A “Deep Dive” towards a novel integrated approach to future-proofing small towns

Funded by the Monash Infrastructure Interdisciplinary
Research (IDR) Seed Funding Scheme
(Project Start Year: 2018)

The Victorian government (Australia) projects there will be 2.1 million people living in regional Victoria by 2015 (VIC Government, 2016). This anticipated growth is underpinned by Government support whereby funds are being invested to attract young people to live and work in regional areas (see e.g. Stronger Regional Communities Plan). If the expansion of regional townships is not planned and managed correctly, this growth may compromise: existing infrastructures; community resilience; liveability; and, nearby waterway health.

Figure 1. Rural City of Wangaratta, location, urban area and main water courses

Regional centres need to plan their futures carefully to ensure that towns can accommodate significant demographic changes, both physically and socially while meeting the ecological needs of nearby waterways and natural environment. For this, a sound understanding of the synergistic relationship between urban development, environment and communities is required. However, data-driven planning is challenging in regional communities for the availability and quality of relevant data is often questionable. By harnessing rich, unconventional data sources such as historical, environmental, social and cultural records, engaging the local community and adopting rigorous scenario-based integrated modelling, we may be able to circumvent traditional data challenges and achieve much greater depth in planning a future-proof regional city

This project seeks to develop a holistic understanding of the interactions between waterways, community and urban development in a regional township.

Drawing on a mixed-methods approach by combining data science, stakeholder/community engagement, policy analysis and integrated modelling, the aim is to examine how we can harness unconventional data sources to  inform future strategic planning for urban growth by guiding our analysis, engagement and modelling. We propose to test this approach on the rural city of Wangaratta in north-eastern Victoria, which has a population of approximately 28,000 and is at the confluence of the King and Ovens Rivers (Figure 1).

The project explores how the integration of three significantly different scientific approaches can guide operational, tactical and strategic planning of regional towns, specifically:

  • Reconstructing historical water quantity, quality and urban development trends from sediment core data;
  • Algorithmic analysis of historical texts, media reports and community engagement outcomes to understand changes in preferences over time; and
  • Integrated modelling of the township and using above-mentioned data sets for model calibration/validation and generation and quantification of future pathways.

This project challenges the conventional ‘silo-ed’ approach to planning by promoting more holistic and collaborative methods. The diverse types of data sets to support planning processes will be brought together, culminating in a smart interactive data platform that will allow stakeholders and community members to: (1) uncover local relationships between urban development, the community and waterways, and (2) interact and visualise the variety of data sets used to develop our understanding of these interactions. Stakeholders involved in the project will be equipped with new knowledge to make better informed planning decisions for regional centres. Research partners will be able to gain a holistic view of the development of the regional centre (past, present and future) and the interactions between this development, the community and the local environment. It is anticipated that this proof-of-concept pilot study will form the basis for a larger, long-term research endeavour that will up-scale and test the findings within other regional towns across Australia and globally.


  • Victorian Government, Victoria in Future 2016: Population and household projections to 2051. 2016, Department of Environment Land, Water and Planning: Melbourne

Approach

The research involves four key tasks (based on a proposed conceptual framework in Figure 2). The first three tasks will occur concurrently, and the results of each step will help inform the others. These tasks are:

  • Task 1 – Data science: extrapolating from historical and environmental records
  • Task 2 – Culture and community: engaging stakeholders to elicit planning preferences
  • Task 3 – Integrated modelling: using models to understand historical change
  • Task 4 – Future proofing Wangaratta: consolidating the integrated planning approach

The Team

The team on this project involves researchers from Australia and Switzerland across three universities.

Anna Lintern (Project Lead)
Lecturer
Civil Engineering, Monash University
Peter Bach (Co-Lead)
Research Scientist
Eastern Switzerland University of Applied Sciences
Megan Farrelly
Associate Professor
School of Geography, Monash University
João P. Leitão
Senior Scientist
Urban Water Management (Eawag)
Behzad Jamali
Research Associate
Water Research Centre (UNSW)

Other Collaborators:

  • Adam Kessler (Earth Sciences, Monash University)
  • Carl Grodach (Architecture/Urban Planning, Monash University)
  • Catherine Murphy (Architecture/Urban Planning, Monash University)

Research Students on the Project:

  • Spencer Browne (Bachelor Project – 2020)
  • Vivian Gong (Bachelor Project – 2021)
  • Alex Sui (Bachelor Project – 2021)
  • Beverly Chen (Bachelor Project – 2021)

Industry Partners

The project is supported by three Australian industry partners who are deeply engaged in future-proofing the Rural City of Wangaratta

Publications from the Project

This list will be updated as new publications become available

  • Browne, S., Lintern, A., Jamali, B., Leitão, J.P. and Bach, P.M., 2021. Stormwater management impacts of small urbanising towns: The necessity of investigating the ‘devil in the detail’. Science of the Total Environment757, p.143835. [Link] (Open Access)