’s current ability to incorporate climate variability and climate change projections in water models. Bringing together an experienced team of hydrologists, hydroclimate scientists, water quality scientists and practitioners, Alluvium Consulting Australia delivered the project in partnership with the Commonwealth Scientific and Industrial Research Organisation (CSIRO) and University of Newcastle. Using the best available science, the project provides a clear pathway to consistent, robust modelling approaches for assessing climate change in Queensland water models.
The outcomes of a workshop, an interview process with key modelling, planning and policy groups and four modelling case studies provided multiple lines of evidence to underpin the Strategic Investment Portfolio in the final project report. The investment portfolio includes 26 recommendations aligning with a primary objective to: Increase Queensland’s ability to understand the impact of climate variability and change on water-related systems, to increase economic, social and ecological resilience.
The recommendations are linked to five key outcomes which will contribute to achieving the primary objective:
- Outcome 1: Increase consistency and defensibility of approaches for assessing risks from climate variability and change.
- Outcome 2: Interpret and summarise the applicability of existing climate science and datasets for Queensland.
- Outcome 3: Address climate science and water modelling gaps through targeted research initiatives.
- Outcome 4: Empower individuals and collectives, and facilitate collaboration.
- Outcome 5: Develop training, communication and guidance materials to support Outcomes 1–4.
Read the full report Critical review of climate change and water modelling in Queensland . Additionally, some useful products (e.g. evaluation criteria for treatment of climate science in water modelling) will be taken from the main report and published in the near future.
The QWMN is coordinating an integrated response to the final report and investment portfolio recommendations. To get involved, contact QWMN@des.qld.gov.au.
Improved Source modelling to support catchment management investment decisions
Source provides a powerful, flexible platform for catchment modelling, but its existing default constituent models (including constituent generation, filtration and transport) are inadequate for catchment management investment decisions. This project, delivered under a collaborative research agreement with ANU, and co-funded by the Department of Natural Resources, Mines and Energy, developed and implemented fit-for-purpose constituent models.
Improved model governance and management for HowLeaky
HowLeaky is a one dimensional, soil water balance model that allows users to explore the impacts of soil physical properties, climate, management practices and crop growth on the soil water balance, runoff/erosion and pesticide and nutrient losses. This project, delivered through a collaborative research agreement with USQ, implemented recommendations from the independent review of the HowLeaky model to improve its governance, version control and long-term stability. Read the project report Developing HowLeaky platform for improved governance . A HowLeaky manual has also been developed to support existing and new users of the model.
Improved model-based decision support through simulator-independent parallelism
The new generation of in-house and cloud-based computing hardware presents previously unavailable options for massive parallelism. Easily implemented parallelism at the model run level can provide a means through which environmental modelling can progress towards its decision-support potential. This project, delivered by Watermark Numerical Computing, develops a new run manager with a front-end application programmers interface (API) callable from multiple languages and a back end optimised for use in office network environments, and on Windows/Linux high-performance computing clusters. Read the project report Uncertainty analysis and reduction through simplified model run parallelisation .
Tracking the effectiveness of gully management at reducing bioavailable nutrients
Modelling and monitoring of dissolved inorganic nitrogen (DIN) generation from eroded sediment helps inform on-ground management interventions such as gully rehabilitation in Great Barrier Reef catchments. This project built on previous work that developed and demonstrated an approach to model DIN generation from eroded sediment using Dynamic Sednet (Project RP178a). This project developed a standard methodology for estimating DIN generation from eroded sediment for application across a range of Paddock to Reef catchment monitoring programs. Led by the Catchment and Riverine Processes team Department of Environment and Science (DES), the project was a collaborative effort from numerous organisations: Department of Natural Resources, Mines and Energy, TropWATER, James Cook University; Precision Erosion and Sediment Management Research Group, Griffith University; CSIRO; Greening Australia; Fruition Environmental; NQ Dry Tropics; Great Barrier Reef Catchment Loads Monitoring Program, DES; Chemistry Centre, DES; Howley Environmental Consulting; Cape York Monitoring Partnership; and the Burdekin Bowen Integrated Floodplain Management Advisory Committee Inc. Read the project report Towards the standardisation of bioavailable particulate nitrogen in sediment methods .
Data management and visualisation to support water quality modelling teams
Data visualisation capability is seen as fundamental in improving uptake and application of model outputs and recommendations by policy makers and resource managers. This project, delivered by Yorb, and co-funded by the Office of the Great Barrier Reef, developed standardised templates for catchment and paddock models, developed standardised data extraction capability and refined the dynamic visualisation layers.
Improvements to the Dynamic SedNet model
The Dynamic SedNet model, which underpins Paddock to Reef catchment modelling, is implemented as a series of plugins to the eWater Source system. Independent reviews suggested Dynamic SedNet could be more efficiently implemented outside of eWater Source. This project, delivered by Yorb, and co-funded by the Department of Natural Resources, Mines and Energy, has developed an improved and independent implementation of Dynamic SedNet.
Integrating paddock scale modelling and water Source models
This project improved the interface between agricultural systems modelling (paddock scale models) and catchment scale water resource/water quality Source models to inform Reef investment decisions and evaluate best management practice implementation effectiveness. Delivered by Alluvium, this project has improved the representation of daily constituent concentrations entering the Reef. Read the project report Integration of Paddock-Scale Modelling and Source .
Development of an annotated catalogue of water models in use in government
This project, delivered by Griffith University, developed an annotated catalogue of the major water models in use by government. The QWMN Water Model Catalogue will serve as a reference for new users and non-experts and facilitate broader and appropriate use of water models in policy and decision-making, inside and outside government.
Enhanced eWater software to inform water resource planning
The eWater SOURCE modelling framework has been used to report on Great Barrier Reef plan water quality targets progress since 2009. The increasing complexity of the SOURCE modelling framework is severely impacting run time efficiency in parallel with a growing demand for more integrated model outputs. This project, delivered by eWater and co-funded by the Department of Natural Resources, Mines and Energy, has supported improvements to the core eWater software to enhance model run time efficiency, performance and stability.
Consensus based streambank and gully conceptual models in Queensland
This project, led by Dr Ian Prosser, synthesised existing knowledge of biophysical processes driving gully, streambank and channel erosion dynamics, focusing on Queensland catchments and conditions, to develop a conceptual framework to support the use of new process knowledge and spatial information to improve the existing modelling framework. Key to the project was a facilitated workshop involving leading Australian researchers in gully and streambank erosion modelling and monitoring.
Good modelling practice principles of the Queensland Water Modelling Network
This project delivered under the Queensland Government's collaborative research agreement with ANU developed a reference document – the Queensland Water Modelling Network Good Modelling Practice Principles – which outlines a current and consistent approach to modelling principles for R&D. It is supporting the broader understanding and use of models in the government, private and university sectors.
Detailed scope of work to support parallelism of models at the simulator level
The increasing complexity of environmental models coupled with model calibration demands results in an increased requirement for computational resources. This project, delivered through Watermark Numerical Computing, developed a detailed scope of work for the development of a software suite, which supports parallelism of models at the simulator level.