太湖流域昆承湖春季颗粒物和有色可溶性有机物吸收特性

利用2010年4月23日在昆承湖采集的水体吸收系数数据,对总悬浮物颗粒物、浮游植物色素颗粒物、非色素颗粒物和有色可溶性有机物的吸收特征进行研究.结果表明,春季昆承湖水体除675 nm附近具有叶绿素吸收峰的红光波段外,非色素颗粒物吸收系数大于浮游植物色素颗粒物吸收系数,总颗粒物吸收系数光谱分布与非色素颗粒物的吸收光谱类似...     

长江中下游大型湖泊水体固有光学特性:Ⅰ.吸收

吸收系数是水体固有光学特性的重要组成部分,也是构建水色参数高精度遥感模型的基础,具有重要的研究意义.本文针对长江中下游三大淡水湖——鄱阳湖(2010 10、2011 08)、太湖(2008 10、2011 08)和巢湖(2009 10)进行5次野外实验,以International Ocean Colour Coordinating Group(IOCCG)2000年报告"Remote Sensing of Ocean Colour in Coastal,and Other Optically-Complex,Waters"为基础,对水体不同光学主导类型进行分类;并根据a_d(非色素颗粒物吸收)、a_ph(浮游植物色素吸收)、a_g(有色可溶性有机物吸收)等不同主导类型光谱曲线特征差异,引入a_d-g(主导类型a_d、a_g、a_d-a_g的合并类型)和a_ph-related(主导类型a_d-a_ph、a_d-a_ph-a_g的合并类型)类型,对主导类型进行归纳合并.结果显示:秋季,鄱阳湖、太湖、巢湖的主导类型较为单一,分别为a_d、a_d-a_g、a_d-a_ph-a_g;夏季,鄱阳湖和太湖同为两种类型共同主导,分别为a_d、a_d-a_g,a_d-a_ph-a_g、a_d-a_ph.总体来说,鄱阳湖夏、秋季和太湖秋季主导类型都属于a_d-g类型,而太湖夏季和巢湖秋季则属于a_ph-related类型.另外,分别针对Gons和Gitelson叶绿素a模型假设条件进行验证,发现不同湖泊水体及不同主导类型下其适用性程度不一致.     

兴凯湖春季水体悬浮颗粒物和CDOM吸收特性

为了分析兴凯湖水体光学活性物质的吸收特性、来源和空间分布以及对400~700 nm范围内总吸收的贡献,于2013年5月对该水体进行野外实验,对水体中浮游藻类、非藻类颗粒物和有色可溶性有机物的吸收特性和水质参数进行测定.结果表明:总悬浮颗粒物的吸收光谱与非藻类颗粒物相似,色素颗粒物含量较少且单一,非藻类颗粒物在总悬浮颗粒物吸收中占主导地位,其贡献率始终在50%以上.CDOM吸收曲线的拟合函数斜率值Sg均高于其它水体.440 nm处总悬浮颗粒物和非藻类颗粒物的吸收系数ap(440)、ad(440)与总悬浮颗粒物、无机悬浮颗粒物和有机悬浮颗粒物浓度相关性均较好,与叶绿素a(Chl.a)浓度的相关性较差.兴凯湖与其它Ⅱ类水体的差异性表现在440 nm处CDOM吸收系数ag(440)与Chl.a浓度、溶解性有机碳(DOC)浓度均无显著相关性,说明DOC以无色部分为主.总体上,大兴凯湖各吸收系数和水质参数均值均低于小兴凯湖,后者水质受农耕区退水及周围渔业、旅游业的影响较大.     

长春市石头口门水库颗粒物光谱吸收特性

针对东北地区水体,以长春市重要水源地石头口门水库为例,分别于2008年6月13日和9月23 日对该水库进行了水体颗牲物吸收特性研究.结果显示:2008年6月水库悬浮物含量高于9月,而叶绿素a含量低于9月:总颗粒物的吸收光谱曲线类似于非色素颗粒物,非色素颗粒物吸收对其的贡献明显大于浮游植物色素,9月份浮游植物吸收对其的贡献略有增加,吸收曲线在440nm左右能明显看到浮游植物引起的吸收峰;非色素颗粒物在440nm的吸收系数与悬浮物浓度存在较好的函数关系,而与叶绿素a浓度的相关性较弱;浮游植物色素吸收系数较低,色素组成中叶绿索a占主导地位,浮游植物在440nm和675nm的吸收系数与叶绿素a含量均存在较好的指数函数关系;6月浮游植物比吸收系数在440nm和750nm的均值分别为0.0483m2/mg和0.0263m2/mg,而9月份的均值分别为0.0337m2/mg和0.01 87m2/mg.     

