An analysis on the formation mechanism of the distributionof high content of chlorophyll-a in the continentalshelf edge waters of East China Sea

On the basis of the data obtained from the comprehensive Kuroshio surveys in 1987-1988,this paper analyses the oceanographic characteristics in the area (125°-130° E,27°-31° N) of the continental shelf edge of the East China Sea (E. C. S. ) and its adjacent waters and discusses the effects of the Kuroshio front,thermocline and upwelling of the Kuroshio subsurface water on the distribution of standing stock of phytoplankton (chlorophyll-a). The distribution of high content of chlorophylly-a has been detected at 20-50 in depth in the water body on the left side of the Kuroshio front in the continental shelf edge waters of the E. C. S. The high content of chlorophyll-a spreads from the shelf area to the Kuroshio area in the form of a tongue and connects with the maximum layer of subsurface chlorophyll-a of the Kuroshio and pelagic sea. The author considers that the formation of the distribution of high content chlorophyll-a in this area results from the bottom topography and oceanic environment and there are close correlations between the high content of chlorophyll-a and the light-nutrient environment.

Estimation of chlorophyll-a concentration in the Zhujiang Estuary from SeaWiFS data

The chlorophyll-a concentration is generally overestimated for the southern China coastalwaters if the default algorithm of the SeaDAS is employed. An algorithm is developed for retrieval of chlorophyll-a concentration in the Zhujiang Estuary, Guangdong Province, China, by using simulated reflectance data. The simulated reflectance is calculated corresponding to the SeaWiFS wavelength bands, via a general model by inputting measured water components, i.e. , the suspended sediment, chlorophyll-a, and yellow substance (DOC) concentration data of 130 samples. Empirical relationships of the chlorophyll-a concentration to 240 different band combinations are investigated based on the simulated reflectance data, and the band combination, R_5R_5/R_3R_4, is found to be the optimum one for the development of an algorithm valid for the Zhujiang Estuary. This algorithm is then employed to determine the chlorophyll-a concentration from SeaWiFS data. The estimated concentrations have a better accuracy than those obtained from the SeaDAS default algorithm when compared with sea truth data. The new algorithm is demonstrated to work well and is used to derive a series of image maps of the chlorophyll-a concentration distribution for the Zhujiang Estuary and adjacent coastal areas.

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.

Phytoplankton size class derived from phytoplankton absorption and chlorophyll-a concentrations in the northern South China Sea

A previously developed model was modified to derive three phytoplankton size classes (micro-, nano-, and pico-phytoplankton) from the overall chlorophyll-a concentration, assuming that each class has a specific absorption coefficient. The modified model performed well using in-situ data from the northern South China Sea, and the results were reliable and accurate. The relative errors of the size-fractioned chlorophyll-a concentration for each size class were: micro-:21%, nano-:41%, pico-:26%, and nano+pico:23%. The model was then applied on ocean color remote sensing data to examine the distribution and variation of phytoplankton size classes in northern South China Sea on a large scale.

A field study on the conversion ratio of phytoplankton biomass carbon to chlorophyll-a in Jiaozhou Bay,China

A one-year field study was conducted to determine the conversion ratio of phytoplankton biomass carbon （Phyto-C） to chlorophyll-a （Chl-a） in Jiaozhou Bay, China. We measured suspended particulate organic carbon （POC） and phytoplankton Chl-a samples collected in surface water monthly from March 2005 to February 2006. The temporal and spatial variations of Chl-a and POC concentrations were observed in the bay. Based on the field measurements, a linear regression model Ⅱwas used to generate the conversion ratio of Phyto-C to Chl-a. In most cases, a good linear correlation was found between the observed POC and Chl-a concentrations, and the calculated conversion ratios ranged from 26 to 250 with a mean value of 56 μg ·μl^-1. The conversion ratio in the fall was higher than that in the winter and spring months, and had the lowest values in the summer. The ratios also exhibited spatial variations, generally with low values in the near shore regions and relatively high values in offshore waters. Our study suggests that temperature was likely to be the main factor influencing the observed seasonal variations of conversion ratios while nutrient supply and light penetration played important roles in controlling the spatial variations.

