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

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.

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Seagrass depth range and water quality in southern Moreton Bay, Queensland, Australia

Marine and Freshwater Research ◽

10.1071/mf9960763 ◽

1996 ◽

Vol 47 (6) ◽

pp. 763 ◽

Cited By ~ 95

Author(s):

EG Abal ◽

WC Dennison

Keyword(s):

Water Quality ◽

Chlorophyll A ◽

Suspended Solids ◽

Light Attenuation ◽

River Mouth ◽

Total Suspended Solids ◽

Quality Parameters ◽

Depth Range ◽

Moreton Bay ◽

A Site

Correlations between water quality parameters and seagrass depth penetration were developed for use as a biological indicator of integrated light availability and long-term trends in water quality. A year-long water quality monitoring programme in Moreton Bay was coupled with a series of seagrass depth transects. A strong gradient between the western (landward) and eastern (seaward) portions of Moreton Bay was observed in both water quality and seagrass depth range. Higher concentrations of chlorophyll a, total suspended solids, dissolved and total nutrients, and light attenuation coefficients in the water column and correspondingly shallower depth limits of the seagrass Zostera capricorni were observed in the western portions of the bay. Relatively high correlation coefficient values (r2 > 0.8) were observed between light attenuation coefficient, total suspended solids, chlorophyll a, total Kjeldahl nitrogen and Zostera capricorni depth range. Low correlation coefficient values (r2 < 0.8) between seagrass depth range and dissolved inorganic nutrients were observed. Seagrasses had disappeared over a five-year period near the mouth of the Logan River, a turbid river with increased land use in its watershed. At a site 9 km from the river mouth, a significant decrease in seagrass depth range corresponded to higher light attenuation, chlorophyll a, total suspended solids and total nitrogen content relative to a site 21 km from the river mouth. Seagrass depth penetration thus appears to be a sensitive bio-indicator of some water quality parameters, with application for water quality management.

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

Sensors ◽

10.3390/s18082699 ◽

2018 ◽

Vol 18 (8) ◽

pp. 2699 ◽

Cited By ~ 2

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.

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

Water ◽

10.3390/w12082192 ◽

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.

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Quantitative comparison of forests and other areas with dry weather input loading in the Lake Biwa catchment area

Water Science & Technology ◽

10.2166/wst.2002.0235 ◽

2002 ◽

Vol 45 (9) ◽

pp. 183-193 ◽

Cited By ~ 1

Author(s):

S. Fujii ◽

H. Tanaka ◽

I. Somiya

Keyword(s):

Water Quality ◽

Lake Biwa ◽

River Mouth ◽

Weather Conditions ◽

Ionic Species ◽

Concentration Difference ◽

Forest Sites ◽

Catchment Areas ◽

Unit Loading ◽

River Mouths

For the evaluation of pollutants loading to Lake Biwa, comprehensive river surveys on river mouths and forest sites were conducted 9 times from 1996 to 1999, on 25–40 main rivers in the Lake Biwa watershed. The main results obtained are as follows. (1) River water quality reflects regional characteristics of their catchment areas, and the concentration difference among rivers ranged between 2–3 fold. (2) Concentration variation shows different patterns with time and location depending on water quality indices used. (3) Indices related to organic matter and nutrients have lower correlation between forests and river mouths, but those related to ionic species showed strong correlation. (4) Flux comparison of forest and river mouth sites suggests that pollutants from catchment areas are conveyed to the lake not only through rivers but also underground. (5) In dry weather conditions, forests contribute 30% to the whole pollutants (TN, TP, and TCODMn) loading, and the remainder is derived mainly from paddy fields and residential/commercial zones. (6) Unit loading factors from forests are estimated as 640, 57 and 1200 kg/km2/y, respectively for TN, TP and TCODMn, while those from other areas are estimated as 2,500, 208 and 4,200 kg/km2/y.

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

Hydrology Research ◽

10.2166/nh.2017.116 ◽

2017 ◽

Vol 49 (5) ◽

pp. 1608-1617 ◽

Cited By ~ 4

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.

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

Remote Sensing ◽

10.3390/rs14010018 ◽

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.

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DISSOLVED SILICATE IN COASTAL WATER OF SOUTH SULAWESI

Jurnal Ilmu dan Teknologi Kelautan Tropis ◽

10.29244/jitkt.v6i2.9022 ◽

2015 ◽

Vol 6 (2) ◽

Author(s):

Muhammad Lukman ◽

Andriani Nasir ◽

Khairul Amri ◽

Rahmadi Tambaru ◽

Muhammad Hatta ◽

...

