| 基于综合营养状态指数和BP神经网络的黑河富营养化评价 |
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| 引用本文： | 鲍广强,尹亮,余金龙,刘畅,邱小琮.基于综合营养状态指数和BP神经网络的黑河富营养化评价[J].水土保持通报,2018,38(1):264-269. |
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| 作者姓名： | 鲍广强 尹亮 余金龙 刘畅 邱小琮 |
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| 作者单位： | 宁夏大学 土木与水利工程学院, 宁夏 银川 750021,宁夏大学 土木与水利工程学院, 宁夏 银川 750021,宁夏大学 土木与水利工程学院, 宁夏 银川 750021,中国水利水电科学研究院 水环境研究所, 北京 100038,宁夏大学 生命科学学院, 宁夏 银川 750021 |
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| 基金项目： | 国家水体污染控制与治理科技重大专项“重点流域水生态功能三级四级分区”（2012ZX07501-002-05） |
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| 摘 要： | 目的]探究黑河流域富营养状态,为黑河流域水体污染综合防治提供基础数据和理论依据。方法]选取叶绿素a(Chl.a)、总氮(TN)、总磷(TP)、高锰酸盐指数(CODMn_)、透明度(SD)作为评价因子,使用综合营养状态指数法和BP神经网络对黑河流域的富营养化进行综合评价。结果]黑河富营养化状况主要以中营养级为主,其中野牛沟和张掖湿地的营养指数接近轻度富营养程度,东居延海处于重度富营养化,尤其是总氮指数很高,应该及时进行治理和保护。结论]相对于综合营养状态指数法,BP神经网络对黑河流域的评价结果更加贴近实际结果,较为客观可靠。
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| 关 键 词： | 黑河流域 综合营养状态指数法 BP神经网络 富营养化评价 |
| 收稿时间： | 2017/6/9 0:00:00 |
| 修稿时间： | 2017/7/28 0:00:00 |
Eutrophication Evaluation of Heihe River Based on Comprehensive Trophic State Index Method and BP Neural Network |
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| BAO Guangqiang,YIN Liang,YU Jinlong,LIU Chang and QIU Xiaocong.Eutrophication Evaluation of Heihe River Based on Comprehensive Trophic State Index Method and BP Neural Network[J].Bulletin of Soil and Water Conservation,2018,38(1):264-269. |
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| Authors: | BAO Guangqiang YIN Liang YU Jinlong LIU Chang and QIU Xiaocong |
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| Institution: | School of Civil and Hydraulic Engineering, Ningxia University, Yinchuan, Ningxia 750021, China,School of Civil and Hydraulic Engineering, Ningxia University, Yinchuan, Ningxia 750021, China,School of Civil and Hydraulic Engineering, Ningxia University, Yinchuan, Ningxia 750021, China,Water Environment Research Institute of China Academy of Water Resources and Hydropower Research, Beijing 100038, China and School of Life Science, Ningxia University, Yinchuan, Ningxia 750021, China |
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| Abstract: | Objective] To evaluate the current eutrophication state and provide basic data and theoretical support for the pollution control in Heihe River basin.Methods] The total nitrogen (TN), total phosphorus (TP), permanganate index (CODMn), chlorophyll a (Chl.a), transparency (SD) were selected as indexes for water quality evaluation, and the comprehensive trophic state index and BP neural network were used to evaluate the eutrophication of Heihe River basin.Results] The eutrophication status of Heihe River basin was mainly in medium level of nutrition. The nutrition status index of Yeniugou and Zhangye wetland were close to mild eutrophication. The eutrophication status of East Juyanhai Lake was severe and the total nitrogen index was high. The water environment of East Juyanhai Lake should be protected in time.Conclusion] Compared to the comprehensive trophic state index method, the evaluation results of BP neural network are closer to the actual situation, and more objective and reliable. |
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| Keywords: | Heihe River basin comprehensive nutrition state index method BP neural network eutrophication evaluation |
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