Simulation of chlorophyll-a concentration in Donghu Lake based on GA-ELM and multiple water quality indexes

2021 ◽  
Author(s):  
Xiaodong Tang ◽  
Mutao Huang
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Chlorophyll A Concentration ◽  
Donghu Lake ◽  
Quality Indexes

scholarly journals OPTMIZATION OF BIO-OPTICAL MODEL PARAMETERS FOR TURBID LAKE WATER QUALITY ESTIMATION USING LANDSAT 8 AND WASI-2D

2020 ◽  
Vol XLII-3/W11 ◽  
pp. 67-72
Author(s):  
A. Manuel ◽  
A. C. Blanco ◽  
A. M. Tamondong ◽  
R. Jalbuena ◽  
O. Cabrera ◽  
...  
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
The Philippines ◽  
Quality Data ◽  
Model Parameters ◽  
Landsat 8 ◽  
Water Quality Data ◽  
Chlorophyll A Concentration ◽  
In Situ Data

Abstract. Laguna Lake, the Philippines’ largest freshwater lake, has always been historically, economically, and ecologically significant to the people living near it. However, as it lies at the center of urban development in Metro Manila, it suffers from water quality degradation. Water quality sampling by current field methods is not enough to assess the spatial and temporal variations of water quality in the lake. Regular water quality monitoring is advised, and remote sensing addresses the need for a synchronized and frequent observation and provides an efficient way to obtain bio-optical water quality parameters. Optimization of bio-optical models is done as local parameters change regionally and seasonally, thus requiring calibration. Field spectral measurements and in-situ water quality data taken during simultaneous satellite overpass were used to calibrate the bio-optical modelling tool WASI-2D to get estimates of chlorophyll-a concentration from the corresponding Landsat-8 images. The initial output values for chlorophyll-a concentration, which ranges from 10–40 μg/L, has an RMSE of up to 10 μg/L when compared with in situ data. Further refinements in the initial and constant parameters of the model resulted in an improved chlorophyll-a concentration retrieval from the Landsat-8 images. The outputs provided a chlorophyll-a concentration range from 5–12 μg/L, well within the usual range of measured values in the lake, with an RMSE of 2.28 μg/L compared to in situ data.

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.

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 Seasonal and Tidal Dynamics of Nutrients and Chlorophyll a Concentration in Water at the Sundarbans Mangrove Ecosystems of Bangladesh

2020 ◽  
Vol 3 (1) ◽  
pp. 50-67
Author(s):  
Md. Sakib Hasan Nion ◽  
Md. Sirajul Islam ◽  
Md. Enamul Hoq ◽  
Md. Humayun Kabir ◽  
Mir Md. Mozammal Hoque
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
High Tide ◽  
Nutrient Concentrations ◽  
Chlorophyll A Concentration ◽  
Post Monsoon ◽  
Mangrove Ecosystems ◽  
Very High ◽  
Sundarbans Mangrove ◽  
The Sundarbans

The seasonal and tidal variations of physicochemical parameters, nutrient concentrations and chlorophyll a concentration from the water of Passur river and Koromjol canal in the Sundarbans mangrove ecosystems were investigated during March 2018 to February 2019. Samples were collected from five sampling stations during March, August and November where these months were considered as pre-monsoon, monsoon and post-monsoon seasons, respectively. The nutrients NH3-N, NO3-N, PO4-P, SO4 and Chlorophyll a concentrations were found 0.001 to 0.09, 3.5 to 50, 0.06 to 5.4, 30 to 272 and 0.18 to 1.75 mg/L, respectively, during high tides, and 0.001 to 0.39, 4.2 to 47, 0.1 to 2.75, 20 to 179 and 0.218 to 1.88 mg/L, respectively, during low tides. The NO3-N was very high than suitable limit during both tides at monsoon and post-monsoon season. The PO4-P was found moderately high during both tides at all stations. The SO4 was found to be 187.8 and 76.87 mg/L during high tide, and 135.4 and 95.73 mg/L during low tides in pre-monsoon and post-monsoon, respectively, that were very high than water quality standards. The Passur river and the Koromjol canal were fluctuating seasonally and tidally in some magnitude and their variations can alter the water quality as well as the density and distribution of living organisms.

