湖泊科学   2020, Vol. 32 Issue (2): 428-439.  DOI: 10.18307/2020.0212.
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研究论文

引用本文 [复制中英文]

张柳青, 杨艳, 李元鹏, 石玉, 周蕾, 周永强, 张运林, 高邮湖、南四湖和东平湖有色可溶性有机物来源组成特征. 湖泊科学, 2020, 32(2): 428-439. DOI: 10.18307/2020.0212.
[复制中文]
ZHANG Liuqing, YANG Yan, LI Yuanpeng, SHI Yu, ZHOU Lei, ZHOU Yongqiang, ZHANG Yunlin. Sources and optical dynamics of chromophoric dissolved organic matter in Lake Gaoyou, Nansi, and Dongping. Journal of Lake Sciences, 2020, 32(2): 428-439. DOI: 10.18307/2020.0212.
[复制英文]

基金项目

国家自然科学基金项目(41807362,41621002)、江苏省自然科学基金项目(BK20181104)、中国科学院前沿科学重点研究计划项目(QYZDB-SSW-DQC016)和中国科学院南京地理与湖泊研究所启动基金项目(NIGLAS2017QD08)联合资助

通信作者

周永强, E-mail:yqzhou@niglas.ac.cn

文章历史

2019-03-11 收稿
2019-07-06 收修改稿

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高邮湖、南四湖和东平湖有色可溶性有机物来源组成特征
张柳青1,2 , 杨艳2 , 李元鹏1 , 石玉1 , 周蕾1,3 , 周永强1,3 , 张运林1,3     
(1: 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)
(2: 西华师范大学环境科学与工程学院, 南充 637000)
(3: 中国科学院大学, 北京 100049)
摘要:高邮湖、南四湖和东平湖作为南水北调东线枢纽湖泊,其水质状况对保障调水安全起到关键性作用.本文运用三维荧光光谱-平行因子分析法(EEMs-PARAFAC)分析了3个湖泊在不同水文情景下有色可溶性有机物(CDOM)吸收、荧光光谱特征以及荧光组分与主要水质参数的相关性,以探究3个湖泊CDOM来源组成特征.结果表明,平行因子分析法解析CDOM三维荧光图谱,得到陆源类腐殖质C1、类色氨酸C2和类酪氨酸C3.不同水文情景对高邮湖CDOM来源与结构组成影响较明显,丰水期其类腐殖质荧光强度显著大于枯水期(t-test,P < 0.01),并且与a(254)呈正相关(R2=0.85,P < 0.01),表明类腐殖质是CDOM主要部分,该荧光组分贡献率可达50%[FmaxC1/(FmaxC1+FmaxC2+FmaxC3)×100%],高邮湖受到入湖河流来水的影响较大,丰水期入湖口附近荧光强度明显高于其他水域.东平湖和南四湖CDOM来源组成特征相似,丰水期东平湖和南四湖组分C2和C3显著低于枯水期(t-test,P < 0.01),两湖泊枯水期工农业等人为污染源影响较大.相关性分析表明高邮湖中类腐殖质荧光特征在一定程度是能反演DOC浓度,并且类腐殖质的输入会增加湖泊总磷、总氮和叶绿素a浓度.而东平湖和南四湖CDOM荧光特征与主要水质参数的相关性较差,这与高邮湖水体存在较大差异.
关键词南水北调    高邮湖    南四湖    东平湖    有色可溶性有机物    平行因子分析    
Sources and optical dynamics of chromophoric dissolved organic matter in Lake Gaoyou, Nansi, and Dongping
ZHANG Liuqing1,2 , YANG Yan2 , LI Yuanpeng1 , SHI Yu1 , ZHOU Lei1,3 , ZHOU Yongqiang1,3 , ZHANG Yunlin1,3     
(1: State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P. R. China)
(2: College of Environment Science and Engineering, China West Normal University, Nanchong 637000, P. R. China)
(3: University of Chinese Academy of Sciences, Beijing 100049, P. R. China)
Abstract: Lake Gaoyou, Nansi, and Dongping are key connecting points on the east line of the South-to-North Water Diversion Project and play vital roles in the safety of water transfer. In this study, three-dimensional fluorescence spectroscopy coupled with parallel factor analysis (EEMs-PARAFAC) was used to analyze the optical characteristics of CDOM and the relationships between fluorescence components and water quality parameters in the three lakes in different hydrological seasons, and to unravel the sources and optical composition characteristics of CDOM. Three fluorescent components were obtained using parallel factor analysis (PARAFAC), including a terrestrial humic-like C1, a tryptophan-like C2 and a tyrosine-like C3. Upstream inflowing discharge have notable effects on the source and optical composition of CDOM in Lake Gaoyou with fluorescence intensity (Fmax) of C1 in the flood season is significantly higher than in the dry season (t-test, P < 0.01), and C1 is positively correlated with a(254) (R2=0.85, P < 0.01), indicating that terrestrial humic-like substances contributed primarily to the DOM pool in the lake. The contribution rate of C1 can reach 50%[FmaxC1/(FmaxC1 + FmaxC2 + FmaxC3)×100%]. Lake Gaoyou is greatly affected by the inflow water. Lake Dongping and Lake Nansi share similar source and optical composition of CDOM. The Fmax mean of C2 and C3 in Lake Dongping and Lake Nansi were significantly lower in the flood season than in the dry season (t-test, P < 0.01), indicating the two lakes have a higher autochthonous CDOM contribution during the dry season. Humic-like C1 in Lake Gaoyou can be used to trace the dynamics of dissolved organic carbon concentration, and the accumulation of humic-like substances may increase the concentration of total phosphorus, totoal nitrogen, and chlorophyll-a in the lake. However, the correlations between C1 and the main water quality parameters including humic-like C1 were poor in Lake Dongping and Lake Nansi, showing different CDOM optical characteristics from that of Lake Gaoyou.
Keywords: The South-to-North Water Diversion Project    Lake Gaoyou    Lake Nansi    Lake Dongping    chromophoric dissolved organic matter (CDOM)    parallel factor analysis (PARAFAC)    