夏季新安江水库(千岛湖)颗粒物吸收光谱特征分析

通过对2013年夏季新安江水库(千岛湖)53个站点悬浮颗粒物的吸收光谱进行研究,系统分析了总颗粒物吸收系数ap(λ)、非藻类颗粒物吸收系数ad(λ)和浮游藻类光谱吸收系数aph(λ)的变化规律以及影响因素.结果表明:总颗粒物吸收除西北河流区上游段外,其他各站点均呈现出明显的浮游藻类吸收特性,反映新安江水库总颗粒物中浮游藻类贡献较高.全库ap(440)在0.068 ～0.629 m-1之间变化,西北河流区总颗粒物吸收系数显著大于其他水域,而湖泊区与西南河流区则显著小于其他水域.非藻类颗粒物吸收光谱随着波长增加大致呈现出指数函数衰减的规律,其光谱斜率Sd均值为8.52±1.62μm-1,存在显著的空间差异,但整体偏低,与新安江水库无机颗粒物含量低有关.ad (440)与浮游藻类色素浓度存在显著的线性相关,表明夏季新安江水库非藻类颗粒物可能主要来源于浮游藻类降解.浮游藻类的光谱吸收在440和675 nm附近有明显的吸收峰.aph(440)和aph(675)存在显著的空间差异,其与浮游藻类色素浓度存在极显著的正线性关系,而与总悬浮颗粒物浓度相关性较弱.     

不同营养水平湖泊浮游植物吸收和比吸收系数变化特征

利用太湖和博斯腾湖8月份、天目湖6 8月份的采样数据,开展不同营养状态下浮游植物吸收和比吸收系数的变化规律研究,并探讨其影响因素.利用综合营养指数法,太湖8月42个采样点中20个点为重度富营养,标记为太湖TⅠ,22个点为中度富营养,标记为太湖TⅡ,天目湖夏季、博斯腾湖8月的富营养水平分别为轻度富营养和中营养.440 nm处浮游植物吸收系数a_ph(440)按照营养水平从高到低由重度富营养到中营养分别为1.02±0.51、0.69±0.40、0.78±0.24和0.20±0.04 m^-1,相应地675 nm处浮游植物吸收系数a_ph(675)分别为0.59±0.32、0.38±0.23、0.41±0.13和0.08±0.02 m^-1.统计检验显示,重、中度富营养的太湖以及轻度富营养的天目湖浮游植物吸收系数显著高于中营养的博斯腾湖.440 nm处浮游植物比吸收系数a_ph^*(440)分别为0.013±0.006、0.012±0.004、0.038±0.008和0.051±0.013 m²/mg Chl.a.统计检验显示,重度、中度富营养的太湖浮游植物比吸收系数显著小于轻度富营养的天目湖,而天目湖浮游植物比吸收系数又显著小于中营养的博斯腾湖.另由400~700 nm浮游植物的光谱曲线可以明显看出不同营养状态浮游植物吸收系数的变化情况,表现为:重度富营养太湖TⅠ>轻度富营养的天目湖>中度富营养的太湖TⅡ>中营养的博斯腾湖.太湖和天目湖属于富营养化湖泊,浮游植物吸收系数明显高于中营养的博斯腾湖,这充分反映了随营养程度增加,浮游植物吸收逐渐增加.天目湖浮游植物略高于太湖TⅡ是因为太湖非藻类悬浮颗粒物含量高,所以吸收系数偏小.比吸收系数的变化情况与吸收系数的变化情况恰好相反,随着营养程度的增加依次递减.随营养程度增加浮游植物吸收逐渐增加是由于水体营养盐增加促进浮游植物生长,浮游植物生物量逐渐增加所致,而比吸收系数逐渐降低则由于色素包裹效应所致.     

