基于哨兵-3A卫星OLCI数据的最大叶绿素指数在太湖蓝藻水华监测中的应用

欧洲航天局于2016年2月16日成功发射哨兵-3A卫星,搭载的水色遥感仪器(OLCI)提供了很好的海洋和内陆水体生态指标观测反演能力。基于OLCI获取的太湖L1b级遥感数据产品,利用OLCI Oa10、Oa11、Oa12波段计算了重要的水色/水生态遥感指标,即最大叶绿素指数(MCI),在此基础上初步分析了MCI在太湖蓝藻水华监测预警中应用效果。研究表明:(1)哨兵-3A卫星OLCI影像质量清晰,构建的MCI能够反映太湖水体叶绿素信号强度;(2)与常用的归一化植被指数相比,在蓝藻没有明显积聚的藻-水混悬水域,MCI与叶绿素浓度有很好的关联,可更灵敏地反映叶绿素浓度的空间分布特征。MCI将在蓝藻监测上具有更好的适用性,可有效提高富营养湖泊蓝藻水华的预警预报精度。     

近岸海域水色异常遥感监测方法研究

水体颜色是判断水体质量的重要依据,利用遥感技术检测水色异常是进行水质评估和水体污染监测的重要技术手法。基于盐城市废黄河入海口处的GF1-WFV影像数据,利用遥感影像自身光谱特征来构建水色异常判断函数,对研究区域的水色异常进行快速提取和定位,并比较分析了基于单景影像特征和多景影像特征设置判断阈值的提取结果。研究结果表明：该方法完全基于遥感影像光谱特征,可有效提取出未知类型的水色异常信息;与基于单景影像设置的判断阈值相比,基于双景影像设置的判断阈值更合理、更适用,提取速度更快,提取范围更精确,Kappa系数为0.80;另外,采用合适窗口大小进行均值滤波处理能有效防止提取结果细碎和斑块化。     

2002-2021年渤海叶绿素a浓度变化及环境响应分析

基于2013-2021年渤海遥感反射率和叶绿素a浓度等实测数据,开展了该海域MODIS影像的叶绿素a浓度遥感反演模型研究。选择OC3经典模型形式,采用渤海的实测数据进行拟合分析,获取了适用于渤海的模型局地化参数,通过真实性检验得到叶绿素a浓度的遥感反演结果与实测值的决定系数为0.84,平均相对误差为24.77%,均方根误差为5.56 μg/L,反演精度较佳。利用该算法反演获取了渤海2002-2021年叶绿素a的月度、季度和年度平均浓度,分析了其时空变化特征,同时结合2001-2021年渤海非优良水质比例开展了环境响应分析。分析结果显示:2001-2021年,渤海非优良水质比例与同时期叶绿素a浓度变化趋势基本一致,呈现先变差后变好的倒V形趋势;5年平均的非优良水质比例与叶绿素a浓度变化趋势更直观地反映了2001-2021年渤海整体的水环境变化趋势,与非优良水质比例相比,叶绿素a浓度对渤海水环境的改善响应更快。     

基于“哨兵3号”卫星OLCI影像和C2RCC算法的南黄海叶绿素a及总悬浮物反演效果分析

利用遥感数据处理软件SNAP中基于神经网络技术的C2RCC算法,对2019年5月9日南黄海“哨兵3号”卫星OLCI影像数据进行了叶绿素a及总悬浮物浓度反演,将其与5月间江苏省海洋环境监测预报中心的海水表层叶绿素a和悬浮物实测数据进行了比较分析。结果表明,叶绿素a的遥感反演尚未能达到业务化应用,总悬浮物遥感反演结果的空间分布与实测值的一致性相对较好。但在星地同日或相差一天监测的南通海域,遥感反演叶绿素a浓度的空间分布趋势以及总悬浮物遥感反演结果与海面实测结果的一致性较好,可达到一定的业务化应用效果。     

基于“哨兵-3A”OLCI影像的太湖蓝藻水华荧光基线高度指数信号特征分析

利用新型遥感数据"哨兵-3A"卫星OLCI影像数据,基于其665,681和708 nm波段构建的"荧光基线高度"指数算法,采用SNAP 6.0遥感专业软件,计算了2017年不同季节4个典型日期太湖FLH的全湖分布及蓝藻水华区信号强度特征。以完成了瑞利散射及气体吸收订正的3个波段的遥感反射率数据计算FLH图像,结果表明,FLH数值的"负偏"程度与蓝藻水华强度有很好的对应关系,FLH值"负偏"越大,蓝藻水华越严重,可以作为比较不同季节水华强度的有效遥感指标;富营养化较严重、较为浑浊、以蓝藻为优势种的内陆水体与大洋清洁、非蓝藻优势浮游植物水体的FLH"正偏"信号特征迥异。     