Correlation of Water Quality Parameters in Tolo Harbour, Hong Kong

1992 ◽  
Vol 26 (9-11) ◽  
pp. 2555-2558 ◽  
Author(s):  
K. W. Chau ◽  
Y. S. Sin
Keyword(s):  
Water Quality ◽  
Hong Kong ◽  
Chlorophyll A ◽  
Secchi Depth ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Phosphorus Concentration ◽  
Control Zone ◽  
Chlorophyll A Concentration ◽  
Tolo Harbour

In this paper, long-term biweekly measurements on the various water quality parameters in Tolo Harbour from year 1982 to 1990, subsequent to the declaration of the area as water control zone, were analyzed and correlated. Correlations have been demonstrated between surface chlorophyll-a concentration with secchi depth and with total nitrogen concentration (TN) in the three sub-zones of Tolo Harbour in Hong Kong with different water quality objectives. The correlation between chlorophyll-a concentration and total phosphorus concentration (TP) is less significant which can be explained by the TN/TP ratio. The correlations are useful for water management, planning and effective pollution control on the land-locked estuary.

scholarly journals Inversion of Chlorophyll-a Concentration in Donghu Lake Based on Machine Learning Algorithm

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1179
Author(s):  
Xiaodong Tang ◽  
Mutao Huang
Keyword(s):  
Machine Learning ◽  
Chlorophyll A ◽  
Learning Algorithm ◽  
Factor Models ◽  
Machine Learning Algorithm ◽  
Single Factor ◽  
Chlorophyll A Concentration ◽  
Donghu Lake ◽  
Svm Model ◽  
Better Than

Machine learning algorithm, as an important method for numerical modeling, has been widely used for chlorophyll-a concentration inversion modeling. In this work, a variety of models were built by applying five kinds of datasets and adopting back propagation neural network (BPNN), extreme learning machine (ELM), support vector machine (SVM). The results revealed that modeling with multi-factor datasets has the possibility to improve the accuracy of inversion model, and seven band combinations are better than seven single bands when modeling, Besides, SVM is more suitable than BPNN and ELM for chlorophyll-a concentration inversion modeling of Donghu Lake. The SVM model based on seven three-band combination dataset (SVM3) is the best inversion one among all multi-factor models that the mean relative error (MRE), mean absolute error (MAE), root mean square error (RMSE) of the SVM model based on single-factor dataset (SF-SVM) are 30.82%, 9.44 μg/L and 12.66 μg/L, respectively. SF-SVM performs best in single-factor models, MRE, MAE, RMSE of SF-SVM are 28.63%, 13.69 μg/L and 16.49 μg/L, respectively. In addition, the simulation effect of SVM3 is better than that of SF-SVM. On the whole, an effective model for retrieving chlorophyll-a concentration has been built based on machine learning algorithm, and our work provides a reliable basis and promotion for exploring accurate and applicable chlorophyll-a inversion model.

scholarly journals Chlorophyll-a concentration retrieval in eutrophic lakes in Lithuania from Sentinel-2 data

2018 ◽  
Vol 4 (1) ◽  
Author(s):  
Dalia Grendaitė ◽  
Edvinas Stonevičius ◽  
Jūratė Karosienė ◽  
Ksenija Savadova ◽  
Jūratė Kasperovičienė
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Remote Sensing Data ◽  
Empirical Equations ◽  
Active Constituent ◽  
Eutrophic Lakes ◽  
Band Ratio ◽  
Local Conditions ◽  
Chlorophyll A Concentration ◽  
Sentinel 2

Inland waters are an important habitat for flora and fauna and are also used for aesthetic, recreational, and industrial needs; therefore, monitoring the current state of freshwaters and applying measures to improve water quality are of high importance. To have an efficient monitoring system that could cover large areas, the use of remote sensing data is crucial. In this study the suitability of the Sentinel-2 Multispectral Imager data is tested for observing cyanobacteria bloom events in the eutrophic lakes and retrieving the chlorophyll-a concentration – an indicator of phytoplankton biomass. The analysis is carried out using data from four lakes in Lithuania – two eutrophic blooming lakes and two oligo-mesotrophic non-blooming lakes. The results showed that reflectances are higher in the eutrophic lakes than in the oligo-mesotrophic lakes due to the presence of an optically active constituent, namely, chlorophyll-a pigment. We tested empirical equations for chlorophyll-a concentration retrieval in eutrophic lakes derived in other studies to check whether they could be used without adaptation to local conditions. Most of the equations performed well (R2 = 0.5–0.8); however, they had high RMSEs = 17–53 μg L–1. The equation used with the bottom of atmosphere data CHL8_L2A (R2 = 0.76) had the lowest RMSE = 9 μg L–1. In addition, we derived empirical equations for eutrophic lakes in Lithuania. The equations that were based on the Sentinel-2 band ratio B5/B4 and the three band (B4, B5, and B8A) expression performed the best (R2 = 0.77–0.79) and had lower RMSE = 7 μg L–1 than empirical equations from other studies. A larger in situ dataset could improve the algorithm performance in retrieving the chlorophyll-a concentration. The first attempts to map water quality parameters in eutrophic lakes in Lithuania using the data received from the Sentinel-2 MSI sensor show good results, as the changes in reflectance, caused by the changes in chlorophyll-a concentration, can be seen from satellite images.

