2011
DOI: 10.1111/j.1752-1688.2011.00552.x
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A Decision-Analytic Approach to Managing Climate Risks: Application to the Upper Great Lakes1

Abstract: Brown, Casey, William Werick, Wendy Leger, and David Fay, 2011. A Decision‐Analytic Approach to Managing Climate Risks: Application to the Upper Great Lakes. Journal of the American Water Resources Association (JAWRA) 47(3):524‐534. DOI: 10.1111/j.1752‐1688.2011.00552.x Abstract:  In this paper, we present a risk analysis and management process designed for use in water resources planning and management under climate change. The process incorporates climate information through a method called decision‐scaling,… Show more

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Cited by 132 publications
(101 citation statements)
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References 20 publications
(26 reference statements)
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“…As a result, the number of successful CC adaptation strategies implemented is small, despite good recommendations from scientists [17,31]. Thus, more decision-oriented adaptation research and practices are emerging [50][51][52][53][54][55][56]. This aspect of the scientific literature, however, reveals the limitations of the reported in developing countries, where much of the adaptation planning and actions are conducted.…”
mentioning
confidence: 84%
“…As a result, the number of successful CC adaptation strategies implemented is small, despite good recommendations from scientists [17,31]. Thus, more decision-oriented adaptation research and practices are emerging [50][51][52][53][54][55][56]. This aspect of the scientific literature, however, reveals the limitations of the reported in developing countries, where much of the adaptation planning and actions are conducted.…”
mentioning
confidence: 84%
“…Applications of SA for this purpose are far less numerous than those for uncertainty investigation and model calibration. However, they are increasingly investigated, see for example Brown et al (2011), Singh et al (2014) and references therein.…”
Section: Sa Dominant Controls Analysis and Robust Decision-makingmentioning
confidence: 99%
“…Climate scenarios can be generated parametrically or stochastically to explore uncertainty in climate variables that affect the system of interest [Prudhomme at al., 2010;Brown et al, 2011]. This allows sampling changes in climate that include but are not constrained by the range of GCM projections.…”
Section: Alternatives To Gcm-based Analysesmentioning
confidence: 99%
“…Other climate modelers assert that the spread of uncertainty may be reduced by adjusting known model biases in simulating present climate [Boberg and Christensen, 2012]. Some researchers are beginning to think that it is better to generate climate scenarios in such a way that one can control, by design, the range of climate changes in the specific variables of interest [e.g., Prudhomme et al, 2010;Brown et al, 2011].…”
Section: Fig 1 Variability Statistics Of Bias-corrected Statisticamentioning
confidence: 99%