动态调水过程水文和理化因子共同驱动丹江口水库库湾浮游植物季节变化

丹江口水库是南水北调中线工程水源地,库湾是水库型湖泊水质安全敏感区,动态调水过程库湾水质直接关系到调水安全.为探究动态调水过程中丹江口水库库湾浮游植物季节变化规律和驱动因子,2018年7月—2019年7月,从丹库入库口到渠首调水口,按季节对18个样点进行水质和浮游植物群落组成分析.从整个丹库来看,浮游植物全年总丰度变化范围为0.43×10~3～4.7× 10~6 cells/L,夏季最高,秋季最低;Shannon-Wiener指数春季最高,秋季最低.春季群落为硅藻—绿藻型,夏季为绿藻—硅藻型,秋季为蓝藻型,冬季为蓝藻—绿藻—硅藻型,秋季蓝藻相对丰度最高.位于丹库准保护区内的库湾胡寨,秋季水体电导率、总氮、总磷和叶绿素a浓度最大,蓝藻丰度最高.从入库口经库湾到调水口,浮游植物群落组成存在明显演替.从水文因子来看,秋季水库水位较高,调水流速和流量增加,线性回归分析表明,水位对ShannonWiener指数的影响最为明显,水位越高则多样性指数越低;流量和流速与Shannon-Wiener指数也呈负相关,但相关性较低.方差分解分析发现,水文因子和理化因子共同影响了浮游植物群落组成;偏Mantel分析显示3个库湾浮游植物群落组成与水温、氧化还原电位、化学需氧量、总氮和总磷浓度相关;典范对应分析也表明,总氮是影响库湾浮游植物群落组成最显著的环境因子.人类干扰活动改变了库湾水质理化性质,强干扰提高了蓝藻门丰度.因此,控制库湾人类干扰强度,尤其在水位和调水量较高的秋季,对于改善水体藻类组成、保护整个丹江口水库水质具有重要意义.

Hydrologic and physicochemical factors co-drive seasonal changes of phytoplankton during dynamic water diversion processes in the Danjiangkou Reservoir*

Reservoir bays are sensitive areas in terms of water quality and safety. This study analyzed water quality in the Danjiangkou Reservoir in China. Specifically, seasonal patterns and drivers of phytoplankton in the reservoir were explored during dynamic water diversion processes. Water quality and phytoplankton community samples were collected from 18 representative sites ranging from the inlet to the outlet of the reservoir, and samples were collected seasonally from July 2018 to July 2019. In the entire reservoir, the total abundance of phytoplankton ranged from 0.43×10³ to 4.7×10⁶ cells/L, with the highest abundance in summer and lowest in autumn. The Shannon-Wiener diversity index was the highest in spring and lowest in autumn. The phytoplankton community was composed of diatoms-Chlorophyta in spring, Chlorophyta-diatoms in summer, cyanobacteria in autumn, and cyanobacteria-Chlorophyta-diatoms in winter. The relative abundance of cyanobacteria was highest in autumn. Conductivity, total nitrogen (TN), total phosphorus (TP), and chlorophyll-a were all highest in autumn, and cyanobacteria abundances were the highest in Huzhai Bay. An obvious succession of phytoplankton communities was observed from the inlet to the bay to the outlet. For hydrological factors, reservoir water levels were the highest in autumn, during which the regulating flow velocity and flow capacity increased. Linear regression analysis showed that water levels were negatively correlated with diversity indices. Variation partitioning showed that stochastic factors and physicochemical factors both influenced the formation of phytoplankton communities. The partial Mantel test indicated that the phytoplankton community composition in bays was correlated with the water temperature, oxidation-reduction potential, chemical oxygen demand, TN, and TP. Canonical correspondence analysis showed that TN was the most significant factor affecting the composition of phytoplankton communities in bays. These findings should be useful for future efforts to improve water quality in the Danjiangkou Reservoir.