Tempo-spatial Variation of Nutrient and Chlorophyll-a Concentrations From Summer to Winter in the Zhangzi Island Area (Northern Yellow Sea)

Nutrient and Chlorophyll-a （Chl-a） concentrations were investigated monthly along three transects extending from a mariculturc area to open waters around the Zhangzi Island area from July to December 2009. The objective of this study is to illus- trate food availability to the bottom-sowed scallop Patinopecten yessoensis under the influences of the Yellow Sea Cold Water Mass （YSCWM）, freshwater input and feedbacks of cultivated scallops. Significant thermal stratification was present in open waters from July to October, and salinity decreased in July and August in surface layers in the mariculture area. Nutrient concentrations increased with depth in both areas in summer, but were similar through water column in November and December. On average, nutrient in- creased from summer to autumn in all components except ammonia. Nutrient concentrations lower than the minimum thresholds for phytoplankton growth were present only in upper layers in summer, but stoichiometric nitrogen limitation existed in the entire inves- tigation period. Column-averaged Chl-a concentration was lower in open waters than in mariculture area in all months. It increased significantly in mariculturc area in August and October, and was less variable in open waters. Our results show that nutrients limita- tion to phytoplankton growth is present mainly in upper layer in association with stratification caused by YSCWM in summer. Freshwater input and upwelling of nutrients accumulated in YSCWM can stimulate phytoplankton production in mariculture area. Farming activities may change stoichiometric nutrient ratios but have less influence on Chl-a concentration.

Application of Bayesian regularized BP neural network model for analysis of aquatic ecological data—A case study of chlorophyll-a prediction in Nanzui water area of Dongting Lake

Bayesian regularized BP neural network（BRBPNN） technique was applied in the chlorophyll-α prediction of Nanzui water area in Dongting Lake. Through BP network interpolation method, the input and output samples of the network were obtained. After the selection of input variables using stepwise/multiple linear regression method in SPSS i1.0 software, the BRBPNN model was established between chlorophyll-α and environmental parameters, biological parameters. The achieved optimal network structure was 3-11-1 with the correlation coefficients and the mean square errors for the training set and the test set as 0.999 and 0.000？8426, 0.981 and 0.0216 respectively. The sum of square weights between each input neuron and the hidden layer of optimal BRBPNN models of different structures indicated that the effect of individual input parameter on chlorophyll- α declined in the order of alga amount 〉 secchi disc depth（SD） 〉 electrical conductivity （EC）. Additionally, it also demonstrated that the contributions of these three factors were the maximal for the change of chlorophyll-α concentration, total phosphorus（TP） and total nitrogen（TN） were the minimal. All the results showed that BRBPNN model was capable of automated regularization parameter selection and thus it may ensure the excellent generation ability and robustness. Thus, this study laid the foundation for the application of BRBPNN model in the analysis of aquatic ecological data（chlorophyll-α prediction） and the explanation about the effective eutrophication treatment measures for Nanzui water area in Dongting Lake.

Relationships of Dissolved Oxygen with Chlorophyll-a and Phytoplankton Composition in Tilapia Ponds

