2014
DOI: 10.1007/s11069-014-1307-0
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Integrated risk assessment method of waterlog disaster in Huaihe River Basin of China

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Cited by 16 publications
(23 citation statements)
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“…By using the grade eigenvalue method [34] and establishing the connection numbers between assessment samples and grades u r (i, g), the connection numbers for agricultural drought disaster assessment CN (r, i) can be obtained as shown by Equation 13:…”
Section: Assessment Of Agricultural Drought Disastermentioning
confidence: 99%
“…By using the grade eigenvalue method [34] and establishing the connection numbers between assessment samples and grades u r (i, g), the connection numbers for agricultural drought disaster assessment CN (r, i) can be obtained as shown by Equation 13:…”
Section: Assessment Of Agricultural Drought Disastermentioning
confidence: 99%
“…Without loss of generality, the level of each index was divided into three grades (i.e., r = 3), and r = 1, 2, 3 representing three types of water resources carrying status, where r = 1 corresponded to the loadable status representing that the regional water resources still owned enough carrying capacity, and the condition of water supply was relatively good; r = 2 corresponded to the critical status representing that although the degree of water resources utilization had reached a high level, there was still a certain development potential, water supply could meet the demand of social economy to some extent; and r = 3 corresponded to the overloaded status representing that the carrying capacity had been close to a saturated value, the potential for further development was small; moreover, if this status lasted for a long time, water shortage would occur and appropriate control measures should be taken in time. An improved fuzzy analytic hierarchy process based on the accelerating genetic algorithm (AGA-FAHP) [ 32 ] was used to calculate the subjective weight { w s ( k , j )| k = 1, 2, 3; j = 1, 2, …, n k } and objective weight { w o ( k , j )| k = 1, 2, 3; j = 1, 2, …, n k } of each index. Subjective weight.…”
Section: Regional Water Resources Carrying Capacity Evaluation Andmentioning
confidence: 99%
“…Corrected A s k was denoted as B s k = ( b k ij ) n k × n k , and the ordering weights of element in B s k were still recorded as { w s ( k , j )| k =1, 2, 3; j =1, 2, …, n k }. In addition, B s k met the following formula: where B s k is regarded as the optimal fuzzy consistency judgment matrix of A s k when the result of CIC reached a minimum value; CIC ( n k ) is the consistency index coefficient; d is a non-negative parameter and selected from 0 to 0.5 for guaranteeing the importance relationship between two indices [ 32 ]. The ordering weights { w s ( k , j )| k = 1, 2, 3; j = 1, 2, …, n k } and all upper-triangular elements in B k were optimization variables, and there were n k ( n k + 1)/2 variables for A s k with n k order in the k -th subsystem.…”
Section: Regional Water Resources Carrying Capacity Evaluation Andmentioning
confidence: 99%
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“…Following Zhao (2000), SPA has seen widespread applications in mathematics, physics, information science, economy, resource assessment, and environmental science. In the context of hydrology and environmental science, SPA has been used for urban ecosystem health assessment (Su et al, 2009), water resources system assessment (Wang et al, 2009), river health evaluation (Xu et al, 2011), landslide hazard degree assessment (Wang and Li, 2012), selection of a reference basin in ungauged regions (Wang et al, 2013), risk assessment and forewarning for regional water resources (Zhao et al, 2013), evaluation of drought index at multi-time scales , water resources trends (Feng et al, 2014), river basin resource compensation characteristics (Chen et al, 2014), river eco-system assessment and restoration (Jiang et al 2015), waterlog disaster risk evaluation (Jin et al, 2015), and sustainability assessment of a water resources system (Du et al 2015).…”
Section: Introductionmentioning
confidence: 99%