| 新安江水库河口区水质及藻类群落结构高频变化 |
| 摘要点击 2304 全文点击 860 投稿时间：2019-06-19 修订日期：2019-09-10 |
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| 中文关键词 饮用水源地 水库 高频监测浮标 浮游植物 水温分层 有害蓝藻 水质风险 |
| 英文关键词 drinking water source reservoir high-frequency monitoring buoy phytoplankton thermal stratification harmful algae water safety |
| 作者 | 单位 | E-mail | | 笪文怡 | 中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室, 南京 210008
西华师范大学环境科学与工程学院, 南充 637002 | dwyzls@163.com | | 朱广伟 | 中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室, 南京 210008 | gwzhu@niglas.ac.cn | | 黎云祥 | 西华师范大学环境科学与工程学院, 南充 637002 | | | 吴志旭 | 杭州市生态环境局淳安分局, 杭州 311700 | | | 郑文婷 | 杭州市生态环境局淳安分局, 杭州 311700 | | | 兰佳 | 杭州市生态环境局淳安分局, 杭州 311700 | | | 王裕成 | 杭州市生态环境局淳安分局, 杭州 311700 | | | 许海 | 中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室, 南京 210008 | | | 朱梦圆 | 中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室, 南京 210008 | |
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| 中文摘要 |
| 水库库尾区的水环境多变，是水库生态系统突变的重要策源地.为探究大型水库水源地水环境演变特征及其突变的促发机制，以新安江水库为例，通过库尾河口断面18个月水质浮标的高频记录及3 d一次的藻类群落结构人工鉴定数据等，分析了气象水文过程影响下的水库库尾区的水温、溶解氧、浊度及营养盐等环境指标及藻类群落结构的高频变化特征，揭示了降雨、入流及季节温度变化等关键气象水文过程对水库水质及藻类群落结构的影响机制.结果表明：①在27 m深的河流入库区的水体温度和溶解氧存在明显的季节分层，相应水体藻类叶绿素a和营养盐等指标也同步发生分层，水温分层从气温达到14℃以上的3月中旬开始，至气温降至24℃后的10月中旬结束，期间较大降雨和入流多次破坏水温分层；②河道入库区水体氮、磷等营养盐变幅大，总磷浓度变幅为0.011~0.188 mg·L-1之间，总氮浓度变幅为0.75~2.76 mg·L-1之间，总磷和总氮中的溶解态占比分别为56%及88%，降雨入流对水体营养盐浓度影响巨大，3 d的累积降雨与水体氮、磷浓度显著正相关，3~6月（雨季）的营养盐含量明显高于其他月份（P<0.001），藻类的季节性增殖反过来也会影响水体总磷浓度；③藻类群落结构及其优势属呈现明显的季节变化，在总体硅藻门类占优的背景下，蓝藻、绿藻、隐藻等在不同季节形成明显峰值，蓝藻在7~10月的夏秋季形成明显的生物量峰值，其峰值形成原因除了高温之外，还与暴雨入流有关.蓝藻主要优势属为束丝藻属（Aphanizomenon spp.）、微囊藻（Microcystis spp.）及颤藻（Oscillatoria spp.）等，绿藻峰值与蓝藻基本同步，优势属为盘星藻属（Pediastrum spp.）和新月藻属（Closterium spp.），隐藻在3~5月形成峰值，优势属为隐藻属（Cryptomonas spp.），硅藻门中的优势属分别为脆杆藻属（Fragilaria spp.）、小环藻属（Cyclotella spp.）、针杆藻属（Synedra spp.）及直链藻属（Melosira spp.）等；④入库流量、温度、水位、透明度、总氮、总磷及氮磷比等均为影响藻类优势属演替的主要因子，秋冬季节的控制因子为气象水文条件，而夏秋季节则受气象水文及营养盐的共同控制.本研究表明强降雨过程能对水库库尾区水环境及水生态系统结构产生巨大冲击，是水库藻类水华发生的可能诱发因子，通过对该过程的规律认识及关键指标监测，能够为水库水源地水质风险提供预警信息. |
| 英文摘要 |
| The tail of the reservoir is the unstable zone regarding water quality and phytoplankton community. Therefore, it is the crucial zone in aquatic ecosystem transitions. To understand the transition characteristics and driving mechanisms of water environment dynamics, high-frequency monitoring of the water environment and phytoplankton community in the tail of a deep and large reservoir, the Xin'anjiang Reservoir in southeast of China, was conducted using a water quality monitoring buoy and three-day interval water sampling during 18 months. Results show clear seasonal thermal and oxygen stratification in the river mouth of the reservoir. The nutrient and chlorophyll-a concentrations also show stratifying phenomena during the thermal stratification period. Heavy rain and inflow quickly consume the stratification. Nutrient concentrations were highly dynamic in the river mouth. The total phosphorus ranges from 0.011 mg·L-1 to 0.188 mg·L-1, and total nitrogen ranges from 0.75 mg·L-1 to 2.76 mg·L-1. Dissolved phosphorus comprised 56% of total phosphorus, and dissolved nitrogen occupied 88% of total nitrogen, respectively. Nutrient concentrations were influenced strongly by rainfall intensity and inflow rate. Total phosphorus and nitrogen concentrations were significantly related to the three-day accumulated rainfall. Nutrient concentrations in the flood season (March to June) were significantly higher than in the non-flood season (P<0.001). Seasonal phytoplankton proliferation also significantly influenced by total phosphorus concentration. The phytoplankton community changes significantly with seasons and flood events. Bacillariophytea was generally dominant throughout the year, with the predominant genus of Fragilaria spp., Cyclotella spp., Synedra spp., and Melosira spp. Cyanophyta biomass peaked in July, August, and September, with the dominant genus of Aphanizomenon spp., Microcystis spp., and Oscillatoria spp. Apart from the high temperature, storm inflow events also triggered Cyanophyta proliferation. The proliferation of Chlorophyta was similar to Cyanophyta, with the predominant genus of Pediastrum spp. and Closterium spp.. While the Cryptophyta biomass peaked during March to May, with the predominant genus of Cryptomonas spp.. Redundancy analysis shows that the influence factors of phytoplankton community dynamics include the inflow rate, temperature, water level, water transparency, total nitrogen, total phosphorus, and nitrogen to phosphorus ratio. The meteorological and hydrological factors were major factors for phytoplankton dynamics during later autumn and winter, while the nutrient will be the co-driving factors of phytoplankton community dynamics during summer and early autumn. The research confirmed the huge influence of the intensity rainfall event on the water environment in reservoirs and described the key environmental conditions for phytoplankton community dynamics. The research is useful for the design of the monitoring and forecasting system for water safety in drinking water source reservoirs. |
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