scholarly journals ESTIMATION OF CHLOROPHYLL-A CONCENTRATION IN SAMPALOC LAKE USING UAS MULTISPECTRAL REMOTE SENSING AND REGRESSION ANALYSIS

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 297-303
Author(s):  
R. M. G. Maravilla ◽  
J. P. Quinalayo ◽  
A. C. Blanco ◽  
C. G. Candido ◽  
E. V. Gubatanga ◽  
...  
Keyword(s):  
Water Quality ◽  
Regression Analysis ◽  
Chlorophyll A ◽  
Linear Regression Analysis ◽  
Quality Data ◽  
Water Quality Data ◽  
Microalgal Biomass ◽  
Chlorophyll A Concentration ◽  
Chl A

Abstract. Sampaloc Lake is providing livelihood for the residents through aquaculture. An increase in the quantity of fish pens inside the lake threatens its water quality condition. One parameter being monitored is microalgal biomass by measuring Chlorophyll-a concentration. This study aims to generate a chlorophyll-a concentration model for easier monitoring of the lake. In-situ water quality data were collected using chl-a data logger and water quality meter at 357 and 12 locations, respectively. Using Parrot Sequoia+ Multispectral Camera, 1496 of 2148 images were acquired and calibrated, producing 18x18cm resolution Green (G), Red(R), Red Edge (RE) and Near Infrared (NIR) reflectance images. NIR was used to mask out non-water features, and to correct sun glint. The in-situ data and the pixel values extracted were used for Simple Linear Regression Analysis. A model with 5 variables – R/NIR, RE2, NIR2, R/NIR2, and NIR/RE2, was generated, yielding an R2 of 0.586 and RMSE of 0.958 μg/l. A chlorophyll-a concentration map was produced, showing that chl-a is higher where fish pens are located and lowers as it moves away from the pens. Although there are apparent fish pens on certain areas of the lake, it still yields low chlorophyll-a because of little amount of residential area or establishments adjacent to it. Also, not all fish pens have the same concentration of Chlorophyll-a due to inconsistent population per fish pen. The center of the lake has low chlorophyll-a as it is far from human activities. The only outlet, Sabang Creek, also indicates high concentration of Chlorophyll-a.

scholarly journals The Effects of Limiting Restoration Treatments in a Shallow Urban Lake

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1383
Author(s):  
Katarzyna Kowalczewska-Madura ◽  
Joanna Rosińska ◽  
Renata Dondajewska-Pielka ◽  
Ryszard Gołdyn ◽  
Lech Kaczmarek
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Municipal Wastewater ◽  
Cyanobacterial Blooms ◽  
Urban Lake ◽  
Low Oxygen ◽  
Gradual Improvement ◽  
Chlorophyll A Concentration ◽  
Phosphorus Inactivation ◽  
Bottom Zone

Swarzędzkie Lake, directly polluted for many years with municipal wastewater and heavily loaded with nutrient compounds from the catchment area, has become degraded and strongly eutrophicated. Strong cyanobacterial blooms have contributed, among others, to the cessation of recreational use of this urban lake. Its sustainable restoration was started in autumn 2011. These treatments were a combination of three complementary methods: aeration with a pulverizing aerator, phosphorus inactivation with small doses of magnesium chloride and iron sulphate (<15 kg ha−1) and biomanipulation. These treatments were carried out for three years (2012–2014), and in the next two (2015–2016), treatments were limited from three to one method—aeration. The obtained effects (a decrease in the number of cyanobacteria in phytoplankton and at the same time an increase in its biodiversity, decrease in chlorophyll a concentration and improvement of transparency) were lost due to the cessation of phosphorus inactivation and biomanipulation. The biological balance was upset, which resulted in an increase in chlorophyll a concentration, the return of cyanobacteria dominance in the phytoplankton and a deterioration of water quality. Leaving only a pulverizing aerator active, to maintain low oxygen concentrations near the bottom zone was not sufficient to ensure a gradual improvement of water quality with quite a significant external load of nutrients.

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