基于无人机高光谱遥感在太湖蓝藻水华监测中的一次应用

采用机载高光谱视频相机,在4个季节对太湖蓝藻进行7次、18个架次的有效拍摄。对拍摄到的高光谱影像进行辐射定标、几何拼接等预处理后,提取不同浓度蓝藻和水草等其他物体的高光谱数据,发现不同浓度的蓝藻光谱在680 nm后表现出较大差异。采用主成分分析（PCA）对高光谱数据降维后,结合k-近邻（kNN）分类算法,可实现对蓝藻的精准定位。定性识别结果经光谱预处理后,采用连续投影算法（SPA）进行特征波段提取,发现蓝藻光谱的季节差异主要表现在450 nm~570 nm和760 nm~910 nm波段。     

香溪河库湾水质特征与非回水区水华响应关系

为探究香溪河在受倒灌影响较弱的河段水华暴发征兆及机理,于水华高发期5~8月对香溪河进行监测,分析电导率、水温、叶绿素a（Chl-a）以及流速.结果表明,在6~8月,香溪河倒灌现象于XX05点（峡口镇）处基本结束,XX06~XX09受倒灌来水影响较弱;香溪河于7月暴发水华,各个监测点位上Chl-a含量均值达到100μg/L以上,XX05~XX06与XX07-XX09点位上暴发不同种水华;在水华暴发前后,水体温度无显著变化,且并无明显分层现象,说明水温分层是水华暴发的主要原因这一理论并不能很好的适用于非回水区;通过对电导率数值的研究发现,数值在垂向上出现显著拐点,而拐点出现在临界层与光补偿层之间,同时与叶绿素a含量分布呈现显著负相关性.香溪河总氮（TN）、总磷（TP）平均值为1.849mg/L和0.157mg/L,均超过富营养化的阈值,水体氮磷含量与Chl-a浓度无显著相关性,水体中除N、P营养盐外的其它离子对香溪河水华的暴发起着重要作用.在水华消退后,电导率数值又逐渐恢复表层高底层低的垂向线性分布特性,与水华的暴发、消退有着明显的响应.     

不同浓度蓝藻水华在好氧条件下的光合作用

为研究不同浓度蓝藻水华在曝气形成的好氧条件下的光合作用,本文按叶绿素a（Chla）浓度32.5,346.8,1413.7和14250.0μg/L设4个处理组（从低到高编号依次为I、Ⅱ、Ⅲ和IV）进行实验.结果表明,各处理Chla浓度均总体呈下降趋势,但均未出现发黑或发褐现象;各处理溶氧、pH值、NH₄⁺-N浓度和最大光合作用能力F_v/F_m均有一定差异（P<0.05）.快速光响应曲线的特征参数α、ETR_max和I_k表明,处理I、Ⅱ和Ⅲ中出现较高的绿藻、硅/甲藻的光能利用效率（P<0.05）,而处理IV中所有藻类的光能利用效率较低（P<0.05）.曝气增氧可以防止高浓度蓝藻水华形成黑水团;蓝藻水华初始Chla浓度约为32.5、346.8、1413.7μg/L时,在曝气形成的好氧条件下,蓝藻水华中会出现其它藻类如绿藻、硅/甲藻的生长,即藻类群落结构朝着多样化变化,对蓝藻水华形成控制.     

反硝化脱氮对太湖蓝藻水华态势的影响

反硝化作用是水生生态系统的主要脱氮过程,与蓝藻生长之间存在对氮素的竞争作用,然而气候变化背景下反硝化脱氮对蓝藻水华发生动态的影响仍不清楚.基于2017~2021年北太湖为期5 a的水质监测历史数据,结合不同温度下蓝藻生长和沉积物泥浆培养实验,探究了湖体反硝化脱氮与蓝藻水华之间的相互影响.监测数据表明,太湖水体藻类生物量（以Chla表示）高值主要出现在夏秋季节,而总氮浓度季节变化规律与藻类生物量完全相反,冬春季较高,夏秋季显著降低,溶解态无机氮主要以硝态氮为主,并且硝态氮浓度在夏秋季节几乎接近于零.总磷浓度与Chla浓度变化一致.蓝藻培养实验结果表明,20℃以下蓝藻不能大量生长繁殖.泥浆培养实验结果发现,太湖反硝化作用的最高温度阈值为25℃,在10~25℃之间反硝化潜力与温度呈现显著的线性关系（R²=0.99）.反硝化作用发生的最高硝态氮浓度阈值为4 mg ·L^-1,远高于太湖水体的硝态氮浓度,反硝化潜力最高达到（62.98±21.36）μmol ·（kg ·h）^-1.太湖水体反硝化速率受到硝态氮浓度的限制,而气候变暖导致湖泊温度提前升高,会使蓝藻提前生长,蓝藻生长对硝态氮的同化吸收会和反硝化作用产生竞争,使得大量氮还未被反硝化作用脱除就被藻类吸收利用,从而加剧蓝藻水华暴发的态势.研究结果对于解释近年来气候变化背景下太湖蓝藻水华反弹的机制具有重要科学意义.     