南水北调东线南起扬州附近长江取水口,途径高邮湖、南四湖及东平湖等湖泊,将长江及沿线枢纽湖泊水源输移到京津冀及山东等地,上述3个湖泊在保障调水工程顺利开展中起到了不可忽视的重要作用,湖泊的水质状况也是决定东线调水工程安全的关键[1].研究发现大规模长途的调水也会改变调蓄湖泊的水环境以及原有生态结构,影响湖泊碳、氮、磷等生源物质的地球化学循环过程[2].近年来,由于经济发展和人口增多,导致东线调蓄湖泊及其周边河流部分水质发生恶化,对受水区饮用水安全产生威胁[3-5].东线工程大部分的输水渠道是利用现有河道或湖泊,为缺水城市提供生活用水、工业用水、环境用水等,因此有必要对工程沿线河道、湖泊的水质变化进行研究[6-7].

溶解性有机物质(dissolved organic matter,DOM)广泛存在于自然水体中,其来源复杂,种类繁多,过量的DOM会致使水体酸臭刺鼻,并且在水处理过程中通常能释放大量致癌物质,既污染处理设备,又会严重威胁人类健康[8].水体有色可溶有机物质(chromophoric DOM, CDOM)是DOM中能强烈吸收紫外和可见光的部分,因而通过其吸收光谱能在一定程度上揭示DOM结构组成特征.另外还有一部分物质能在短波激发下发出长于激发波长的荧光,这部分物质即为发荧光溶解性有机物(fluorescent DOM, FDOM)[9].近年来已有多位相关领域的研究者利用CDOM的光学特性及遥感反演等技术手段监测有机污染物浓度、来源及组成变化,相关研究主要针对富营养湖泊、海洋及河口等水域[10-11].许多研究者在运用三维荧光结合平行因子分析法(EEMs-PARAFAC)对CDOM进行半定量和定性的研究领域中有所成果. Shang等[12]强调了CDOM对研究水体DOM输入的重要性,并且加强了营养状态指数与CDOM来源组成特征之间的联系,有助于建立一种新的水库营养状态监测模式. Hu等[13]应用平行因子分析法对洪泽湖CDOM来源与组成特征进行分析,揭示了其水质状况及其影响因素. Coch等[14]通过研究CDOM光学特性来实现对北极河流的DOM的反演.

