| 云南星云湖水质变化及其人文因素驱动力分析 |
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| 引用本文： | 郑田甜,赵祖军,赵筱青,顾泽贤,普军伟,卢飞飞.云南星云湖水质变化及其人文因素驱动力分析[J].湖泊科学,2018,30(1):79-90. |
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| 作者姓名： | 郑田甜 赵祖军 赵筱青 顾泽贤 普军伟 卢飞飞 |
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| 作者单位： | 云南大学资源环境与地球科学学院, 昆明 650500,云南省环境监测中心站, 昆明 650034,云南大学资源环境与地球科学学院, 昆明 650500,云南大学资源环境与地球科学学院, 昆明 650500,云南大学资源环境与地球科学学院, 昆明 650500,云南大学资源环境与地球科学学院, 昆明 650500 |
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| 基金项目： | 玉溪地区三大湖泊（抚仙湖、星云湖、杞麓湖）遥感监测项目（玮元-A2016191）、“第二批云岭学者培养”项目（C6153001）和云南大学第八届研究生科研创新项目（ynuy2016113）联合资助. |
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| 摘 要： | 星云湖目前存在水污染加重、富营养化进程加快、水体功能受损等问题.以星云湖为研究对象,根据星云湖2005-2015年的水质数据、社会经济统计数据和遥感影像图,运用目视解译、叠加分析、污染足迹模型及主成分分析法,分析了星云湖流域近10年以来水质变化趋势、入湖河流污染物污染足迹及其人文因素驱动力.结果表明:(1)水质数据趋势表明,从月变化看,3月份水质最好,9月份水质最差;从年变化看,2005-2015年间,2008年水质状况最好,2014年的水质状况最差,从2008-2014年水质持续变差,到2015年好转.(2)2015年有机物、氮和磷的污染足迹分别为583.26、705.88和494.11 km~2.污染足迹前4位的入湖河流依次为:大街河东西大河东河渔村河东西大河西河,占星云湖流域总污染足迹的66.21%.污染程度大的大街河、东西大河和渔村河周边土地利用类型为水田、旱地和村庄.(3)星云湖水质影响因素第1主成分(总人口、播种面积、农村人口、化肥使用量、农膜使用量、大牲畜存栏量)与农村生活和农业面源污染有关;第2主成分(人均GDP、第一产业产值、第二产业产值、第三产业产值)与社会经济发展有关.因此,星云湖流域水质变化的人文因素驱动力为农村生活和农业面源污染类和社会经济发展类,其中第1主成分的贡献率是84.389%,农村生活和农业面源污染是水质变化的主要驱动力.
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| 关 键 词： | 星云湖 入湖河流 面源污染 足迹 社会经济因素 高原湖泊 |
| 收稿时间： | 2016/11/23 0:00:00 |
| 修稿时间： | 2017/3/3 0:00:00 |
Water quality change and humanities driving force in Lake Xingyun, Yunnan Province |
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| ZHENG Tiantian,ZHAO Zujun,ZHAO Xiaoqing,GU Zexian,PU Junwei and LU Feifei.Water quality change and humanities driving force in Lake Xingyun, Yunnan Province[J].Journal of Lake Science,2018,30(1):79-90. |
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| Authors: | ZHENG Tiantian ZHAO Zujun ZHAO Xiaoqing GU Zexian PU Junwei and LU Feifei |
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| Institution: | College of Resource Environment and Earth Science, Yunnan University, Kunming 650500, P. R. China,Yunnan Environmental Monitoring Center Station, Kunming 650034, P. R. China,College of Resource Environment and Earth Science, Yunnan University, Kunming 650500, P. R. China,College of Resource Environment and Earth Science, Yunnan University, Kunming 650500, P. R. China,College of Resource Environment and Earth Science, Yunnan University, Kunming 650500, P. R. China and College of Resource Environment and Earth Science, Yunnan University, Kunming 650500, P. R. China |
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| Abstract: | Lake Xingyun faces the problems of worsening water pollution, accelerating eutrophication and damaged function of water body. This paper employs visual interpretation, overlay analysis, pollution footprint model and principal component analysis to analyze water quality changes as well as the pollution footprint and humanities driving force of the pollutants in the lake and rivers based on water quality data, statistical data on the society and economy, as well as remote sensing images. The results show that the water quality at Lake Xingyun is best in March and worst in September. During the period from 2005 to 2015, the water quality was best in 2008 but worst in 2014. From 2008 to 2014, the water quality got worsening and then reversed since 2015. In 2015, the pollution footprint of organic matter, nitrogen and phosphorus pollution occupied 583.26, 705.88 and 494.11 km2, respectively. The top four rivers with the most pollution footprint for the pollutants in the lake and river are listed as Dajie River, Eastern River, Yucun River and Western River, accounted for 66.21% of the total pollution footprint in Lake Xingyun. The land use in the four rivers with the highest degree of pollution can be classified as the paddy field, dry land or village. The first principal component (total population, planting area, rural population, fertilizer use amount, plastic sheeting use amount, large livestock stock amount) influencing the water quality of Lake Xingyun is related to the rural life and agricultural pollution. The second principal component (per capita GDP, firstly industry output value, secondary industry output value, tertiary industry output value) is connected with the social and economic development. Hence, the humanities driving force for water quality changes in Lake Xingyun can be classified as the rural life and agricultural pollution or social and economic development. The first principal component has a contribution rate of 84.389%, which means that it is the major driving force for water quality changes. |
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| Keywords: | Lake Xingyun inflow non-point source pollution footprint social economic factors plateau lakes |
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