Modelling algal blooms in the Dutch coastal waters by integrated numerical and fuzzy cellular automata approaches

In this paper, an integrated numerical and fuzzy cellular automata model was developed to predict possible algal blooms in Dutch coastal waters basing on the irradiance, nutrients and neighbourhood conditions. The numerical module used Delft3D-WAQ to compute the abiotic conditions, and fuzzy cellular automata approach was applied to predict the algal biomass that was indicated by chlorophyll a concentration. The simulated results of year 1995 were compared with that from BLOOM II model, and the advantages, disadvantages as well as future improvement were presented. In general, through this study, it is seen that the integrated modelling deserves more research inputs because: (1) the hydrodynamic processes and nutrients concentrations can be simulated in details by numerical method; (2) the irregular and sparse water quality and biological data, and the empirical knowledge from experts can be explored by the fuzzy logic technique; (3) the spatial heterogeneity, local interactions and the emerge of patchiness could be well captured through the cellular automata paradigm.     

滇池水华综合控制对策探讨

水华污染已成为滇池目前面临的主要环境问题，滇池水华治理被国家列为重中之重的项目而予以高度重视，据多年的监测资料，滇池水华的各类主要是蓝藻门的微囊藻，其次为束丝藻和鱼腥藻。该文从多方面分析了滇池水华泛滥的原因，在此基础上提出了滇池水华控制和富营养化治理的综合对策，特别强调了滇池水华必须坚持控制污染源与生态修复相结合的原则。     

藻源性黑水团环境效应:对水-沉积物界面氮磷变化的驱动作用

利用自制的静态模拟实验装置,通过连续抽取间隙水来研究藻细胞沉降在沉积物表面后对水-沉积物界面处的N、P变化的驱动作用及影响效果.结果表明,藻细胞沉降后,在50 min内就完全消耗掉水-沉积物界面处的溶解氧,同时水体出现严重的发黑、发臭现象;形成的厌氧、强还原环境,使得死亡的藻细胞在界面处发生强烈的厌氧矿化作用,界面处的水溶性PO34--P、NH 4+-N在实验的第2 d开始向上覆水中扩散,含量不断增加.至实验结束时(实验第8 d),界面处PO34--P、NH 4+-N的含量分别达到4.00 mg/L、39.45 mg/L,分别为同期对照实验样柱中的10倍和241倍(对照样柱中的PO43--P、NH 4+-N的含量分别为0.42 mg/L、0.16 mg/L).藻细胞的厌氧矿化加剧了氮磷营养盐向上覆水的扩散,在加重水体营养盐含量的同时,也为藻华的再次发生提供了物质基础.     

长江口及东海赤潮海洋环境特征综合探讨

针对我国东海及长江口邻近海域赤潮频繁发生的现象,本文通过大量文献查阅和研究追踪,分别从东海赤潮的生物化学、物理海洋和地质沉积三大方面对其爆发的海洋环境特征进行了综合研究。具体涉及浮游藻类密度、叶绿素a含量、初级生产力、海洋温盐流、地貌沉积八个分项的解释,从整体上对长江口及东海赤潮生消演变的海洋环境进行了初步的探讨,为进一步的认识赤潮提供了研究基础。     

Growth inhibition and oxidative damage of Microcystis aeruginosa induced by crude extract of Sagittaria trifolia tubers

Aquatic macrophytes are considered to be promising in controlling harmful cyanobacterial blooms. In this research, an aqueous extract of Sagittaria trifolia tubers was prepared to study its inhibitory effect on Microcystis aeruginosa in the laboratory. Several physiological indices of M. aeruginosa, in response to the environmental stress, were analyzed. Results showed that S. trifolia tuber aqueous extract significantly inhibited the growth of M. aeruginosa in a concentration-dependent way. The highest inhibition rate reached 90% after 6 day treatment. The Chlorophyll-a concentration of M. aeruginosa cells decreased from 343.1 to314.2 μg/L in the treatment group. The activities of superoxide dismutase and peroxidase and the content of reduced glutathione in M. aeruginosa cells initially increased as a response to the oxidative stress posed by S. trifolia tuber aqueous extract, but then decreased as time prolonged. The lipid peroxidation damage of the cyanobacterial cell membranes was reflected by the malondialdehyde level, which was notably higher in the treatment group compared with the controls. It was concluded that the oxidative damage of M. aeruginosa induced by S.trifolia tuber aqueous extract might be one of the mechanisms for the inhibitory effects.     

A remote sensing tool for near real-time monitoring of harmful algal blooms and turbidity in reservoirs

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real-time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll-a concentrations (chl-a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real-time monitoring of HABs. Landsat-8 and Sentinel-2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl-a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R² values of 0.75, 0.82, and 0.79 for chl-a, turbidity, and phycocyanin, while multiple regression had R² values of 0.29, 0.51, and 0.46 and SVR had R² values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open-source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.