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乌梁素海水环境现状评价与趋势预测的研究

Water Environment Evaluation and Prediction for the Lake of Wuliangsuhai

【作者】 代进锋

【导师】 李畅游;

【作者基本信息】 内蒙古农业大学 , 水文学及水资源, 2008, 硕士

【摘要】 湖泊是由水体、水生植物、水生动物、各种微生物及营养成分组成的一个循环生态系统。处于蒙新高原地区的乌梁素海,水域面积285.38km2,多年平均降雨量为224mm,是全国的八大淡水湖泊之一,它不仅是河套灌区农田退水的唯一承泄区,而且还具有维持生物多样性、调节气候、蓄纳洪水、调节地表径流、净化水质等功能。但是随着经济的发展,农田退水、工业生活污水的排放量也日益增加,导致大量营养物不断流入湖泊,湖泊已成为接纳污水的天然大水体,因而面临着严重的水环境污染问题。本文从可持续发展理论出发,以干旱寒冷地区的草型湖泊乌梁素海为研究区,基于2005年~2007年实地监测数据,结合乌梁素海自然环境资料、社会经济资料、水文资料、水质水量的历史监测资料及污染源排放口各水质因子的监测数据,利用物理成因和统计分析,得出乌梁素海水环境的主要影响因子。用综合营养状态指数法对2006年和2007年各年5月、7月、9月的乌梁素海的水体富营养化进行评价和对比分析。在水环境现状分析和富营养化评价的基础上,运用神经网络进行水体中水质指标叶绿素变化趋势的预测研究。结果表明,Chla是表征水体富营养化现象及其程度的最重要的指示剂之一,从年际上看,2007年水质好于2006年;从年内上看,2006年富营养化程度为:夏季>春季>秋季,2007年富营养化程度为:春季>夏季>秋季。

【Abstract】 A lake is normally a complicated ecosystem regarding water, aquatic plants, aquatic animals, manyl kinds of microorganisms and nutritional ingredients. The lake of Wuliangsuhai having an open water area of 285.38 km2, is loacated in the Mongolia-Xinjiang altiplano region with a precipitation of 224 mm, which is one of the eight largest fresh water lakes in China. It is not only the unique drainage water receiving basin from the cultivated farmland of Hetao Irrigation Districte, but also has the function in maintaining biodiversity, adjusting the local climate, storing the seasonal floodwater, purifing water quality, and so on. Since the source waters are having been polluted by using more and more fertilizer over the farmland, developing industries within the catchment and receiving sanitary sewage from the towns, a great deal of nutrients are transported into the lake. As a result of this, lake’s water has been seriously polluted.The water quality of the lake has been monitored and analyzed for three years. This paper mainly focuses on the water quality evaluation and forecast with respect to the sustainable development point of view. The cataminats were analyzed and the eutrophication indicators were worked out. The index method of synthetical nutrition was used to estimate eutrophication degrees over the open water area. Then, the method of neural network was employed to predicte the change of water quality index in terms of chlorpophyll. The results showed that Chla is one of the most sensitive indicators to characterize eutrophication degrees, the water quality is better in the year of 2007 than 2006 and in the Summer than Spring than Autom within a year.

  • 【分类号】X832;X824
  • 【被引频次】5
  • 【下载频次】306
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