Spatiotemporal Variation of Chlorophyll a and its Relationship with other Water Quality Factors in the Tai Lake

2011 ◽  
Vol 183-185 ◽  
pp. 783-789
Author(s):  
Xing Cai Liu ◽  
Zong Xue Xu ◽  
Guo Qiang Wang
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Temporal Variations ◽  
Quality Factors ◽  
Mean Values ◽  
Chl A ◽  
Four Seasons ◽  
Tai Lake ◽  
Sample Data ◽  
Meiliang Bay

Algae bloom in the Tai Lake is a major issue and affects the water supply to the surrounding cities greatly. Chlorophyll a (Chl-a) is a common indicator that represent the trophic status in lakes. Spatial and temporal variations of Chl-a concentration are analyzed on the basis of sample data at 21 sites during the period of 2001 to 2005. Data at the sites located in the Meiliang Bay, Zhushan and Wulihu show greater fluctuations than that at other sites. A general trend showing that high values in northern part and low values in southern part of the Tai Lake is observed in seasonal mean values of Chl-a concentration for four seasons. Most high Chl-a concentrations occurred in summer (June to August) and autumn (September to November). Quantitative relationships between Chl-a and other water quality factors are investigated at all sites. Relative good relationships are obtained between Chl-a concentration and other water quality factors during 2001 to 2004 by using partial least squared regression. Prediction of Chl-a concentration in 2005 with above models produce worse results, which may be due to the occurrence of some extreme high values of Chl-a concentration in that year. Even though, acceptable predictions are obtained at several sites. Since the water quality in the lake is affected greatly by the inflow of nutrients from rivers, these relationships will be helpful for monitoring Chl-a variation with the combination of hydrological models that is able to simulate the inflow of nutrients.

scholarly journals Temporal Variation of Chlorophyll-a Concentrations in Highly Dynamic Waters from Unattended Sensors and Remote Sensing Observations

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2699 ◽  
Author(s):  
Jian Li ◽  
Liqiao Tian ◽  
Qingjun Song ◽  
Zhaohua Sun ◽  
Hongjing Yu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Chlorophyll Fluorescence ◽  
Chlorophyll A ◽  
Temporal Variations ◽  
Lake Area ◽  
Short Term ◽  
Chl A ◽  
Spatio Temporal

Monitoring of water quality changes in highly dynamic inland lakes is frequently impeded by insufficient spatial and temporal coverage, for both field surveys and remote sensing methods. To track short-term variations of chlorophyll fluorescence and chlorophyll-a concentrations in Poyang Lake, the largest freshwater lake in China, high-frequency, in-situ, measurements were collected from two fixed stations. The K-mean clustering method was also applied to identify clusters with similar spatio-temporal variations, using remote sensing Chl-a data products from the MERIS satellite, taken from 2003 to 2012. Four lake area classes were obtained with distinct spatio-temporal patterns, two of which were selected for in situ measurement. Distinct daily periodic variations were observed, with peaks at approximately 3:00 PM and troughs at night or early morning. Short-term variations of chlorophyll fluorescence and Chl-a levels were revealed, with a maximum intra-diurnal ratio of 5.1 and inter-diurnal ratio of 7.4, respectively. Using geostatistical analysis, the temporal range of chlorophyll fluorescence and corresponding Chl-a variations was determined to be 9.6 h, which indicates that there is a temporal discrepancy between Chl-a variations and the sampling frequency of current satellite missions. An analysis of the optimal sampling strategies demonstrated that the influence of the sampling time on the mean Chl-a concentrations observed was higher than 25%, and the uncertainty of any single Terra/MODIS or Aqua/MODIS observation was approximately 15%. Therefore, sampling twice a day is essential to resolve Chl-a variations with a bias level of 10% or less. The results highlight short-term variations of critical water quality parameters in freshwater, and they help identify specific design requirements for geostationary earth observation missions, so that they can better address the challenges of monitoring complex coastal and inland environments around the world.

scholarly journals Temporal and Spatial Variations of Chlorophyll a Concentration and Eutrophication Assessment (1987–2018) of Donghu Lake in Wuhan Using Landsat Images

