WATER QUALITY MODELING IN THE UPPER REACHES OF THE CHOWAN RIVER1

ABSTRACT: The Chowan River system consists of three rivers in southeast Virginia that form two confluences before flowing into Albermarle Sound in North Carolina. A computer program was written to simulate flows through the river system to determine flow rates, velocities, and depths. The output of the flow program was input into a second program that calculated the concentrations of BOD₅, COD, DO, and four nitrogen parameters (organic, ammonia, nitrite-nitrate and algal-N). Measured field data were used to calibrate the model. The effect of reducing the concentration of nutrients from overland runoff on algal concentrations at the mouth of the river was studied. The program was also run to simulate the water quality of the watershed in a primitive condition, in which the watershed was assumed to consist only of forests. The results of the computer program indicate that the major changes in the water quality of the river are simulated satisfactorily. The program can be used to assess the impact of any management scheme to improve water quality.     

Adaptive Management of Nonnative Species: Moving Beyond the “Either-Or” Through Experimental Pluralism

This paper develops the outlines of a pragmatic, adaptive management-based approach toward the control of invasive nonnative species (INS) through a case study of Kings Bay/Crystal River, a large artesian springs ecosystem that is one of Florida’s most important habitats for endangered West Indian manatees (Trichechus manatus). Building upon recent critiques of invasion biology, principles of adaptive management, and our own interview and participant–observer research, we argue that this case study represents an example in which rigid application of invasion biology’s a␣priori imperative to minimize INS has produced counterproductive results from both an ecological and social standpoint. As such, we recommend that INS control in Kings Bay should be relaxed in conjunction with an overall program of adaptive ecosystem management that includes meaningful participation and input from non-institutional stakeholders. However, we also note that adaptive management and INS control are by no means mutually exclusive, in Kings Bay or elsewhere. Instead, we suggest that adaptive management offers a means by which INS control efforts can emerge from—and be evaluated through—ongoing scientific research and participatory dialogue about the condition of specific places, rather than non-contextual assumptions about the harmfulness of INS as a general class.     

三峡库区四条支流藻类多样性评价及“水华”防治

应用多样性指数、丰富度指数和均匀性指数对长江4条支流水域的藻类多样性进行了评价.比较了4条支流春、秋两季浮游藻类优势种、细胞密度和生物量等指标,对三峡蓄水后库区“水华”成因进行了初步分析.结果表明,4条支流的营养水平均属于中-富营养型,童庄河的水质最差,其次为香溪河和青干河,九畹溪的水质较好.春季硅藻的种类数多,绿藻种类数少;秋季则相反.藻类细胞密度的最高值出现在香溪河(6.036×106个/L),生物量的最高值出现在童庄河(19.997mg/L).2项指标的最低值均出现在九畹溪.在春季,童庄河还出现了拟多甲藻(Peridiniopsissp.)“水华”,并伴有较大量的小环藻(Cyclotellasp.)和卵形隐藻(Cryptomonasovata).三峡库区的水华属于季节性水华,可通过控制外源污染和增加水体流速来控制.     

高藻水中污染物氧化降解及卤代烃生成的控制

研究了O₃、ClO₂、Cl₂ 3 种氧化剂对高藻期原水中藻类、细菌、有机物的预处理效果,分析了不同氧化过程中卤代烃的形成原因及其前体物的控制效果.结果表明,O₃杀藻灭菌作用明显强于 ClO₂和 Cl₂,对 UV₂₅₄ 表征的具有共轭结构或含有芳环结构的不饱和有机物去除率较高.试验水中三氯甲烷(CHCl₃)前体物含量高达 80μg/L .与Cl₂相比,O₃、 ClO₂预氧化处理能显著地控制 CHCl₃生成,并有效地降低 CHCl₂、CCl₃ 前体物含量,二者对 CHCl₃ 生成量的影响不同.3 种预氧化方法均不会使水中 CCl₄ 含量增加.CHCl₃ 是原水预氧化后生成卤代烃的主要成分.3 种预氧化处理工艺适宜的浓度与反应时间分别为 O₃1.5mg/L、15min, ClO₂4.0mg/L、30min,.     

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。     

三峡库区大宁河藻细胞昼夜垂直迁移研究

旨在准确为三峡库区藻华预警提供基础数据,本研究于2011年7月底在三峡库区大宁河流域进行藻细胞昼夜垂直迁移试验.结果表明,大宁河在此期间,藻细胞主要以绿藻、蓝藻、硅藻和甲藻为主;藻细胞在水体中的分布不均匀,72.5%～76.2%的藻细胞集中在0.5～4.0 m水体之间,0～0.5 m处藻细胞较少,占垂直水体藻密度的7.5%～16.3%,白天藻细胞Morisita指数(MI)为1.41～1.97,夜晚MI指数为1.17～1.55,叶绿素a白天MI指数为1.31～1.59,而夜晚MI指数为1.17～1.39.藻细胞在水体中存在明显的昼夜垂直迁移现象,该现象主要发生在0.5～4.0 m水体之间.水体中的藻密度受营养盐的影响较小,与可溶解性总磷显著相关(r=0.89),藻密度主要受温度、pH值和导电率影响,藻密度与温度、pH值和导电率呈极显著相关,相关系数分别为0.96、0.97和-0.99.     

