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Modelling biophysical vulnerability of wheat to future climate change: A case study in the eastern Australian wheat belt

  • Bin Wang
  • , Puyu Feng
  • , De Li Liu
  • , Cathy Waters

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Assessing the vulnerability of agriculture to climate change can identify knowledge gaps and direct where adaptation options are required. However, determining the vulnerability of agricultural production to climate change is a challenge due to the complex nature of the problem. We propose a climate-crop modelling approach illustrated by using the APSIM crop model forced with daily climate data as a case study in eastern Australia to assess the biophysical vulnerability of wheat to future climate change. This impact assessment is based on the Intergovernmental Panel on Climate Change's definition of vulnerability as a derivative of exposure, sensitivity and adaptive capacity. We selected one Global Climate Model (GCM) CSIRO-Mk3-6-0 representing dry conditions under high emission scenarios to explore the feasibility of proposed methodology. Our results show that, historically, the most vulnerable areas were the western parts of the wheat belt, accounting for 18% of the total wheat-growing area. However, areas of very high vulnerability would expand to central and eastern parts of the wheat belt into the future, accounting for 41% of the study area in the 2040s and 62% in the 2080s. With increased exposure to dry climate, adjusting sowing time and cultivar shift consistently improved wheat yield but were insufficient to decrease wheat vulnerability. We found the key driver for increased vulnerability was increased exposure to dry climate. We expect this study will help growers, farm advisors and state policymakers to adopt relevant adaptation strategies and promote efficient farming practices such as breeding drought-tolerant crop cultivars in highly vulnerable western areas.

Original languageEnglish
Article number106290
JournalEcological Indicators
Volume114
DOIs
Publication statusPublished - Jul 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020 Elsevier Ltd

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger
  2. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Adaptive capacity
  • Agricultural vulnerability
  • APSIM
  • Crop modelling
  • Wheat yield

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