环境科学  2019, Vol. 40 Issue (7): 3018-3029   PDF    
南水北调东线中游枢纽湖泊有色可溶性有机物来源组成特征
张柳青1,2, 彭凯2,3, 周蕾2,3, 石玉2, 李元鹏2, 周永强2, 龚志军2, 张运林2, 杨艳1     
1. 西华师范大学环境科学与工程学院, 南充 637000;
2. 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;
3. 中国科学院大学, 北京 100049
摘要: 运用三维荧光光谱(excitation-emission matrices,EEMs)与平行因子分析模型(parallel factor analysis,PARAFAC)技术手段对南水北调东线枢纽湖泊洪泽湖、骆马湖两个水体中CDOM的来源组成特征进行分析.结果表明:①解析出两湖泊均得到3个荧光组分,陆源类腐殖质C1、类色氨酸C2和类酪氨酸C3.②两湖泊3种组分荧光强度在入湖河口附近明显高于其他水域,且丰水季节3种组分荧光强度均显著大于枯水季节(t-test,P < 0.01),其中陆源类腐殖质C1的荧光强度在丰水期最大.表明两湖水体CDOM来源与组成受上游水系来水量和水文过程的影响较大,尤其是陆源类腐殖质浓度的高低.③相关性分析得出,陆源类腐殖质C1与DOC浓度、吸收系数a(254)有极显著相关性(r2=0.60,P < 0.01;r2=0.88,P < 0.01),相关性高于其余两种组分,表明陆源类腐殖质为CDOM的主要来源.另外,陆源类腐殖质C1与SUVA、S275-295IC:IT具有很好的相关性(r2=0.49,P < 0.01;r2=0.61,P < 0.01;r2=0.93,P < 0.01),进一步说明了两湖泊CDOM来源与组成受陆源影响较大.洪泽湖、骆马湖CDOM来源与组成受到不同水文情景和入湖河流的影响,应加强丰水期对入湖河流的水质管理.
关键词: 南水北调      洪泽湖      骆马湖      有色可溶性有机物      平行因子分析     
Characterizing Chromophoric Dissolved Organic Matter in Key Lakes in the Middle Reaches of the East Route of the South-North Water Diversion Project
ZHANG Liu-qing1,2 , PENG Kai2,3 , ZHOU Lei2,3 , SHI Yu2 , LI Yuan-peng2 , ZHOU Yong-qiang2 , GONG Zhi-jun2 , ZHANG Yun-lin2 , YANG Yan1     
1. College of Environment Science and Engineering, China West Normal University, Nanchong 637000, China;
2. State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;
3. University of Chinese Academy of Sciences, Beijing 100049, China
Abstract: Lake Hongze and Lake Luoma are two key lakes located in the middle reaches of the east line of the South-to-North Water Diversion Project. We attempted to unravel the sources and optical composition of CDOM for samples collected from these lakes using excitation-emission matrices (EEMs) and parallel factor analysis (PARAFAC). ① Three fluorescent components were obtained using PARAFAC, including a terrestrial humic-like C1, a tryptophan-like C2, and a tyrosine-like C3. The sources and optical composition of CDOM in the two lakes were, to a large extent, affected by upstream inflow. ② Specifically, fluorescence intensity (Fmax) of the three components C1-C3 in the inflowing river mouths of the two lakes was notably higher than in the other lake regions, and Fmax of the three components during the flood season was significantly higher than during the dry season (t-test, P < 0.01). During the flood season, the fluorescence intensity of the terrestrial humic-like component was the highest. This indicates that the source and composition of CDOM in the two lakes are greatly affected by the inflow from the upstream water system, and that the hydrological processes control the abundance and sources of CDOM, especially the terrestrial humic-like C1.③ Significant positive relationships were found between the terrestrial humic-like C1 and the DOC concentrations and CDOM absorption a(254) (r2=0.60, P < 0.01; r2=0.88, P < 0.01), and the correlation was higher than the other two components. This indicated that the terrestrial humic-like component was the main source of CDOM. In addition, the terrestrial humic-like C1 had a significant positive correlation with SUVA, S275-295, and the integration ratio of the fluorescence peak C to peak T (IC:IT) (r2=0.49, P < 0.01; r2=0.61, P < 0.01; r2=0.93, P < 0.01). It is further revealed that the source and composition of CDOM in the two lakes are greatly affected by land sources. This study reveals the response of CDOM source and composition in Lake Hongze and Lake Luoma to different hydrological scenarios and water transfer processes. Based on these results, the water quality management of the rivers entering the lake should be strengthened during the flood season.
Key words: South-North Water Diversion Project      Lake Hongze      Lake Luoma      chromophoric dissolved organic matter (CDOM)      parallel factor analysis (PARAFAC)     

南水北调工程是我国战略性水利工程, 关系到国计民生的长远发展, 该工程分为东、中、西三条线路, 旨在解决我国北方, 尤其是京、津、冀缺水问题[1].其东线工程起点位于江苏省扬州附近的长江干流, 通过京杭大运河以及与之平行的河道输水, 连通高邮湖、洪泽湖、骆马湖、南四湖等湖泊作为调蓄湖泊.洪泽湖和骆马湖同属于淮河水系淡水湖泊, 物产丰富, 是重要的水源地, 同时也是南水北调东线工程重要枢纽, 其水质关系到淮河流域经济带的可持续性发展以及南水北调的水质安全[2~5].近年来, 由于流域经济的快速发展, 洪泽湖和骆马湖水质受到人类活动以及大规模调水的影响, 各种来源的污染物排到放湖泊, 导致水体中溶解性有机物(dissolved organic matter, DOM)浓度升高且来源更为复杂.姚昕等[6]和邢友华等[7]对东平湖的研究发现其主要入湖河流携带大量的工业废水、生活污水, 加上农田径流、水产养殖等污染物的输入, 致使东平湖水体富营养化和有机污染的加重.另外, 水体交换过程导致部分DOM经生物和光化学过程不断矿化, 而难于降解的DOM继续迁移, 对相连的湖泊水体造成一定的影响, 还会影响局地碳循环过程[8~10].