本研究对高邮湖、南四湖和东平湖在不同水文情境下CDOM的时空分布特征进行分析,探讨了高邮湖、南四湖和东平湖CDOM来源和组成特征,丰富了南水北调东线枢纽湖泊水质的研究资料,以期为进一步保障南水北调东线调水安全和制定管理方案提供参考依据.

1 材料与方法 1.1 样品采集与处理

图 1所示,在高邮湖、南四湖和东平湖分别布设7个(7个样点×2次观测)、15个(15个样点×2次观测)及6个(6个样点×2次观测)表层(0.5 m)水样采样点,于2018年4、7月进行野外样品采集.采集好的样品用酸洗过的聚氯乙烯瓶避光冷藏保存并及时送回实验室.先使用高温灼烧过(450℃烧4 h)的0.7 μm的Whatman GF/F玻璃纤维滤膜过滤,所得水样再通过0.22 μm Millipore滤膜过滤,滤后水样装入棕色玻璃瓶,并于4℃恒温冷藏保存,在5天内完成所有指标的监测分析.通过0.7 μm滤膜的水样用于测定溶解性有机碳(dissolved organic carbon, DOC)浓度;通过0.22 μm滤膜的水样用于测定CDOM吸收光谱和三维荧光光谱.

图 1 高邮湖、南四湖及东平湖采样点及流域来水及南水北调路线 Fig.1 Location of sampling sites in Lake Gaoyou, Lake Nansi and Lake Dongping
1.2 水文数据

本研究水文数据资料来自水利部淮河水利委员会(http://www.hrc.gov.cn/)和黄河水利委员会(http://www.yrcc.gov.cn/),包括2018年逐月淮河流域降雨量和2018年逐月东平湖蓄水量.

1.3 样品参数的测定 1.3.1 主要水质参数测定

采样结束当天取200~500 mL表层水通过高温灼烧过的Whatman GF/F滤膜,记录过滤体积,滤膜用铝箔包好冷冻保存,测定时先用90 %乙醇在80℃提取,然后采用分光光度法测定665 nm和750 nm处的吸光度值以计算出叶绿素a(Chl.a)浓度,总氮(TN)、总磷(TP)浓度的测定均先在120℃高温下消煮40 min,采用Shimadzu UV-2550PC UV-Vis测定[15-16].利用Shimadzu总有机碳分析(TOC-L)在680℃高温环境下采用NPOC扫吹模式测定DOC浓度[17].

1.3.2 紫外可见吸收光谱

CDOM的吸收光谱参数采用Shimazdu UV-2550 UV-Vis分光光度计测定.以Milli-Q水为空白对照,将水样装入5 cm比色皿中,在200~800 nm和间隔1 nm的设置下测量CDOM的吸光度.根据公式(1)计算对应波长的吸收系数[18]

$ a(\lambda ) = 2.303D(\lambda )/r $ (1)

式中,a(λ)指波长λ对应CDOM吸收系数(m-1),D(λ)指扣除700 nm处吸光度后在波长λ的吸光度,r指光程路径(m).