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2192
Author(s):  
Xujie Yang ◽  
Yan Jiang ◽  
Xuwei Deng ◽  
Ying Zheng ◽  
Zhiying Yue
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Chlorophyll A ◽  
Dynamic Monitoring ◽  
Water Quality Parameter ◽  
Landsat Images ◽  
Chl A ◽  
Donghu Lake ◽  
Cubic Model

Chlorophyll a (Chl-a) concentration, which reflects the biomass and primary productivity of phytoplankton in water, is an important water quality parameter to assess the eutrophication status of water. The band combinations shown in the images of Donghu Lake (Wuhan City, China) captured by Landsat satellites from 1987 to 2018 were analyzed. The (B4 − B3)/(B4 + B3) [(Green − Red)/(Green + Red)] band combination was employed to construct linear, power, exponential, logarithmic and cubic polynomial models based on Chl-a values in Donghu Lake in April 2016. The correlation coefficient (R2), the relative error (RE) and the root mean square error (RMSE) of the cubic model were 0.859, 9.175% and 11.194 μg/L, respectively and those of the validation model were 0.831, 6.509% and 19.846μg/L, respectively. Remote sensing images from 1987 to 2018 were applied to the model and the spatial distribution of Chl-a concentrations in spring and autumn of these years was obtained. At the same time, the eutrophication status of Donghu Lake was monitored and evaluated based on the comprehensive trophic level index (TLI). The results showed that the TLI (∑) of Donghu Lake in April 2016 was 63.49 and the historical data on Chl-a concentration showed that Donghu Lake had been eutrophic. The distribution of Chl-a concentration in Donghu Lake was affected by factors such as construction of bridges and dams, commercial activities and enclosure culture in the lake. The overall distribution of Chl-a concentration in each sub-lake was higher than that in the main lake region and Chl-a concentration was highest in summer, followed by spring, autumn and winter. Based on the data of three long-term (2005–2018) monitoring points in Donghu Lake, the matching patterns between meteorological data and Chl-a concentration were analyzed. It revealed that the Chl-a concentration was relatively high in warmer years or rainy years. The long-term measured data also verified the accuracy of the cubic model for Chl-a concentration. The R2, RE and RMSE of the validation model were 0.641, 2.518% and 22.606 μg/L, respectively, which indicated that it was feasible to use Landsat images to retrieve long-term Chl-a concentrations. Based on longitudinal remote sensing data from 1987 to 2018, long-term and large-scale dynamic monitoring of Chl-a concentrations in Donghu Lake was carried out in this study, providing reference and guidance for lake water quality management in the future.

Long-term effects of hydrometeorological and water quality conditions on algal dynamics in the Paldang dam watershed, Korea

2014 ◽  
Vol 14 (4) ◽  
pp. 601-608
Author(s):  
D.-W. Kim ◽  
J.-H. Min ◽  
M. Yoo ◽  
M. Kang ◽  
K. Kim
Keyword(s):  
Water Quality ◽  
Water Temperature ◽  
Chlorophyll A ◽  
Algal Bloom ◽  
Temporal Variations ◽  
Regulated River ◽  
Han River ◽  
Nutrient Levels ◽  
Short Period

The primary goal of this study is to shed light on some important factors that control algal bloom in a large-scale regulated river system. Long-term impacts of environmental conditions on algal dynamics were investigated in the Paldang dam watershed, Korea. Dam inflow, water temperature, chlorophyll-a, TN, PO4-P and TP data collected at five major dams located on the North Han River (NHR) and at four water quality monitoring sites on the South Han River were analyzed for 21 years (1992 to 2012) to examine spatio-temporal variations in each. A pattern of slightly increasing chlorophyll-a and nutrient levels in the NHR since 2001 indicates that algal dynamics were affected by the increased nutrient levels as well as the reduced flow conditions (−10% to −37%). The temporal variations in monthly averaged data collected during summer monsoon seasons (mainly July) over the two decades show that high chlorophyll-a levels observed in both rivers corresponded to the relatively lower flow condition, which means a reduced amount of dam water release due to low or no rainfall over a short period of time, and abnormally high water temperature. This study shows that flow control is most critical for effectively managing algal level in the rivers in the short term, and nutrient management in the watershed is the key to reducing the potential for algal bloom in the long term.