太湖有色溶解有机物对水体总吸收贡献的遥感估算

有色溶解有机物(CDOM)是决定自然水体水色的主要溶解物质,其吸光能力和光化降解产物对水体初级生产力和碳循环过程具有重要影响.以太湖为研究区,2004年10月、2008年10月、2010年4月和2011年1月和3月共5期实测数据,采集了333个有效样点,分析不同时期CDOM对水体总吸收的贡献,并利用遥感技术估算[a_CDOM/a_t](412).结果表明:不同时期[a_CDOM/a_t](412)均值变化明显,2011年[a_CDOM/a_t](412)的均值最大(0.369),高于所有样点[a_CDOM/a_t](412)均值(0.295±0.139);201004期的[a_CDOM/a_t](412)在0.046~0.455之间变化,其均值最小(0.236±0.108);200410和200810两期数据[a_CDOM/a_t](412)均值相差不大.竺山湾、梅梁湾与整个太湖相比,竺山湾[a_CDOM/a_t](412)均值较高,对太湖[a_CDOM/a_t](412)的贡献较大,而梅梁湾[a_CDOM/a_t](412)均值与整个太湖相差较小.利用多元线性模型估算[a_CDOM/a_t](412)精度较高(n=333,RMSE=34.60%).悬浮泥沙和浮游色素是影响[a_CDOM/a_t](412)遥感估算精度的主要原因,浮游色素的吸收造成[a_CDOM/a_t](412)的值被低估,而悬浮泥沙的吸收使得[a_CDOM/a_t](412)的值被高估,并且悬浮泥沙是影响CDOM吸收的主要原因.     

藻源性湖泛发生过程CDOM变化对水色的影响

利用Y-型沉积物再悬浮发生装置模拟湖泛发生过程,分析其中有色可溶性有机物(CDOM)的变化特征及其对水色的影响.结果表明,藻类死亡过程消耗大量的氧气,水中溶解氧在短时间内消失殆尽,形成厌氧环境;并同时分解产生大量CDOM,使得水中CDOM显著增多.前期阶段,CDOM浓度随时间一直升高,第6 d时CDOM浓度达到峰值,CDOM在443 nm处的吸收系数a_g(443)为4.48 m^-1.水体黑度值(FeS浓度)呈先增大后减小的趋势,最大值0.35mmol/L同样出现在第6 d,整个过程中,CDOM浓度和黑度值变化趋势一致,a_g(443)与水体黑度呈显著正相关.利用Hydrolight和CIE颜色匹配函数模拟不同梯度的CDOM对水色的影响,发现随a_g(443)增大,水体颜色也逐渐由绿色转为棕色,整体向长波方向移动,水色逐渐变暗.因此,可以认为CDOM浓度变化是引起湖泛水体发黑的重要原因之一,可作为定量监测湖泛强度的指示性参数.     

贵阳市百花湖近10年(2009-2018年)的水质时空变化

百花湖是贵阳市重要的城市饮用水源地,并且近年来经常发生水质异常现象.本文利用2009-2018年百花湖长时间序列的监测数据,采用综合营养状态指数法和Pearson相关性分析,研究了百花湖10年间的水质变化特征和影响因素.结果表明：1）库区叶绿素a（Chl.a）、总磷（TP）、总氮（TN）、高锰酸盐指数（COD_Mn）和透明度（SD）的浓度范围分别是3.43~39.72 mg/m³、0.034~0.115 mg/L、1.200~2.759 mg/L、1.41~5.51 mg/L和0.75~2.07 m,且高氮磷比（12~63）表明百花湖是磷限制型.2）在空间上,TP、TN、氨氮、COD_Mn和Chl.a浓度沿水体流向逐渐降低,SD呈相反变化趋势.3）10年来,百花湖水质由Ⅳ类转变为Ⅲ类,综合营养状态由轻度富营养化状态转变为中营养状态,水质整体向好.4）入库支流是影响百花湖库区水质的主要因素,长期以来,东门桥河、南门河水质TP和TN等超标严重,给库区水质稳定达标带来威胁.5）百花湖Chl.a浓度与气温、水位、风速和TP等指标显著相关,是受水文、气象及营养盐因素的综合控制.未来在百花湖水环境保护治理过程中,应加大对东门桥河、南门河等重点支流的污染治理,加强对水动力学、气候变化等水文气象因素影响库区水质（藻类水华）的机制研究.     