This study investigated the relationships among the parameters of dissolved oxygen, chlorophyll-a and phytoplankton composition in tilapia ponds. Each pond (a total of 18 ponds) was sampled once in the dry, winter season between January and March and again early in the rainy season between May and June. The data were analyzed by examining correlations among parameters as affected by season, altitude and culture system. Observations were made at sites located in 5 selected provinces of northern Thailand: Chiangrai, Chiangmai, Phayao, Lampang and Nakornsawan. Mean elevation of these areas range from 25 to 582 meters above sea level (masl) and were categorized into low (400 masl) elevation sites. Ponds were 0.8 - 2.0 m deep, 0.16 - 0.64 ha in area and could be further categorized into high and low input systems.Mean air temperature in winter ranged between 16.5°C - 35.8°C while mean water temperature ranged between 25.5°C - 27.1°C. In rainy season, air temperature ranged between 22.0°C - 37.3°C and water temperature ranged between 29.4°C - 31.8°C. The amount of chlorophyll-a in both seasons were comparable (p > 0.05), but chlorophyll-a in high input system was significantly higher (p 0.05) than in low input ponds. Only weak correlation was found between chlorophyll-a, DOmax and DOmin. Multifactor-ANOVA was used to analyze the difference of total bacteria and filamentous cyanobacteria in ponds based upon elevation, culture systems and season. Result shows that there is a significant interaction observed between elevation, culture system and season (p 0.05). Species diversity and composition of phytoplankton in fish ponds in 2 seasons revealed the presence of 90 genera of phytoplankton under all 7 divisions. Divisions Chlorophyta and Cyanophyta had the most number of genera identified in both seasons with Pediastrum spp., and Scendesmus spp., and Anabaena spp. as dominant genera/genus, respectively.

Effect of Chlorophyll-a Spatial Distribution on Upper Ocean Temperature in the Central and Eastern Equatorial Pacific

Effect of the spatial distributions of chlorophyll-a concentration on upper ocean temperature and currents in the equatorial Pacific is investigated through a set of numerical experiments by using an ocean general circulation model. This study indicates that enhanced meridional gradient of chlorophyll-a between the equator and off-equatorial regions can strengthen zonal circulation and lead to a decrease in equatorial sea surface temperature （SST）. However, the circulation changes by themselves are not effective enough to affect SST in the equatorial cold tongue （CT） region. The comparison between the experiments indicates that the CT SST are more sensitive to chlorophyll-a distribution away from the equator. The off-equatorial chlorophyll-a traps more solar radiation in the mixed layer, therefore, the temperature in the thermoeline decreases. The cold water can then be transported to the equator by the meridional circulation within the mixed layer. Furthermore, the relation among CT SST, the surface heat flux, and the equatorial upwelling are discussed. The study implies the simulation biases of temperature on the equator are not only related to the local ocean dynamics but also related to some deficiency in simulating off-equatorial processes.

Study on the Relationship between Chlorophyll-a and Environmental Impact Factors in Deep Reservoir in Karst Areas——Taking Aha Reservoir for Example

[Objective] The aim was to study the relationship between chlorophyll-a and environmental impact factors in deep reservoir in Karst Areas.[Method] Taking Aha Reservoir for example,the changes of chlorophyll-a content and its relationship with environmental impact factors were researched,and the water quality of Aha Reservoir was assessed by means of modified Carlson trophic state index.[Result] Chlorophyll-a content in Aha Reservoir was higher in March,April,May and September and lower from June to August,and there was obvious seasonal variation,namely its variation trend was spring>summer>autumn>winter.In addition,chlorophyll-a content showed extremely significant correlation with transparency and dissolved oxygen (P<0.01) and significant correlation with ammonia nitrogen (P<0.05).Meanwhile,trophic state index was higher in whole year in Aha Reservoir which was in moderate trophic state in August,October and November and eutrophic state in other months.[Conclusion] The study could provide scientific reference for discussing the mechanism of lake eutrophication.

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.

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.

Summer Monsoon Impacts on Chlorophyll-a Concentration in the Middle of the South China Sea:Climatological Mean and Annual Variability

Climatological mean and annual variations of Chlorophyll-a （Chl-a） distribution, sea surface wind （SSW）, and sea surface temperature （SST） from 1998 to 2008 were analyzed in the middle of the South China Sea （SCS）, focusing on the typical region off the east coast of Vietnam （8.5-14°N, 109.5-114°E）. Based on remote sensing data and SCS summer monsoon index （SCSSMI） data, high Chl-a concentrations in the middle of the SCS in the southwest summer monsoon season （June-September） may be related to strong Ekman pumping and strong wind stress. The maximum of the monthly averaged cli- matological Chl-a in the summer appeared in August. According to the annual variation, there was a significant negative correlation （r = -0.42） between the SCSSMI and SST, a strongly positive correlation （r=0.61） between the SCSSMI and Chl-a, and a strongly negative correlation （r = -0.74） between the SST and Chl-a in the typical region off the east coast of Vietnam during 1998-2008. Due to the E1 Nifio event specifically, the phenomena of a low Chl-a concentration, high SST and weak SCSSMI were extremely predominant in the summer of 1998. These relationships imply that the SCSSMI associated with the SST could be used to predict the annual variability of summer Chl-a in the SCS.

