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Contact


Email

reihaneh.bandari@unimelb.edu.au

Credentials


Position
Porstdoctoral Research Fellow
Department of Infrastructure Engineering
ORCID

0000-0002-7357-1897

Dr Reihaneh Bandari

Porstdoctoral Research Fellow
Department of Infrastructure Engineering

13 Scholarly works
0 Projects

HIGHLIGHTS

  • 2026

    Journal article

    Assessing irrigation-driven carbon emissions across the Murray–Darling Basin: first insight from publicly available datasets
    DOI: 10.1088/1748-9326/aea7b7
  • 2026

    Journal article

    Systematic review of knowledge co-production and stakeholder engagement in spatial planning for sustainability in China
    DOI: 10.1038/s44458-026-00135-6
  • 2026

    Journal article

    Conservation, Sustainable Use and Equity in Biological Resource Research and Development Governance: Australian Scientists’ Perspectives
    DOI: 10.3390/su18073293
  • 2026

    Journal article

    Socio-economic and environmental sustainability of biomanufactured food and agricultural products: An integrated assessment framework
    DOI: 10.1016/j.isci.2025.114624
  • 2024

    Journal article

    Transdisciplinary approaches to local sustainability: aligning local governance and navigating spillovers with global action towards the Sustainable Development Goals
    DOI: 10.1007/s11625-024-01494-6
  • 2024

    Report

    Farming Resilience Futures, Navigating Three Possibilities for the Goulburn-Murray Region
  • 2023

    Journal article

    Participatory Modeling for Analyzing Interactions Between High-Priority Sustainable Development Goals to Promote Local Sustainability
    DOI: 10.1029/2023EF003948
Reihaneh Bandari

RECENT SCHOLARLY WORKS

  • 2022

    Journal article

    Prioritising Sustainable Development Goals, characterising interactions, and identifying solutions for local sustainability
    DOI: 10.1016/j.envsci.2021.09.016
  • 2021

    Journal article

    Evaluating Participatory Modeling Methods for Co-creating Pathways to Sustainability
    DOI: 10.1029/2020EF001843
  • 2020

    Journal article

    Improving Daily Peak Flow Forecasts Using Hybrid Fourier-Series Autoregressive Integrated Moving Average and Recurrent Artificial Neural Network Models
    DOI: 10.3390/ai1020017

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