| 引用本文: | 钱瑞,彭福利,薛坤,齐凌艳,段洪涛,邱银国,陈青,陈粉丽,高俊峰,黄佳聪.大型湖库滨岸带蓝藻水华堆积风险评估——以巢湖为例.湖泊科学,2022,34(1):49-60. DOI:10.18307/2022.0103 |
| Qian Rui,Peng Fuli,Xue Kun,Qi Lingyan,Duan Hongtao,Qiu Yinguo,Chen Qing,Chen Fenli,Gao Junfeng,Huang Jiacong.Assessing the risks of harmful algal bloom accumulation atlittoral zone of large lakes and reservoirs: An example from Lake Chaohu. J. Lake Sci.2022,34(1):49-60. DOI:10.18307/2022.0103 |
|
| |
|
|
| 本文已被：浏览 3421次 下载 2390次 |
码上扫一扫！ |
|
|
| 大型湖库滨岸带蓝藻水华堆积风险评估——以巢湖为例 |
|
钱瑞1,2, 彭福利3, 薛坤2, 齐凌艳4,5, 段洪涛2, 邱银国2, 陈青2, 陈粉丽1, 高俊峰2, 黄佳聪2
|
|
1.西北师范大学地理与环境科学学院, 兰州 730070;2.中国科学院南京地理与湖泊研究所中国科学院流域地理学重点实验室, 南京 210008;3.中国环境监测总站, 北京 100012;4.安徽师范大学地理与旅游学院, 芜湖 231003;5.资源环境与地理信息工程安徽省工程技术研究中心, 芜湖 231003
|
|
| 摘要: |
| 淡水湖库富营养化与蓝藻水华是全球性的突出水环境问题，尤其是滨岸带严重蓝藻水华堆积甚至造成了水体黑臭、威胁饮用水安全等严重危害，科学评估滨岸带蓝藻水华堆积风险、精准识别蓝藻水华易堆积区域是水环境管理与研究中亟待解决的关键科学问题.本研究以我国长江中下游的大型浅水富营养化湖泊巢湖为研究对象，依托流域水文与湖泊水动力模拟、遥感反演、GIS空间分析等技术，综合考虑藻类生物量、岸线形态、湖泊水动力、风速和风向等要素，创新构建了蓝藻水华堆积风险评估指标体系，量化评估了2018-2019年的巢湖滨岸带的蓝藻水华堆积风险，并将滨岸带蓝藻水华堆积风险等级划分为5级（Ⅰ、Ⅱ、Ⅲ、Ⅳ、Ⅴ），绘制了蓝藻水华滨岸带堆积风险的空间分布，识别了蓝藻水华的易堆积区域.评估结果表明：巢湖滨岸带蓝藻水华堆积的高风险区域呈连续片状分布于西巢湖西岸与西北岸，占巢湖沿岸区域的12.1%，是巢湖蓝藻水华应急处置管理的关键区域，评估结果与调研结论总体一致.研发的蓝藻水华堆积风险评估方法可应用于其他大型富营养化湖库，为蓝藻水华应急处置管理提供关键技术支撑. |
| 关键词: 富营养化 湖泊水动力 蓝藻水华 岸线 应急处置 巢湖 |
| DOI：10.18307/2022.0103 |
| 分类号: |
| 基金项目:中国科学院青年创新促进会项目（2019313）、中国科学院战略性先导科技专项A类（XDA23020201）、江苏省水利科技项目（2019025，2018003，2020042，2020032）和安徽省自然科学基金青年项目（1908085QD151）联合资助. |
|
| Assessing the risks of harmful algal bloom accumulation atlittoral zone of large lakes and reservoirs: An example from Lake Chaohu |
|
Qian Rui1,2, Peng Fuli3, Xue Kun2, Qi Lingyan4,5, Duan Hongtao2, Qiu Yinguo2, Chen Qing2, Chen Fenli1, Gao Junfeng2, Huang Jiacong2
|
|
1.College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, P. R China;2.Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P. R. China;3.China National Environmental Monitoring Centre, Beijing 100012, P. R. China;4.College of Geography and Tourism, Anhui Normal University, Wuhu 231003, P. R. China;5.Engineering Technology Research Center of Resources Environment and GIS, Wuhu 231003, P. R. China
|
| Abstract: |
| Eutrophication and harmful algal blooms (HABs) in freshwater lakes and reservoirs are severe global problems for aquatic ecosystems. In particular, severe HABs accumulation in the littoral zone is likely to cause hypoxia (black and odorous water), and thus threaten drinking water safety. Therefore, assessing the risks of HABs accumulation and accurately identifying the littoral zones that is prone to HABs accumulation are of particular importance for water management practice. This study took Lake Chaohu, a large shallow eutrophic lake in the middle and lower reaches of the Yangtze River in China as the study area. Based on the technological advances in hydrological and hydrodynamic modelling in the lake-watershed system, remote sensing monitoring, spatial analysis in GIS software, etc., we developed a novel risk assessment index for HABs accumulation by considering the factors of phytoplankton biomass, shoreline shape, hydrodynamic and wind conditions. The index was applied in Lake Chaohu to assess its risk of HABs accumulation during 2018-2019. The assessment results were divided into five levels from I to V, and were mapped to identify the area with a high risk of HABs accumulation. Our investigation results showed that the high-risk areas of HABs accumulation are mainly located in the western and northwest areas of Western Lake Chaohu, accounting for 12.1% of the littoral zone in Lake Chaohu. These areas should be highly concerned in the emergency management of HABs in Lake Chaohu. The assessment results were generally consistent with our survey findings. The developed risk index for HABs accumulation can be easily transferred to other large eutrophic lakes and reservoirs, and can well support the emergency management practice of HABs. |
| Key words: Eutrophication lake hydrodynamics algal blooms shoreline emergency response Lake Chaohu |
|
|
|
|