天然水体中存在的DOM是生物圈中最大的有机碳库, 在全球碳循环中起重要作用[9]. DOM是由富里酸、腐殖质、脂肪族和芳烃合物等一系列复杂的有机物质组成, 高浓度的DOM酸臭刺鼻, 在水处理过程中通常能释放大量致癌物质, 不仅污染处理设备, 还会严重威胁人类健康[11].有色可溶性有机物质(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浓度和组成[12]. CDOM化学结构复杂, 一部分功能基团能与水体中的有机污染物发生相互作用, 从而影响它们的迁移转化和生物可利用性等, 同时CDOM还能作为水质状况的监测指标[13].

三维荧光光谱-平行因子分析法结合解析出CDOM组分的方法已经被广泛运用到各类水体中, 可有效地揭示CDOM来源、组成及迁移转化途径[14], 施坤等[15]对比分析了太湖、巢湖水体CDOM吸收特性和组成的异同, 周倩倩等[16]运用三维荧光-平行因子分析对舟山渔场CDOM的分布特征进行了研究, 但是对洪泽湖和骆马湖的水质的研究较少.本文基于洪泽湖、骆马湖CDOM吸收和荧光变化特征, 探究南水北调工程枢纽湖泊CDOM的来源组成及潜在驱动机制, 通过进一步丰富对洪泽湖和骆马湖水体CDOM的研究资料, 弄清外源输入CDOM来源和组成结构特征, 以期为保证南水北调工程良好可持续地开展以及制定有效的保护措施提供参考依据.

1 材料与方法 1.1 样品采集与处理

在洪泽湖和骆马湖分别均匀布设10个表层水样采样点(图 1), 在2017年的9、12月, 2018年4月对洪泽湖, 并在2017年的9、12月, 2018年的4、6、7月对骆马湖进行样品采集, 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0.70 μm孔径的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, 滤后水样装入棕色瓶并于4℃恒温冷藏保存, 通常在5 d内完成所有测试分析.通过0.70 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 洪泽湖和骆马湖采样点及流域水文控制站位置 Fig. 1 Location of sampling sites in Lake Hongze and Lake Luoma and hydrological gauging stations in the two lake watersheds

1.2 水文数据

本研究收集的水文资料来自于水利部淮河水利委员会(http://www.hrc.gov.cn/)、中国河流泥沙公报, 包括2014~2017年淮河、沂河两个控制站(分别为蚌埠和临沂)的月均径流量数据、2008~2016年洪泽湖、骆马湖年径流量和蓄水量数据以及引江济淮调水量数据.

1.3 样品参数测定 1.3.1 紫外-可见吸收光谱及DOC的测定

采用Shimazdu UV-2550 UV-Vis分光光度计测定CDOM的吸收光谱, 用5 cm比色皿, 以Milli-Q水为空白对照, 在200~800 nm和间隔1 nm的设置下测量CDOM的吸光度.扣除700 nm吸光度以扣除潜在散射效应, 而后根据公式(1)计算对应波长的吸收系数[17]:

(1)

式中, a(λ)表示波长λ对应CDOM吸收系数(m-1), D(λ)表示扣除700 nm处吸光度在波长λ的吸光度, r指光程路径(m).在本研究使用特征波长吸收系数a(254)、比紫外吸光系数SUVA和光谱斜率S275-295等吸收光谱指标表征CDOM丰度、来源和组成.

a(254)指CDOM在254 nm处的吸收系数.比紫外吸光系数SUVA是a(254)与DOC浓度的比值, 能够指示水体中包括芳香族化合物在内的具有不饱和碳碳键的化合物的浓度变化, 该指标值越高, 陆源类腐殖质信号越强[18]. 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的陆源腐殖程度越高.根据公式(2)计算光谱斜率S275-295[19]

(2)

式中, λ0表示参照波长440 nm, S表示光谱斜率.

DOC浓度采用岛津总有机碳分析仪(TOC-L)在高温(680℃)环境下采用NPOC扫吹模式进行测定[20].

1.3.2 三维荧光光谱测定

CDOM荧光激发-发射光谱矩阵(excitation-emission matrices, EEMs)采用F-7000型荧光光度计(Hitachi公司)测定, 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进行水拉曼散射校正, 即扣除超纯水(Milli-Q)空白EEMs, 并以超纯水EEMs中350nm下的荧光强度将所有EEMs定标为拉曼单位(Raman unit, R. U.)[21]; 再采用MATLAB软件中的drEEM工具包通过切除及插值的方法进行瑞利散射校正; 内滤波效应采用每个样品EEMs激发发射波长处相对应的吸光度进行校正[22, 23].荧光峰C峰与T峰积分比值IC:IT能很好地表征陆源类腐殖质荧光峰信号与内源类色氨酸荧光峰信号之间的比值差异, 能有效揭示CDOM来源组成特征, 尤其是表征陆源类腐殖质输入信号强弱[24].

