Prediction of chlorophyll a concentration using HJ-1 satellite imagery for Xiangxi Bay in Three Gorges Reservoir

Since the impoundment of the Three Gorges Reservoir in 2003, algal blooms have frequently been observed in it. The chlorophyll a concentration is an important parameter for evaluating algal blooms. In this study, the chlorophyll a concentration in Xiangxi Bay, in the Three Gorges Reservoir, was predicted using HJ-1 satellite imagery. Several models were established based on a correlation analysis between in situ measurements of the chlorophyll a concentration and the values obtained from satellite images of the study area from January 2010 to December 2011. Chlorophyll a concentrations in Xiangxi Bay were predicted based on the established models. The results show that the maximum correlation is between the reflectance of the band combination of B4/（B2＋B3） and in situ measurements of chlorophyll a concentration. The root mean square errors of the predicted values using the linear and quadratic models are 18.49 mg/m3 and 18.52 mg/m3, respectively, and the average relative errors are 37.79% and 36.79%, respectively. The results provide a reference for water bloom prediction in typical tributaries of the Three Gorges Reservoir and contribute to large-scale remote sensing monitoring and water quality management.

The Distribution and Variability of Simulated Chlorophyll Concentration over the Tropical Indian Ocean from Five CMIP5 Models

Performances of 5 models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) in simulating the chloro-phyll concentration over the tropical Indian Ocean are evaluated. Results show that these models are able to capture the dominant spatial distribution of observed chlorophyll concentration and reproduce the maximum chlorophyll concentration over the western part of the Arabian Sea, around the tip of the Indian subcontinent, and in the southeast tropical Indian Ocean. The seasonal evolution of chlorophyll concentration over these regions is also reproduced with significant amplitude diversity among models. All of 5 mod-els is able to simulate the interannual variability of chlorophyll concentration. The maximum interannual variation occurs at the same regions where the maximum climatological chlorophyll concentration is located. Further analysis also reveals that the Indian Ocean Dipole events have great impact on chlorophyll concentration in the tropical Indian Ocean. In the general successful simulation of chlorophyll concentration, most of the CMIP5 models present higher than normal chlorophyll concentration in the eastern equatorial Indian Ocean.

Inversion and verification of chlorophyll a concentration in the Bohai Bay

Chlorophyll a concentration is to characterize the amount of phytoplankton.In this paper,the chlorophyll a concentration is retrieved using the OC3M and OC2algorithms based on the MODIS remote sensing data,and using the band ratio,OC3G and YOC algorithms based on the GOCI remote sensing data.Based on the chlorophyll a measured data in the Bohai Bay in spring,2012,the spatial distribution trends of retrieval results are consistent with the measured results.By the inversion precision analysis,the accuracy of retrieval results of band ratio method based on GOCI is similar to that of OC3M method based on the MODIS.The precision retrieval results of YOC method based on GOCI are higher than the other methods.

Response of Sea Surface Temperature to Chlorophyll-a Concentration in the Tropical Pacific:Annual Mean,Seasonal Cycle,and Interannual Variability

The response of the upper-ocean temperatures and currents in the tropical Pacific to the spatial distribution of chlorophyll-a and its seasonal cycle is investigated using a coupled atmosphere-ocean model and a stand-alone oceanic general circulation model.The spatial distribution of chlorophyll-a significantly influences the mean state of models in the tropical Pacific.The annual mean SST in the eastern equatorial Pacific decreases accompanied by a shallow thermocline and stronger currents because of shallow penetration depth of solar radiation.Equatorial upwelling dominates the heat budget in that region.Atmosphere-ocean interaction processes can further amplify such changes. The seasonal cycle of chlorophyll-a can dramatically change ENSO period in the coupled model.After introducing the seasonal cycle of chlorophyll-a concentration,the peak of the power spectrum becomes broad,and longer periods（3 years） are found.These changes led to ENSO irregularities in the model. The increasing period is mainly due to the slow speed of Rossby waves,which are caused by the shallow mean thermocline in the northeastern Pacific.

