| 浙江青山水库富营养化状况评价 |
| Water Quality Eutrophication Assessment of Qingshan Reservoir in Zhejiang Province |
| 投稿时间：2014-09-15 修订日期：2015-06-29 |
| DOI：10.15928/j.1674-3075.2015.04.003 |
| 中文关键词:青山水库，BP神经网络，富营养化 |
| 英文关键词:Qingshan Reservoir BP neural network eutrophication |
| 基金项目:湖州市科技计划项目（2013GY04）；浙江省科技计划项目（2015F30020）。 |
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| 中文摘要: |
| 对青山水库富营养化情况进行评价，为管理和决策提供理论依据。沿库区水流方向共设7个采样点，其中S1、S2、S4位于水库上游，分别靠近入库支流灵溪、横溪、南苕溪；S7位于水库下游，靠近大坝。 2013年4、7、10及12月，现场测定透明度，实验室内测定表层水样的高锰酸盐指数、总氮、总磷、叶绿素a等4个指标，应用BP神经网络模型进行水质富营养化评价。青山水库水质富营养化状态总体为中营养。人工神经网络评价结果，富营养化状态4月最低、平均为1.130，7月相对较高、平均为1.338；4、7月与其他月份之间富营养化状态差异显著（P＜0.01），10月与12月间无显著性差异（P＞0.05）。富营养化数值最大的站点4、7月为下游S6，10、12月为下游S7；水库的上游（S4）站位富营养化评价结果与其他6个站位间差异极显著（P＜0.01）。青山水库富营养化程度随着水流方向呈现增加的趋势，受入库支流影响较大。 |
| 英文摘要: |
| The eutrophication evaluation of 646 reservoirs by the Ministry of Water Resources of the People's Republic of China (2013) showed that 58.0% of the reservoirs were mesotrophic, and 42.0% of the reservoirs were eutrophic. These results indicate that the reservoir eutrophication problem is nation-wide. The reservoirs in Zhejiang Province have shown obvious eutrophication over the last 10 years and it is affecting the safety of drinking water. In this study, we evaluated the eutrophication of Qingshang Reservoir in Hangzhou using a backpropagated (BP) artificial neural network model. The eutrophication assessment, and the BP artificial neural network model, of Qingshan Reservoir were based on 5 water quality parameters (CODMn, SD, TP, TN and Chl-a) monitored in April, July, October and December of 2013. The study provides theoretical evidence that will help administrators manage the reservoir more effectively. Qingshan Reservoir is located in the middle and lower reaches of Nantiaoxi River and three tributaries (Nantiaoxi River, Hengxi River and Lingxi River) flow into it. In the spring and summer, there is plentiful rainfall in this region, accounting for 70% of the annual precipitation and the fall and winter are much drier. Based on water flow patterns in the reservoir, seven sampling sites were selected (S1, S2 and S4 near the three tributary inflows in the upper reservoir, S7 near the dam, and S3, S5 and S6 spatially distributed to give full coverage). The transparency of the water body was measured in situ and surface water samples were collected for laboratory determination of CODMn, TP, TN and Chl-a. Results indicate that the waters of Qingshan Reservoir are generally mesotrophic, but with obvious spatial and temporal variations. The output values of the BP neural network model were lowest in April and highest in July, averaging 1.130 and 1.338, respectively. These values are significantly different from other months (P＜0.01), but differences for October and December were not significant (P＞0.05). Spatially, the degree of eutrophication increased with direction of water flow and eutrophication in the upstream section (S4) was significantly different than for other monitoring sites in the reservoir (p＜0.05). The highest eutrophication level in April and July was observed at S6, and the highest eutrophication level in October and December was observed at S7, both located in the lower reach of the reservoir, where the dam creates perfect hydrostatic conditions for phytoplankton growth. |
| 施沁璇,韦肖杭,施礼科,张敏,姚伟忠,崔雁娜,王俊,沈萍萍,赵汉取.2015.浙江青山水库富营养化状况评价[J].水生态学杂志,36(4):20-24. |
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