摘要
为了探究茅洲河流域感潮河网面源污染空间分布特征和降雨径流污染规律,基于空间分析、统计分析与流域水动力-水质耦合模拟方法,对典型降雨情景下河网水质情况进行模拟分析,提出基于水质改善目标的生态补水点位空间布局优化策略.研究表明,层次聚类凝聚算法和K-均值法迭代组合可以较好地实现面源污染分级与分类;茅洲河各支流中,石岩渠、松岗河中上游等河道(段)由于面源污染负荷相对较高且缺乏生态补水,雨后水质恢复缓慢;基于补水总量不变原则,对生态补水方案进行局部优化,优化结果可使雨后受污染重点河道(段)水质恢复速度加快一倍以上,提高了流域水质的整体稳定性.研究结论可为进一步认识茅洲河流域水污染特征、实现流域水环境精细化管理提供支撑.
To explore the spatial distribution characteristics and pollution pattern of non-point source pollution of the tidal river network in the Maozhouhe River basin,the river network water quality under typical rainfall scenarios was simulated and analysed based on spatial analysis,statistical analysis and hydrodynamic-water quality coupling simulation method.An ecological water supply optimization strategy based on the target of water quality improvement was proposed.The results showed that the combination of hierarchical clustering aggregation algorithm and K-means can preferably distinguish the level and class of non-point source pollution.The water quality of the Shiyanqu River and the middle and upper reaches of the Songganghe River recovered slowly after rain fall due to the high non-point source pollution load and the lack of ecological water supply.A local optimized ecological water supply scheme was proposed based on the principle of constant amount of water replenishment.The recovery speed of water quality in key polluted rivers after rainfall was doubled by the optimized results,and the overall stability of river water quality in the basin was improved.The research conclusions provide support to the further understanding on the water pollution characteristics of the Maozhouhe River basin and the delicacy management of watershed water environment.
作者
张凤山
尚明珠
赵朋晓
程开宇
唐颖栋
魏俊
ZHANG Feng-shan;SHANG Ming-zhu;ZHAO Peng-xiao;CHENG Kai-yu;TANG Ying-dong;WEI Jun(Power China Huadong Engineering Corporation Limited,Hangzhou 311122,China)
出处
《中国环境科学》
EI
CAS
CSCD
北大核心
2021年第4期1834-1841,共8页
China Environmental Science
基金
广东省重点领域研发计划“污染防治与修复”重点专项(2019B110205005)。
关键词
感潮河网
面源污染
数值模拟
茅洲河
tidal river networks
non-point source pollution
numerical modelling
Maozhouhe River