scholarly journals Limnology of wastewater treatment lagoons at Pagla, Narayanganj

1970 ◽  
Vol 40 (1) ◽  
pp. 35-40
Author(s):  
Md Ataul Gani ◽  
Md Almujaddade Alfasane ◽  
Moniruzzaman Khondker
Keyword(s):  
Water Quality ◽  
Wastewater Treatment ◽  
Population Density ◽  
Water Temperature ◽  
Significant Positive Correlation ◽  
Secchi Depth ◽  
Gradual Improvement ◽  
Mean Values ◽  
Chl A ◽  
Suspended Matters

Limnology of two wastewater treatment lagoons, (Lagoon numbers 1 and 10 are treated as L-1 and L-2, respectively) at Pagla, Narayanganj considering 15 water quality variables had been carried out for 10 months. Air and water temperature did not vary significantly. Secchi depth (Zs) showed gradual improvement from the lagoon 1 to lagoon 10 due to low loading of suspended matters. Improvement of water quality from L-1 to L-2 has also been observed in respect to alkalinity, conductivity and TDS. Similar trends were also seen for SRS and SRP. In L-1 anoxia occurred three times whereas it was absent in L-2. In the present study, improved DO prompted NO3-N and TDS concentration. However in L-2, mean values of SRP dropped by about 13% than L-1. A significant positive correlation between the density of phytoplankton and SRP in L-2 at 5% level was obtained. A total of 105 species of phytoplankton belonging to 6 different algal classes were recorded from the lagoons. Highest number of species was obtained from Chlorophyceae followed by Euglenophyceae, Bacillariophyceae, Cyanophyceae, Cryptophyceae and Dinophyceae. The population density of phytoplankton and that of zooplankton in L-1 was low compared to L-2. Higher number of genera and species occurred in L-2 than L-1. Chl a and pheopigment concentrations were also higher in L-2. Results indicated that water quality has increased in the treatment pond number 10. Key words: Limnology; Wastewater treatment lagoons; Pagla; Bangladesh DOI: http://dx.doi.org/10.3329/bjb.v40i1.7995 Bangladesh J. Bot. 40(1): 35-40, 2011 (June)

scholarly journals Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir

2017 ◽  
Vol 49 (5) ◽  
pp. 1608-1617 ◽  
Author(s):  
Matias Bonansea ◽  
Claudia Rodriguez ◽  
Lucio Pinotti
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Landsat Imagery ◽  
Quality Parameters ◽  
Landsat 8 ◽  
Chlorophyll A Concentration ◽  
Chl A ◽  
Sensing Applications ◽  
Wide Range ◽  
Quality Assessments

Abstract Landsat satellites, 5 and 7, have significant potential for estimating several water quality parameters, but to our knowledge, there are few investigations which integrate these earlier sensors with the newest and improved mission of Landsat 8 satellite. Thus, the comparability of water quality assessing across different Landsat sensors needs to be evaluated. The main objective of this study was to assess the feasibility of integrating Landsat sensors to estimate chlorophyll-a concentration (Chl-a) in Río Tercero reservoir (Argentina). A general model to retrieve Chl-a was developed (R2 = 0.88). Using observed versus predicted Chl-a values the model was validated (R2 = 0.89) and applied to Landsat imagery obtaining spatial representations of Chl-a in the reservoir. Results showed that Landsat 8 can be combined with Landsat 5 and 7 to construct an empirical model to estimate water quality characteristics, such as Chl-a in a reservoir. As the number of available and upcoming sensors with open access will increase with time, we expect that this trend will certainly further promote remote sensing applications and serve as a valuable basis for a wide range of water quality assessments.

scholarly journals Spatial Distributions and Model Selections of Commercial Estuarine Fish (Sciaenidae) Populations Related to Water Quality, Chl-a, and AML in Musi River mouth, South Sumatra