应用遥感监测技术分析扬州市五年植被覆盖状况

利用扬州市2006—2010年间卫星遥感数据,对扬州市植被覆盖状况进行了研究。首先对遥感影像进行几何校正,其次对遥感影像进行解译,提取植被覆盖信息,计算扬州市植被覆盖指数,同时对扬州市近5年植被覆盖进行了动态变化分析。研究表明,扬州市近5年林地面积大幅度提高,植被覆盖指数逐年增加,生态环境状况逐年好转。     

温升包络线在核电站温排水监测中的应用

采用核电站温排水遥感监测影像叠加合并方法提取温升包络线,监测核电站附近海域海表温升数据,确定核电温排水的影响范围,对海面温升面积进行计算,判断核电站温排水是否符合我国相关海洋空间管理标准。以某核电站实例表明,通过遥感监测获得的温升包络线在核电站温排水监测中具有应用价值。     

地表水环境遥感监测关键技术与系统

介绍了地表水环境遥感监测的关键技术与系统及其典型应用,其代表性机理模型和应用示范成果主要来自于中国科学院遥感与数字地球研究所的高光谱遥感团队在最近几年中取得的一些研究进展,主要包括建立了基于改进双峰法的水体分布自动化遥感提取方法,实现了简单、高效和高精度的水体提取；提出了大型湖泊长时序水量估算方法,并以青藏高原湖区为例,重建了典型湖泊面积、水位和水量序列；发展了基于“软分类”的典型内陆水体叶绿素a浓度反演方法,构建了基于生物光学模型的高度浑浊水体悬浮物浓度遥感反演半解析方法,提高了反演方法的区域和季节适用性；构建了基于水色指数的大范围湖库营养状态和透明度遥感监测方法,实现了全球大型湖库营养状态遥感监测,以及全国大型湖库透明度遥感监测；在此基础上,开发了地表水环境遥感监测系统,提高了水环境遥感监测效率,促进了卫星遥感在水环境监测中的高精度业务化应用。     

一种基于Landsat 8 OLI影像的水体信息提取方法研究

提出一种基于Landsat 8 OLI影像提取水体信息的斜率比值法（SR）,比对不同方法、不同类型水体和不同季节影像的数据,结果表明：SR法相比归一化差异水体指数法（NDWI）和改进的归一化差异水体指数法（MNDWI）,水体信息提取精度更高,且对阈值精确度的要求低,阈值一般设定为2.0;SR法适用于清澈水体、浑浊水体、浅水河滩等水体,对河流干流和较大支流的提取精度达到99%,细小支流、沟渠的提取精度为66%,面积较小的水体提取精度为65%;在冬季太阳高度角较低时,SR也能较好地去除阴影。     

基于EOS/MODIS卫星遥感数据的渤海海冰变化趋势及特征应用研究

根据卫星遥感数据的分辨率、采集频次、获取方式等特点，将MODIS卫星遥感数据应用到渤海海冰遥感监测中。通过海冰在可见光和红外光波段的光谱存在特定差异的特性，对海冰发生面积进行提取。同时对渤海海冰进行了遥感监测，并完整地监测到海冰从发生到极盛再到消退的全过程。同时，在海冰发生最为严重的时段，对辽东湾海域进行了密集监测。研究结果表明，MODIS卫星遥感数据在海冰监测中有着及时、准确的优势。     

渤海环流对近岸海域无机氮分布特征的影响

基于2017年渤海近岸海域无机氮监测数据和HYCOM数值模拟结果,分析了渤海环流对无机氮污染分布特征的影响,结果表明渤海无机氮的空间分布特征与其环流结构密切相关:受渤海环流的影响,在春、夏、秋季,无机氮含量高值区呈现不同的强度和范围；在辽东湾,与春季相比,夏季环流结构与春季相反、速度大于春季,盘锦、营口近岸海域夏季无机氮污染范围缩小、含量降低,在锦州近岸海域亦出现高值；在渤海湾、莱州湾,与春季相比,夏季和秋季无机氮含量高值区范围缩小,无机氮含量等值线均随环流向高值中心扩展。     

渤海湾入海溶解无机氮总量控制研究

基于渤海湾近岸海域的实际调查结果,采取生态物理耦合模型,对渤海湾的主要污染物-溶解无机氮(DIN)的基准环境容量和极小剩余海洋环境容量进行了计算。结果表明,渤海湾DIN的极小剩余海洋环境容量在Ⅰ类和Ⅱ类水质标准下均为负值,渤海湾的DIN已经超标。结合实际的海水功能区水质管理目标,应重点控制非点源的排放,加强上游携带入境污染物的处理,从总量上控制DIN入海污染通量,改善渤海湾水质。     

黄河口的水质、底质污染及其变化

分析了2001年在黄河口附近所取的3处水样和3处泥样中污染物的含量,并与历史数据进行了比较.利用<地表水环境质量标准>(GB3838-2002)和美国国家海洋大气管理局(NOAA)水体泥沙质量标准等分别对水体和底泥中的重金属(砷)和氮磷污染进行了评价.认为黄河口的水污染严重,主要污染物为汞和氮;泥沙污染尚不严重,但污染物的增长率高;水体中较高的氮含量和泥沙中氮含量的迅速增高可能会对渤海湾的富营养化情况产生影响.     

