scholarly journals Indicative Lake Water Quality Assessment Using Remote Sensing Images-Effect of COVID-19 Lockdown

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 73
Author(s):  
Poonam Wagh ◽  
Jency M. Sojan ◽  
Sriram J. Babu ◽  
Renu Valsala ◽  
Suman Bhatia ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Lake Water ◽  
Water Quality Assessment ◽  
Quality Parameters ◽  
Landsat 8 ◽  
Lake Water Quality ◽  
Chl A ◽  
Pollution Levels ◽  
Remote Sensing Techniques

The major lockdown due to the COVID-19 pandemic has affected the socio-economic development of the world. On the other hand, there are also reports of reduced pollution levels. In this study, an indicative analysis is adopted to understand the effect of lockdown on the changes in the water quality parameters for Lake Hussain Sagar using two remote sensing techniques: (i) spectral reflectance (SR) and (ii) chromaticity analysis (Forel-Ule color Index (FUI) and Excitation Purity). The empirical relationships from earlier studies imply that (i) increase in SR values (band B2) indicates a reduction in Chlorophyll-a (Chl-a) and Colored Dissolved Organic Matter (CDOM) concentrations, and (ii) increase in FUI indicates an increase in Total Suspended Solids (TSS). The Landsat 8 OLI satellite images are adopted for comparison between (i) January to May of year 2020: the effect of lockdown on water quality, and (ii) March and April for years 2015 to 2020: historical variations in water quality. The results show notable changes in SR values and FUI due to lockdown compared to before lockdown and after unlock suggesting a significant reduction in lake water pollution. In addition, the historical variations within April suggest that the pollution levels are least in the year 2020.

scholarly journals An Overview on Water Quality Trending for Lake Water Classification in Malaysia

2018 ◽  
Vol 7 (3.23) ◽  
pp. 5
Author(s):  
Muhammad Muzzammil Shahabudin ◽  
Sabariah Musa
Keyword(s):  
Water Quality ◽  
Water Resources ◽  
Lake Water ◽  
Quality Index ◽  
Water Quality Assessment ◽  
Lake Water Quality ◽  
Water Classification ◽  
Quality Classification ◽  
Water Quality Classification ◽  
Quality Assessments

Lake water is important to all life and surroundings with multiples benefits and forms either in natural or man-made conditions. One of the most well-known tools for assessing the water quality is Water Quality Index (WQI) and widely used including Malaysia. Lake water quality should be represented in lucid way like other surface water regarding to the WQI standards for water quality assessment on lakes. This paper aims to review on lake water quality classification and its uses based on WQI standards in Malaysia. In this review, the uses of WQI for assessing the lake water and functioned of lakes are discussed. Results on pH from 5.0 to 9.2, BOD in mg/l from 0 to 180, COD in mg/l from 5 to 150, SS in mg/l from o to 1800, DO in mg/l from 0 to 8 and AN in mg/l N from -1 to 26. Variety of numbers is due to different loading of pollutions and location. With used of WQI on lake water quality assessments, further action can be taken for the uses on water resources by maintaining the quality. It also will broaden the uses of lake water as alternative of water resources in Malaysia.  

scholarly journals Composition, Structure and Functional Feeding of Aquatic Entomofauna in Kodjoboué Lake: Water Quality Assessment

2020 ◽  
Vol 10 (04) ◽  
pp. 160-176
Author(s):  
Idrissa Adama Camara ◽  
Mathieu Kobenan Kra ◽  
Norbert Kouakou Kouadio ◽  
Mexmin Koffi Konan ◽  
Edia Oi Edia ◽  
...  
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Lake Water ◽  
Water Quality Assessment ◽  
Lake Water Quality ◽  
Composition Structure

scholarly journals Detecting spatiotemporal variability in the physicochemical properties of water in the Lower Mearim using remote sensing data

2020 ◽  
Vol 42 ◽  
pp. e32
Author(s):  
George Colares Silva Filho ◽  
Juliana Martins dos Santos ◽  
Paulo Cesar Mendes Villis ◽  
Ingrid Santos Gonçalves ◽  
Isael Coelho Correia ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Physicochemical Properties ◽  
Monitoring Program ◽  
Remote Sensing Data ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Spatiotemporal Variability ◽  
Landsat 8 ◽  
Solids Content

Natural or anthropogenic chemical compounds of different origins often accumulate in estuarine regions. These compounds may alter the water quality. Therefore, It is important to constantly monitor the quality of estuarine regions. A combination of remote sensing and traditional sampling can lead to a better monitoring program for water quality parameters. The objective of this work is to assess the spatiotemporal variability of the physicochemical properties of water in the lower region of the Mearim River and estimate water quality parameters via remote sensing. Samples were collected at 16 points, from Baixo Arari to the mouth of the watershed, using a multiparameter meter and Landsat 8 satellite images. The physicochemical parameters of the water had high salinity levels, between 2.30 and 20.10 parts per trillion; a high total dissolved solids content, between 2.77 and 19.70 g/L; and minimum dissolved oxygen values. Estimating the physicochemical properties of the water via remote sensing proved feasible, particularly in the dry season when there is less cloud cover.

scholarly journals Remote sensing inversion of lake water quality parameters based on ensemble modelling

2020 ◽  
Vol 143 ◽  
pp. 02007
Author(s):  
Li Xiaojuan ◽  
Huang Mutao ◽  
Li Jianbao
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Entropy Weight ◽  
Ensemble Modelling ◽  
Chl A ◽  
Inversion Model ◽  
Entropy Weight Method ◽  
Weight Method

In this paper, combined with water quality sampling data and Landsat8 satellite remote sensing image data, the inversion model of Chl-a and TN water quality parameter concentration was constructed based on machine learning algorithm. After the verification and evaluation of the inversion results of the test samples, Chl-a TN inversion model with high correlation between model test results and measured data was selected to participate in remote sensing inversion ensemble modelling of water quality parameters. Then, the ensemble remote sensing inversion model of water quality parameters was established based on entropy weight method and error analysis. By applying the idea of ensemble modelling to remote sensing inversion of water quality parameters, the advantages of different models can be integrated and the precision of water quality parameters inversion can be improved. Through the evaluation and comparative analysis of the model results, the entropy weight method can improve the inversion accuracy to some extent, but the improvement space is limited. In the verification of the two methods of ensemble modelling based on error analysis, compared with the optimal results of a single model, the determination coefficient (R2) of Chlorophyll a and TN concentration inversion results was increased from 0.9288 to 0.9313 and from 0.8339 to 0.8838, and the root mean square error was decreased from 14.2615 μ/L to 10.4194 μ/L and from1.1002mg/L to 0.8621mg/L. At the same time, with the increase of the number of models involved in the set modelling, the inversion accuracy is higher.

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.

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