Identifying and prioritising adaptation options for a coastal freshwater supply and demand system under climatic and non
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ORIGINAL ARTICLE
Identifying and prioritising adaptation options for a coastal freshwater supply and demand system under climatic and non-climatic changes Thuc D. Phan 1,2
&
James C. R. Smart 3 & Oz Sahin 4 & Ben Stewart-Koster 3 & Wade L. Hadwen 3 & Samantha J. Capon 3
Received: 6 September 2019 / Accepted: 18 June 2020 # Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Coastal freshwater supply and demand systems are expected to be significantly affected by changes to both climatic and nonclimatic drivers over coming decades. Adapting to these changes to secure adequate freshwater to meet the rising demands of socio-economic development has become a critical task for decision-makers. Whilst a range of adaptation options may be available, the complexity and interconnectedness of water resource systems make it challenging to identify which options are likely to be most feasible and effective. Here, we present a Bayesian decision network (BDN) that was co-developed with local experts to identify appropriate adaptation options for freshwater management under both current and likely future conditions in the Da Do Basin of coastal Vietnam. Potential adaptation options were prioritised according to cost-effectiveness based on relative costs incurred and relative utilities delivered across a range of future scenarios. The BDN model indicated that costeffectiveness of adaptation options varied between future scenarios. Constructing pumping stations was the most cost-effective option under climate change scenarios, whilst a higher water price was the most cost-effective option under non-climatic changes. Under combined climatic and non-climatic changes, constructing pumping stations in combination with increasing water prices provided the most cost-effective option. The model affords an opportunity for decision-makers in the Da Do Basin to prioritise and evaluate appropriate and feasible adaptation actions under different scenarios with respect to multiple drivers. Keywords Bayesian decisionnetwork . Climate changeadaptation . Coastal water management . Developing country . Population growth . Sea level rise
Introduction Water supply and demand systems are threatened by both climate change and human development (Blazejczak et al. 2012; Phan et al. 2018). In coastal areas, sea level rise and
precipitation change are major climatic drivers of freshwater supply (Sušnik et al. 2015) which interact to affect river discharge, water levels and saltwater penetration in estuaries (Ross et al. 2015). These factors, in turn, determine the operation of infrastructure used to deliver freshwater to water
Communicated by Xiangzheng Deng * Thuc D. Phan [email protected]
Samantha J. Capon [email protected]
James C. R. Smart [email protected]
1
Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam
Oz Sahin [email protected]
2
Griffith Centre for Coastal Management, Griffith University, Gold Coast, Queensland 4215, Australia
Ben Stewart-Koster b.stewart-koster
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