Combining Principal Component Regression and Artificial Neural Network to Predict Chlorophyll-a Concentration of Yuqiao Reservoir’s Outflow

In order to investigate the eutrophication degree of Yuqiao Reservoir, a hybrid method, combining principal component regression (PCR) and artificial neural network (ANN), was adopted to predict chlorophyll-a concentration of Yuqiao Reservoir’s outflow. The data were obtained from two sampling sites, site 1 in the reservoir, and site 2 near the dam. Seven water variables, namely chlorophyll-a concentration of site 2 at time t and that of both sites 10 days before t, total phosphorus(TP), total nitrogen(TN),...

Impact of Cyclone PHAILIN on Chlorophyll-a Concentration and Productivity in the Bay of Bengal

Ocean colour remote sensing is one of the conventional methods in satellite oceanography used to study the biological response of the upper ocean to the tropical cyclones. This paper aims to study the impact of the Very Severe Cyclonic storm PHAILIN, and its consequence on the surface chlorophyll-aconcentration distribution in the Bay of Bengal using Oceansat-2 Ocean Colour Monitor (OCM). The impact of this cyclone on ocean primary productivity has been studied using MODIS-A data. Sea surface temperature (SST) plays an important role in the generation of primary productivity along with the other oceanographic parameters;SST patterns in the Bay of Bengal during the cyclone period were studied. From the analysis, it is observed that the chlorophyll-aconcentration has increased from 1.08 (before) to 7.06 mg/m3 after the cyclone with an SST drop of ~3°C (29.19°C to 26°C). The primary productivity has increased from 410.0506 to 779.9814 mg/C/m2/day after the cyclone. In addition to the above analysis, an attempt has also been made to study the impact of cyclone intensity on the chlorophyll concentration. The study shows that the comparison between cyclone intensity (CI) and chlorophyll concentration shows a positive relationship.

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.

Improved the Prediction of Multiple Linear Regression Model Performance Using the Hybrid Approach: A Case Study of Chlorophyll-a at the Offshore Kuala Terengganu, Terengganu

Efficiency and precision in prediction of Chlorophyll-a using this model is still a pandemic among researchers, due to the natural conditions in ocean water systems itself, which involved chemical, biological and physical processes and interaction among them may affect the model performance drastically. Thus, to overcome this problem as well as to improve the strength of MLR, we proposed a hybrid approach, i.e., an Artificial Neural Network to the MLR coins as Artificial Neural Network-Multiple Linear Regression (ANN-MLR). To investigate the performance of the proposed model, we compared Multiple Linear Regression (MLR), Artificial Neural Network (ANN) and proposed hybrid Artificial Neural Network and Multiple Linear Regression (ANN-MLR) in the prediction of chlorophyll-a (chl-a) concentration by statistical measurement which are MSE and MAE. Achieving our objectives of study, we used 4 parameters, i.e. temperature (°C), pH, salinity (ppt), DO (ppm) at the Offshore Kuala Terengganu, Terengganu, Malaysia. The results showed that our proposed model can improve the performance of the model as compared to ANN and MLR due to small errors generated, error reduced, and increased the correlation coefficient for all parameters in both MSE and MAE, respectively. Thus, this result indicated that our proposed model is efficient, precise and almost perfect correlation as compared to ANN and MLR.

