基于DFA-灰色聚类模型的亚高山草甸风电场土地损毁评价OA

[Objective]A land damage assessment model for subalpine meadow wind farms was developed,and empirical research was conducted in order to provide a theoretical basis and technical reference for the precise identification and evaluation of land damage areas in this area and other wind farm construction projects.[Methods]A subalpine meadow wind farm located on Gaoben Mountain in Xundian County,Yunnan Province,was taken as an example.Seventeen evaluation indicators(10 soil-related and 7 damage-related)were selected.The indicator weights were determined using the Delphi-Fuzzy-AHP(hereafter referred to as DFA)method.A possibility function was established by integrating it with the grey clustering method.Observed values were used to calculate the possibility function values of seven evaluation units(two units in the phase Ⅰ wind turbine zone,two units in the phase Ⅱ wind turbine zone,a waste dump,a quarry and the original topography).Finally,by comparing the magnitude of the coefficients,the land damage severity grades for each evaluation unit were determined.[Results]① The weight of damage factors(0.642 0)was significantly higher than that of soil factors(0.358 0).The core damage factors were slope length of the damaged surface(0.183 2)and vegetation coverage(0.167 6),reflecting their direct influence on engineering safety and soil erosion.Among soil factors,soil bulk density(0.069 5)and organic matter content(0.050 4)had the highest weights,mainly due to soil structure change and fertility decline caused by construction disturbance.② Grey clustering evaluation showed that the damage degree of the phase Ⅰ wind turbine zone was moderate(grade Ⅲ),that of the phase Ⅱ wind turbine zone was very strong(grade Ⅴ),that of the waste dump was strong(grade Ⅳ),that of the quarry was severe(gradeⅥ),and that of the original topography was light(grade Ⅱ).③ The difference in land damage degree resulted from construction disturbance intensity and restoration cycle.The phase Ⅰ project achieved better ecological restoration because surface soil was preserved and natural recovery time was longer,whereas the phase Ⅱ project involved a larger disturbance area and a shorter time since completion,resulting in delayed vegetation recovery.[Conclusion]Currently,land damage caused by wind farm construction is relatively serious,and the damage is dominated by construction disturbance.The high weights of damage factors highlight their priority for engineering safety and ecological risk.The results also verify the applicability of the DFA-grey clustering model in ecological restoration and management of wind farms.