Comparison of inversion of Chlorophyll concentration in the Bohai Bay based on GOCI Data

Bohai bay has poor water circulation capacity and low self-purification capacity,and a large number of land-sourced pollutants are accepted every year.The estimation of chlorophyll concentration based on remote sensing plays an important role in the study of marine red tide and the monitoring of water quality in the Bohai Bay.So it is necessary to select the best algorithm by comparing the performance of each algorithm.Choosing the best algorithm is helpful to improve the precision of chlorophyll concentration.Based on the in-situ measurement data of the Bohai Bay and the GOCI remote sensing reflectance data,the retrieval models of chlorophyll concentration were established in this paper by using the methods of fluorescence line height(FLH),OC3,blue-green band ratio and NIR-red band ratio.The above algorithms were evaluated by comparing the simulation results and the verification results.The results showed that there are obvious differences in the accuracy of different retrieval methods.The fitting and retrieval effect of FLH is the best and NIR-red band ratio is the worst,and the OC3is similar to the blue-green band ratio method.

The algorithms of chlorophyll-a concentration for CMODIS

The algorithms of extracting chlorophyll-a （Chl-a） concentration have been established for Chinese moderate resolution imaging spectrometer （CMODIS） mounted on Shenzhou-3 spaceship launched on 25 March 2002. The CMODIS is an ocean color sensor with 30 visible channels and 4 infrared channels, much different from other ocean color satellites and needs new algorithms to process data. Three models of Chl-a concentration were established based on Chl-a data retrieved from sea-viewing wide field-ofview sensor （SeaWiFS）, with the average relative errors of 26. 6%, 24%. 0% and 33.5%, respectively. This practical and economic approach can be used for developing the algorithms of Chinese ocean color and temperature sensor （COCTS） on the satellite Haiyang-1 to derive the Chl-a concentration concentration distribution. The applicability of the algorithms was analyzed using some in situ measurements. Suspended sediment is the main factor influencing the accuracy of the spectral ratio algorithms of Chl-a concentration. The algorithms are suitable to using in the regions where suspended sediment concentrations （ SSC ） are less than 5 g/m^3 under the condition of relative error of Chl-a concentration retrieval within 35%. High concentration of suspended sediment leads to the overestimate remote sensing retrieval of concentration of Chl-a, while low-middle SSCs lead to the low Chl-a concentration values using the spectral ratio algorithms. Since the accuracy of Chl-a concentration by the spectral ratio algorithms is limited to waters of Case 2, it is necessary to develop semi-analytical models to improve the performance of satellite ocean color remote sensing in turbid coastal waters.

Relationship of Abundance of Oceanic Sea Skaters, Halobates in the Tropical Pacific Ocean to Surface Biomass and Chlorophyll/Oxygen Concentrations

Relationship of population density of oceanic sea skaters collected from tropical and subtropical zones in the Pacific Ocean was examined to chlorophyll concentration/Dissolved Oxygen concentration and biomass in surface sea water. The four parameters shown above were measured at the site of 12oN 135oN during the cruise, MR13-03 cruise, and at the site of 25oN 160oE during another cruise KH-14-02. Significant and positive correlation between all biomass (especially invertebrates) and population density of oceanic sea skaters collected with a Neuston-Net trailing during 15 min was shown in overall analysis on the data of the both samplings (p oN 160oE than that at 12oN 135oN with similar value of chlorophyll value (p oN 160oE than that at 12oN 135oN for keeping high density population of oceanic sea skaters.

Statistical characteristics of chlorophyll-a concentration in Hong Kong's coastal waters

In this paper seven of the ten Water Control Zones (WCZs) in Hong Kong's coastal waters with monthly or bi-weekly sampling data of 17 parameters collected at 37 monitoring stations from 1988 to 1999 were selected to analyze the spatial and temporal variations of chlorophyll-a and its influencing factors. Cluster analysis was employed to group the monitoring stations based on the structure of the data set. Multiple step regression was employed to determine the significant influencing factors of chlorophyll-a level. The results suggest that all the monitoring stations could be grouped into two clusters. Cluster Ⅰ with frequent red tide incidents comprises two WCZs which are semi-enclosed bays. Cluster Ⅱ with less red tide occurrence comprises the other five WCZs in an estuarine environment in the west. For both clusters, the organic contents indicator, BODS, was a common significant influencing factor of the chlorophyll-a level. Nitrogen and light penetration condition related to turbidity, total volatile solids and suspended solids had more influence on the cholophyll-a level in Cluster Ⅰ than in Cluster Ⅱ, while phosphorus and oceanographic conditions associated with salinity, temperature, dissolved oxygen and pH were more important in Cluster Ⅱ than in Cluster Ⅰ. Generally, there was a higher average chlorophyll-a level in winter and autumn in a year. The chlorophyll-a level was much higher in Cluster Ⅰ than in Cluster Ⅱ among all seasons. Although the chlorophyll-a concentration had great variations from place to place in Hong Kong's coastal waters, it seemed to have a common long term fluctuation period of 8-10 years with a high-low-high variation in the period in the whole region, which might be influenced by other factors of global scale.