1.3.3 平行因子分析(PARAFAC)

平行因子分析(PARAFAC)采用交替最小二乘原理的迭代型三维数阵分解算法, 将三维荧光数据解析为若干个具有唯一对应发射波长极值的荧光组分[14, 25~27].采用MATLAB R2015b的drEEM工具箱(ver.0.2.0)进行平行因子分析, 共选取77个(洪泽湖30个, 骆马湖47个)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子集均从3个组分模型逐步到6个组分检验.结果表明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).将平行因子分析结果中每个荧光组分的最大荧光强度(Fmax)作为各类荧光物质浓度和荧光组分强度的表征[28].

1.4 数据处理

使用SPSS进行皮尔逊相关性分析, 图表数据统计与数据绘制采用Origin 8.5, ArcGIS 10.2软件绘制采样点布设图及CDOM吸收、荧光参数插值图. EEMs光谱的平行因子分析采用MATLAB R2015b软件的drEEM工具箱进行CDOM吸收光谱的拟合和相关指标的计算.

2 结果与分析 2.1 洪泽湖和骆马湖水文特征

淮河和沂河分别是洪泽湖、骆马湖的主要来水河流, 图 2(a)分别是淮河蚌埠站和沂河临沂站2014~2017年监测的月均径流量.整体来看, 两湖泊在丰水期的来水量均大于枯水期, 且洪泽湖接纳淮河来水量远高于骆马湖接纳沂河的来水量.沂河枯水期时间长于淮河, 除7、8月水量增高外, 其余时间径流量基本相同.淮河月径流量充沛, 相对而言沂河丰、枯水期更替现象更为明显.图 2(b)~2(c)可以看出, 洪泽湖年蓄水量和主要来水河流年径流量均大于骆马湖, 除了2014~2016年外, 两湖泊主要入湖河流淮河和沂河年径流量大于两湖泊的年蓄水量.每年引江济淮年调水量也低于洪泽湖主要入湖河流年径流量.

(a) 2014~2017年蚌埠站和临沂站平均月均径流量情况, (b) 2008~2016年洪泽湖、骆马湖年蓄水量情况, (c) 2008~2016年引江济淮调水量和蚌埠站、临沂站年径流量情况 图 2 洪泽湖和骆马湖月均径流量、年蓄水量、年径流量以及引江济淮年调水量情况 Fig. 2 Monthly mean runoff, annual storage and yearly mean runoff in Lake Hongze and Lake Luoma, and the amount of water transferred from the River Yangtze to the River Huaihe

2.2 CDOM光谱特性及DOC的时空特征

表 1可知, 洪泽湖丰水期SUVA(t-test, P < 0.05)、DOC浓度和a(254)均显著高于枯水期(t-test, P < 0.01).图 3(a)~3(c)3(j)~3(l)显示, 丰水期洪泽湖DOC浓度、吸收系数a(254)在西南区域, 即新汴河、淮河等入湖周围较高, 枯水期(2018年4月)在东南区域DOC浓度和a(254)均小于其他区域, CDOM浓度降低.从图 3(d)~3(e)看出, 丰水期(2017年9月)和枯水期(2017年12月)主要是大分子有机物质较多, 并且CDOM腐殖化程度较高. S275-295在丰、枯水期无显著差异, CDOM可能具有同源性.从图 3(g)~3(i)可以看出, S275-295在丰、枯水期, 总是北部小片水滞留区域较大, 从入湖口自水流方向较小, 表明入湖河流为洪泽湖CDOM的主要来源.丰水期SUVA值在淮河入湖处及周围区域高于其他区域, 在枯水期(2017年12月), 新汴河、徐洪河对洪泽湖SUVA影响增加.

表 1 丰水期和枯水期DOC浓度、SUVA、S275-295a(254)均值及差异显著性水平t检验结果 Table 1 Properties of the means of DOC, SUVA, S275-295, and a(254) during the flood season and the dry season, and significance levels of difference between seasons using a t-test

图 3 洪泽湖在不同水文情景下DOC、SUVA、S275-295a(254)空间分布 Fig. 3 Spatial variabilities of dissolved organic carbon(DOC), ratio of specific ultraviolet absorption at 254 nm to DOC concentration(SUVA), CDOM spectral slope S275-295, and CDOM absorption coefficient a(254) in Lake Hongze under different hydrological scenarios

骆马湖DOC浓度和a(254)在丰水期显著高于枯水期(P < 0.01), 而丰水期和枯水期的SUVA和S275-295值无显著差异.图 4(a)~4(e)可以看出, 丰水期骆马湖上游水系携带大量陆源CDOM输入, 且DOC浓度自北部入湖区域向南部敞水区逐渐递减. a(254)在丰水期和枯水期分布与DOC相似[见图 4(p)~4(t)]. SUVA丰、枯水期表现为自西北入湖河口向东南下游敞水区逐次递减的趋势, 这在丰水期(7、9月)表现得尤为显著, 表明骆马湖CDOM主要是河流输入.

