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Modelling individual farmer behaviours in Coupled Human Natural Systems under changing climate and society

Modelling individual farmer behaviours in Coupled Human Natural Systems under changing climate and society

Objective

Agriculture is one of the sectors most affected by climate change, especially in lower latitude areas, were climate change will result in increased temperature, reduced rainfall, and increased frequency of extreme weather events such as floods and droughts. Water and food nexus, often embedded in seemingly endless ecological, social and political interactions, are context-dependent, socially constructed and technically uncertain. Modelling techniques have been recognized, also in social sciences, as effective computational techniques to simulate social influence processes in human-nature systems from interactions within community of individual agents. The aim of the proposal is to reduce the vulnerability and improve the resilience of multifunctional irrigation systems to climate change scenarios by modelling individual farmer’ behaviour and informing managers and decision-makers about the effectiveness of different types of interventions. Through the combination of qualitative and quantitative methods and evidence-based analysis from social learning process (survey sample, interviews, statistical analyses, behavioural modelling simulations, artificial intelligence), insights are collected on how individual farmer and key stakeholders behave with respect to climate change adaptation in Coupled Human Natural Systems (CHNS), such as hydrosocial systems (e.g. multifunctional irrigation systems). A key question in today climate change adaptation research will be addressed: Can behaviour modelling help farmers to promote actions and anticipate decisions to adapt to climate change and become more sustainable and resilient? The assessment of farmer’ behavioural on climate change adaptation measures will be conducted on the Muzza irrigation district, located southeast of the city of Milan (Northern Italy). Modelling human behaviour can be used as a safe laboratory for policy experimentation, testing the effectiveness of strategies and policy measures on climate change.
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Coordinator

POLITECNICO DI MILANO

Address

Piazza Leonardo Da Vinci 32
20133 Milano

Italy

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 171 473,28

Project information

Grant agreement ID: 832464

Status

Grant agreement signed

  • Start date

    1 September 2020

  • End date

    31 August 2022

Funded under:

H2020-EU.1.3.2.

  • Overall budget:

    € 171 473,28

  • EU contribution

    € 171 473,28

Coordinated by:

POLITECNICO DI MILANO

Italy