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Spatial multicriteria decision analysis of flood risks in aging-dam management in China: a framework and case study.

Yang M, Qian X, Zhang Y, Sheng J, Shen D, Ge Y - Int J Environ Res Public Health (2011)

Bottom Line: Approximately 30,000 dams in China are aging and are considered to be high-level risks.Based on the theories of spatial multicriteria decision analysis, this report generalizes a framework consisting of scenario definition, problem structuring, criteria construction, spatial quantification of criteria, criteria weighting, decision rules, sensitivity analyses, and scenario appraisal.With adjustments and improvement to the specific methods (according to the circumstances and available data) this framework may be applied to other sites.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210046, China. yngjyangmeng@gmail.com

ABSTRACT
Approximately 30,000 dams in China are aging and are considered to be high-level risks. Developing a framework for analyzing spatial multicriteria flood risk is crucial to ranking management scenarios for these dams, especially in densely populated areas. Based on the theories of spatial multicriteria decision analysis, this report generalizes a framework consisting of scenario definition, problem structuring, criteria construction, spatial quantification of criteria, criteria weighting, decision rules, sensitivity analyses, and scenario appraisal. The framework is presented in detail by using a case study to rank dam rehabilitation, decommissioning and existing-condition scenarios. The results show that there was a serious inundation, and that a dam rehabilitation scenario could reduce the multicriteria flood risk by 0.25 in the most affected areas; this indicates a mean risk decrease of less than 23%. Although increased risk (<0.20) was found for some residential and commercial buildings, if the dam were to be decommissioned, the mean risk would not be greater than the current existing risk, indicating that the dam rehabilitation scenario had a higher rank for decreasing the flood risk than the decommissioning scenario, but that dam rehabilitation alone might be of little help in abating flood risk. With adjustments and improvement to the specific methods (according to the circumstances and available data) this framework may be applied to other sites.

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Sensitivity analyses results: the changes of mean multicriteria flood risk for each alternative with an increment (increasing or decreasing by 0.02) of the weight of each individual indicator.
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f10-ijerph-08-01368: Sensitivity analyses results: the changes of mean multicriteria flood risk for each alternative with an increment (increasing or decreasing by 0.02) of the weight of each individual indicator.

Mentions: The sensitivity analyses were carried out by using an incremental change (0.02) in the weight of each individual indicator. The multicriteria map was translated into a non-spatial multicriteria analysis by spatial aggregation. The most commonly used method is to take the average of the values in the map [18]. After spatial aggregation, the mean risk values of the cells are used to rank the ability of the scenarios to reduce the multicriteria flood risk (Figure 10). The most sensitive relative indicators were erosion and economic loss, which resulted in the ranking of the dam-decommissioning scenario at a level very close to the ranking of the existing conditions. The perturbation of the weights in other indicators (particularly social hot spots) had a slight impact on the rankings. This revealed that the rankings were almost independent of changes in the weights associated with this indicator; thus the ranking was robust [15]. Although the results obtained from the sets of weights displayed some differences, the general structure of the final rankings was similar: the rehabilitation scenario placed first, the decommissioning scenario was second, and the existing conditions tended to be in the last position (Figure 10).


Spatial multicriteria decision analysis of flood risks in aging-dam management in China: a framework and case study.

Yang M, Qian X, Zhang Y, Sheng J, Shen D, Ge Y - Int J Environ Res Public Health (2011)

Sensitivity analyses results: the changes of mean multicriteria flood risk for each alternative with an increment (increasing or decreasing by 0.02) of the weight of each individual indicator.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC3108115&req=5

f10-ijerph-08-01368: Sensitivity analyses results: the changes of mean multicriteria flood risk for each alternative with an increment (increasing or decreasing by 0.02) of the weight of each individual indicator.
Mentions: The sensitivity analyses were carried out by using an incremental change (0.02) in the weight of each individual indicator. The multicriteria map was translated into a non-spatial multicriteria analysis by spatial aggregation. The most commonly used method is to take the average of the values in the map [18]. After spatial aggregation, the mean risk values of the cells are used to rank the ability of the scenarios to reduce the multicriteria flood risk (Figure 10). The most sensitive relative indicators were erosion and economic loss, which resulted in the ranking of the dam-decommissioning scenario at a level very close to the ranking of the existing conditions. The perturbation of the weights in other indicators (particularly social hot spots) had a slight impact on the rankings. This revealed that the rankings were almost independent of changes in the weights associated with this indicator; thus the ranking was robust [15]. Although the results obtained from the sets of weights displayed some differences, the general structure of the final rankings was similar: the rehabilitation scenario placed first, the decommissioning scenario was second, and the existing conditions tended to be in the last position (Figure 10).

Bottom Line: Approximately 30,000 dams in China are aging and are considered to be high-level risks.Based on the theories of spatial multicriteria decision analysis, this report generalizes a framework consisting of scenario definition, problem structuring, criteria construction, spatial quantification of criteria, criteria weighting, decision rules, sensitivity analyses, and scenario appraisal.With adjustments and improvement to the specific methods (according to the circumstances and available data) this framework may be applied to other sites.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210046, China. yngjyangmeng@gmail.com

ABSTRACT
Approximately 30,000 dams in China are aging and are considered to be high-level risks. Developing a framework for analyzing spatial multicriteria flood risk is crucial to ranking management scenarios for these dams, especially in densely populated areas. Based on the theories of spatial multicriteria decision analysis, this report generalizes a framework consisting of scenario definition, problem structuring, criteria construction, spatial quantification of criteria, criteria weighting, decision rules, sensitivity analyses, and scenario appraisal. The framework is presented in detail by using a case study to rank dam rehabilitation, decommissioning and existing-condition scenarios. The results show that there was a serious inundation, and that a dam rehabilitation scenario could reduce the multicriteria flood risk by 0.25 in the most affected areas; this indicates a mean risk decrease of less than 23%. Although increased risk (<0.20) was found for some residential and commercial buildings, if the dam were to be decommissioned, the mean risk would not be greater than the current existing risk, indicating that the dam rehabilitation scenario had a higher rank for decreasing the flood risk than the decommissioning scenario, but that dam rehabilitation alone might be of little help in abating flood risk. With adjustments and improvement to the specific methods (according to the circumstances and available data) this framework may be applied to other sites.

Show MeSH
Related in: MedlinePlus