引用本文: | 张倚铭,兰佳,李慧赟,刘凤龙,罗潋葱,吴志旭,虞左明,刘明亮.新安江对千岛湖外源输入总量的贡献分析(2006-2016年).湖泊科学,2019,31(6):1534-1546. DOI:10.18307/2019.0621 |
| ZHANG Yiming,LAN Jia,LI Huiyun,LIU Fenglong,LUO Liancong,WU Zhixu,YU Zuoming,LIU Mingliang.Estimation of external nutrient loadings from the main tributary (Xin'anjiang) into Lake Qiandao, 2006-2016. J. Lake Sci.2019,31(6):1534-1546. DOI:10.18307/2019.0621 |
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新安江对千岛湖外源输入总量的贡献分析(2006-2016年) |
张倚铭1,2, 兰佳3, 李慧赟4, 刘凤龙5, 罗潋葱2, 吴志旭3, 虞左明6, 刘明亮6
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1.西华师范大学环境科学与工程学院, 南充 637002;2.云南大学资源环境与地球科学学院, 昆明 650000;3.杭州市生态环境局淳安分局, 杭州 311700;4.中国科学院南京地理与湖泊研究所, 南京 210008;5.湖南人文科技学院, 娄底 417000;6.杭州市环境保护科学研究院, 杭州 310014
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摘要: |
运用新安江模型,计算了千岛湖25条主要入湖河流在2006-2016年间的入湖流量,结合同时期入湖河道的逐月水质监测数据,分析了最大入流新安江的营养盐——总氮(TN)、总磷(TP)、氨氮(NH3-N)和高锰酸盐指数(CODMn)总量输入在该时段内的年际变化和季节变化规律,研究了新安江营养盐输入总量变化与新安江水质水量、黄山市人口、GDP和土地利用的关系,探讨了影响新安江营养盐总量的关键影响因素及其对千岛湖水质的影响.结果表明,研究时段内新安江多年平均年入湖水量占千岛湖多年平均年入湖水量的51.4%,占25条主要河流年总入流量的67.3%,新安江CODMn、TP、TN、NH3-N多年平均的输入总量分别为11458.4、214.9、7649.2和756.5 t/a,分别占千岛湖年总负荷的50.7%、34.3%、63.7%和48.4%.各指标的年入湖总量在统计期间均呈上升趋势,且春、夏两季高于秋、冬两季.相关性分析表明,黄山市GDP与新安江CODMn、TN和TP入湖总量呈显著正相关关系,农业面源污染对新安江TN输入总量有显著影响.作为千岛湖最大的入湖河流,新安江营养盐(TP、TN、NH3-N)的输入能显著影响千岛湖的生态系统健康. |
关键词: 新安江模型 千岛湖 外源负荷 季节变化 |
DOI:10.18307/2019.0621 |
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基金项目:国家自然科学基金项目(41671205,41661134036,91747103)、淳安县环境保护局水质水华预测预警系统开发项目(CAZFCGGK2016-111)和中国科学院南京地理与湖泊研究所自主部署项目(NIGLAS2017GH04)联合资助. |
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Estimation of external nutrient loadings from the main tributary (Xin'anjiang) into Lake Qiandao, 2006-2016 |
ZHANG Yiming1,2, LAN Jia3, LI Huiyun4, LIU Fenglong5, LUO Liancong2, WU Zhixu3, YU Zuoming6, LIU Mingliang6
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1.College of Environmental Science and Engineering, China West Normal University, Nanchong 637002, P. R. China;2.School of Resource Environment and Earth Science, Yunnan University, Kunming 650000, P. R. China;3.Chun'an Branch of Hangzhou Bureau of Ecology and Environment, Hangzhou 311700, P. R. China;4.Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P. R. China;5.Hunan University of Humanities, Science and Technology, Loudi 417000, P. R. China;6.Hangzhou Institute of Environment Science, Hangzhou 310014, P. R. China
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Abstract: |
There are 25 tributaries carrying significant water and nutrients into Lake Qiandao. As the largest tributary, Xin'anjiang has remarkable impacts on water capacity and water quality of Lake Qiandao. In order to provide substantial information for the exact annual amount of water and nutrients from Xin'anjiang, the inflow volumes during 2006-2016 were calculated based on a catchment model-Xin'anjiang Model. The annual external loadings including total nitrogen (TN), total phosphorus (TP), ammonia (NH3-N) and chemical oxygen demand (CODMn) were further calculated with monthly-monitored TN, TP, NH3-N and CODMn at Xin'anjiang in the same period. For investigating the impact factors of external loading from Xin'anjiang, statistical analysis was conducted with the external loadings correlating the water quality parameters, inflow volume at Xin'anjiang, the population, GDP, economic development and land use at the catchment. The results show that Xin'anjiang is carrying about 51.4% of the total inputted lake water including surface water, ground water and precipitation, accounting for 67.3% of the total water input by the main 25 tributaries. The annual loadings of CODMn, TP, TN and NH3-N from Xin'anjiang are 11458.4 t, 214.9 t, 7649.2 t and 756.5 t which account for 50.7%, 34.3%, 63.7% and 48.4% of the total annual loading from catchment respectively. During 2006-2016, there was an increasing trend of loading CODMn, NH3-N, TN and TP by Xin'anjiang. The external loadings from Xin'anjiang in spring and summer were higher than those in autumn and winter for all parameters. Statistical analysis shows that the CODMn, TN and TP loadings are positively correlated with the catchment GDP. The non-point sources from agriculture in Huangshan City have a significant impact on the Xin'anjiang TN loading. The riverine inputs of TP, TN and NH3-N from Xin'anjiang are having remarkable influence on water quality and ecosystem health at Lake Qiandao. |
Key words: Xin'anjiang Model Lake Qiandao external loading seasonal variation |
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