基于演化四元减法集对势模糊数随机模拟的旱灾风险评估

Risk assessment of drought disaster based on evolutionary quadratic subtraction set for fuzzy number stochastic simulation

  • 摘要: 为有效评估旱灾风险,将五元联系数中的不确定性差异度项分解到偏同差异度项和偏反差异度项上,得到演化四元减法集对势,并对其中的差异度系数进行三角模糊数随机模拟,建立基于演化四元减法集对势模糊数随机模拟的旱灾风险评估模型,并应用于淮南市旱灾风险评估。结果表明:淮南市2008—2017年旱灾风险等级整体处于2~3级,属于弱中险状态,但在2014年后等级呈小幅上升趋势;在旱灾风险评估子系统中,危险性子系统、暴露性子系统和灾损敏感性子系统风险等级均逐渐降低,有向好的发展趋势,而抗旱能力子系统等级逐渐增高;单位面积水资源量、灌溉指数、复种指数、水田面积比和森林覆盖率被识别为主要障碍因子。基于演化四元减法集对势模糊数随机模拟的旱灾风险评估方法包含了五元减法集对势的计算结果,且其计算结果是一个等级置信区间,可综合反映旱灾风险变化的多因素影响、不确定性等特点。

     

    Abstract: In order to effectively assess drought risk, the uncertainty divergence term in the quintuple correlation number is decomposed into partial similarity divergence and partial dissimilarity divergence terms, resulting in an evolutionary quadruple subtraction set for potential, and the divergence coefficients are subjected to triangular fuzzy number stochastic simulation. A drought risk assessment model based on evolutionary quadruple subtraction set for fuzzy number stochastic simulation is established and applied to the drought risk assessment in Huainan City. The results show that from 2008 to 2017, the overall drought risk level in Huainan City ranged from level 2 to level 3, indicating a moderately low risk state, but there was a slight upward trend in risk level after 2014. In the subsystems of drought risk assessment, the risk levels of the hazard subsystem, exposure subsystem, and vulnerability subsystem gradually decreased, showing a positive development trend, while the resilience subsystem level gradually increased. Factors such as per unit area water resources, irrigation index, replanting index, ratio of paddy field area, and forest coverage rate were identified as the main obstacles. The drought risk assessment method based on evolutionary quadruple subtraction set for fuzzy number stochastic simulation includes the calculation results of quintuple subtraction set for potential, and its calculation results form a grade confidence interval, which can comprehensively reflect the multi-factor influences and uncertainties of drought risk changes.

     

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