a(254)表示CDOM在254 nm处的吸收系数,用于表征CDOM丰度[19].比紫外吸收系数SUVA是a(254)与DOC浓度的比值,其值随着CDOM的腐殖化程度的增加而增大[20]. CDOM光谱斜率S275-295表示275~295 nm波长范围内拟合得到的指数函数的光谱斜率,能够在一定程度上反映CDOM组成,其值越小,反映CDOM的陆源腐殖酸信号越强.根据公式(2)计算光谱斜率S275-295[21]

$ a(\lambda ) = a\left( {{\lambda _0}} \right)\exp \left[ {S\left( {{\lambda _0} - \lambda } \right)} \right] $ (2)

式中,λ0表示参照波长440 nm,S表示光谱斜率.

1.3.3 三维荧光光谱测定

采用F-7000型荧光光度计(Hitachi公司)测定CDOM荧光激发发射光谱矩阵(excitation-emission matrices, EEMs).激发光谱范围在200~450 nm,间隔5 nm;发射光谱范围在250~600 nm,间隔1 nm.测得的三维荧光光谱先用超纯水进行拉曼散射校正,即扣除超纯水EEMs光谱,并以超纯水EEMs中350 nm激发波长和371~428 nm发射波长下的荧光强度积分值将所有EEMs定标为拉曼单位(Raman unit,R.U.);再采用drEEM工具包裁剪插值的方法进行瑞丽散射校正[22];内滤波效应采用相应激发发射波长处吸光度校正予以消除[23]. 1.3.4平行因子分析(PARAFAC)采用MATLAB R2015b的drEEM工具箱(ver.0.2.0)进行平行因子分析,共抽取56个(东平湖6个样点×2次观测,南四湖15个样点×2次观测,高邮湖7个样点×2次观测)EEMs矩阵进行运算,每个矩阵对应251个发射波长、45个激发波长.数据被剖分成6个随机子集,取3个子集用于建模,另外3个用于模型验证,每个EEMs子集均逐步从3个组分模型逐步到6个组分检验.本研究结果显示3个组分模型能很好地通过对半检验(split-half analysis)、随机初始化分析(random initialization analysis)及残差分析(residual analysis).最后以平行因子分析结果中每个荧光组分的最大荧光强度(Fmax)来表征荧光物质浓度和荧光组分强度[24].

1.4 数据处理

采用SPSS软件对数据进行皮尔逊相关性分析,数据统计与图表绘制采用Origin 8.5软件,采用MATLAB R2015b软件的drEEM工具箱进行平行因子分析建模.

2 结果与分析 2.1 水文特征

南四湖、高邮湖和东平湖老湖区(大汶河经老湖区输入东平湖)均属于淮河流域.水文数据表明,淮河流域1-4月和9-12月降雨量范围在16.0~58.2 mm,而5-8月降雨量范围在89.4~196.9 mm.东平湖2018年1-5月蓄水量在2.6亿~2.8亿m3/s,6-12月蓄水量在2.9亿~5.3亿m3/s.据此,本研究将2018年4月划为枯水期,2018年7月划为丰水期.

2.2 主要水质参数特征

丰水期东平湖TP、TN和Chl.a浓度显著高于枯水期(t-test, P < 0.01及P < 0.01).南四湖TN、TP、Chl.a(P < 0.01)和DOC (P < 0.05)浓度在丰水期时高于枯水期.高邮湖TP、TN和Chl.a浓度在丰水期均显著高于枯水期(t-test, P < 0.01),DOC浓度无显著差异.