2021 ◽  
Vol 3 (2) ◽  
pp. 1-11
Author(s):  
Andriwibowo Andriwibowo ◽  
Adi Basukriadi ◽  
Erwin Nurdin
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
River Mouth ◽  
Estuarine Fish ◽  
Limiting Factor ◽  
Spatial Distributions ◽  
The West ◽  
Chl A ◽  
East River ◽  
River Mouths

Estuary and river mouth are essential habitats for many commercial estuarine fishes, including the Sciaenidae family. While recently, estuaries have been threatened by anthropogenic marine litter (AML) transported from nearby land and river. An important type of AML is plastic litter since it takes a long degradation time. In the South Sumatra Province, Indonesia, one of the vital estuaries is the Musi estuary. This paper aims to map the spatial distributions of two Sciaenids, including Panna microdon and Otolithoides pama, and Sciaenid’s environmental covariates, including water quality, chlorophyll a, and plastic litters in Musi estuary and model the correlations of Sciaenids with their covariates. The maps were developed using GIS, and the model was validated using AIC methods. The data were collected from 3 river mouths in the west, central, and east of the Musi estuary. The data showed that the populations of both Sciaenids were higher in the east river mouth rather than in the west. Sciaenid populations were positively correlated with high salinity, DO, chlorophyll a, moderate transparency, and low temperature. A high load of AML’s frequency (7.54 items/m2) and weights (36.8 gram/m2) has reduced both Sciaenid populations in the central river mouth of the estuary. In contrast, low AML loads in the east have correlated with high Sciaenid populations. Model selection based on AIC values shows the best model for P.microdon retained an effect of AML weight with AIC values of 22.591 and 28.321 for O. pama. This concludes that the weight of plastic litter in estuary water was the main limiting factor for Sciaenid populations in Musi.

scholarly journals A Deep Multitask Semisupervised Learning Approach for Chlorophyll-a Retrieval from Remote Sensing Images

2021 ◽  
Vol 14 (1) ◽  
pp. 18
Author(s):  
Melike Ilteralp ◽  
Sema Ariman ◽  
Erchan Aptoula
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Image Analysis ◽  
Chlorophyll A ◽  
Water Quality Assessment ◽  
Remote Sensing Image ◽  
Semisupervised Learning ◽  
Main Task ◽  
Chl A ◽  
Multitemporal Remote Sensing

This article addresses the scarcity of labeled data in multitemporal remote sensing image analysis, and especially in the context of Chlorophyll-a (Chl-a) estimation for inland water quality assessment. We propose a multitask CNN architecture that can exploit unlabeled satellite imagery and that can be generalized to other multitemporal remote sensing image analysis contexts where the target parameter exhibits seasonal fluctuations. Specifically, Chl-a estimation is set as the main task, and an unlabeled sample’s month classification is set as an auxiliary network task. The proposed approach is validated with multitemporal/spectral Sentinel-2 images of Lake Balik in Turkey using in situ measurements acquired during 2017–2019. We show that harnessing unlabeled data through multitask learning improves water quality estimation performance.

scholarly journals SATELLITE-MEASURED SPATIAL AND TEMPORAL CHLOROPHYLL-A VARIABILITY IN THE GULF OF TOMINI, SULAWESI

2009 ◽  
Vol 4 (2) ◽  
pp. 147
Author(s):  
I Nyoman Radiarta
Keyword(s):  
Chlorophyll A ◽  
Temporal Variations ◽  
Sea Surface ◽  
Spatial And Temporal Variability ◽  
Wide Field ◽  
Wind Condition ◽  
Marine Aquaculture ◽  
Chl A ◽  
Fisheries Resources ◽  
Aquaculture Development

Chlorophyll-a concentration, an index of phytoplankton biomass, is an important parameter for fisheries resources and marine aquaculture development. Spatial and temporal variability of surface cholophyll-a (chl-a) concentration and water condition in the Gulf of Tomini were investigated using monthly climatologies the Sea-viewing Wide Field-of-view sensor (SeaWiFS), sea surface temperature (SST), and wind data from January 2000 to December 2007. The results showed seasonal variation of chla and SST in the Gulf of Tomini. High chl-a concentrations located in the eastern part of the gulf were observed during the southeast monsoon in August. During the northwest monsoon, chl-a concentrations were relatively low (<0.2 mg m-3) and distributed uniformly throughout most of the region. Chl-a concentrations peaked in August at every year, and chl-a concentrations were observed low in November at every year from 2000 to 2007. SSTs were relatively high (> 28oC) during the northwest monsoon, but low during the southeast monsoon. High wind speed was coincided with high chl-a concentrations. Local forcing such as sea surface heating and wind condition are the mechanisms that controlled the spatial and temporal variations of chlorophyll concentrations.