Declined trends of chlorophyll a in the South China Sea over 2005–2019 from remote sensing reconstruction

Chlorophyll a concentration(CHL)is an important proxy of the marine ecological environment and phytoplankton production.Long-term trends in CHL of the South China Sea(SCS)reflect the changes in the ecosystem’s productivity and functionality in the regional carbon cycle.In this study,we applied a previously reconstructed 15-a(2005–2019)CHL product,which has a complete coverage at 4 km and daily resolutions,to analyze the long-term trends of CHL in the SCS.Quantile regression was used to elaborate on the long-term trends of high,median,and low CHL values,as an extended method of conventional linear regression.The results showed downward trends of the SCS CHL for the 75th,50th,and 25th quantile in the past 15 a,which were−0.0040 mg/(m^(3)·a)(−1.62%per year),−0.0023 mg/(m^(3)·a)(−1.10%per year),and−0.0019 mg/(m^(3)·a)(−1.01%per year).The negative trends in winter(November to March)were more prominent than those in summer(May to September).In terms of spatial distribution,the downward trend was more significant in regions with higher CHL.These led to a reduced standard deviation of CHL over time and space.We further explored the influence of various dynamic factors on CHL trends for the entire SCS and two typical systems(winter Luzon Strait(LZ)and summer Vietnam Upwelling System(SV))with single-variate linear regression and multivariate Random Forest analysis.The multivariate analysis suggested the CHL trend pattern can be best explained by the trends of wind speed and mixed-layer depth.The divergent importance of controlling factors for LZ and SV can explain the different CHL trends for the two systems.This study expanded our understanding of the long-term changes of CHL in the SCS and provided a reference for investigating changes in the marine ecosystem.

Distribution of dissolved oxygen and causes of maximum concentration in the Bering Sea in July 2010

According to data obtained in the Bering Sea during the 4th Chinese National Arctic Research Expedition, the distribution of dissolved oxygen （DO） was studied, causes of its maximum concentration were discussed, and the relationships between DO and other parameters, such as saliniW, temperature, and chlorophyll a were analyzed. The results showed DO concentration ranged from 0.53 to 12.05 mg/L in the Bering Sea basin. The upper waters contained high concentrations and the maximum occurred at the depth range from 20 to 50 m. The DO concentration decreased rapidly when the depth was deeper than 200 m and reached the minimum at the depth range from 500 to 1000 m, and then increased slowly with the depth increasing but still kept at a low level. On the shelf, the DO concentration ranged from 6.53 to 16.63 mg/L with a mean value of 10.75 mg/L, and showed a characteristic of decreasing from north to south. The DO concentration was higher in the area between the Bering Sea and Lawrence Island and was lower in the southeast and southwest of Lawrence Island at the latitude of 62°N. The formation of maximum DO concentration was concerned with phytoplankton photosynthesis and formation of the themocline. To the south of Sta. B07 in the Bering Sea basin, the oxygen produced by photosynthesis permeated to the deeper water and the themocline made it difficult to exchange vertically, and to the north of Sta. B07, the maximum DO concen- tration occurred above the themocline due to phytoplankton activities. On the shelf, the oxygen produced by phytoplankton photosynthesis gathered at the bottom of the thermocline and formed the DO maximum concentration. In the Bering Sea basin, the DO and salinity showed a weak negative correlation （r=0.40） when the salinity was lower than 33.1, a significant negative correlation （r=-0.92） when the salinity ranged from 33.1 to 33.7, and an irregular reversed parabola （r=0.95） when the salinity was greater than 33.7. Key words： Bering Sea, dissolved oxygen, maximum concentration, stratification, chlorophyll a

