Farmers facing droughts: Capturing adaptation dynamics in disaster risk models

Research output: PhD ThesisPhD-Thesis - Research and graduation internal

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Abstract

Drought disaster risk models have long neglected the potential of people and communities to adapt to the serious hazard posed by droughts. Failing to account for the dynamic nature of individual human adaptive behaviour leads to incomplete risk estimates. Therefore, this thesis explored how to integrate heterogeneous individual adaptive behaviour in drought disaster risk assessments. It acknowledges the unique characteristics of droughts and details how to deal with adaptation decisions and their interaction with drought disaster risk. This thesis proposes a conceptual framework to guide modellers to address the dynamic nature of drought disaster risk in time and space. Applying the framework, multiple data collection activities were conducted to disentangle the complexities of drought adaptive behaviour, and with this, a novel drought disaster risk adaptation model, ADOPT, was developed. It combines a crop-water model with an agent-based decision model and simulates small-scale agricultural adaptation decisions in response to drought disaster risk. ADOPT was used to simulate how smallholder farmers respond to pro- and reactive drought policy interventions and (future) drought events. This research contributes to drought disaster risk science through exploring the potential of explicitly including the adaptation decisions of smallholder farmers in agricultural drought disaster risk assessments. The presented conceptual framework and the ADOPT model are by no means an ultimate and exclusive solution but are mainly intended to demonstrate how drought disaster risk dynamics should be modelled with an interdisciplinary approach. This thesis demonstrates a practical example of how to improve understanding of possible evolutions of drought disaster risk under climate change and risk reduction policies. In addition, it showcases ways to support the heterogeneous smallholder farmers in Kenya’s drylands to adopt effective adaptation measures in order to achieve the Sustainable Development Goals ‘no poverty’ and ‘zero hunger’.
Original languageEnglish
QualificationPhD
Awarding Institution
  • Vrije Universiteit Amsterdam
Supervisors/Advisors
  • Aerts, Jeroen, Supervisor
  • van Loon, Anne, Supervisor
  • Veldkamp, Ted Isis Elize, Co-supervisor
Award date9 Sept 2022
Publication statusPublished - 9 Sept 2022

Keywords

  • agent-based model, drought, risk, disaster risk reduction, adaptation, farmers, agriculture, socio-hydrology, human behaviour, adaptation decisions

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