富营养化湖泊典型水华蓝藻的固有光学特性

固有光学特性是水体光学特性的重要内容,掌握富营养化湖泊水体内典型水华蓝藻的固有光学特性,是开展不同水华蓝藻遥感识别的理论基础.利用AC-S吸收衰减仪、BB9后向散射仪,通过实验室纯藻培养,研究微囊藻（Microcystis）、鱼腥藻（Dolichospermum）和束丝藻（Aphanizomenon）3种典型水华蓝藻的固有光学特性,并探讨色素浓度、色素占比以及藻类等效粒径对不同水华蓝藻固有光学特性的影响.结果表明,3种典型水华蓝藻的吸收光谱曲线均具有440、620和675 nm吸收峰,微囊藻620和675 nm的比吸收系数最大,鱼腥藻440 nm处的比吸收系数最大;束丝藻单位色素浓度的散射和后向散射能力最高,鱼腥藻次之,微囊藻最低;固有光学特性影响因子分析表明,色素浓度和藻蓝素占比是影响3种水华蓝藻固有光学特性的主要因素.3种蓝藻的吸收系数、散射系数以及鱼腥藻、束丝藻的后向散射系数均随着色素浓度（叶绿素a或藻蓝素）的增加而增大;当蓝藻中藻蓝素占比增加时,3种蓝藻的单位色素浓度的后向散射系数逐渐下降;而藻细胞粒径与固有光学特性之间并未表现出很好的相关性.因此,3种水华蓝藻单位色素浓度的固有光学特性将为典型水华蓝藻的遥感识别提供重要的理论基础和数据支持.     

淮河流域周村水库夏季CDOM吸收光谱特征、空间分布及其来源分析

基于2015年8月采集的24个淮河流域以周村水源水库为代表的表层水样的有色溶解性有机物(CDOM)吸收系数数据,研究了CDOM吸收光谱的空间分布特征,考察了CDOM的吸收系数与水质参数的相关关系,同时探讨了周村水库夏季CDOM的潜在来源.结果显示:依据CDOM的吸收光谱空间分布特性及采样点分布特征,周村水库分为入库口、过渡区和主库区3个特征水域;CDOM的吸收系数沿入库口到主库区依次递减,S值呈现相反的趋势;分析发现S240~500与a(355)和a*(355)呈极显著负相关(R~2=0.98、0.88);CDOM吸收系数a(355)与溶解性有机碳(DOC)浓度具有良好的线性相关,有利于建立DOC遥感反演模型;同时,CDOM吸收系数a(355)与a_(ph)(440)存在极显著正线性相关,表明浮游植物的新陈代谢及其降解产物是夏季周村水库CDOM的潜在来源.综上,通过对夏季周村水库水体CDOM的研究,丰富了关于水源水体CDOM的调查资料,可为日后水库的管理提供技术支撑.     

Contrasting phytoplankton community structure and associated light absorption characteristics of the western Bay of Bengal

Absorption spectra, particulate pigments, and hydrochemical constituents were measured in the western Bay of Bengal (BoB) during July-August 2010 when influence of river discharge is at peak. Chromophoric dissolved organic matter (CDOM) absorption coefficient (a_CDOM(440)) displayed a significant inverse linear relationship with salinity in the surface waters implying conservative mixing of marine and terrestrial end members. The northern part of the study area is influenced by discharge from the river Ganga and a dominant terrestrial CDOM signal is seen. The southern part receives discharge from peninsular rivers with corresponding signals of higher CDOM than the linear model would indicate and higher UV-specific absorption coefficient (SUVA) indicating more aged and humified DOM. Lower contribution of CDOM to total non-water absorption and higher phytoplankton biomass (chlorophyll a absorption coefficient, a_ph(440)) but lower chlorophyll a specific phytoplankton absorption coefficient (a _ph ^* (440)) characterize the northern part, compared to the southern part. Chlorophyll b had a distinct linear relationship with chlorophyll a in the latter. The size index (SI) indicated dominance of microphytoplankton in the northern and nano and picophytoplankton in the southern parts. Chlorophyll a is significantly related to a _ph ^* (440) by an inverse power model in the northern part but by an inverse linear model in the southern part. Our study suggests that knowledge of the phytoplankton community structure is essential to improve chlorophyll a algorithm in the coastal Bay of Bengal.     