图 4 骆马湖在不同水文情景下DOC、SUVA、S275-295a(254)空间分布 Fig. 4 Spatial variabilities of dissolved organic carbon (DOC), ratio of specific ultraviolet absorption at 254 nm to DOC concentration(SUVA), CDOM spectral slope S275-295, and CDOM absorption coefficient a(254) in Lake Luoma under different hydrological scenarios

2.3 荧光特征 2.3.1 CDOM的荧光组分特征分析

采用PARAFAC模型对洪泽湖和骆马湖水样的三维荧光光谱矩阵进行解析和对半检验, 最终确定3个荧光组分模型可以很好地模拟三维荧光光谱集, 根据相关文献可以确定3个组分分别为:C1陆源类腐殖质、C2类色氨酸和C3类酪氨酸(图 5)[29].组分腐殖质C1荧光光谱类具有陆生植物或土壤有机物质光谱特征(250/410 nm)[30], 说明两个湖泊中CDOM外源输入的主要信号为陆源类腐殖质, 一般为土壤淋溶随河流携入湖泊. C2组分荧光光谱有一个发射波长在330 nm处, 两个激发波长, 即230 nm和285 nm处, 为类蛋白质中的类色氨酸荧光物质, 通常为藻源或者生活废水伴生CDOM[31]. C3组分荧光光谱光谱(275/315 nm)代表类蛋白质中的酪氨酸荧光物质, 可能为藻源, 抑或为其他荧光组分经光化学或微生物矿化过程后的产物[32].

图 5 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. 5 Fluorescence spectra of the three PARAFAC components and the three-component-model was well validated using split-half validation

2.3.2 CDOM荧光组分时空分布特征

表 2可知, 洪泽湖3组分荧光强度在丰水期均显著高于枯水期(t-test, P < 0.01), 且组分C1荧光强度均高于其余两组分.丰水期(2017年9月)组分C1荧光强度在西南区域高于东北区域, 夏秋交替季节雨水量大, 受入湖河流的影响较大.枯水期(2017年12月和2018年4月)组分C1在洪泽湖分布比较均匀, 仅北边小片区域较低.枯水期(2017年12月)的组分C2和C3荧光强度在东南、西南区域浓度低于其余区域.此外, 枯水期组分C3在洪泽湖北部区域荧光信号较强(图 6).

表 2 丰水期和枯水期3种荧光组分荧光强度均值及差异显著性水平t检验结果 Table 2 Properties of the means of the three components during the flood season and the dry season, and significance levels of difference between these two seasons using a t-test

图 6 洪泽湖3种荧光组分在不同水文情景下的空间分布 Fig. 6 Spatial variations of the three components in Lake Hongze under different hydrological scenarios

骆马湖丰水期3种荧光组分荧光强度均显著高于枯水期(t-teat, P < 0.01), 类色氨酸C2在丰水期最高, 枯水期陆源类腐殖质C1荧光强度最低.整体来看, 3种荧光物质呈由北到南逐渐降低的趋势(图 7).从图 7(c)~7(e)可以看出组分C1荧光强度空间分布均匀, 同时组分C2在枯水期(2018年4月)和丰水期(2018年6月、7月)空间分布相似, 入湖口较高, 随后逐渐降低.丰水期(2018年6、7月)组分C3高于其余两种荧光物质, 随梅雨季节后, 气温升高, 湖水发生轻微藻华, 从而导致其浓度的升高.

图 7 骆马湖3种荧光组分在不同水文情景下的空间分布 Fig. 7 Spatial variations of the three components in Lake Luoma under different hydrological scenarios

2.3.3 相关性分析

图 89表 3可知, DOC浓度、吸收系数a(254)与3种组分荧光强度均有显著正相关性, 其中陆源腐殖质C1与a(254)的相关性最好(r2= 0.88, P < 0.01), 是CDOM组成的主要组分.而DOC浓度与3种组分荧光强度的比例的相关性弱.S275-295与C1、C3组分荧光强度的比例有显著相关性(r2=0.61, P < 0.01;r2=0.82, P < 0.01)、SUVA和IC:IT与3种组分荧光强度的比例显著相关, 其中陆源类腐殖质C1荧光强度的比例与IC:IT的相关性最好(r2=0.93, P < 0.01), 除了类色氨酸C2与S275-295和SUVA均无显著相关性外, 其余两种组分荧光强度与S275-295、SUVA和IC:IT均有显著相关性, SUVA和IC:IT能很好地反映两湖泊CDOM的组成特征.

图 8 SUVA、S275-295IC:IT和3个组分荧光强度百分比的相关性分析 Fig. 8 Relationships between of percentage of the three components and SUVA, S275-295, and IC:IT

图 9 DOC、a(254)和3个组分荧光强度的相关性分析 Fig. 9 Correlations between the three components, DOC, and a(254)

表 3 DOC、S275-295、SUVA、a(254)、IC:IT与3个荧光组分的皮尔逊相关系数1) Table 3 Pearson's correlation coefficient between DOC, S275-295, SUVA, a(254), IC:IT, and the three components

3 讨论 3.1 入湖河流对洪泽湖、骆马湖CDOM来源及组成的影响

洪泽湖是淮河中游湖泊, 主要入湖河流有淮河、新沂河、徐洪河等, 骆马湖南面与洪泽湖相连, 京杭运河、沂河为其主要入湖河流[33, 34].有研究结果显示, 洪泽湖和骆马湖CDOM的来源与组成受入湖河流影响较大,这可能是由于两湖泊均是淮河水系且夏季受东南季风的影响, 湖水主要补给形式为降水径流[35], 因此入湖河流水质主要决定湖泊CDOM来源与组成, 从陆源类腐殖质的空间分布情况也能印证.陆源类腐殖质与SUVA、S275-295IC:IT具有很好的相关性, 进一步说明了陆源类腐殖质占主导地位.入湖河流携带CDOM进入湖泊后随迁移过程发生光降解或微生物降解, 这可能是导致CDOM相对分子质量逐渐下降的原因[36], 这一规律在骆马湖水体中更为明显, 而洪泽湖北部区域S275-295总高于其余区域, 该区域主要为小分子有机物质, 受其入湖河流的影响较小.从SUVA的分布来看, 也能发现其腐殖化程度低于其余区域.

