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Streams and sessions for MODSIM2023 are listed below. You can expand the list of sessions under each stream and click on each session title to see a description.

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A. Applied and computational mathematics

Stream Leaders: Barry Croke and Georgy Sofronov

The Applied and computational mathematics stream focuses on mathematical contributions to modelling and simulation (e.g. based on statistical, stochastic and PDE modelling). This includes development, application and testing of algorithms used in data analysis, model formulation (including component integration), sensitivity analysis and uncertainty quantification. Examples of areas of interest include inverse problems, machine learning, and industrial applications.

B. Biological systems

Stream Leaders: Malcolm McPhee and Val Snow

Biological Systems welcomes submissions from a wide range of modelling styles: mathematical, mechanistic process-based, agent-based, systems dynamics, and/or data science approaches as applied to biological and agricultural systems. Topics can be inclusive of models and simulation: from descriptions, to development, to applications. Examples of areas of interest include: uncertainty and sensitivity analysis; image analysis; machine learning and artificial intelligence; advances in agent-based modelling of wildlife and pests; livestock, rangelands, pasture and cropping systems; drought resilience, terrestrial and aquatic food webs, and value chain modelling

C. Computer science and engineering

Stream Leaders: Min Chen and Dan Ames

Methods for sharing data and computational resources, integrating models, and building simulation systems integrating various disciplines in the open web environment are rapidly changing with the continual development of new information and communications technologies (ICT) including cloud computing, edge computing, blockchain computing, high-performance computing and high-speed Internet. We encourage the submission of papers that provide further insights in novel, emerging and advanced ICT, other software technologies and computational methods; and that support decision making to solve comprehensive complex issues in the era of ‘big science’.

This stream is supported and co-led by the International Environmental Modelling and Software Society (iEMSs, and The Open Modeling Foundation (

D. Economics and finance

Stream Leaders: Chia-Lin Chang, Hamid Yahyaei and Lurion De Mello

The Economics and finance stream welcomes proposals from a wide range of issues pertaining to Innovation and Trade, Risk Management, and impacts of Climate variability/change on financial markets and economies more generally. Examples of topics include any original research and comprehensive review papers at the intersection of economics and finance with commodity markets, international trade, financial risk modelling, and computational finance, and financial markets and climate impact modelling.

E. Energy, integrated infrastructure and urban planning

Stream Leaders: John Boland and Behzad Rismanchi

Australia is in the midst of an energy transition.  The move to Electrify Everything is underway.  This revolution requires a myriad of activities in various areas.  This stream focuses on multiple ways infrastructure networks, systems and services contribute to urban renewal, regional development, better liveability and enhanced productivity. Smart data analytics, resource assessment and forecasting, digital twins, real-time modelling and complex network optimisation are becoming essential instruments for planning, managing, protecting and upgrading these systems. The stream can include submissions covering forecasting of renewables, energy efficient building design, microgrid design, precinct infrastructure, and related topics.

F. Environment and ecology

Stream Leaders: Stefan Reis and Shawn Laffan

Modelling, simulation and software systems play a pivotal role in our understanding of environmental and ecological systems. Complex interactions and relationships require environmental modelling and software tools to underpin and improve decision making in policy and regulatory contexts. Advances in data science, machine learning and approaches to harness big data are key to tackle vast challenges of environmental degradation and global climate change. We encourage the submission of sessions which focus on the development of generic frameworks and integration of models across issues, scales, disciplines and stakeholders. The stream will accommodate sessions spanning a scope from advances in modelling, software and simulation, the development and use of advanced software tools, interdisciplinary and transdisciplinary environmental modelling, the integration of models and software tools across issues, scales, disciplines and stakeholders, to the application of novel data science concepts in decision support.

This stream is supported and co-led by the International Environmental Modelling and Software Society (iEMSs,

G. Global change and natural hazards

Stream Leaders: Jason Evans and Christoph Rudiger

In this stream we are interested in all aspects of global change and natural hazards and their interactions within the earth system. Topical streams may include modelling of natural hazards such as drought, heatwaves, hail, fires, tropical cyclones, earthquakes, and tsunamis. It also covers modelling of global change issues such as climate change, land degradation (including desertification and plant migration), and the relevance for United Nations sustainable development goals. New model developments and modelling of the phenomena, their impacts on human and natural systems, potential techniques for adaptation, and the use of remote sensing data to address these, are all of interest.

