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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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(a) MAE of different values of Manning’s roughness from 0.01 to 0.4; (b) comparison of the observed and modeled inundation depth using Manning’s roughness of 0.22.
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f5-ijerph-08-01368: (a) MAE of different values of Manning’s roughness from 0.01 to 0.4; (b) comparison of the observed and modeled inundation depth using Manning’s roughness of 0.22.

Mentions: The most detailed data observed in the study were the inundation depth of 18 points (Figure 2) in the flood event that occurred on August 1, 2008. This event, which had an estimated return period of 30–100 years [41], was caused by a rainstorm that generated up to 429 mm of rain in approximately 24 hours [42] and led to the inundation of various localities with water depths of more than 1.5 m, causing extensive property damage [41]. To calibrate the roughness coefficient of these observed data, 16 simulations were conducted with the Manning’s n values varying from 0.01 to 0.4 [33,37,43]. The response surface (Figure 5a) suggests an improvement in model performance at high values of Manning’s n, but values larger than 0.22 decreased model performance. Consequently, a uniform Manning’s n of 0.22 was used.


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)

(a) MAE of different values of Manning’s roughness from 0.01 to 0.4; (b) comparison of the observed and modeled inundation depth using Manning’s roughness of 0.22.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f5-ijerph-08-01368: (a) MAE of different values of Manning’s roughness from 0.01 to 0.4; (b) comparison of the observed and modeled inundation depth using Manning’s roughness of 0.22.
Mentions: The most detailed data observed in the study were the inundation depth of 18 points (Figure 2) in the flood event that occurred on August 1, 2008. This event, which had an estimated return period of 30–100 years [41], was caused by a rainstorm that generated up to 429 mm of rain in approximately 24 hours [42] and led to the inundation of various localities with water depths of more than 1.5 m, causing extensive property damage [41]. To calibrate the roughness coefficient of these observed data, 16 simulations were conducted with the Manning’s n values varying from 0.01 to 0.4 [33,37,43]. The response surface (Figure 5a) suggests an improvement in model performance at high values of Manning’s n, but values larger than 0.22 decreased model performance. Consequently, a uniform Manning’s n of 0.22 was used.

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