3.2 不同水文情景对洪泽湖、骆马湖CDOM来源及组成的影响

骆马湖水体中陆源类腐殖质和两种类蛋白物质荧光强度的空间分布与洪泽湖有类似的季节性变化, 丰水期3种荧光物质浓度明显高于枯水期, 且3种荧光物质浓度与DOC浓度和a(254)有显著正相关性, 表明两湖泊CDOM的来源可能存在同源性, 这与两水体中CDOM主要贡献为陆源类腐殖质的研究结果相符合.两湖通过徐洪河等河道连通, 水体的交互作用可能也是其CDOM荧光组分在不同水文情景下分布相似的原因.洪泽湖陆源腐殖质C1高于骆马湖, 这可能是由于丰水期洪泽湖月径流量大于骆马湖, 且接纳淮河来水量较大, 受陆源影响明显[5].洪泽湖3种组分在西南区域(即入湖河流区域)高于其余区域, 丰水期尤为明显, 骆马湖与洪泽湖有类似的规律, 进一步表明了入湖河流对两湖泊CDOM的贡献较大.

然而, 两湖泊类腐殖质和类蛋白物质含量在枯水期降低, 这是由于枯水期温度较低, 藻类等生长缓慢, 内源释放较低.相反, 丰水期温度升高, 光照增强, 加快了藻类的生长和大分子物质光降解作用, 导致类色氨酸和类酪氨酸含量明显增高, 与Yao[37]和刘兆冰[38]的研究结果相似, 此现象在洪泽湖北部水滞留区域尤为明显, 这可能是由于水体交换速率较低, 促进CDOM的矿化, 亦或是内源贡献较高.骆马湖丰、枯水期SUVA、S275-295无显著差异, 可能是由于其入湖河流水量及蓄水量较低, CDOM组成结构受水文交替的影响较小.但骆马湖9月CDOM相对分子质量较低, 沿河流入湖的方向腐殖化程度降低, 表明夏季骆马湖内源补给较为明显, 这是因为夏季温度升高, 浮游植物生长速度加快, 其胞外分泌物和残体降解过程中可能释放大量内源CDOM[39, 40].洪泽湖在丰水期CDOM腐殖化程度高于枯水期, 但相对分子质量与其无显著差异, 表明CDOM组成结构相似, 一方面可能由于秋冬季节光照和微生物分解能力降低, CDOM内源补给水平较低, 另一方面由于陆源类腐殖质输入高[41].

3.3 南水北调工程对洪泽湖、骆马湖CDOM来源及组成的影响

南水北调是大规模的跨流域调水工程, 调水过程必定会引起调入区和调出区的水体环境, 如泥沙、水生植物和生态环境等方面的变化[42].本研究结果表明了两湖泊水体中CDOM的来源、组成结构以及空间分布情况很相似, 且骆马湖陆源类腐殖质低于洪泽湖, 这可能是旱季调水经过洪泽湖后再进入骆马湖, CDOM同时受洪泽湖和调水影响, 矿化作用小于洪泽湖[17].本研究也显示了两湖泊枯水期, 即调水期间, DOC浓度和吸收系数a(254)值低于丰水期, 可能是由于调水水质较好, 起到一定的稀释作用, 亦或是水交换过程改变了湖泊的环境, 导致CDOM组成发生变化[43, 44].进一步影响水体中CDOM来源与组成特征.骆马湖在调水(枯水期)和非调水期间其SUVA和 S275-295值均无显著差异, 其CDOM结构组成受调水的影响较小.此外, 有研究发现从长江调水过程增大了湖泊富营养化的可能性[33, 45], 改变了碳氮比, 影响水体植物的生长发育, 已有研究表明, 当植物生长过程中发生氮限制, 其会释放一部分初级生产力到水体中[46, 47].

4 结论

(1) 运用PARAFAC解析洪泽湖、骆马湖CDOM的三维荧光光谱, 得出陆源类腐殖质(C1)、内源类色氨酸(C2)和类酪氨酸(C3)这3种荧光组分.丰水期入湖河流输入是两湖泊CDOM的主要贡献源, 增加了骆马湖CDOM的内源贡献.不同水文情景下洪泽湖CDOM陆源类腐殖质占主导地位.

(2) 南水北调东线调水对湖泊CDOM来源及组成特征的影响小于入湖河流, 但是在一定程度上增强了输水通道陆源类腐殖质输入, 尤其是洪泽湖.调水期间两湖泊CDOM降低, 对湖泊水质提高有一定的促进作用.

(3) 洪泽湖和骆马湖水质受入湖河流的影响较大, 为改善和保证南水北调东线调水质量, 可在入湖口种植水生植物或设网拦蓄形成缓冲区域, 达到截留和转化外源污染物的目的.从入湖河道着手, 尤其在丰水期, 加强对流域中河流污染源排放的控制管理.