表 1 不同季节之间3个湖泊主要水质参数均值差异性t检验结果 Tab. 1 Mean difference of main water quality parameters of three lakes in different seasons using t-test
2.3 CDOM组成来源及丰度的时空分布特征

表 2可以看出,东平湖的S275-295在丰水期显著大于枯水期(t-test, P < 0.05),而a(254)和SUVA在丰、枯水期无显著差异.丰水期东平湖a(254)和SUVA值在湖中部区域较大,出湖口和入湖口较低,S275-295值在出湖口最大.枯水期a(254)与丰水期相似,S275-295在入湖口较大,出湖口最低. SUVA变化规律与S275-295正相反(图 2e~f).南四湖不同水文情景下a(254)、S275-295和SUVA无显著差异,与东平湖相似.丰水期a(254)在不同湖区分布较一致,S275-295在下级湖南部小部分湖区较低,而SUVA值分布与S275-295相反,其值在下级湖泊较高.枯水期a(254)在上级入湖口最高,S275-295在上级湖较高,而在下级出湖口最低,SUVA与之相反(图 2g~l).高邮湖在丰水期的吸收系数a(254)、SUVA值均显著高于枯水期(t-test, P < 0.01),而S275-295显著低于枯水期(t-test, P < 0.01).丰水期a(254)值在高邮湖西南入湖区域最大,自西向东呈递减趋势,S275-295值在西南区域较低,而SUVA值在该湖西北和西南区域较高.枯水期a(254)、S275-295和SUVA分布较一致(图 2m~r).

表 2 CDOM主要特征参数在不同水文条件下的t检验结果 Tab. 2 Properties of the mean of the three fluorescent components and significance levels of difference between in different hydrological scenarios using t-test
图 2 东平湖丰、南四湖和高邮湖a(254)、S275-295和SUVA时空分布 ((a)~(f)为东平湖,(g)~(l)为南四湖,(m)~(r)为高邮湖) Fig.2 Spatial and temporal distribution of a(254), CDOM spectral slope S275-295 and specific ultraviolet absorption at 254 nm SUVA in Lake Dongping, Lake Nansi and Lake Gaoyou ((a)-(f) are Lake Dongping, (g)-(l) are Lake Nansi and (m)-(r) are Lake Gaoyou)
2.4 荧光组分特征 2.4.1 荧光组分分析

图 3是采用PARAFAC模型对东平湖、南四湖和高邮湖水样的三维荧光光谱矩阵进行解析和对半检验得出的3个荧光组分. 3个荧光组分模型可以很好地模拟三维荧光光谱集,最终确定3个组分分别陆源类腐殖质C1,类色氨酸C2和类酪氨酸C3.组分C1荧光光谱类具有陆生植物或土壤有机物质光谱特征,发射和激发波长分别为430、250 nm[25].组分C2荧光光谱通常与藻源、生活废水排放有关,为类蛋白质中的类色氨酸荧光物质,有1个发射波长在350 nm处,2个激发波长,即225和275 nm处[26].组分C3一般是藻源,或其他荧光组分在水体中经光化学、微生物矿化等作用的产物,其荧光光谱光谱(275 nm/310 nm)代表类蛋白质中的酪氨酸荧光物质[27].

2.4.2 荧光组分时空分布特征

表 3可知,丰水期东平湖3个组分荧光强度显著低于枯水期(t-test, P < 0.01),而且丰水期3个组分空间分布较一致(图 4a~f).与东平湖相同的是,南四湖组分C2、C3荧光强度在丰水期均显著低于枯水期(t-test, P < 0.01),且组分C2荧光强度在枯水期最高.不同水文情境下,组分C2、C3荧光强度均高于组分C1. 图 4g~j表明从上级湖区至下级湖区方向,组分C2、C3有递增趋势,而组分C1在不同水文情景下空间分布相似,且在出湖口较低.与东平湖、南四湖相反,高邮湖组分C1荧光强度在丰、枯水期高于两种类蛋白质物质,且组分C1、C2荧光强度显著高于枯水期(t-test, P < 0.01). 图 4mq表明丰水期高邮湖西北湖区组分C1、C3荧光强度均高于其他区域.枯水期3个组分在高邮湖空间分布较均匀(图 4n, p, r).

