干旱区研究 ›› 2021, Vol. 38 ›› Issue (6): 1534-1545.doi: 10.13866/j.azr.2021.06.05

• 水资源及其利用 • 上一篇    下一篇

2011—2020年呼伦湖水质及富营养化变化分析

于海峰1(),史小红1(),孙标1,赵胜男1,刘禹1,赵美丽2   

  1. 1.内蒙古农业大学水利与土木建筑工程学院,内蒙古 呼和浩特 010018
    2.内蒙古自治区野生动植物保护中心,内蒙古 呼和浩特 010010
  • 收稿日期:2021-04-24 修回日期:2021-07-15 出版日期:2021-11-15 发布日期:2021-11-29
  • 通讯作者: 史小红
  • 作者简介:于海峰(1997-),男,硕士研究生,主要从事水环境保护与修复的相关研究. E-mail: yhf970204@163.com
  • 基金资助:
    国家重点研发计划专项(2017YFE0114800);国家重点研发计划专项(2019YFC0409200);国家自然科学基金项目(51779118);国家自然科学基金项目(51869020);内蒙古自治区自然科学基金项目(2019MS05032);内蒙古自治区高等学校“青年科技英才支持计划”(NJYT-19-B11);内蒙古自治区科技计划项目(2021GG0089)

Analysis of water quality and eutrophication changes in Hulun Lake from 2011 to 2020

YU Haifeng1(),SHI Xiaohong1(),SUN Biao1,ZHAO Shengnan1,LIU Yu1,ZHAO Meili2   

  1. 1. Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, Inner Mongolia, China
    2. Wildlife Conservation Center of Inner Mongolia, Hohhot 010010, Inner Mongolia, China
  • Received:2021-04-24 Revised:2021-07-15 Online:2021-11-15 Published:2021-11-29
  • Contact: Xiaohong SHI

摘要:

以呼伦湖为研究对象,选取2011—2020年长时间序列实测水质指标,分析了盐度(S)、电导率(EC)、总溶解性固体(TDS)、pH、透明度(SD)、叶绿素a(Chl.a)、溶解氧(DO)、化学需氧量(COD)、总氮(TN)和总磷(TP)的年际变化。基于灰色模式识别模型和综合营养状态指数法对呼伦湖2011—2020年的水质与水体富营养化程度进行评价,结合呼伦湖的实际情况,从外源输入与气象条件两方面对水质与水体富营养化程度进行分析。结果显示:(1) 2011—2020年,S、TDS、EC均有下降,水体盐化现象好转;pH在8.86~9.37之间,水体呈弱碱性;除TP外,TN、COD均有下降。灰色模式综合指数(GC)表明:近10 a中水质最优年为2012年,水质最差年为2011年,整体上看,GC由2011年的4.01降低到2020年的3.35,水质趋于好转。(2) 综合营养状态指数(TLI)表明:2011—2020年水体经历中度富营养化—重度富营养化—中度富营养化的变化过程,TLI先上升后下降,由2011年的61.837上升到2016年的71.815,再下降到2020年的61.535,同时风速(WS)和水深(H)是呼伦湖水体富营养化的驱动因素。现阶段呼伦湖水体污染以氮、磷和有机污染为主,控制上游污废水排放,严控草畜平衡,提高补给水源的水质是改善呼伦湖水质的重要举措。

关键词: 呼伦湖, 富营养化, 灰色模式识别模型, 综合营养状态指数法

Abstract:

In this study, Hulun Lake was taken as the research object, and water quality indicators measured in a long time series from 2011 to 2020 were selected. Interannual variations in Salinity (S), Electrical Conductivity (EC), Total Dissolved Solids (TDS), pH, Transparency (SD), Chlorophyll a (Chl.a), Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), Total Nitrogen (TN), and Total Phosphorus (TP) were analyzed. The water quality and eutrophication degree of Hulun Lake from 2011 to 2020 were evaluated on the basis of the gray pattern recognition model and comprehensive nutrient state index. Combined with the actual situation of Hulun Lake, the water quality and eutrophication degree of Hulun Lake were examined from two aspects of external input and meteorological conditions. Results showed that S, TDS, and EC decreased from 2011 to 2020, and water salinity improved. pH was between 8.86 and 9.37, and water was weakly alkaline. TN and COD decreased, but TP did not. Grey Pattern Composite Index (GC) indicated that the best water quality of the decade was observed in 2012, and the worst water quality was documented in 2011. Overall, GC decreased from 4.01 in 2011 to 3.35 in 2020, indicating that water quality improved. Comprehensive Nutritional Status Index (TLI) implied that water underwent moderate eutrophication, severe eutrophication, and another moderate eutrophication from 2011 to 2020. TLI initially increased and subsequently decreased; in particular, it increased from 61.837 in 2011 to 71. 815 in 2016 and then decreased to 61.535 in 2020. Wind speed and water depth were the driving factors of eutrophication in Hulun Lake. At present, the main pollution in Hulun Lake is caused by nitrogen, phosphorus, and organic pollutants. The water quality of Hulun Lake can be enhanced by implementing effective measures, such as controlling the discharge of upstream sewage, strictly regulating the balance of grass and graziery, and improving the quality of water supply.

Key words: Hulun Lake, eutrophication, grey model, integrated nutritional status index method