致谢: 感谢邹伟、邢晓晟、夏忠、陈业、刘宁超和郭锐等同志在野外和实验过程中提供的帮助.
参考文献
[1] Office of the South-to-North Water Diversion Project Construction Committee, State Council, P RC. The south-to-north water diversion project[J]. Engineering, 2016, 2(3): 265-267. DOI:10.1016/J.ENG.2016.03.022
[2] Ma Y J, Li X Y, Wilson M, et al. Water loss by evaporation from China's South-North Water Transfer Project[J]. Ecological Engineering, 2016, 95: 206-215. DOI:10.1016/j.ecoleng.2016.06.086
[3] 张晓松, 曹命凯, 丁艳霞, 等. 南水北调东线典型受水区降雨特征分析[J]. 南水北调与水利科技, 2018, 16(3): 59-64.
Zhang X S, Cao M K, Ding Y X, et al. Rainfall characteristics in typical water-receiving area of East Route of South-to-North Water Diversion Project[J]. South-to-North Water Transfers and Water Science & Technology, 2018, 16(3): 59-64.
[4] Yang Y, Yin L, Zhang Q Z. Quantity versus quality in China's South-to-North Water Diversion Project:A system dynamics analysis[J]. Water, 2015, 7(5): 2142-2160.
[5] Yin Y X, Chen Y, Yu S T, et al. Maximum water level of Hongze Lake and its relationship with natural changes and human activities from 1736 to 2005[J]. Quaternary International, 2013, 304: 85-94. DOI:10.1016/j.quaint.2012.12.042
[6] 姚昕, 孙将凌, 董杰, 等. 东平湖CDOM的光谱吸收特征及环境指示意义[J]. 光谱学与谱分析, 2016, 36(10): 3232-3236.
Yao X, Sun J L, Dong J, et al. Absorption characteristics and environmental significance of dissolved organic matter in Lake Dongping[J]. Spectroscopy and Spectral Analysis, 2016, 36(10): 3232-3236.
[7] 邢友华, 董洁, 李晓晨, 等. 东平湖表层沉积物中磷的吸附容量及潜在释放风险分析[J]. 农业环境科学学报, 2010, 29(4): 746-751.
Xing Y H, Dong J, Li X C, et al. Phosphorus sorption capacity of the surfical sediment in the Dongping Lake and risk assessment of potential phosphorus release[J]. Journal of Agro-Environment Science, 2010, 29(4): 746-751.
[8] Xu J, Wang Y Q, Gao D, et al. Optical properties and spatial distribution of chromophoric dissolved organic matter (CDOM) in Poyang Lake, China[J]. Journal of Great Lakes Research, 2017, 43(4): 700-709. DOI:10.1016/j.jglr.2017.06.002
[9] Yu M, Wang C R, Liu Y, et al. Sustainability of mega water diversion projects:experience and lessons from China[J]. Science of the Total Environment, 2018, 619-620: 721-731. DOI:10.1016/j.scitotenv.2017.11.006
[10] Shao T T, Song K S, Du J, et al. Seasonal variations of CDOM optical properties in rivers across the Liaohe Delta[J]. Wetlands, 2016, 36(S1): 181-192. DOI:10.1007/s13157-014-0622-2
[11] Wang M, Chen Y G. Generation and characterization of DOM in wastewater treatment processes[J]. Chemosphere, 2018, 201: 96-109. DOI:10.1016/j.chemosphere.2018.02.124
[12] Song K S, Li L, Tedesco L, et al. Spectral characterization of colored dissolved organic matter for productive inland waters and its source analysis[J]. Chinese Geographical Science, 2015, 25(3): 295-308. DOI:10.1007/s11769-014-0690-5
[13] Huang M, Li Z W, Luo N L, et al. Application potential of biochar in environment:Insight from degradation of biochar-derived DOM and complexation of DOM with heavy metals[J]. Science of the Total Environment, 2019, 646: 220-228. DOI:10.1016/j.scitotenv.2018.07.282
[14] Murphy K R, Stedmon C A, Graeber D, et al. Fluorescence spectroscopy and multi-way techniques. PARAFAC[J]. Analytical Methods, 2013, 5(23): 6557-6566. DOI:10.1039/c3ay41160e
[15] 施坤, 李云梅, 王桥, 等. 太湖、巢湖水体CDOM吸收特性和组成的异同[J]. 环境科学, 2010, 31(5): 1183-1191.
Shi K, Li Y M, Wang Q, et al. Similarities and differences in absorption characteristics and composition of CDOM between Taihu Lake and Chaohu Lake[J]. Environment Science, 2010, 31(5): 1183-1191.
[16] 周倩倩, 苏荣国, 白莹, 等. 舟山渔场有色溶解有机物(CDOM)的三维荧光-平行因子分析[J]. 环境科学, 2015, 36(1): 163-171.
Zhou Q Q, Su R G, Bai Y, et al. Characterization of chromophoric dissolved organic matter (CDOM) in Zhoushan Fishery using excitation-emission matrix spectroscopy (EEMs) and parallel factor analysis (PARAFAC)[J]. Environment Science, 2015, 36(1): 163-171.
[17] 刘笑菡, 张运林, 殷燕, 等. 三维荧光光谱及平行因子分析法在CDOM研究中的应用[J]. 海洋湖沼通报, 2012(3): 133-145.