水温分层对三峡水库香溪河库湾春季水华的影响

三峡水库蓄水以来,其支流库湾年复一年暴发严重的春季水华.为找出支流库湾春季水华的关键影响因子,2010年春季对三峡水库库首最大的支流香溪河库湾进行了原位定点连续监测,主要监测指标包括水温、水体透明度、水下光照及营养盐浓度等环境因子.结果表明,春季水温分层发育导致水体混合层深度突然减小是春季水华暴发的直接诱因,真光层与水体混合层之比(Zeu/Zmix)与叶绿素a(Chl-a)的皮尔逊相关系数达0.934(P<0.01).表明Critical Depth模型可用于解释三峡水库典型支流库湾水华生消机制.本研究将为三峡水库支流库湾水华预报及防治提供重要参考.     

典型湖泊有机聚集体时空特征及驱动因子

有机聚集体(OA)是水体中物质循环和能量流通的重要枢纽,但在不同营养水平湖泊中的比较研究仍相当匮乏.于2019～2021年间,采集了不同季节贫营养抚仙湖、中营养天目湖、中度富营养太湖和重度富营养星云湖表层水样,利用扫描电镜、表面荧光显微镜和流式细胞仪等研究了4个典型湖泊中OA及其附着细菌的时空变化特征.结果表明：(1)抚仙湖、天目湖、太湖和星云湖中,OA丰度的年均值分别为1.4×10⁴、 7.0×10⁴、 27.7×10⁴和16.0×10⁴ind·mL^-1; OA附着细菌丰度的年均值分别为0.3×10⁶、 1.9×10⁶、 4.9×10⁶和6.2×10⁶ cells·mL^-1;附着细菌占总细菌的比值分别为30%、 31%、 50%和38%.(2)夏季OA丰度显著高于秋冬季;但夏季附着细菌占总细菌的比值为26%,显著低于其它3个季节.(3)湖泊营养状态是影响OA及其附着细...     

Selection of water source for water transfer based on algal growth potential to prevent algal blooms

Water transfer is becoming a popular method for solving the problems of water quality deterioration and water level drawdown in lakes. However, the principle of choosing water sources for water transfer projects has mainly been based on the effects on water quality, which neglects the influence in the variation of phytoplankton community and the risk of algal blooms. In this study, algal growth potential (AGP) test was applied to predict changes in the phytoplankton community caused by water transfer projects. The feasibility of proposed water transfer sources (Baqing River and Jinsha River) was assessed through the changes in both water quality and phytoplankton community in Chenghai Lake, Southwest China. The results showed that the concentration of total nitrogen (TN) and total phosphorus (TP) in Chenghai Lake could be decreased to 0.52 mg/L and 0.02 mg/L respectively with the simulated water transfer source of Jinsha River. The algal cell density could be reduced by 60%, and the phytoplankton community would become relatively stable with the Jinsha River water transfer project, and the dominant species of Anabaena cylindrica evolved into Anabaenopsis arnoldii due to the species competition. However, the risk of algal blooms would be increased after the Baqing River water transfer project even with the improved water quality. Algae gained faster proliferation with the same dominant species in water transfer source. Therefore, water transfer projects should be assessed from not only the variation of water quality but also the risk of algal blooms.     

Formation of regulated and unregulated disinfection byproducts during chlorination and chloramination: Roles of dissolved organic matter type, bromide, and iodide

Algal blooms and wastewater effluents can introduce algal organic matter (AOM) and effluent organic matter (EfOM) into surface waters, respectively. In this study, the impact of bromide and iodide on the formation of halogenated disinfection byproducts (DBPs) during chlorination and chloramination from various types of dissolved organic matter (DOM, e.g., natural organic matter (NOM), AOM, and EfOM) were investigated based on the data collected from literature. In general, higher formation of trihalomethanes (THMs) and haloacetic acids (HAAs) was observed in NOM than AOM and EfOM, indicating high reactivities of phenolic moieties with both chlorine and monochloramine. The formation of haloacetaldehydes (HALs), haloacetonitriles (HANs) and haloacetamides (HAMs) was much lower than THMs and HAAs. Increasing initial bromide concentrations increased the formation of THMs, HAAs, HANs, and HAMs, but not HALs. Bromine substitution factor (BSF) values of DBPs formed in chlorination decreased as specific ultraviolet absorbance (SUVA) increased. AOM favored the formation of iodinated THMs (I-THMs) during chloramination using preformed chloramines and chlorination-chloramination processes. Increasing prechlorination time can reduce the I-THM concentrations because of the conversion of iodide to iodate, but this increased the formation of chlorinated and brominated DBPs. In an analogous way, iodine substitution factor (ISF) values of I-THMs formed in chloramination decreased as SUVA values of DOM increased. Compared to chlorination, the formation of noniodinated DBPs is low in chloramination.