An empirical research on Integrated Modelling Approach - Zillur Rahman
People’s Perceptions of Climate Change Impacts on Rural Water Resources: An empirical research on Integrated Modelling Approach - Zillur Rahman
Bangladesh is highly vulnerable to the impacts of climate change on water resources leading to extreme weather events such as floods, droughts, storms, and inundation of coastal regions. These extreme weather events threaten human life, water security and crop production. Changes in the observed frequency and intensity of these events are believed to be the consequence of changes in climate. Bangladesh government organisations have undertaken initiatives to achieve the sustainability of water resources and to adapt to, and mitigate, the impacts of climate change on water resources, but these initiatives have focused largely on the scientific perspective.
This thesis explores the social dimensions of local peoples’ understanding of the impacts of climate change and interactions with local water resources and environment under the conditions of uncertainties. The research examines the nature of the link between social-cultural perceptions about current environmental impacts and historical social-cultural traditions in Bangladesh. It develops an integrated water resource management model that incorporates this socio-cultural knowledge with other factors.
Two main tools and methods were used to analyse the data. Social cognitive aspects are investigated using social network analysis (SNA) method to better understand social-cultural perceptions and pattern of social ties for environmental knowledge sharing among participants in the communities in Bangladesh. The Bayesian Network (BN) approach is used in this thesis to integrate knowledge from the natural and human sciences, and to represent interrelationships between social, cultural, economic factors and environmental aspects. The analyses and modelling tools used in this thesis, were based on semi-structured surveys undertaken in two rural villages in Bangladesh: Bogra and Meherpur.
Results identified that people are mostly connected with a few influential actors within and outside the community for environmental knowledge sharing. These social connections are to some degree influenced by peoples’ social and cognitive factors. Results showed that people have various cultural and traditional views about the negative impacts of extreme weather events on water resources due to the impacts of climate change. Among the perceptions about the impacts of climate change, ‘Divine retribution’ is most commonly identified by participants which are linked to people’s historical traditions, and multi faith religions, but lack a contemporary environmental context in education. Bayesian networks integrated modelling frameworks in this thesis provided different observations under various scenarios and identified the most influential variables (factors) in the system: environmental impact context and policy context are influential variables in both locations. In Bogra the national authority variable is important, while in Meherpur the local authority variable is important.
The study experienced number several challenges that could be addressed in future research. Due to the small sample size, sub-group analysis was limited and statistical significance could not be tested. More structured surveys in larger sample populations might produce statistically significant results and would be better suited to the development of BN conditional probability tables using learning algorithms. The evaluation of the model was restricted to sensitivity analysis future model development quantitative performance should be based on a full evaluation process.