Liu X H, Zhang Y L, Yin Y, et al. Application of three-dimensional fluorescence spectroscopy and parallel factor analysis in CDOM study[J]. Transactions of Oceanology and Limnology, 2012(3): 133-145.
[18] Singh S, D'Sa E J, Swenson E M. Chromophoric dissolved organic matter (CDOM) variability in Barataria Basin using excitation-emission matrix (EEM) fluorescence and parallel factor analysis (PARAFAC)[J]. Science of the Total Environment, 2010, 408(16): 3211-3222. DOI:10.1016/j.scitotenv.2010.03.044
[19] Fichot C G, Benner R. The spectral slope coefficient of chromophoric dissolved organic matter (S275-295) as a tracer of terrigenous dissolved organic carbon in river-influenced ocean margins[J]. Limnology and Oceanography, 2012, 57(5): 1453-1466. DOI:10.4319/lo.2012.57.5.1453
[20] Wang Y, Zhang D, Shen Z Y, et al. Characterization and spacial distribution variability of chromophoric dissolved organic matter (CDOM) in the Yangtze Estuary[J]. Chemosphere, 2014, 95: 353-362. DOI:10.1016/j.chemosphere.2013.09.044
[21] Lawaetz A J, Stedmon C A. Fluorescence intensity calibration using the Raman scatter peak of water[J]. Applied Spectroscopy, 2009, 63(8): 936-940. DOI:10.1366/000370209788964548
[22] Zepp R G, Sheldon W M, Moran M A. Dissolved organic fluorophores in southeastern US coastal waters:Correction method for eliminating Rayleigh and Raman scattering peaks in excitation-emission matrices[J]. Marine Chemistry, 2004, 89(1-4): 15-36. DOI:10.1016/j.marchem.2004.02.006
[23] Wang Z G, Cao J, Meng F G. Interactions between protein-like and humic-like components in dissolved organic matter revealed by fluorescence quenching[J]. Water Research, 2015, 68: 404-413. DOI:10.1016/j.watres.2014.10.024
[24] Zhao Y, Song K S, Wen Z D, et al. Evaluation of CDOM sources and their links with water quality in the lakes of Northeast China using fluorescence spectroscopy[J]. Journal of Hydrology, 2017, 550: 80-91. DOI:10.1016/j.jhydrol.2017.04.027
[25] Dainard P G, Guéguen C. Distribution of PARAFAC modeled CDOM components in the North Pacific Ocean, Bering, Chukchi and Beaufort Seas[J]. Marine Chemistry, 2013, 157: 216-223. DOI:10.1016/j.marchem.2013.10.007
[26] Stedmon C A, Markager S, Bro R. Tracing dissolved organic matter in aquatic environments using a new approach to fluorescence spectroscopy[J]. Marine Chemistry, 2003, 82(3-4): 239-254. DOI:10.1016/S0304-4203(03)00072-0
[27] Stedmon C A, Bro R. Characterizing dissolved organic matter fluorescence with parallel factor analysis:A tutorial[J]. Limnology and Oceanography:Methods, 2008, 6(11): 572-579. DOI:10.4319/lom.2008.6.572
[28] Osburn C L, Wigdahl C R, Fritz S C, et al. Dissolved organic matter composition and photoreactivity in prairie lakes of the U. S. Great Plains[J]. Limnology and Oceanography, 2011, 56(6): 2371-2390. DOI:10.4319/lo.2011.56.6.2371
[29] Yamashita Y, Jaffé R, Maie N, et al. Assessing the dynamics of dissolved organic matter (DOM) in coastal environments by excitation emission matrix fluorescence and parallel factor analysis (EEMs-PARAFAC)[J]. Limnology and Oceanography, 2008, 53(5): 1900-1908. DOI:10.4319/lo.2008.53.5.1900
[30] 赵夏婷, 李珊, 王兆炜, 等. 黄河兰州段水体中有色溶解性有机质组成、空间分布特征及来源分析[J]. 环境科学, 2018, 39(9): 4105-4113.
Zhao X T, Li S, Wang Z W, et al. Composition, spatial distribution characteristics and source analysis of chromophoric dissolved organic matter in the Lanzhou reach of the Yellow River[J]. Environmental Science, 2018, 39(9): 4105-4113.
[31] 唐永, 孙语嫣, 石晓勇, 等. 黄渤海海域秋季营养盐及有色溶解有机物分布特征[J]. 环境科学, 2017, 38(11): 4501-4512.
Tang Y, Sun Y Y, Shi X Y, et al. Distribution characteristics of chromophoric dissolved organic matter and nutrients from the Yellow Sea and Bohai Sea in autumn[J]. Environmental Science, 2017, 38(11): 4501-4512.
[32] Zhang Y L, Gao G, Shi K, et al. Absorption and fluorescence characteristics of rainwater CDOM and contribution to Lake Taihu, China[J]. Atmospheric Environment, 2014, 98: 483-491. DOI:10.1016/j.atmosenv.2014.09.038
[33] 邓恒, 徐国宾, 段宇, 等. 淮河与洪泽湖河湖关系研究进展及展望[J]. 水资源与水工程学报, 2018, 29(5): 142-147.
