Climate Change Frames in Public Health and Water Resource Management: Towards Intersectoral Climate Change Adaptation

Author(s):  
Lindsay P. Galway ◽  
Margot W. Parkes ◽  
Kitty K. Corbett ◽  
Diana M. Allen ◽  
Timothy K. Takaro

2015 ◽  
Author(s):  
Alberto Vega ◽  
Roberto Jiménez ◽  
Fernando Miralles-Wilhelm ◽  
Raúl Muñoz Castillo


2010 ◽  
Vol 103 (3-4) ◽  
pp. 537-554 ◽  
Author(s):  
Gina Ziervogel ◽  
Peter Johnston ◽  
Margaret Matthew ◽  
Pierre Mukheibir


Author(s):  
R. T. Montes-Rojas ◽  
J. E. Ospina-Noreña ◽  
C. Gay-García ◽  
C. Rueda-Abad ◽  
I. Navarro-González




Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2642 ◽  
Author(s):  
Thuc D. Phan ◽  
James C. R. Smart ◽  
Ben Stewart-Koster ◽  
Oz. Sahin ◽  
Wade L. Hadwen ◽  
...  

Bayesian networks (BNs) are widely implemented as graphical decision support tools which use probability inferences to generate “what if?” and “which is best?” analyses of potential management options for water resource management, under climate change and socio-economic stressors. This paper presents a systematic quantitative literature review of applications of BNs for decision support in water resource management. The review quantifies to what extent different types of data (quantitative and/or qualitative) are used, to what extent optimization-based and/or scenario-based approaches are adopted for decision support, and to what extent different categories of adaptation measures are evaluated. Most reviewed publications applied scenario-based approaches (68%) to evaluate the performance of management measures, whilst relatively few studies (18%) applied optimization-based approaches to optimize management measures. Institutional and social measures (62%) were mostly applied to the management of water-related concerns, followed by technological and engineered measures (47%), and ecosystem-based measures (37%). There was no significant difference in the use of quantitative and/or qualitative data across different decision support approaches (p = 0.54), or in the evaluation of different categories of management measures (p = 0.25). However, there was significant dependence (p = 0.076) between the types of management measure(s) evaluated, and the decision support approaches used for that evaluation. The potential and limitations of BN applications as decision support systems are discussed along with solutions and recommendations, thereby further facilitating the application of this promising decision support tool for future research priorities and challenges surrounding uncertain and complex water resource systems driven by multiple interactions amongst climatic and non-climatic changes.



Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1062 ◽  
Author(s):  
Sleemin Lee ◽  
Doosun Kang

The increasing frequency of extreme droughts and flash floods in recent years due to climate change has increased the interest in sustainable water use and efficient water resource management. Because the water resource sector is closely related to human activities and affected by interactions between the humanities and social sciences, there is a need for interdisciplinary research that can consider various elements, such as society and the economy. This study elucidates relationships within the social and hydrological systems and quantitatively analyzes the effects of a multi-purpose dam on the target society using a system dynamics model. A causal loop was used to identify causal relationships between the social and hydrological components of the target area, and a simulation model was constructed using the system dynamics technique. Additionally, climate change and socio-economic scenarios were applied to analyze the future effects of the multi-purpose dam on population change, the regional economy, water use, and flood damage prevention in the target area. The model proved reliable in predicting socio-economic changes in the target area and can be used to make decisions about efficient water resource management and water-resource-related facility planning.





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