Phytoplankton absorption spectra along the water column in deep North Patagonian Andean lakes (Argentina)

During a summer period we studied the vertical variation of in vivo and chlorophyll a specific phytoplankton absorption spectra in relation to the underwater light climate of ten deep North Patagonian Andean lakes of Argentina. The lakes were thermally stratified, and the underwater light climate was characterized by extended euphotic zones which included highly illuminated epilimnetic layers (both UVR and PAR) and metalimnia exposed to dim blue-green light. Most of the lakes presented the development of Deep Chlorophyll Maxima (DCM) at the metalimnetic layers, near 1% of surface PAR irradiance. Analyzing the fourth-derivative plots of in vivo phytoplankton absorption spectra [d^IVa_ph(λ)], we were able to identify several maxima absorption values attributed to different pigments. Considering lakes with DCM, a significant positive linear relationship was found between d^IVa_ph (495–500 nm) normalized by chlorophyll a and downward irradiance. Indeed, a negative significant relationship was found between d^IVa_ph (495–500 nm) normalized by chlorophyll a and diffuse PAR attenuation coefficients. These results point out an increase in the relative concentration of different carotenoids at surface layers indicating the role of photoprotection of these pigments. On the other hand, significant negative linear relationships were found between fourth-derivative spectra normalized by chlorophyll a at 650, 590–595, 560–565 and 520–525 nm and downward irradiance. These results indicated an increase in the relative concentration of photosynthetic accessory pigments at deep layers of the euphotic zone. Furthermore, we found a decrease in depth of specific absorption spectra at 440, 670 nm and in the ratio a_ph* (440 nm) to a_ph* (670 nm). This pattern was associated with the package effect concept. The increase in relative photosynthetic accessory pigment concentrations and the decrease in values of specific absorption spectra at the bottom of the euphotic zone were attributed to changes in phytoplankton communities between surface and deep layers. These outcomes pointed out that the underwater light climate and temperature water structure are, like in marine systems, very important factors governing the distribution of phytoplanktonic organisms. In addition, the possession of specific photosynthetic accessory pigments suggests that dominant species in the DCM are well adapted to these dim blue-green light scenarios.     

抚仙湖秋、冬季光衰减特征及其与有色可溶性有机物的关系

为了研究抚仙湖紫外辐射(UVR)和光合有效辐射(PAR)衰减的时空特征及其与有色可溶性有机物(CDOM)、悬浮物(SS)、浮游植物(叶绿素a表征)等因子的关系,于2014年10月(秋季)、2015年1月(冬季)开展现场调查,结果显示:秋季不同波长(段)的漫射衰减系数Kd(305)、Kd(340)和Kd(PAR)分别为1.27±0.12、0.68±0.11和0.32±0.13 m-1,冬季分别为1.13±0.10、0.63±0.07和0.36±0.07 m-1;秋季CDOM的不同波长吸收系数ag(254)、ag(305)和ag(340)分别为4.09±0.26、1.18±0.09和0.57±0.05 m-1,冬季分别为2.95±0.24、0.61±0.11和0.11±0.07 m-1,秋季ag(254)、ag(305)和ag(340)显著高于冬季;秋季Kd(305)显著大于冬季,这与秋季(雨季)较高的CDOM丰度、浮游植物生物量(及SS浓度)有关.秋季ag(305)/Kd(305)、ag(340)/Kd(340)均显著高于冬季;秋季及秋冬季整体而言,ag(254)与Kd(305)、Kd(340)呈显著正相关,各多元逐步回归方程中均包含ag(254),说明CDOM吸收对UVR的衰减有重要贡献.空间差异方面,秋季北部的ag(254)、Kd(305)和Kd(340)显著高于南部,冬季南北部无明显差异,或与雨旱季北岸河流输入的CDOM和SS的情况有关.此外,浮游植物对UV-B衰减的影响和SS(与CDOM的交互作用)对UV-A衰减的影响更在于季节变化方面,而影响UVR、PAR衰减的各因子的相对贡献有待进一步量化.     

