摘要
随着社会经济的发展,海河流域水资源遭到破坏性的开发,水污染问题日益严重.为了分析流域整体水平上的水质时空变异规律,本文选取了海河流域内2004-2016年7个水质自动监测断面的水质监测数据,利用Mann-Kendall非参数检验对7个点位的pH以及DO、CODMn、NH3-N等物质质量浓度进行检验,得出其随时间的变化趋势及突变点.以天津三岔口断面为例,利用散点图的方式直观判断出各监测因子年内变化规律.根据水质监测数据分别计算出各断面pH及DO、CODMn、NH3-N质量浓度的均值及标准差,分析比较得出流域内水质的空间分布状况.结果表明:1)海河流域的水质状况在2004-2016年间有改善的趋势;2)海河流域的水质突变主要集中在2006-2007年,降水量过少是导致水质突变的主要因素;3)通过空间分析得出岗南水库水质最好,聊城秤钩湾水质状况最差,水质空间分布总体符合支流优于干流、上游优于下游的规律.
Recent developments in society and economy have been accompanied by adverse changes in water resources in Haihe River Basin,with increasingly serious water pollution.Water quality monitoring data at 7 automatic monitoring sections in Haihe River Basin from 2004 to 2016 were therefore analyze for overall temporal and spatial variations.Environmental factors(pH,DO,CODMn and NH3-N)were analyzed by Mann-Kendall non-parametric test,change trend and abrupt points were obtained.Scatter plot was used to intuitively determine variation law of each factor for the Tianjin Sanchakou section during the year.Mean and standard deviation of pH,DO,CODMn,NH3-N at each section were calculated and spatial distribution of water quality was then analyzed and compared.Water quality in Haihe River Basin was found to show a trend of improvement from 2004 to 2016,sudden changes were observed in 2006 to 2007,largely due to very little precipitation.Spatial analysis revealed best water quality at Gangnan Reservoir,worst at Chenggou Bay in Liaocheng.Water quality at tributary has been found to be generally better than at main stream,upstream better than downstream.
作者
白会滨
刘淑曼
俞淞
薛宝林
BAI Huibin;LIU Shuman;YU Song;XUE Baolin(College of Water Science,Beijing Normal University,100875,Beijing,China;School of Environmental Science and Engineering,Southern University of Science and Technology,518055,Shenzhen,China;Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology,100875,Beijing,China)
出处
《北京师范大学学报(自然科学版)》
CAS
CSCD
北大核心
2020年第2期290-297,共8页
Journal of Beijing Normal University(Natural Science)
基金
水体污染控制与治理科技重大专项资助项目(2017ZX07302004)
国家自然科学基金资助项目(31670451)。