Keyword(s):

Water Quality ◽

Chlorophyll A ◽

Coastal Water ◽

Coastal Waters ◽

Dry Season ◽

Limiting Factor ◽

Western Coast ◽

Wet Season ◽

South Sulawesi ◽

Dissolved Silicate

ABSTRACT Dissolved silicate (DSi) in coastal waters plays a crucial role in phytoplankton growth particularly diatom. This study aimed to determine DSi concentration seasonally in waters of the western coast of South Sulawesi in relation to coastal water quality indicator. Water, chlorophyll-a, and diatom samples were collected from the coastal areas of the Tallo-Makassar, Maros, and Pangkep, in April 2013 (transitional season), June 2013 (dry season), and February 2014 (wet season). Factorial analysis of variance was used to identify significant seasonal and temporal variations, and linear regression was used to test the relationship of chlorophyll-a and diatom abundance to DSi concentrations. The results showed that the DSi concentration was higher in the wet season of 35.2-85.2 µM than in the other seasons (transitional season: 10.8-68.4 µM, dry season: 9.59-24.1 µM). The abundance of diatoms during the transitional season reached ~9.7x107 cell/m3 in the Pangkep river, 2.3x107 cell/m3 in the Tallo river, and 1.3 x 107 cell/m3 in the Maros river. Chaetoceros, Nitzschia, and Rhizosolenia dominated the diatom composition. The mean concentration of chlorophyll-a in the Makassar coastal waters was 4.52±4.66 mg/m3, while in the Maros and Pangkep waters of 1.40±1.06, and 2.72±1.94 mg/m3, respectively. There was no strong linear corelation between DSi and diatom abundances, nor chlorophyll-a. These results suggested that DSi become a non-limiting factor for the diatom growth and potentially reduce the water quality via eutrophication and diatom blooms. Keywords: dissolved silicate, diatom, chlorophyll-a, coastal waters, South Sulawesi

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DISSOLVED SILICATE IN COASTAL WATER OF SOUTH SULAWESI

Jurnal Ilmu dan Teknologi Kelautan Tropis ◽

10.28930/jitkt.v6i2.9022 ◽

2015 ◽

Vol 6 (2) ◽

Author(s):

Muhammad Lukman ◽

Andriani Nasir ◽

Khairul Amri ◽

Rahmadi Tambaru ◽

Muhammad Hatta ◽

...

Keyword(s):

Water Quality ◽

Chlorophyll A ◽

Coastal Water ◽

Coastal Waters ◽

Dry Season ◽

Limiting Factor ◽

Western Coast ◽

Wet Season ◽

South Sulawesi ◽

Dissolved Silicate

ABSTRACT Dissolved silicate (DSi) in coastal waters plays a crucial role in phytoplankton growth particularly diatom. This study aimed to determine DSi concentration seasonally in waters of the western coast of South Sulawesi in relation to coastal water quality indicator. Water, chlorophyll-a, and diatom samples were collected from the coastal areas of the Tallo-Makassar, Maros, and Pangkep, in April 2013 (transitional season), June 2013 (dry season), and February 2014 (wet season). Factorial analysis of variance was used to identify significant seasonal and temporal variations, and linear regression was used to test the relationship of chlorophyll-a and diatom abundance to DSi concentrations. The results showed that the DSi concentration was higher in the wet season of 35.2-85.2 µM than in the other seasons (transitional season: 10.8-68.4 µM, dry season: 9.59-24.1 µM). The abundance of diatoms during the transitional season reached ~9.7x107 cell/m3 in the Pangkep river, 2.3x107 cell/m3 in the Tallo river, and 1.3 x 107 cell/m3 in the Maros river. Chaetoceros, Nitzschia, and Rhizosolenia dominated the diatom composition. The mean concentration of chlorophyll-a in the Makassar coastal waters was 4.52±4.66 mg/m3, while in the Maros and Pangkep waters of 1.40±1.06, and 2.72±1.94 mg/m3, respectively. There was no strong linear corelation between DSi and diatom abundances, nor chlorophyll-a. These results suggested that DSi become a non-limiting factor for the diatom growth and potentially reduce the water quality via eutrophication and diatom blooms. Keywords: dissolved silicate, diatom, chlorophyll-a, coastal waters, South Sulawesi

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

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-4-w19-233-2019 ◽

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.

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

Water Science & Technology Water Supply ◽

10.2166/ws.2019.080 ◽

2019 ◽

Vol 19 (7) ◽

pp. 2021-2027 ◽

Cited By ~ 2

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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