H2020Индивидуална стипендия2020–2022

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

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2020-09-01 → 2022-08-31
Финансиране от ЕС: 171 473 €
Участници: 1
Схема: MSCA-IF

Линиите свързват координатора с партньорите.

Накратко на български

Поведението на фермерите и тяхното възприятие за климатичните промени се анализират чрез компютърни модели, например как вземат решения за напояване на посевите. Това помага за тестване на стратегии и политики, които да подобрят адаптацията на хората към променящата се среда.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

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

Climate change impacts such as high temperature, reduced rainfall, and increased frequency of extreme weather events will add new threats to irrigation systems and will compound existing human pressures through changes to hydrological processes and socio-ecosystem interactions. Social learning is considered an important issue to reinforce individuals and communities' adaptive capacity because 1) Local experience can be shared and compared and this would be useful to identify common patterns and individual strategies (to be transferred to policy-makers), and 2) assess the perception and effectiveness of climate change responses is the first step towards adaptation. In this context, modelling human behaviour can be used as a safe laboratory for policy experimentation, testing the effectiveness of strategies and policy measures on climate change by learning from human experience. Farmers are key constituents in the social-learning process of understanding both climate change impacts on food and water systems and how best to mitigate and adapt to these impacts. Modelling human behaviour, however, is rather a non-trivial task: human behaviour is well recognized as a complex non-linear, multi-variate process due to the high heterogeneity and uncertainties in human cognition and decision-making processes. The MODFABE project aims to increase the robustness of decision-making processes in Coupled Human-Nature Systems (CHNS) by modelling farmers’ perceptions and adaptation capacity to climate change, also including feedback from irrigation districts managers. The MODFABE’s core is to integrate observational data (farmers’ perception and irrigation districts perspectives) into an Agent-Based Model (ABM) to simulate end users, managers and decision-makers attitudes and increase the rationality of farmers’ interventions regarding water resources and climate change adaptation, by considering multiple competing purposes and a multiobjective context.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

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.

Оригинален текст от CORDIS (на английски).

Участници

POLITECNICO DI MILANO · MilanoКоординаторИталия