基于云模型的鄱阳湖秋季周边湿地水体富营养化评价 |
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引用本文: | 方娜,游清徽,刘玲玲,李菊媛,卢成芳,张琍,杨涛,余紫萍,吕泽兰,阳文静. 基于云模型的鄱阳湖秋季周边湿地水体富营养化评价[J]. 生态学报, 2019, 39(17): 6314-6321 |
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作者姓名: | 方娜 游清徽 刘玲玲 李菊媛 卢成芳 张琍 杨涛 余紫萍 吕泽兰 阳文静 |
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作者单位: | 江西师范大学鄱阳湖湿地与流域研究教育部重点实验室, 南昌 330022;江西师范大学地理与环境学院, 南昌 330022,江西师范大学生命科学学院, 南昌 330022,江西师范大学鄱阳湖湿地与流域研究教育部重点实验室, 南昌 330022;江西师范大学地理与环境学院, 南昌 330022,江西师范大学鄱阳湖湿地与流域研究教育部重点实验室, 南昌 330022;江西师范大学地理与环境学院, 南昌 330022,江西师范大学鄱阳湖湿地与流域研究教育部重点实验室, 南昌 330022;江西师范大学地理与环境学院, 南昌 330022,江西师范大学鄱阳湖湿地与流域研究教育部重点实验室, 南昌 330022;江西师范大学地理与环境学院, 南昌 330022;江西师范大学江西省鄱阳湖综合治理与资源开发重点实验室, 南昌 330022,江西师范大学鄱阳湖湿地与流域研究教育部重点实验室, 南昌 330022;江西师范大学地理与环境学院, 南昌 330022;江西师范大学江西省鄱阳湖综合治理与资源开发重点实验室, 南昌 330022,江西师范大学鄱阳湖湿地与流域研究教育部重点实验室, 南昌 330022;江西师范大学地理与环境学院, 南昌 330022,江西师范大学鄱阳湖湿地与流域研究教育部重点实验室, 南昌 330022;江西师范大学地理与环境学院, 南昌 330022,江西师范大学鄱阳湖湿地与流域研究教育部重点实验室, 南昌 330022;江西师范大学地理与环境学院, 南昌 330022;江西师范大学江西省鄱阳湖综合治理与资源开发重点实验室, 南昌 330022 |
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基金项目: | 国家自然科学基金项目(41561097,41967055);江西省教育厅科学研究项目(GJJ170199);鄱阳湖湿地与流域研究教育部重点实验室开放基金项目(PK2017004) |
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摘 要: | 针对水体富营养化评价过程中存在随机性和模糊性的特点,基于鄱阳湖周边湿地30个采样点的实测水质数据,选取叶绿素a(Chl-a)、总磷(TP)、总氮(TN)、高锰酸盐指数(CODMn)及透明度(SD)为水质评价因子,生成云模型对鄱阳湖周边湿地水体进行富营养化评价,并与综合营养状态指数评价结果进行比较。结果表明:两种方法的评价结果存在一定差异,但都反映了鄱阳湖周边湿地水体总体上处于轻度富营养化状态。该方法能为鄱阳湖湿地水体富营养化评价提供重要的方法和手段。
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关 键 词: | 云模型 富营养化 水质评价 鄱阳湖湿地 |
收稿时间: | 2018-08-22 |
修稿时间: | 2019-04-12 |
Evaluation of eutrophication in Poyang Lake wetland during autumn based on the cloud model |
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Affiliation: | Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China;School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China,College of Life Sciences, Jiangxi Normal University, Nanchang 330022, China,Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China;School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China,Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China;School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China,Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China;School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China,Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China;School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China;Jiangxi Provincial Key Laboratory of Poyang Lake Comprehensive Management and Resource Development, Jiangxi Normal University, Nanchang 330022, China,Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China;School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China;Jiangxi Provincial Key Laboratory of Poyang Lake Comprehensive Management and Resource Development, Jiangxi Normal University, Nanchang 330022, China,Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China;School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China,Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China;School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China and Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China;School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China;Jiangxi Provincial Key Laboratory of Poyang Lake Comprehensive Management and Resource Development, Jiangxi Normal University, Nanchang 330022, China |
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Abstract: | With the fast-growing human population and attendant human activities, eutrophication has become a severe problem in fresh as well as coastal waters in many regions of the world. Evaluation of eutrophication can provide critical information for the governance and management of water resources. However, two basic and significant uncertainties, i.e. randomness and fuzziness, are ubiquitous in water quality evaluation. The cloud model method has been proposed to address the two uncertainties based on the principle of maximum entropy (POME) and engineering fuzzy set theory (EFST). Poyang Lake is the largest fresh water lake in China with one of the most important wetlands in the world, recognized by the International Union for the Conservation of Nature (IUCN). Poyang Lake has been severely disturbed by human activities, such as sewage discharge and sand mining, which has caused a severe degradation of water quality. Previous evaluations of eutrophication have mainly focused on the central areas of Poyang Lake, whereas the surrounding wetland has much been neglected. In this study, we aimed to develop a cloud model to assess eutrophication in Poyang Lake wetland. We also employed the widely used comprehensive trophic level index (TLI) and tested whether the two methods generated different results. We conducted field surveys to obtain the data on water quality at 30 sample sites in Poyang Lake wetland during September 25 and October 31, 2016. Five key physico-chemical parameters, i.e., chlorophyll-a (Chl-a), Secchi disk depth (SD), chemical oxygen demand using manganese (CODMn), total nitrogen (TN), and total phosphorus (TP) were analyzed in the laboratory and used as the input data for the cloud model and TLI. The clouds of each water quality parameter at five eutrophication levels (i.e., oligotrophic, mesotrophic, light eutrophic, middle eutrophic, and hyper eutrophic) were generated in Matlab based on the criteria for eutrophication level classification proposed by the Ministry of Environmental Protection of the People''s Republic of China. The eutrophication level at each sample site was then determined by the maximum degree of certainty. Both of the two methods indicated that Poyang Lake wetland was overall in a light eutrophic state. The cloud model showed that seven sample sites were classified as mesotrophic, seventeen as light eutrophic, five as middle eutrophic, and one as hyper eutrophic, whereas the TLI indicated that twelve sample sites were classified as mesotrophic, fifteen as light eutrophic, and three as middle eutrophic. The reason for the difference between the two sets of results was that water physico-chemical parameters were weighted differently in the two methods. Highest weights were given to TN and TP in the cloud model, whereas Chl-a concentration was the most important variable in the TLI. Nitrogen and phosphorus were the main pollutants in Poyang Lake, whereas Chl-a concentration was not high, because the fast flow of water, as well as the high concentration of suspended sediment, limited the growth of phytoplankton. We thus considered that the cloud model method was more appropriate for eutrophication evaluation in Poyang Lake wetland. |
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Keywords: | cloud model eutrophication water quality evaluation Poyang Lake wetland |
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