基于BP神经网络的藻类水华预测模型研究

以宁波大学校内池塘2009年3—10月间30周的监测数据为基础,运用BP人工神经网络方法构建预测模型,探求颤藻生物量与总氮、总磷、透明度等6项环境因子之间的关系,选出最佳预测模型,并对模型进行敏感度分析。结果显示:①BP神经网络模型对颤藻生物量预测值与实测值之间拟合程度良好,相关系数达到了0.984,说明BP神经网络模型可以用于水体中藻类水华的短期预测。②通过对构建的BP神经网络模型进行敏感度分析,阐明了宁波大学校内池塘藻类水华的主要驱动因素,并指出控制水体的pH是宁波大学校内池塘藻类水华防治工作的重点。     

典型湖泊水华特征及相关影响因素分析

通过2011-2015年对太湖、巢湖和滇池水华高发季节的连续监测，以藻类密度和水华面积为判据评价了3个湖体的水华情况及变化趋势，探讨了水华发生的主要影响因素。结果表明：太湖水华程度以"轻度水华"为主，巢湖水华程度以"轻微水华"为主，滇池水华程度以"中度水华"为主；太湖、巢湖和滇池水华规模均以"零星性水华"为主；太湖和巢湖藻类密度与水温、pH、溶解氧、总氮、总磷和高锰酸盐指数均呈显著正相关，与透明度呈显著负相关，与氨氮无显著相关性；滇池藻类密度与水温、总磷和高锰酸盐指数均呈显著正相关，与透明度和氨氮呈显著负相关，与pH、溶解氧和总氮无显著相关性。     

氮、磷等环境因子对太湖微囊藻与水华鱼腥藻生长的影响

为探索太湖主要水华藻类（微囊藻与水华鱼腥藻）在多种环境因子作用下的生长变化机理，在实验室内对部分水华藻类（微囊藻、鱼腥藻）进行分离培养，研究氮、磷、温度等环境因子对水华藻类生长增殖的影响。研究表明，高水温（30℃）是微囊藻的最适生长温度；随着氮、磷浓度的提高，微囊藻的生长速率加快；低磷是鱼腥藻生长的限制因子。同时，通过野外测定的各项指标发现，当藻类密度较低时，其与总氮、总磷呈正相关。     

洋河水库蓝藻水华爆发预测影响因子研究

为了预测洋河水库富营养化变化趋势和蓝藻水华爆发的风险,对洋河水库水体进行采样,分析其环境质量.研究结果表明,近年来洋河水库叶绿素a含量处于高位,氮、磷含量不断上升,特别是总氮质量浓度在5 mg/L左右,主要以硝态氮的形式存在,富营养化程度不断加剧,具有大规模爆发蓝藻水华的风险.对洋河水库藻华爆发的环境条件进行分析,提出...     

Inter-relations between biological and physicochemical factors in a database for a shallow estuarine system

This paper examines data obtained since 1976 in Peel Inlet and the Harvey Estuary, a shallow estuarine system in Western Australia, which has nuisance growths of macroalgae and seasonal blooms of the cyanobacterium (blue-green alga)Nodularia spumigena. Data collected at the same sites at weekly or fortnightly intervals include phytoplankton (chlorophylla), water nutrients (nitrogen and phosphorus), salinity, temperature and light penetration. Seasonally, the biomass of macroalgae has been measured at a number of sites and used to estimate total biomass.The data are characterised by large season-to-season differences, attributable to the seasonality and volume of river flow. The information has been used to relate the magnitude of summer blue-green algal blooms to the winter loading of phosphorus from the surrounding catchment, and the magnitude of macroalgal biomass to light penetration through the water column.     

Phytoplankton variation and its relationship with the environment in Xiangxi Bay in spring after damming of the Three-Gorges, China

Following the completion of the Three-Gorges Dam, there was a strong spring phytoplankton bloom in Xiangxi Bay of Three-Gorges Reservoir. However, our knowledge of relationship between spring phytoplankton bloom and environmental factors was still limited. In this study, phytoplankton species composition, biomass, chlorophyll a concentration and environmental factors at two sampling sites in Xiangxi Bay were investigated during 25 March to 18 May 2007. The Xiangxi Bay was eutrophic with the lowest values of total nitrogen and total phosphorus being 0.80 and 0.07?mg/L, respectively. A total of 66 algal taxa belonging to seven phyla and 45 genera were identified. Peridiniopsis niei Liu was the most abundant species which preferred standing water. Canonical correspondence analysis and correlation analysis revealed that nitrate was significantly associated with phytoplankton growth. The phytoplankton chlorophyll a concentration was correlated significantly negatively with nitrate concentration, and nitrate concentration was very low during bloom periods. Heavy rainfall was the main reason of phytoplankton chlorophyll a concentration and biomass decreasing and blooms disappearing. In addition, heavy rainfall also brought more nitrate into the Bay which provided sufficient nitrogen source for blooms occurring again.     

