摘要
突发水污染事故会破坏环境、危害健康,开展西北内陆河流域突发水污染风险评估对于维护西部脆弱生态安全尤为重要。该文针对西北内陆河流域突发水污染问题,利用PSR模型遴选18个因素建立突发水污染风险评价指标体系,基于径向基神经网络模型(RBF)构建突发水污染风险评价模型。为进一步保证模型精度,采用改进惯性权重因子和学习因子的粒子群算法(IPSO)对神经网络模型参数进行优化,建立IPSO-RBF神经网络西北内陆河突发水污染风险评价模型,并运用该模型对石羊河流域武威段2017-2022年突发水污染进行风险等级评价。结果显示,石羊河流域武威段突发水污染2017-2019年风险等级为Ⅱ级,2020-2022年风险等级为Ⅲ级,结果与熵权-TOPSIS法一致,与流域治理情况相符。该研究成果有利于提升石羊河流域突发水污染的防控水平与应急处置能力,对于西北内陆河流域水资源管理以及祁连山生态保护具有重要意义。
The sudden water pollution accident damages the ecological environment and endangers human life and health,conducting risk assessment of sudden water contamination in inland river basins is particularly important for maintaining fragile ecological security in the western region.In response to the sudden water pollution problem in the northwest inland river basin,the PSR model was used to select 18 factors to establish the risk evaluation index system of sudden water pollution,and the risk evaluation model of sudden water pollution was constructed based on the radial basis neural network model(RBF).To further ensure the model accuracy,the neural network model parameters are optimized using the particle swarm algorithm(IPSO)with improved inertia weighting factors and learning factors.Finally,an IPSO-RBF neural network risk assessment model for sudden water pollution in the northwest inland river was established,using this model to evaluate the risk class of sudden water contamination in the Wuwei Section of Shiyang River Basin from 2017 to 2022.The results show that the risk level of sudden water contamination was levelⅡfrom 2017 to 2019,and levelⅢfrom 2020 to 2022.The results are consistent with the entropy weight TOPSIS method and the watershed governance situation.The research results are beneficial for improving the prevention and control level and emergency response capacity of sudden water pollution in Shiyang River Basin,and are of great significance for water resource management in the northwest inland river basin and ecological protection in Qilian Mountains.
作者
靳春玲
蔡惠春
贡力
田亮
李战江
JIN Chunling;CAI Huichun;GONG Li;TIAN Liang;LI Zhanjiang(College of Civil Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China)
出处
《环境科学与技术》
CAS
CSCD
北大核心
2024年第9期120-127,共8页
Environmental Science & Technology
基金
国家自然科学基金项目(72261024)
甘肃省科技计划资助(23ZDFA002)。