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Economic analysis of adaptive strategies for flood risk management under climate change

Overview of attention for article published in Mitigation and Adaptation Strategies for Global Change, March 2015
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134 Mendeley
Title
Economic analysis of adaptive strategies for flood risk management under climate change
Published in
Mitigation and Adaptation Strategies for Global Change, March 2015
DOI 10.1007/s11027-015-9637-0
Pubmed ID
Authors

Thomas D. van der Pol, Ekko C. van Ierland, Silke Gabbert

Abstract

Climate change requires reconsideration of flood risk management strategies. Cost-benefit analysis (CBA), an economic decision-support tool, has been widely applied to assess these strategies. This paper aims to describe and discuss probabilistic extensions of CBA to identify welfare-maximising flood risk management strategies under climate change. First, uncertainty about the changes in return periods of hydro-meteorological extremes is introduced by probability-weighted climate scenarios. Second, the analysis is extended by learning about climate change impacts. Learning occurs upon the probabilistic arrival of information. We distinguish between learning from scientific progress, from statistical evidence and from flood disasters. These probabilistic extensions can be used to analyse and compare the economic efficiency and flexibility of flood risk management strategies under climate change. We offer a critical discussion of the scope of such extensions and options for increasing flexibility. We find that uncertainty reduction from scientific progress may reduce initial investments, while other types of learning may increase initial investments. This requires analysing effects of different types of learning. We also find that probabilistic information about climate change impacts and learning is imprecise. We conclude that risk-based CBA with learning improves the flexibility of flood risk management strategies under climate change. However, CBA provides subjective estimates of expected outcomes and reflects different decision-maker preferences than those captured in robustness analyses. We therefore advocate robustness analysis in addition to, or combined with, cost-benefit analysis to support local investment decisions on flood risk reduction and global strategies on allocation of adaptation funds for flood risk management.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 134 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 <1%
Australia 1 <1%
Canada 1 <1%
Brazil 1 <1%
Unknown 130 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 26 19%
Student > Ph. D. Student 24 18%
Researcher 23 17%
Student > Bachelor 8 6%
Student > Doctoral Student 6 4%
Other 17 13%
Unknown 30 22%
Readers by discipline Count As %
Environmental Science 32 24%
Engineering 19 14%
Economics, Econometrics and Finance 12 9%
Earth and Planetary Sciences 9 7%
Social Sciences 9 7%
Other 15 11%
Unknown 38 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 March 2015.
All research outputs
#15,682,052
of 23,906,448 outputs
Outputs from Mitigation and Adaptation Strategies for Global Change
#609
of 688 outputs
Outputs of similar age
#147,097
of 259,411 outputs
Outputs of similar age from Mitigation and Adaptation Strategies for Global Change
#6
of 10 outputs
Altmetric has tracked 23,906,448 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 688 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.8. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 259,411 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.