浙江省水体富营养化特征及防治对策

为研究浙江省水体富营养化特征,对全省历年省控断面地表水水质、污染源和重点藻华高发河流营养盐通量等数据进行了统计分析。结果表明:全省水体营养盐水平总体仍处于高位,重点流域富营养化问题突出,省控断面富营养、重富营养占比分别为78.7%和43.0%,营养盐已持续成为地表水首要污染超标因子。通过近年来的集中整治,浙江省水体营养盐浓度下降明显。但治理过程中也出现了总氮减排滞后,部分水域总磷浓度反弹等不利现象。特别是相应的藻类生长势能尚未进入下降敏感区间,对藻华防控贡献有限。同时,全省入河营养盐城镇生活源和农业面源占比突出,总氮合计占89.27%,总磷占95.45%。重点流域地表径流对营养盐入河通量贡献明显,汛期其对河流总磷浓度的贡献明显高于固定源排放。建议在营养盐总量控制、跨部门协调机制、水资源配置、农业面源管理、城镇雨污管网建设、雨污处理以及河流生态修复等方面加强应对。     

贵州黔东南州三板溪水库春季拟多甲藻水华特征

2011年3月13日对贵州省黔东南州三板溪水库进行春季浮游植物调查的结果表明,三板溪水库Ⅱ号采样点(下革东)发生以佩纳形拟多甲藻为优势种的拟多甲藻水华,细胞密度高达1.15×10⁷cell/L;板溪水库总氮的最低值为2.09 mg/L,总磷的最低值为0.95 mg/L,三板溪水库的总氮、总磷含量较丰富,不存在总氮或总磷是限制性因子;通过SPSS16.0统计软件分别进行Pearson 积距相关系数分析表明,氮磷比是三板溪水库发生拟多甲藻水华的主要影响原因。     

太湖蓝藻水华暴发主要特征初析

太湖水体富营养化加剧引起了多方面的关注,针对近年实际监测结果,结合历年流域水环境质量的变化,初步归纳了当前太湖蓝藻水华暴发的地域特征、时间周期特点及主要水质指标的变化规律,总结了太湖蓝藻水华的暴发呈多峰形状态.2007年太湖沙渚水源地藻类生物量的两峰三阶段的特征进一步表明,太湖蓝藻水华的暴发进入了高频期.     

Water Quality Prediction of Water Sources Based on Meteorological Factors using the CA-NARX Approach

With the increasingly serious problem of surface water environmental safety, it is of great significance to study the changing trend of reservoir water quality, and it is necessary to establish a water quality prediction and early warning system for the management and maintenance of water resources. Aiming at the problem of water quality prediction in reservoirs, a CA-NARX algorithm is designed, which combines the improved dynamic clustering algorithm with the idea of machine learning and the forward dynamic regression neural network. The improved dynamic clustering algorithm is used to classify the eutrophication degree of waterbodies according to the total phosphorus and total nitrogen content. Considering four meteorological factors, air temperature, water temperature, water surface evaporation, and rainfall, synthetically for each water quality condition, the total phosphorus and total nitrogen in the waterbody are forecasted by an improved forward NARX dynamic regression neural network. Based on this, the CA-NARX prediction algorithm can realize short period water quality prediction. Compared with the traditional support vector regression machine model, improved GA-BP neural network, and exponential smoothing method, the CA-NARX model has the least prediction error.

     

Response of algal metrics to nutrients and physical factors and identification of nutrient thresholds in agricultural streams

Many streams within the United States are impaired due to nutrient enrichment, particularly in agricultural settings. The present study examines the response of benthic algal communities in agricultural and minimally disturbed sites from across the western United States to a suite of environmental factors, including nutrients, collected at multiple scales. The first objective was to identify the relative importance of nutrients, habitat and watershed features, and macroinvertebrate trophic structure to explain algal metrics derived from deposition and erosion habitats. The second objective was to determine if thresholds in total nitrogen (TN) and total phosphorus (TP) related to algal metrics could be identified and how these thresholds varied across metrics and habitats. Nutrient concentrations within the agricultural areas were elevated and greater than published threshold values. All algal metrics examined responded to nutrients as hypothesized. Although nutrients typically were the most important variables in explaining the variation in each of the algal metrics, environmental factors operating at multiple scales also were important. Calculated thresholds for TN or TP based on the algal metrics generated from samples collected from erosion and deposition habitats were not significantly different. Little variability in threshold values for each metric for TN and TP was observed. The consistency of the threshold values measured across multiple metrics and habitats suggest that the thresholds identified in this study are ecologically relevant. Additional work to characterize the relationship between algal metrics, physical and chemical features, and nuisance algal growth would be of benefit to the development of nutrient thresholds and criteria.     

