Supporting Adaptive Delta Management

Systematic Exploration of Community Livelihood Adaptation as Uncertainty

Doctoral Thesis (2021)
Author(s)

U. Kulsum (TU Delft - Policy Analysis)

Research Group
Policy Analysis
Copyright
© 2021 U. Kulsum
More Info
expand_more
Publication Year
2021
Language
English
Copyright
© 2021 U. Kulsum
Research Group
Policy Analysis
ISBN (print)
978-94-6366-264-2
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Long-term planning in urbanizing deltas has to deal with deep uncertainties in socio-economic development and climate change. Adaptive Delta Management (ADM) has been developed as an approach that acknowledges these and similar uncertainties. The Bangladesh Delta Plan 2100 has, in principle, adopted the ADM approach, and it recognizes general uncertainties in (external) physical and socio-economic conditions. It does, however, not acknowledge uncertainties in the way local communities may adapt to uncertain conditions and policy measures. Historical analysis confirms that local adaptation may be different from policymaker’s expectations, and that ignoring this may seriously harm the effectiveness of such a planning approach. This research offers two novel approaches for systematic exploration of the uncertainties in community livelihood adaptation under a variety of uncertain future conditions. The first approach looks into the mental model that guides local actors’ decision making, while the second approach uses a model describing the impact of (external) triggers on actors’ motivation and abilities for a variety of adaptation actions. While both these approaches might be improved, case study applications in the polders of southwest Bangladesh illustrate their utility as instruments to create awareness of possible developments and to act as vehicles for participatory learning by both policymakers and local communities.

Files

Thesis_1.pdf
(pdf | 49.2 Mb)
License info not available