System Dynamics and Bayesian Network Models for Vulnerability and Adaptation Assessment of a Coastal Water Supply and Demand System
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A coastal water supply and demand system is a highly uncertain and dynamically complex system. The degree of high uncertainty can arise from future climate change, population growth, water consumption trends, land use changes and socio-economic development, resulting in limited availability of empirical data. The effects of temporal and spatial interactions among such driving factors further contribute to the high dynamic complexity of coastal freshwater management. To effectively manage a coastal freshwater system with high levels of uncertainty and complexity, a participatory integrated System dynamics (SD) and Bayesian networks (BNs) modelling framework was suggested to assess the vulnerability and adaptation potential of a coastal water supply and demand system in a developing country. This integrated framework enhances our ability to understand the feedback-based dynamic processes of a dynamically complex system by developing systems maps and running the SD model. It also enables decision-makers to understand and address uncertainties through scenario development and participatory involvement in constructing and analysing the sensitivity of BN models. One of the most important aspects of the integrated modelling framework is the opportunity to increase the performance of the BN model by incorporating results from the SD model to populate conditional probability tables (CPTs) for some variables in the BN model. Subsequently, the best adaptation options identified from the BN model can be tested in the SD model over time. Finally, the framework enables water managers to identify appropriate management options, which incorporate multidisciplinary perspectives. Da Do Basin in Hai Phong City, Vietnam is used a case study to apply the participatory integrated modelling framework. Although, several steps (historical data collection, the development of a causal loop diagram, the initial SD and BN models) in the integrated modelling framework have been conducted in the case study, some future work is required to finalise the framework.
Proceedings of the 8th International Congress on Environmental Modelling and Software: Supporting Sustainable Futures
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Water Resources Engineering