scholarly journals ASSESSMENT OF SEAGRASS PERCENT COVER AND WATER QUALITY USING UAV IMAGES AND FIELD MEASUREMENTS IN BOLINAO, PANGASINAN

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 233-240
Author(s):  
M. K. M. R. Guerrero ◽  
J. A. M. Vivar ◽  
R. V. Ramos ◽  
A. M. Tamondong
Keyword(s):  
Water Quality ◽  
Regression Analysis ◽  
Chlorophyll A ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Support Vector ◽  
Percent Cover ◽  
Chl A ◽  
Relationship Of ◽  
The Relationship

Abstract. The sensitivity to changes in water quality inherent to seagrass communities makes them vital for determining the overall health of the coastal ecosystem. Numerous efforts including community-based coastal resource management, conservation and rehabilitation plans are currently undertaken to protect these marine species. In this study, the relationship of water quality parameters, specifically chlorophyll-a (chl-a) and turbidity, with seagrass percent cover is assessed quantitatively. Support Vector Machine, a pixel-based image classification method, is applied to determine seagrass and non-seagrass areas from the orthomosaic which yielded a 91.0369% accuracy. In-situ measurements of chl-a and turbidity are acquired using an infinity-CLW water quality sensor. Geostatistical techniques are utilized in this study to determine accurate surfaces for chl-a and turbidity. In two hundred interpolation tests for both chl-a and turbidity, Simple Kriging (Gaussian-model type and Smooth- neighborhood type) performs best with Mean Prediction equal to −0.1371 FTU and 0.0061 μg/L, Root Mean Square Standardized error equal to −0.0688 FTU and −0.0048 μg/L, RMS error of 8.7699 FTU and 1.8006 μg/L and Average Standard Error equal to 10.8360 FTU and 1.6726 μg/L. Zones are determined using fishnet tool and Moran’s I to calculate for the seagrass percent cover. Ordinary Least Squares (OLS) is used as a regression analysis to quantify the relationship of seagrass percent cover and water quality parameters. The regression analysis result indicates that turbidity has an inverse relationship while chlorophyll-a has a direct relationship with seagrass percent cover.

scholarly journals Estimation of chlorophyll-a concentration using Landsat 8 in the Cassaffousth reservoir

2019 ◽  
Vol 19 (7) ◽  
pp. 2021-2027 ◽  
Author(s):  
María Micaela Ledesma ◽  
Matías Bonansea ◽  
Claudia Rosa Ledesma ◽  
Claudia Rodríguez ◽  
Joel Carreño ◽  
...  
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Field Data ◽  
Warning System ◽  
Landsat 8 ◽  
Chl A ◽  
Physico Chemical ◽  
Regression Techniques ◽  
Remote Sensing Techniques

Abstract The physico-chemical and biological composition of a reservoir's effluents directly influences water quality. The values of variables such as high values of concentrations of chlorophyll-a (Chl-a) are indicators of pollution. The objective of this work was to monitor the trophic status and water quality of the Cassaffousth reservoir (Córdoba, Argentina) through the development of statistical models based on field data and satellite information. During 2016 and 2017, samples were taken bimonthly. Seven sampling sites were selected and physico-chemical and biological parameters were assessed. By using regression techniques, Landsat 8 information was related with field data to construct and validate a statistical model to determine the distribution of Chl-a in the reservoir (R2 = 0.87). The generated algorithm was used to generate maps which contained information about the dynamics of Chl-a in the entire reservoir. Remote sensing techniques can be used to expand the knowledge of the dynamics of the Cassaffousth reservoir. Moreover, these techniques can be used as baselines for the development of an early warning system for this and other reservoirs in the region.

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