Attenuation of UVR and PAR in a clear and deep lake: Spatial distribution and affecting factors

Light attenuation is considered as a sentinel for environmental change in lakes and has a profound influence on aquatic ecosystems. However, the spatial distribution of ultraviolet radiation (UVR) and photosynthetically active radiation (PAR) attenuation, and the underlying mechanisms are still not fully understood. We carried out a field investigation with 60 sampling sites covering the entire Lake Qiandaohu from November 29 to December 1, 2013, during the weak stratification period to elucidate the spatial pattern and driving mechanisms. The diffuse attenuation coefficient of UVB (K_d(313)), UVA (K_d(340)) and PAR (K_d(PAR)) varied from 1.48 to 4.63 m⁻¹, 1.09 to 3.43 m⁻¹, and 0.26 to 0.94 m⁻¹, respectively. The corresponding ranges for the 1% attenuation depths were from 0.10 to 3.11 m, 1.34–4.21 m and 4.87–17.58 m, respectively. Total suspended matter (TSM) concentration was highly significantly correlated with K_d(313), K_d(340) and K_d(PAR) indicating that TSM was the main driver of UVR and PAR attenuation in Lake Qiandaohu in the late autumn and early winter. TSM concentration, K_d(313), K_d(340) and K_d(PAR) had obvious horizontal spatial heterogeneity presenting a decreasing trend from the estuary area to the center area in the lake. These results suggested that the spatial distribution of TSM from the inflow drived the spatial distribution of UVR and PAR attenuation. Significantly positive correlations were also observed between the chromophoric dissolved organic matter (CDOM) absorption coefficient and K_d(313). TSM and CDOM absorption spectra showed that in the UVR waveband (350–400 nm), the mean relative contribution rates of CDOM (a_g(λ)), non-algal particles (a_nap(λ)), phytoplankton (a_ph(λ)) and pure water (a_w(λ)) to the total absorption were 67.5 %, 24.0 %, 5.0 % and 3.5 %, respectively. In the PAR waveband, the mean relative contribution rates of a_g(λ), a_nap(λ), a_ph(λ) and a_w(λ) to the total absorption were 25.4 %, 18.6 %, 9.4 % and 46.6 %, respectively. Our findings could provide support for ecological environment protection in Lake Qiandaohu considering the importance of UVR and PAR attenuation in aquatic ecosystems.     

Variations in light absorption properties during a phytoplankton bloom in the Pearl River estuary

From 15 to 28 August in 2007, a Chaetoceros socialis bloom was detected in the Pearl River Estuary water with chlorophyll a concentration (Chl a) up to 30 mg m⁻³ and cell density up to 10⁶ cells L⁻¹. Time series of bio-optical measurements was obtained at a single site (114.29°E, 22.06°N) with the mooring of marine optical buoy. Light absorption properties of seawater experienced large variability throughout the algal bloom. Absorption by colored dissolved organic matter (CDOM) was one of the dominant optical components of the light absorption (30–70%) especially for pre- and post-bloom waters, and it tended to decrease with Chl a during the algal bloom. Absorption by phytoplankton was another dominant optical component (18–50%) and increased rapidly with Chl a. Phytoplankton and accompanying material played dominant roles in light absorption as indicated by the relationship between absorption coefficient and Chl a. At high pigment concentrations, water samples showed significantly lower specific phytoplankton absorption, compared with pre- and post-bloom conditions, with the specific phytoplankton concentration at 443 nm varied between 0.011 and 0.022 m² mg⁻¹ and that at 676 nm between 0.007 and 0.018 m² mg⁻¹; small values of blue-to-red ratio of phytoplankton were also observed. These lower values were associated with variations in phytoplankton size structure. Spectral variability of phytoplankton absorption and total absorption (not including the fixed background absorption by pure water itself) could be expressed as simple linear functions linking absorption at one wavelength to the absorption at the other wavelengths, with the slope of the relationship changing with wavelength. The absorption coefficients by non-algal particles and CDOM follow the general exponential functions with remarkably limited variability in the exponent with means of 0.0105 and 0.0166 nm⁻¹, respectively. These spectral dependencies of absorption coefficients provide useful information for retrieving inherent optical properties from reflectance data in a remote-sensing context.