Spectral Geometric Triangle Properties of Chlorophyll-A Inversion in Taihu Lake Based on TM Data

The main objective of this study was to develop and validate the applicability of the Area Chlorophyll-a Concentration Retrieved Model (ACCRM), Height Chlorophyll-a Concentration Retrieved Model (HCCRM), Angle Chlorophyll-a Concentration Retrieved Model (AgCCRM), and Ratio Model of TM2/TM3 (RM) in estimating the chlorophyll-a concentration in Case II water bodies, such as Taihu Lake in Jiangsu Province, China. Water samples were collected from 23 stations on the 27th and 28th of October, 2003. The four empirical models were calibrated against the calibration dataset (samples from 19 stations) and validated using the validation dataset (samples from 4 stations). The regression analysis showed higher correlation coefficients for the ACCRM and the HCCRM than for the AgCCRM and the Ratio Model;and the HCCRM was slightly superior to the ACCRM. The performance of the ACCRM and the HCCRM was validated, and the ACCRM underestimated concentration values more than the HCCRM. The distribution of chlorophyll-a concentrations in Taihu Lake on October 27, 2003 was estimated based on the Landsat/TM data using the ACCRM and the HCCRM. Both models indicated higher chlorophyll-a concentrations in the east, north and center of the lake, but lower concentrations in the south. The accuracy of results obtained from the HCCRM and the ACCRM were also supported by the validation dataset. The study revealed that the HCCRM and the ACCRM had the best potential for accurately assessing the chlorophyll-a concentration in the highly turbid water bodies.

Response of Chlorophyll a, SPAD Values and Chlorophyll Fluorescence Parameters in Leaves of Apricot Affected Some Abiotic Factors

Experimental trail conducted in Jasenica, Bosnia and Herzegovina have showed apricot （Prunus persica L） leaf injures especially on the edges in the middle of the season. Leaf edges show chlorosis starting from the tip due to lack of Chlorophyll. Affected leaves start falling and renew leaves masse as respond to stress conditions which also delay fruits maturation. Technological development in detecting the stress of high plants trough the leaf fluorescence and Chlorophyll concentration have led to the introduction of instruments which utilize fluorescence as a basis for determining stress level. The paper was aimed to show whether the productivity values calculated from Chlorophyll fluorescence Fv/Fm were comparable to those produced by spectrophotometric method in detecting Chlorophyll a concentration and SPAD values detected by Chlorophyll meter （SPAD-502）. Measurements of nitrogen content were also provided in order to obtain accuracy of SPAD meter since Chlorophyll molecules contain nitrogen in their structure. To test the relationship between these three technique regression relationship was obtained. Regression coefficient between Fv/Fm values and Chlorophyll a concentration mg g-t was high. Also, strong regression coefficient was observed between Chlorophyll a and SPAD values indicating a good accuracy of this device which was also confirmed by good regression between nitrogen content and SPAD values. Fluorometer measurements on injured leaves samples of apricot have also reviled the Fv/Fm values below 0.83 which is in according with numerous authors who considered a line for indicating stress factors.

典型自然源气溶胶沉降引起的海洋初级生产响应

大气沉降是陆源物质向海洋输入营养盐的重要方式,沙尘、野火和火山喷发均能够产生气溶胶,这些典型的自然源气溶胶在风场的作用下,能够进行远距离的输运,期间由于沉降作用进入海洋,为上层海洋提供限制性营养盐促进海洋浮游植物生长,提升海洋的初级生产力,促进碳循环过程。以海表叶绿素浓度作为海洋初级生产力的重要指标,通过海表叶绿素浓度的响应,探究沙尘、野火和火山这三种典型自然源气溶胶的传输路径及其沉降对海洋初级生产的影响。结果显示,海洋初级生产对气溶胶沉降的响应不仅与气溶胶排放类型有关,也与温度、动力过程、光合有效辐射等海域初级生产影响因素有关,体现了海洋初级生产对自然源气溶胶的敏感性,自然源气溶胶沉降所驱动的海洋初级生产在全球碳循环中具有重要的潜在影响。