Deng H, Xu G B, Duan Y, et al. Research progress and prospect of the relationship between Huaihe River and Hongze Lake[J]. Journal of Water Resources and Water Engineering, 2018, 29(5): 142-147.
[34] Hu B, Wang P F, Qian J, et al. Characteristics, sources, and photobleaching of chromophoric dissolved organic matter (CDOM) in large and shallow Hongze Lake, China[J]. Journal of Great Lakes Research, 2017, 43(6): 1165-1172. DOI:10.1016/j.jglr.2017.09.004
[35] 李波, 濮培民. 淮河流域及洪泽湖水质的演变趋势分析[J]. 长江流域资源与环境, 2003, 12(1): 67-73.
Li B, Pu P M. Study on the evolution tendency of water quality in Huai River Basin and Hongze Lake[J]. Resources and Environment in the Yangtze Basin, 2003, 12(1): 67-73. DOI:10.3969/j.issn.1004-8227.2003.01.014
[36] 南楠, 张波, 李海东, 等. 洪泽湖湿地主要植物群落的水质净化能力研究[J]. 水土保持研究, 2011, 18(1): 228-231, 235.
Nan N, Zhang B, Li H D, et al. Water quality purification ability of main wetland plant community in Hongze Lake[J]. Research of Soil and Water Conservation, 2011, 18(1): 228-231, 235.
[37] Yao X L, Zhang L, Zhang Y L, et al. Water diversion projects negatively impact lake metabolism:A case study in Lake Dazong, China[J]. Science of the Total Environment, 2018, 613-614: 1460-1468. DOI:10.1016/j.scitotenv.2017.06.130
[38] 刘兆冰, 梁文健, 秦礼萍, 等. 渤海和北黄海有色溶解有机物(CDOM)的分布特征和季节变化[J]. 环境科学, 2019, 40(3): 1198-1208.
Liu Z B, Liang W J, Qin L P, et al. Distribution and seasonal variations of chromophoric dissolved organic matter(CDOM) in the Bohai Sea and the North Yellow Sea[J]. Environment Science, 2019, 40(3): 1198-1208.
[39] Asmala E, Stedmon C A, Thomas D N. Linking CDOM spectral absorption to dissolved organic carbon concentrations and loadings in boreal estuaries[J]. Estuarine, Coastal and Shelf Science, 2012, 111: 107-117. DOI:10.1016/j.ecss.2012.06.015
[40] 宋炎炎, 苏东辉, 邵田田. 东辽河流域河湖光学吸收特性的季节变化[J]. 应用生态学报, 2017, 28(6): 2013-2023.
Song Y Y, Su D H, Shao T T. Seasonal changes of optical absorption properties of river and lake in East Liaohe River basin, Northeast China[J]. Chinese Journal of Applied Ecology, 2017, 28(6): 2013-2023.
[41] Xing L Q, Zhang Q, Sun X, et al. Occurrence, distribution and risk assessment of organophosphate esters in surface water and sediment from a shallow freshwater Lake, China[J]. Science of the Total Environment, 2018, 636: 632-640. DOI:10.1016/j.scitotenv.2018.04.320
[42] 李其梁, 苑希民, 杨敏, 等. 淮沂水系洪泽湖-骆马湖水资源联合优化调度研究[J]. 南水北调与水利科技, 2013, 11(2): 10-13.
Li Q L, Yuan X M, Yang M, et al. Research on joint optimal regulation of water resources in the Hongze and Luoma Lakes of Huaiyi water system[J]. South-to-North Water Transfers and Water Science & Technology, 2013, 11(2): 10-13.
[43] 宋亚净, 刘立华, 石兆英, 等. 长距离调水对沿线及受纳水体水环境的影响[J]. 南水北调与水利科技, 2012, 10(3): 98-102, 136.
Song Y J, Liu L H, Shi Z Y, et al. Environmental impact of long distance water transfer on the water conveyance line and receiving water body[J]. South-to-North Water Transfers and Water Science & Technology, 2012, 10(3): 98-102, 136.
[44] 吕学研, 张咏, 徐亮, 等. 南水北调东线一期江苏段试调水期间的水质变化[J]. 水资源与水工程学报, 2015, 26(6): 12-18.
Lü X Y, Zhang Y, Xu L, et al. Variation of water quality of Jiangsu during water transfer test in first phase of eastern section of south to north water diversion project[J]. Journal of Water Resources & Water Engineering, 2015, 26(6): 12-18.
[45] Zhu Y P, Zhang H P, Chen L, et al. Influence of the South-North Water Diversion Project and the mitigation projects on the water quality of Han River[J]. Science of the Total Environment, 2008, 406(1-2): 57-68. DOI:10.1016/j.scitotenv.2008.08.008
[46] 叶琳琳, 吴晓东, 刘波, 等. 巢湖溶解性有机物时空分布规律及其影响因素[J]. 环境科学, 2015, 36(9): 3186-3193.
Ye L L, Wu X D, Liu B, et al. Temporal and spatial distribution characteristics of dissolved organic matter and influencing factors in Lake Chaohu[J]. Environment Science, 2015, 36(9): 3186-3193.
[47] 余辉, 张文斌, 卢少勇, 等. 洪泽湖表层底质营养盐的形态分布特征与评价[J]. 环境科学, 2010, 31(4): 961-968.
Yu H, Zhang W B, Lu S Y, et al. Spatial distribution characteristics of surface sediments nutrients in Lake Hongze and their pollution status evaluation[J]. Environment Science, 2010, 31(4): 961-968.