图 3 平行因子分析得到的3个荧光组分荧光光谱和对半检验结果 Fig.3 Fluorescent spectra of the three PARAFAC components (The three-component-model was well-validated using split-half validation procedure)
表 3 3个组分荧光强度在不同水文条件下的均值差异显著性水平t检验结果 Tab. 3 Properties of the mean of the three fluorescent components and significance levels of difference in different hydrological scenarios using t-test
图 4 东平湖、南四湖和高邮湖3种组分荧光强度时空分布((a)~(f)为东平湖,(g)~(l)为南四湖,(m)~(r)为高邮湖) Fig.4 Spatial and temporal distribution of fluorescence intensity of three components in Lake Dongping, Lake Nansi and Lake Gaoyou((a)-(f) are Lake Dongping, (g)-(l) are Lake Nansi and (m)-(r) are Lake Gaoyou)
2.5 荧光组分与主要水质参数相关性

东平湖和南四湖的CDOM吸收、荧光光谱以及水质参数在不同水文情景下和空间分布存在相似的规律,高邮湖与这2个湖泊存在明显的差异,因此将东平湖、南四湖数据合并进行相关性分析.由图 5图 6可以看出,TP、TN和Chl.a与高邮湖中类腐殖质荧光强度均有显著正相关性,类蛋白与Chl.a浓度呈负相关.东平湖、南四湖类腐殖质荧光强度与TP有较好的正相关性,类色氨酸荧光强度与TN呈负相关,两类蛋白组分与Chl.a、DOC也均呈负相关.高邮湖的类腐殖质荧光强度与a(254)、SUVA呈显著正相关,而南四湖和东平湖类腐殖质荧光强度与a(254)相关性较好.

图 5 3组荧光组分与主要水质参数的相关性分析 Fig.5 Correlations between the three PARAFAC components and main water quality parameters
图 6 3组荧光组分与荧光特征参数的相关性分析 Fig.6 Correlations between the three PARAFAC components and fluorescence characteristic parameter
3 讨论 3.1 水质参数与CDOM的来源组成的关系

CDOM荧光光谱测定能在一定程度上反映DOC的来源,与李奕洁等[28]的研究相同,不同水文情境下高邮湖DOC浓度与类腐殖质荧光强度呈显著正相关,与两个蛋白组分荧光强度相关性较差,这意味着类腐殖质是高邮湖DOC主要组成部分.这是由于高邮湖位于洪泽湖下游,为典型过水型湖泊,水力滞留时间短,该湖CDOM和DOC主要来自上游淮河流域降水径流等冲刷的土壤有机质输入.然而南四湖和东平湖类腐殖质与DOC相关性较差,两类蛋白荧光强度与DOC呈负相关,而DOC在枯水期较低,表明两湖泊在枯水期受流域内工农业污染以及点源污染的影响较大[29].江俊武等[30]研究结果显示Chl.a浓度较高,水体中类蛋白荧光强度也较高,然而也有研究者发现二者并无显著相关性[31-32],本研究3个湖泊中Chl.a浓度与两种类蛋白物质有负相关性,3个湖泊类蛋白组分荧光强度均高于丰水期. Mayer等[33]发现缅因州河口部分点位CDOM样品也有该现象,这意味着3个湖泊中两种类蛋白物质, 即类色氨酸和类酪氨酸并非主要来自浮游生物死亡降解.有研究表明城市生活污水通常携带强烈的类色氨酸及类酪氨酸等类蛋白荧光信号[34-35], 意味着3个湖泊两种类蛋白物质在春季(枯水期)较高可能与湖泊周边流域人类生产生活废水排入相关.而高邮湖类腐殖质与Chl.a浓度有较好的正相关性,表明了高邮湖中浮游植物的生长伴随着较高的陆源类腐殖质输入,丰水期Chl.a浓度、a(254)和类腐殖质荧光强度均高于枯水期可以进一步说明.同时,高邮湖的类腐殖质荧光强度与TN、TP有显著正相关也表明了陆源腐殖质的输入与氮磷元素的迁移转化密切相关,这与王书航等[36]的研究一致.