淮河流域淮安段着生藻类群落结构特征分析

于2021年5月对淮安境内淮河主要干支流8个点位的水质状况和着生藻类群落结构采样调查,应用3种多样性指数模型评价区域水生态健康状况,并探究影响着生藻类多样性的因素。结果表明：采样期间淮河流域淮安市域共检出着生藻类3门23科32属（种）,由硅藻门、蓝藻门和绿藻门组成,硅藻门占绝对优势;多样性指数计算结果显示,流域水生态状况良好,整体表现为清洁-轻污型水体,淮河上游水质稍差于其他水域;结合水质监测数据与卫星遥感影像分析,认为生境状况是影响着生藻类群落分布的主要因素。     

Metal contents in coastal waters of San Jorge Bay, Antofagasta, northern Chile: a base line for establishing seawater quality guidelines

We measured the concentration of 12 metals in coastal waters of seven sites of San Jorge Bay in Antofagasta (northern Chile), in order to relate the presence of metals with the different uses of San Jorge Bay coastal border, and to evaluate the quality of the bay's bodies of water according to the proposed current Chilean Quality Guide for trace elements in seawater (CONAMA 2003). The results suggest that the coastal water of San Jorge Bay has very good quality according to the proposed regulation mentioned above. However, the distribution of metals such as Cu and Pb along the bay's coast line evidences a notorious effect of the industrial activity, which would involve different behavior patterns for some trace elements in some bodies of water, suggesting that the levels indicated in the environmental guideline of the Chilean legislation do not represent pollution-free environments.     

Scaling the trophic index (TRIX) in oligotrophic marine environments

The TRIX index used for the assessment of trophic status of coastal waters has been applied in many European seas (Adriatic, Tyrrhenian, Baltic, Black Sea, and North Sea). However, all these waters are characterized by high nutrient levels and phytoplankton biomass; index calibration based on systems that are principally eutrophic may introduce bias to the index scaling. In the present work the TRIX trophic index is evaluated using three standard sets of data characterizing oligotrophy, mesotrophy, and eutrophication in the Aegean (Eastern Mediterranean) marine environment. A natural eutrophication scale based on the TRIX index that is suitable to characterize trophic conditions in oligotrophic Mediterranean water bodies is proposed. This scale was developed into a five-grade water quality classification scheme describing different levels of eutrophication. It is questionable whether this index can form a universal index of eutrophication or the scaling of TRIX should be region specific.     

Water quality assessment using integrated modeling and monitoring in Narva Bay, Gulf of Finland

A coupled three-dimensional hydrodynamic–ecological model was used for the assessment of water quality in Narva Bay during one biologically active season. Narva Bay is located in the south-eastern Gulf of Finland. Narva River with a catchment’s area covering part of Russia and Estonia discharges water and nutrients to Narva Bay. The ecological model includes phytoplankton carbon, nitrogen and phosphorus, chlorophyll a, zooplankton, detritus carbon, nitrogen and phosphorus, inorganic nitrogen, inorganic phosphorus and dissolved oxygen as state variables. Both the hydrodynamic and ecosystem models were validated using a limited number of measurements. The hydrodynamic model validation included comparison of time series of currents and temperature and salinity profiles. The ecological model results were compared with the monitoring data of phytoplankton biomass, total nitrogen and phosphorus and dissolved oxygen. The comparison of hydrodynamic parameters, phytoplankton biomass, surface layer total phosphorus and dissolved oxygen and near-bottom layer total nitrogen was reasonable. Time series of spatially mean values and standard deviations of selected parameters were calculated for the whole Narva Bay. Combining model results and monitoring data, the characteristic concentrations of phytoplankton biomass, total nitrogen and phosphorus and near-bottom dissolved oxygen were estimated. Phytoplankton biomass and total phosphorus showed seasonal variations, of 0.6–1.1 and 0.022–0.032 mg/l, respectively, during spring bloom, 0.1–0.3 and 0.015–0.025 mg/l in summer and 0.2–0.6 and 0.017–0.035 mg/l during autumn bloom. Total nitrogen and near-bottom oxygen concentrations were rather steady, being 0.25–0.35 and 2–6 mg/l, respectively. The total nitrogen and phosphorus concentrations show that according to the classification of Estonian coastal waters, Narva Bay water belongs to a good water quality class.     