MRMR-SA-EGA-ELM的叶绿素a浓度预测模型研究

为提高叶绿素a浓度的预测精度,以南太湖区域-湖州市新塘港2020年5月至11月份的水质监测数据为原始样本数据,使用最大相关最小冗余算法(MRMR)从原始样本数据中选取效果更优的特征值,作为预测模型的输入数据,将精英遗传算法(EGA)与模拟退火算法(SA)组合优化极限学习机(ELM)网络的初始参数,最终构建MRMR-SA-EGA-ELM叶绿素a浓度预测模型。实验结果表明,MRMR-SA-EGA-ELM模型预测叶绿素a浓度的平均绝对误差(MAE)、均方误差(MSE)、决定系数(R^(2))分别为1.009、1.607、0.903,而ELM模型预测结果的MAE、MSE、R^(2)分别为2.078、8.249、0.562,MRMR-SA-EGA-ELM模型的效果得到显著提升,可实现对叶绿素a浓度的准确预测。

基于空间插值的长江口邻近海域春季悬浮物和叶绿素a空间分布分析

针对目前利用实测数据对长江口邻近海域水质状况进行分析研究相对偏少的情况,基于“淞航”号2018年春季航次对该海域的综合观测,利用实验室水样分析数据对船载温盐深仪(CTD)的测量数据进行校正,并对该区域2018年春季时节悬浮物(TSM)和叶绿素a(Chl-a)浓度的空间插值结果进行分析。研究结果表明:CTD观测数据与水样分析数据呈较强线性相关关系。反距离权重插值对TSM和Chl-a浓度空间分布具有整体最优的效果。TSM浓度在近岸和近海底较高,在观测区域内出现两个高值中心;Chl-a浓度在近岸海域较高,有较明显的片状高值结构,垂向上表层较高。TSM与Chl-a浓度分布在长江口南北表现出不同的特征,且两者具有一定的负相关性。长江径流、外海洋流、潮汐混合等水动力过程是影响该区域TSM和Chl-a浓度分布的主要因素。

北部湾叶绿素a浓度时空变化及影响因素

【目的】研究北部湾表层叶绿素a质量浓度的时空分布及其影响因子,为北部湾初级生产力评估及深远海养殖提供依据。【方法】基于2003-2020年逐月卫星遥感叶绿素a质量浓度、海表面温度(SST)、降雨数据以及再分析风场数据,利用经验正交分解(EOF)、小波相干等方法分析SST、降雨、风等环境因子对北部湾叶绿素a质量浓度的影响。【结果与结论】北部湾叶绿素a质量浓度呈近岸高、中央低的空间分布规律。年际变化特征明显,2016年为浓度峰值年,平均质量浓度为1.6 mg·m^(-3),2010年质量浓度最低,仅为1.1 mg·m^(-3)。在季节变化方面,北部湾区域平均叶绿素a质量浓度冬季最高,春季浓度最低,涠洲岛南侧海域平均叶绿素a质量浓度冬季最高,夏季节最低。红河河口区域夏、秋叶绿素a质量浓度高于春、冬叶绿素a质量浓度。长山山脉东侧区域平均叶绿素a质量浓度在秋季最高,在春季最低。月变化方面,北部湾叶绿素a质量浓度在5月最低,12月最高。海表面温度、降雨和风是影响北部湾叶绿素a质量浓度时空分布的主要因素。在北部湾的中、东海域,海表面温度与叶绿素a质量浓度显著负相关(P <0.05,r <-0.8)。降雨的影响主要集中在湾西部,降雨增加的径流量提供更多营养物质,使红河河口区域夏、秋季叶绿素a质量浓度较高,长山山脉东岸区域叶绿素a质量浓度在秋季达到峰值。风速与北部湾叶绿素a质量浓度显著正相关(P <0.01,r=0.4)。