Pre and Post Effects Assessment of Marine Ranch Construction in Chlorophyll-a Concentration Using MODIS Data and a Web-Based Tool. A Case Study in Zhelin Bay, China

Chlorophyll-a (Chl-a) concentration in lakes can tell a lot about a lake’s water quality and ecosystem. It is a measure of the amount of algae growing in a waterbody and can be used to monitor the trophic condition of a waterbody. We studied the pre and post effects of marine ranch construction in Chl-a concentration in Zhelin Bay, Southern China using Normalized Difference Chlorophyll Index (NDCI) and a web-based tool (https://mapcoordinates.info/). We used 8 day composite MODIS image collections of 500 m resolution and randomly selected two stations to extract the chlorophyll-a concentration values through the web-based tool. We recorded the slight increase in NDCI values in all stations after the construction of marine ranch which is a good indicator of the marine organisms’ reproduction and survival.

Periodically hydrologic alterations decouple the relationships between physicochemical variables and chlorophyll-a in a dam-induced urban lake

Periodically hydrologic alterations driven by seasonal change and water storage capacity management strongly modify physicochemical properties and chlorophyll-a(Chl-a)and their interactions in dam-induced lakes.However,the extent and magnitude of these changes still remain unclear.This study aimed to determine the effects of periodically hydrologic alterations on physicochemical variables and Chl-a in the dam-induced urban Hanfeng Lake,upstream of Three Gorges Reservoir.Shifts in Chl-a and 13 physicochemical variables were recorded monthly in the lake from January 2013 to December 2014.Chl-a was neither seasonal nor inter-annual differences while a few physical variables such as flow velocity(V)exhibited significantly seasonal variabilities,and chemical variables like total nitrogen(TN),nitrate-nitrogen(NO3-N),total phosphorus(TP),dissolved silica(DSi)were markedly inter-annual differences.Higher TN:TP(40:1)and lower NO3-N:DSi(0.8:1)relative to balanced stoichiometric ratios suggested changes in composition of phytoplankton communities and potentially increased proportion of diatom in Hanfeng Lake.Chl-a was predicable by combination of dissolved oxygen(DO),TN and DSi in dry season,and by V alone in wet season.During the whole study period,Chl-a was solely negatively correlated with TN:TP,indicating decline in N concentration and increase in P could therefore increase Chl-a.Our results highlight pronounced decoupling of linkages between Chl-a and physicochemical variables affected by periodically hydrologic alterations in dam-induced aquatic systems.

Bathymetrical influences on spatial and temporal characteristics of chlorophyll-a concentrations in the Southern Ocean from 2002 to 2012(October to March)using MODIS

Phytoplankton blooms,particularly in the Southern Ocean,can have significant impact on global biogeochemistry cycling.To investigate the accuracy of chlorophyll-a distribution,and to better understand the spatial and temporal dynamics of phytoplankton biomass,we examine chlorophyll-a estimates(October-March from 2002 to 2012)derived from Moderate Resolution Imaging Spectrometer(MODIS)data following the ocean chlorophyll-a 3 model(OC3M)algorithm.Noticeable seasonality occurs in the temporal distribution of chlorophyll-a concentrations,which shows the highest value in December and January and an increasing tendency during the 2002-2012 period.The spatial distribution of chlorophyll-a varies greatly with latitude,as higher latitudes experience more phytoplankton blooms(chlorophyll-a concentration larger than 1 mg/m3)and marginal seas(Ross Sea and Amundsen Sea)show different bloom anomalies caused by two dominant algae species.Areas at higher latitudes and shallow water(<500 m)experience the shorter icefree periods with greater seasonality.A noticeable bathymetry gradient exists at 2500-m isobaths,while water at the 500-2500-m depth experiences quite long ice-free periods with a stable water environment.Blooms generally occur near topographic features where currents have strong interactions when the water depth is more than 2500 m.Based on these findings,we can classify the Southern Ocean into two bloom subregions,0-500 m as an enhanced bloom zone(EBZ),and 500-2500 m as a moderate bloom zone(MBZ).The EBZ has a quite high-bloom probability of about 30%,while the MBZ has only 10%.