三峡库区大宁河2010年春季水华特征

以大宁河春季水华期间调查数据为基础,运用数理统计分析手段,通过描述大宁河春季水华期藻类及主要理化因子分布特征,揭示出影响藻类生长的主要因子。结果表明:大宁河春季水华期水华河段水体氮、磷含量较高,总氮浓度为1.2～4.11mg/L,平均值为1.748mg/L,总磷浓度为0.027～0.615mg/L,氮磷比均值为17.5。春季水华藻类适宜的光照强度为1400～3800lx,水温为13.0～14.0℃时叶绿素a含量有最大增长,平均水温为13.4℃,藻密度与总氮、总磷、水温、DO、pH、浊度、高锰酸盐指数呈显著正相关关系,与透明度呈负相关关系。回水河段流速小于0.05m/s,流速是藻类生长最主要的限制因子。大宁河回水河段春季水华藻类分布较广,主要有甲藻门、绿藻门、硅藻门、隐藻门、蓝藻门、裸藻门和黄藻门7门28属,其中甲藻门分布最广,其次是绿藻门。春季水华优势种主要有甲藻门的拟多甲藻,绿藻门的衣藻、小球藻,硅藻门的直链藻,蓝藻门的色球藻等。     

联合多源光学和雷达遥感的巢湖水华长时序时空变化分析

以巢湖水华爆发现象为研究对象,利用多源光学遥感和全极化SAR遥感作为数据源,对研究区域2008—2017年的水华进行识别提取,定量和定性分析水华面积及区域位置的时空变化。结果表明:在时间上,每年二、三季度巢湖水华面积普遍高于一、四季度,总体上呈现年平均水华面积逐渐减小趋势,前五年的水华面积比后五年高。在空间上,巢湖西北部水华发生频率最高,西部水华比东部水华发生频率高,沿岸比湖中心发生频率高。巢湖水华整体呈现改善趋势。     

Study of harmful algal blooms in a eutrophic pond, Bangladesh

The purpose of this research was to analyze the underlying mechanisms and contributing factors related to the seasonal dynamic of harmful algal blooms in a shallow eutrophic pond, Bangladesh during September 2005–July 2006. Two conspicuous events were noted simultaneously throughout the study period: high concentration of phosphate–phosphorus (>3.03; SD 1.29 mg l^???1) and permanent cyanobacterial blooms {>3,981.88 × 10³ cells l^???1 (SD 508.73)}. Cyanobacterial blooms were characterized by three abundance phases, each of which was associated with different ecological processes. High nitrate–nitrogen (>2.35; SD 0.83 mg l^???1), for example, was associated with high cyanobacterial abundance, while low nitrate–nitrogen (0.36; SD 0.2 mg l^???1) was recorded during moderate abundance phase. Extremely low NO₃–N/PO₄–P ratio (>3.55, SD 2.31) was recorded, and all blooming taxa were negatively correlated with this ratio. Cyanobacterial blooms were positively correlated with temperature (r?=?0.345) and pH (0.833; p?=?0.05) and negatively correlated with transparency (r?=???0.956; p?=?0.01). Although Anabaena showed similar relationship with water quality parameters as cyanobacteria, the co-dominant Microcystis exhibited negative relationship with temperature (r?=???0.386) and nitrate–nitrogen (r?=???0.172). This was attributed to excessive growth of Anabaena that suppressed Microcystis’s growth. Planktothrix was the third most dominant taxa, while Euglena was regarded as opportunistic.     

洪泽湖藻类与环境因子逐步回归统计和蓝藻水华初步预测

以洪泽湖2008—2010年的连续监测资料为基础,运用多元逐步回归统计方法,选择水温等12项环境因子与藻类叶绿素a等5项生物因子进行逐步回归分析,找出与生物因子显著相关的因子,建立多元逐步回归方程,预测洪泽湖藻类密度的变化情况,初步进行了洪泽湖蓝藻水华的预测预报。结果显示,总磷、总氮、氨氮和水深为洪泽湖藻类密度的显著相关因子,透明度、水温、水深为蓝藻密度的显著相关因子。     

太湖蓝藻水华暴发程度年度预测

近年来,尽管太湖主要水质指标有所改善,但蓝藻水华暴发的频次和面积并未明显减少.为了探讨太湖蓝藻水华暴发的环境驱动因子,统计了2012—2020年历年4—10月预警期间的太湖蓝藻水华发生规模与频次,结合同步浮标自动监测数据和实验室分析数据,构建了蓝藻水华预测模型.以太湖蓝藻水华综合指数(Ic)表征蓝藻水华强度,并通过Ic...     

