摘要
东武仕水库是滏阳河干流上一座以防洪和供水为主的大型水库,但由于水库以上流域为峰峰矿区,矿区的工业废水和生活污水大量排入河道,使水中氨氮、有机质等含量提高,造成水体富营养化,藻类植物大量繁殖,从而导致水库区域长期处于污染状态。因为叶绿素浓度与藻密度正相关,并且植被指数与叶绿素具有很强的相关性,所以植被指数可以作为水体污染的间接反演标志。通过Landsat5 TM、Landsat8OLI数据,计算库区水体比值植被指数的均值和标准差,以均值±标准差作为阈值分割标准,分析东武仕水库2009—2019近十年的水质变化情况。结果表明,运用此方法能较好地反映历年水体的污染分布情况,可以为该地区利用遥感数据监测水体污染及后续治理工作提供依据。
Fuyang River Dongwushi reservoir is a flood control and water supply-based large reservoir. However, because the basin above the reservoir is Fengfeng mining area, a large amount of industrial wastewater and domestic sewage from the mining area are discharged into the river, which increases the content of ammonia nitrogen and organic matter in the water, resulting in eutrophication of the water body and the proliferation of algae, thus leading to long-term pollution in the reservoir area. The concentration of chlorophyll is positively correlated with the density of algae, and the vegetation index has a strong correlation with chlorophyll, so the vegetation index can be used as an indirect inversion indicator of water pollution. In this paper, Landsat5 TM and Landsat8 OLI data were used to calculate the mean and standard deviation of the water body ratio vegetation index in the reservoir area, and the mean ± standard deviation was used as the threshold segmentation standard to analyze the water quality change of Dongwushi Reservoir in the recent ten years from 2009 to 2019. The results show that this method can better reflect the water pollution distribution over the years, and provide a basis for monitoring water pollution and subsequent treatment by using remote sensing data in this area.
作者
白杨林
李耀耀
苏鸿博
符雨
吕凤军
BAI Yang-lin;LI Yao-yao;SU Hong-bo;FU Yu;LV Feng-jun(Hebei GEO University,Shijiazhuang 050031,China;Fuxin Ecological Environment Protection Service Center,Fuxin 123000,China)
出处
《河北地质大学学报》
2022年第2期97-103,共7页
Journal of Hebei Geo University
基金
国家重点研发计划(2018YFA0606101)
河北省地矿局项目(201348)
河北地质大学博士科研启动基金(BQ2018014)。
关键词
东武仕水库
水体污染
遥感监测
植被指数
OLI数据
TM数据
Dongwushi Reservoir
water pollution
remote sensing monitoring
vegetation index
OLI data
TM data