Identification of spatiotemporal nutrient patterns in a coastal bay via an integrated k-means clustering and gravity model

This study presents an integrated k-means clustering and gravity model (IKCGM) for investigating the spatiotemporal patterns of nutrient and associated dissolved oxygen levels in Tampa Bay, Florida. By using a k-means clustering analysis to first partition the nutrient data into a user-specified number of subsets, it is possible to discover the spatiotemporal patterns of nutrient distribution in the bay and capture the inherent linkages of hydrodynamic and biogeochemical features. Such patterns may then be combined with a gravity model to link the nutrient source contribution from each coastal watershed to the generated clusters in the bay to aid in the source proportion analysis for environmental management. The clustering analysis was carried out based on 1 year (2008) water quality data composed of 55 sample stations throughout Tampa Bay collected by the Environmental Protection Commission of Hillsborough County. In addition, hydrological and river water quality data of the same year were acquired from the United States Geological Survey's National Water Information System to support the gravity modeling analysis. The results show that the k-means model with 8 clusters is the optimal choice, in which cluster 2 at Lower Tampa Bay had the minimum values of total nitrogen (TN) concentrations, chlorophyll a (Chl-a) concentrations, and ocean color values in every season as well as the minimum concentration of total phosphorus (TP) in three consecutive seasons in 2008. The datasets indicate that Lower Tampa Bay is an area with limited nutrient input throughout the year. Cluster 5, located in Middle Tampa Bay, displayed elevated TN concentrations, ocean color values, and Chl-a concentrations, suggesting that high values of colored dissolved organic matter are linked with some nutrient sources. The data presented by the gravity modeling analysis indicate that the Alafia River Basin is the major contributor of nutrients in terms of both TP and TN values in all seasons. With this new integration, improvements for environmental monitoring and assessment were achieved to advance our understanding of sea-land interactions and nutrient cycling in a critical coastal bay, the Gulf of Mexico.     

细菌在近海污染监测及评价中的应用研究

通过对天津渤海湾的三个河流入海口(青静黄排水河、独流减河和海河),不同季节实地采集的水样中微生物数量及理化因子如温度、盐度、溶解氧(DO)、化学需氧量(COD)、无机氮等的研究,发现细菌指标与理化指标对污染指示结果有一定的相似性,都指示青静黄排水河河口污染较严重.利用SPSS软件的相关性分析方法对实验结果进行分析,发现水环境中细菌指标与理化因子具有一定的相关性.其中异养菌数与COD呈显著正相关性(P<0.05),与DO呈负相关性(P=0.051);大肠菌群数与理化因子DO呈极显著负相关关系(P<0.01),与COD呈正相关关系(P=0.061),与NO3-N,盐度呈负相关性(P>0.05).其他细菌指标与各理化因子也存在一定的相关性,但不明显.     

Dissolved organic iodine in marine waters: role in the estuarine geochemistry of iodine

Non-volatile dissolved organic iodine (DOI) can be a major, or even the dominant, species of dissolved I in coastal, inshore and estuarine waters. It can be converted to IO3- in the presence of an oxidizing agent and to I- by reacting it with a reducing agent. Depending on the exact experimental conditions, the yields of these reactions may not be quantitative. In previous analytical schemes for the determination of IO3-, I- and DOI in marine waters, if oxidation or reduction steps are involved and the concentrations of one or more species are estimated by difference, the presence of DOI can lead to an overestimation of the concentrations of the inorganic species determined by difference and an underestimation of the concentration of DOI. In two cruises covering the James River to the southern Chesapeake Bay and from the southern Chesapeake Bay to the Atlantic, above a salinity (S) of 2, the contribution of DOI to total I increased with decreasing salinity and reached a maximum of 80%. DOI, I- and IO3- were successively the dominant form of dissolved I at 0.1 < S < 15 in the James River estuary, 15 < S < 30 in the Southern Chesapeake Bay and S > 30 in the Atlantic Ocean at the Bay mouth, respectively. Total I behaved conservatively (i.e., no evidence of consumption or production) during estuarine mixing during both cruises. In the southern Chesapeake Bay, total inorganic I was also approximately conservative. The primary process affecting the speciation of dissolved I was the conversion of IO3- to I-. In the James River estuary, there were indications of the conversion of both IO3- and I- to DOI. The concentrations of total I, IO3-, I- and DOI in James River water were 0.121, undetectable, 0.068 and 0.053 microM, respectively. These concentrations of total I and I- are significantly higher while that of IO3- is noticeably lower than those used presently for estimating global riverine input of these I species to the oceans. The riverine flux of DOI to the oceans is presently unknown.