H. Health and biosecurity

Stream Leaders: Louise Freebairn and Irene Hudson

The Australian bushfires and COVID-19 pandemic brought into sharp focus the importance of data analytic and systems science methods to support evidence-based decision and policy making for health. The Health and biosecurity stream will focus on latest developments, applications and challenges for epidemiological and biosecurity modelling, data science and machine learning. Health applications include but are not limited to disease surveillance, communicable diseases, chronic diseases, health services and systems, human behaviour and health, climate change and environmental exposures and health risks.

I. Social systems and modelling processes

Stream Leaders: Kate O'Brien and Oz Sahin

This stream covers all aspects of the human and cultural dimensions of modelling. This includes modelling socio-ecological systems (human-environment interactions), applications or approaches which bring a social-systems lens to modelling, and the process of modelling and associated challenges and best practice. Suitable content for this stream includes model development, data and knowledge management, pedagogical culture, application, case-studies, theory, practice, challenges, opportunities and insights into integration for modelling socio-ecological systems, and for a life-cycle approach to modelling which incorporates input from decision-makers and diverse knowledge sources from model conceptualisation through to application. Submissions that include Indigenous perspectives on modelling are particularly encouraged.

J. Water resources

Stream Leaders: Jai Vaze and Murray Peel

The Water Resources stream focuses on research into hydrological processes and hydrological modelling tools (landscape and river system) that advance our understanding and management of surface water and groundwater at catchment, regional and continental scales over time scales from hours to decades.

Topics of relevance include (but are not limited to):

  • water balance tools that integrate models and multiple data sources to deliver aggregated national and regional water accounts
  • hydrological modelling frameworks for national and regional water assessments, including those informing environmental flows, flooding and climate change
  • data-driven studies that inform our understanding of hydrological change and dynamics, both historically and under climate change
  • fully coupled surface water, groundwater and river system models (with uncertainty quantification) for development of catchment and basin water management and sharing plans
  • improved understanding of hydrological processes and hydrological modelling methods through model-data fusion (parameterisation, reanalyses and calibration against multiple data sources), system-wide calibration of water balance components (catchment rainfall-runoff, river routing and losses).

K. Hydroclimate

Stream Leaders: Yongqiang Zhang and Conrad Wasko

This stream focuses on the research fields between climate and hydrology. With continuous climate change in the past several decades and the foreseeable future, our understanding of the hydroclimate continues to evolve, and the complexity in forecasting, predicting, simulating, or attributing change, means many processes, and their interactions, remain not completely understood. However, new data sets, statistical tools, modelling techniques, and advances in computing are all providing us opportunities to improve the understanding of the hydroclimate. We invite proposals from a wide variety of disciplines that analyse and model all aspects of the hydroclimate, from rainfall, to streamflow, evapotranspiration, groundwater, temperature, and their related hazards. We encourage proposals aiming to improve our process understanding, untangle uncertainties, and attribute changes across all time and spatial scales in the hydroclimate.

L. Water quality

Stream Leaders: Andrew Western, Danlu Guo and Anna Lintern

Poor water quality has social, economic and environmental consequences, and maintaining good water quality is key to sustaining human life. While we still need to understand fundamental water quality processes, we increasingly have a need to model new and emerging water treatment systems, emerging chemicals, the impacts of climate change and land and water management on water quality, and interactions between socio-economic systems and water quality. We invite proposals that focus on monitoring, modelling and analyses of all aspects of water quality across all environments including natural, agricultural, urban, peri-urban catchments, as well as rivers, groundwater, lakes, estuaries and other receiving waters.


Stream Leaders: Melanie Ayre and Simon Dunstall

The Operations Research (OR) stream seeks high-quality contributions from across the broad spectrum of OR methods, techniques and applications in academia, defence and industry. Techniques may include (but are not limited to) mixed integer-linear programming, constraint programming, metaheuristics, and modelling and simulation through to more recent approaches in matheuristics, artificial intelligence (AI), machine learning (ML) and data sciences (DS). Applications areas may include (but are not limited to) emergency management and natural hazards, defence, transport, logistics, mining, agriculture and healthcare. We encourage collaboration between academia and industry in both session proposals and paper submissions.

Z. General

Stream Leaders: Susan Cuddy and David Post

While all efforts have been made to cater for all types of modelling and simulation within the streams listed above, there may be some papers that just don't quite fit. This Stream has been established to cater for those papers.

SESSION: Z1. General
This session is a placeholder for papers that don't fit easily into other sessions, either because they describe a new modelling paradigm or are so general that they transcend all other streams.