In situ nitrogen enrichment experiments in two Idaho (U.S.A.) streams

We conducted a series ofin situ experimental nutrient additions in two Idaho streams: Deep Creek, a desert stream located in Southeastern Idaho, and Big Wood River, situated in a mountainous region of Central Idaho. In both streams, a homogeneous reach was partitioned into almost identical channels. This allowed us to vary nutrient levels and measure algal response in experiments uncomplicated by differences in other factors.Ammonium nitrate was added to the treatment channels in Deep Creek. After nine days,Cladophora glomerata still predominated in both the control and treatment channels and algal biomass was not statistically different between the two. In the Big Wood River experiment significant differences in chlorophylla concentrations were not detected among three treatments of differing nitrogen enrichment and the control for both natural and artificial substrates. Also chlorophylla levels were not correlated with nitrogen concentrations, and the composition of algal communities remained similar among all treatments.We conclude that macronutrient enrichment of streams does not necessarily result in an increase in algal density or a change in algal community structure so long as other factors, which may limit the use of nutrients by algae, remain unaltered. Our results suggest that light, current velocity, and macroinvertebrate grazing may account for the failure of the periphyton to respond toin situ additions of nitrogen (and phosphorus) in our study streams.     

Monitoring of ocean surface algal blooms in coastal and oceanic waters around India

The National Aeronautics and Space Administration’s (NASA) sensor MODIS-Aqua provides an important tool for reliable observations of the changing ocean surface algal bloom paradigms in coastal and oceanic waters around India. A time series of the MODIS-Aqua-derived OSABI (ocean surface algal bloom index) and its seasonal composite images report new information and comprehensive pictures of these blooms and their evolution stages in a wide variety of events occurred at different times of the years from 2003 to 2011, providing the first large area survey of such phenomena around India. For most of the years, the results show a strong seasonal pattern of surface algal blooms elucidated by certain physical and meteorological conditions. The extent of these blooms reaches a maximum in winter (November–February) and a minimum in summer (June–September), especially in the northern Arabian Sea. Their spatial distribution and retention period are also significantly increased in the recent years. The increased spatial distribution and intensity of these blooms in the northern Arabian Sea in winter are likely caused by enhanced cooling, increased convective mixing, favorable winds, and atmospheric deposition of the mineral aerosols (from surrounding deserts) of the post-southwest monsoon period. The southward Oman coastal current and southwestward winds become apparently responsible for their extension up to the central Arabian Sea. Strong upwelling along this coast further triggers their initiation and growth. Though there is a warming condition associated with increased sea surface height anomalies along the coasts of India and Sri Lanka in winter, surface algal bloom patches are still persistent along these coasts due to northeast monsoonal winds, enhanced precipitation, and subsequent nutrient enrichment in these areas. The occurrence of the surface algal blooms in the northern Bay of Bengal coincides with a region of the well-known Ganges–Brahmaputra Estuarine Frontal (GBEF) system, which increases supply of nutrients in addition to the land-derived inputs triggering surface algal blooms in this region. Low density (initiation stage) of such blooms observed in clear oceanic waters southeast and northeast of Sri Lanka may be caused by the vertical mixing processes (strong monsoonal winds) and the occurrence of Indian Ocean Dipole events. Findings based on the analyses of time series satellite data indicate that the new information on surface algal blooms will have important bearing on regional fisheries, ecosystem and environmental studies, and implications of climate change scenarios.     

富营养化与温度因素对太湖藻类生长的影响研究

为了研究气候变暖和富营养化对湖泊水生态系统的影响,应用阿列纽斯方程修正的Monod生长模型定量研究长期以来太湖藻类生物量与营养元素和温度的关系.研究表明,在近年来的富营养化状况下,年均气温每增加1.0℃,年均藻类生物量增加0.145倍.湖泊富营养化越严重.年平均气温对藻类生长的影响就越大,由此可以定量评估和预测年均气温...     

基于细胞自身特征的铜绿微囊藻比生长速率预测

生物量累积是水华形成前的一个重要过程,因此研究藻类生长速率的变化对于水华早期预警具有重要意义。通过控制P浓度和光照条件获得了不同的铜绿微囊藻生长性质,研究了细胞自身特征与比生长速率的变化关系。初步建立了基于细胞P含量、细胞碳水化合物含量和细胞体积的比生长速率预测耦合模型。