摘要
密云水库主要通过上游河道来水及降水补给,为保证密云水库水质安全,应密切关注上游河道水质状况。基于2010—2021年密云水库上游河道逐月水质监测数据,分析了上游河道水质时空变化特征,结果表明:密云水库上游河道呈现氮污染严重;高锰酸盐指数、总氮、总磷、氨氮浓度年均值2010—2020年总体呈下降趋势,2021年总氮、总磷浓度有小幅回升;溶解氧浓度呈逐年向好趋势。近年,河道各水质指标大致呈逐年向好趋势,主要与密云水库上游采取的若干整治措施有关。经综合评判,白河流域天河水质最差,潮河入北京境处水质最差;按河道流向分析,河流入境至入库过程中各水质指标的距平系数大致呈下降趋势。因此,上游采取的整治措施效果明显,应继续实施河道长效管护,确保入库水质安全。
Miyun Reservoir is mainly replenished by upstream river inflow and precipitation.In order to ensure the water quality safety of Miyun Reservoir,close attention should be paid to the water quality of the upstream river.Based on the analysis of monthly monitoring data of water quality of the upstream river of Miyun Reservoir from 2010 to 2021,the temporal and spatial variation characteristics of water quality are obtained as follows:nitrogen pollution is serious;the annual mean values of permanganate index,total nitrogen,total phosphorus and ammonia nitrogen show an overall downward trend from 2010 to 2020,and concentrations of total nitrogen and total phosphorus increase slightly in 2021;the concentration of dissolved oxygen shows a good trend year by year.In recent years,the water quality indexes of the river channel generally show a good trend year by year,which is related to some remediation measures taken in the upstream of Miyun Reservoir.According to the comprehensive evaluation,the water quality of Tianhe River in Baihe River basin is the worst,while that of Chaohe River entering Beijing is the worst.Based on the analysis of river flow direction,the anomalous coefficient of each water quality index during the process of river entry to the reservoir generally shows a downward trend.It is necessary to continue to implement long-term management and protection of the river channel to ensure the safety of water quality of the reservoir.
作者
胡春春
李亚楠
杨倩
任民
HU Chun-chun;LI Ya-nan;YANG Qian;REN Min(Beijing Miyun Reservoir Management Office,Beijing 101512,China)
出处
《海河水利》
2023年第1期20-24,共5页
Haihe Water Resources
关键词
密云水库
上游河道
水质
时空变化
Miyun Reservoir
upstream river channel
water quality
temporal and spatial variation