利用Sentinel-2卫星影像反演骆马湖叶绿素a浓度

本文利用2023年6月15日采集的骆马湖水质参数、光谱数据和同期Sentinel-2影像数据,构建了基于数学统计和机器学习方法的水质反演模型,并对骆马湖叶绿素a(Chl-a)浓度进行了定量反演。通过对比分析,选定了性能最优的模型分析骆马湖Chl-a浓度状况。研究发现,Chl-a浓度与Sentinel-2影像B5和B9波段表现出较高的相关性,且经波段组合处理后,相关性进一步提升。在Chl-a反演模型中,FA-SVR模型相较于传统数学统计回归模型及其他机器学习模型(FA-RF、FA-XGBoost)表现出最高的精度(R^(2)=0.86,RMSE=2.77,MAE=2.10)。反演结果揭示,骆马湖东北部近岸区域的Chl-a浓度较高,这可能与北部水域存在鱼塘养殖、水体富营养高有关。本文突显了机器学习技术在提升水质遥感反演精度方面的重要应用价值,为湖泊水质监控和管理提供了重要的技术支撑。

基于AGA-RBF神经网络模型的叶绿素a质量浓度预测研究

叶绿素a质量浓度是预测湖泊水华形成的重要影响因子,但常用的径向基(radial basis function,RBF)神经网络存在容易陷入局部极值,导致预测精度欠佳.针对这一问题,采用自适应遗传算法(adaptive genetic algorithm,AGA)对RBF神经网络进行优化,构建基于AGA-RBF神经网络预测模型,以莆田东圳水库为应用案例,对叶绿素a质量浓度进行预测,通过采集到的数据对预测模型进行仿真,对比均方根误差(RMSE)、相对误差(RE)以及平均相对误差(MRE),验证改进后的AGA-RBF模型具有更好的预测精度,以期对叶绿素a质量浓度进行长期预测.

海水表层叶绿素a及悬移质浓度的激光雷达初步探测实验研究

针对海水表层叶绿素a和悬移质浓度在线监测的实际需求,设计并研发了一套双视场海洋激光雷达系统。首先利用实验水槽,在实验室开展了叶绿素a浓度测量实验,其结果与叶绿素荧光计/浊度计测量结果的相关系数为0.94,且不同激光发射能量下测量的叶绿素a的浓度值与叶绿素荧光计/浊度计的结果也趋于一致;同时对不同粒径的悬移质浓度进行了测量,其结果与叶绿素荧光计/浊度计测量结果的相关系数优于0.91。进而利用海洋激光雷达对青岛近海海水表层叶绿素a和悬移质浓度进行了现场观测,其测量结果与叶绿素荧光计/浊度计测量结果的相关系数分别为0.74和0.86,初步验证了自研海洋激光雷达应用于海水表层叶绿素a与悬移质浓度探测上的可行性。

pH和镁离子协同作用对茶树叶绿素合成的影响

【目的】探明土壤pH与镁离子协同作用下茶树叶绿素的合成规律,为茶树栽培及新品种选育提供理论基础。【方法】以福鼎大白茶为研究对象,采用植物组织酶活性试剂盒测定土壤不同pH[pH 4(P_(1))、pH 5(P_(2))]和不同镁离子浓度[0 mg/L(T_(0),CK)、50 mg/L(T_(1))、100 mg/L(T_(2))、150 mg/L(T_(3))]协同作用下茶树叶绿素合成关键酶——镁离子螯合酶、尿卟啉原Ⅲ合酶和5-氨基酮戊酸脱水酶的活性,并采用高通量技术对各处理福鼎大白茶叶片组织进行转录组测序,在此基础上研究土壤pH与镁离子协同作用对茶树叶绿素合成的影响。【结果】土壤pH与镁离子协同作用对茶树叶绿素合成关键酶——镁离子螯合酶、尿卟啉原Ⅲ合酶和5-氨基酮戊酸脱水酶活性的影响存在差异。其中,P_(2)T_(1)的镁离子螯合酶、尿卟啉原Ⅲ合酶及5-氨基酮戊酸脱水酶活性均最高,分别为492.41、336.28和132.24 U/L;GO和KEGG功能富集分析显示,福鼎大白茶叶片组织发育过程中的关键调控基因主要参与碳水化合物代谢、多糖代谢等过程,差异表达基因主要富集在淀粉和蔗糖代谢、二苯乙烯类等途径;KEGG代谢通路光合作用碳固定途径分析结果显示,P_(2)T_(1)能显著提高茶树的碳固定途径,同时对光合作用和糖类积累均有促进作用。【结论】P_(2)T_(1)(pH 5和镁离子浓度50 mg/L)协同作用对茶树叶绿素合成最好,有利于物质的合成和累积,并能提高茶树的产量和品质。