3.2 主要入湖河流对湖泊CDOM来源与组成的影响

一般情况下,内陆水体中CDOM主要来自陆源输入,并且陆源输入会携带大量的大分子有机物质进入水体[37].本研究结果表明,高邮湖CDOM丰度在河流入湖区域较高,自西向东有下降的趋势,S275-295值为相反的变化规律,亦即S275-295值自河口区向敞水区逐渐增大,这意味着陆源土壤有机质输入信号也逐渐减弱,入湖河流输入为高邮湖CDOM的主要贡献源,且CDOM向敞水区输移过程中一方面逐渐被湖水稀释,另一方面,微生物活动及光降解作用亦导致高邮湖CDOM逐渐被降解[38].类腐殖质和类酪氨酸荧光强度逐渐降低进一步印证上述结论.南四湖入湖河流主要经上级湖泊汇入,枯水期南四湖下级湖泊CDOM丰度高于上级湖泊.并且不同水文情景下,类蛋白组分荧光强度和a(254)在下级湖区较高,表明入湖河流对上级湖泊CDOM的影响较小,然而下级湖泊出现高值主要是受到山东枣庄、济宁、菏泽城市废水的影响,加上冬季来水量较低,稀释作用不明显,类蛋白组分在湖泊中较高[39].东平湖a(254)值在南部和湖中心区域较大,表明CDOM丰度也受入湖河流的影响,这与吕伟伟等[40]的研究结果一致.

3.3 不同水文情景对湖泊CDOM来源与组成的影响

高邮湖在丰水期其类腐殖质荧光强度较高,自西向东有递减趋势,这与a(254)的分布趋势一致,表明高邮湖CDOM在丰水期受陆源输入的影响较大,类腐殖质与a(254)、S275-295、SUVA有较好的相关性能进一步说明该现象.东平湖和南四湖3个组分荧光强度在枯水期均高于丰水期,但不同水文情景下3个荧光组分与a(254)、S275-295和SUVA相关性较差,相关分析结果也表明浮游植物不是CDOM的主要来源,根据姚昕等[11]的研究,表明这与东平湖沉积物再悬浮以及外源输入有关.东平湖丰水期TP、TN和Chl.a浓度均高于枯水期,这与该湖泊处于中富富营养化相关,张菊等[41]的研究也发现东平湖夏、秋季节会有一部分草和藻出现死亡现象,特别是菹草的腐烂降解会对TN有巨大的贡献.整体来看,南四湖枯水期上级湖北部区域CDOM荧光强度较低,下级湖区接纳的东线调水对湖泊自净能力有一定的提升作用,因此沿调水方向CDOM荧光强度减弱,这与赵世新等[42]对南四湖水质状况的研究结果相似.湖泊的营养状况、水生植物多样性以及底泥沉积物的释放等过程对CDOM的来源组成特征影响因素,因此仍需要进一步的研究[43].

4 结论

1) 高邮湖丰水期类腐殖质是其CDOM库的主要贡献者.枯水期东平湖和南四湖下级湖泊类蛋白组分受外源人类活动污染源排放的影响较大.

2) 不同水文情景对高邮湖CDOM荧光特征的影响最明显,丰水期CDOM以陆源输入为主.不同水文情景对东平湖和南四湖CDOM组成结构影响较小,类蛋白荧光强度在枯水期较高,藻类降解的作用贡献较小.

3) 高邮湖的类腐殖质荧光特征能较好地反演DOC,还能在一定程度上预测TN、TP和Chl.a水质参数的变化情况.而南四湖、东平湖CDOM荧光特征与主要水质参数相关性较差.

致谢: 感谢邹伟、徐轩、任浩宇、刘淼、李娜、张成英及邢晓晟等同志在野外与室内实验过程中给予的帮助.

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