摘要
为对新型复合树脂生态护坡配套狐尾藻、黄菖蒲、龙须草等3种植物的净化效果进行评估,基于地累积指数法(I geo)、富集系数法(EF)和Hakanson潜在生态风险指数法对采用不同措施的河道潜在生态风险进行了评估,并分析相对应情况下的水质分布情况。基于改进麻雀搜索算法(MSSA)及改进FCM算法,将相对较优措施应用于城市河道中,并将改进FCM算法应用于T-S模糊神经网络模型中,对实施护坡前后的实际河道水质风险进行了综合评估。结果表明:采用生态护坡配套狐尾藻措施可大幅度降低河道重金属的质量分数,同时I geo指数处于清洁状态的采样点超过50%,EF指数为无或轻度富集等级,潜在生态风险指数均为低风险等级,基于T-S模型对风险进行评估的结果可知,该措施下实际河道15个采样点均为低风险等级。
In order to evaluate the purification effect of three kinds of plants,such as foxtail algae,gladiolus and asparagus,as the support of the new composite resin ecological slope protection,based on the geoaccumulation index method(I geo),the enrichment factor method(EF)and the Hakanson potential ecological risk index method,the potential ecological risk of the river channel with different measures was evaluated and the distribution of water quality in the corresponding situation was also analyzed.Based on the improved sparrow search algorithm(MSSA)and the improved FCM algorithm,the relatively better measures were applied to urban river channels.The improved FCM algorithm was applied to the T-S fuzzy neural network model,and the risk of river water quality before and after slope protection was assessed comprehensively.The results showed that ecological slope protection supported by verticillatum measures can greatly reduce the content of heavy metals in the river.The I geo index is basically in a clean state at different sampling points,the EF index is no or slightly enriched,and the potential ecological risk index is all low risk.The results of risk assessment based on T-S model show that all the 15 sampling points in the actual river channel by this measure are all at low risk level.
作者
匡义
陈一新
张迅
丁春梅
KUANG Yi;CHEN Yixin;ZHANG Xun;DING Chunmei(Forestry and Water Resources Bureau of Fuyang District,Hangzhou 311400,China;College of Water Conservancy and Environment Engineering,Zhejiang University of Water Resources and Electric Power,Hangzhou 310018,China)
出处
《浙江水利水电学院学报》
2023年第3期43-49,64,共8页
Journal of Zhejiang University of Water Resources and Electric Power
基金
浙江省水利厅科技计划项目(RC2228)
浙江省重点水利科技项目(RB2022)。
关键词
生态护坡
狐尾藻
生态风险
麻雀算法
T-S模糊神经网络
ecological slope protection
verticillatum
ecological risk
Sparrow Search Algorithm
T-S fuzzy neural network