scholarly journals Assessment of chlorophyll and water quality using remote sensing and GIS imagery in the Cauvery watershed of Karnataka, India

2019 ◽  
Vol 66 (2) ◽  
Author(s):  
D. Karunakaran ◽  
S.K. Sahu ◽  
Arun Pandit ◽  
A.P. Sharma
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Specific Conductivity ◽  
Short Wave ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Total Alkalinity ◽  
Atmospheric Effects ◽  
Infrared Band ◽  
Dark Pixel

India has vast inland water resources having immense potential for aquaculture potential. Assessment of water quality parameters is a pre-requisite to any scientific intervention as they are of prime importance in fisheries perspective. However, monitoring water quality parameters of such vast area is not an easy task with the conventional tools and methods. In the present study, water quality parameters and chlorophyll pigment concentration were assessed using IRS P-6 remote sensing imagery in the Cauvery watershed of Karnataka State, India. Images captured by optical satellite sensors are often obscured by atmospheric effects. Hence, the images were rectified by Dark pixel subtraction method before analysing data in order to extract useful information from the imagery. The study revealed that there was significant correlation between spectral reflectance and in-situ water quality parameters. Near infra-red band (0.77-0.86 µm), was useful to assess the water quality parameters like depth, specific conductivity, total alkalinity, chlorinity, salinity and turbidity. Similarly, short wave infrared band (1.55-1.70 µm) was useful for assessing chlorophyll-a. However, the models were found to be region specific and they appear to have potential for monitoring water quality of large water bodies at regular intervals.

scholarly journals Cladoceran abundance in relation to water quality parameters of Chakki Talab, Bodhan, Telangana

2018 ◽  
Vol 8 (01) ◽  
Author(s):  
Vasudha Lingampally ◽  
V.R. Solanki ◽  
D. L. Anuradha ◽  
Sabita Raja
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Oxygen Demand ◽  
Total Dissolved Solids ◽  
Quality Parameters ◽  
Biological Oxygen Demand ◽  
Water Quality Parameters ◽  
Total Alkalinity ◽  
Total Hardness ◽  
One Year

In the present study an attempt has been made to evaluate water quality and related density of Cladocerans for a period of one year, October 2015 to September 2016. Water quality parameters such as temperature, PH, total dissolved solids, dissolved oxygen, biological oxygen demand, total alkalinity, total hardness, chlorides, phosphates, and nitrates are presented here to relate with the abundance of Cladocerans. The Cladoceran abundance reflects the eutrophic nature of the Chakki talab.

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 Potensi budidaya ikan di Waduk Embung Klamalu Kabupaten Sorong Provinsi Papua Barat: Kajian kualitas fisika kimia air

2013 ◽  
Vol 1 (3) ◽  
Author(s):  
Agustina Frasawi ◽  
Robert J Rompas ◽  
Juliaan Ch. Watung
Keyword(s):  
Carbon Dioxide ◽  
Water Quality ◽  
Dissolved Oxygen ◽  
Good Condition ◽  
Fish Farming ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Total Alkalinity ◽  
Physical Chemical ◽  
Papua Barat

The objective of this research was to measure and analyze the water quality parameters including temperature, brightness, pH, dissolved oxygen, total alkalinity, carbon dioxide and BOD in reservoir Embung Klamalu Sorong regency, and to know the factors that affected the water quality of Embung Klamalu. Measurement of water quality parameters was done in situ for temperature, brightness, pH and in laboratory for dissolved oxygen, total alkalinity, carbon dioxide, and BOD. The results showed the temperature at the five observation stations ranged from 26.2 to 29.8 0C, brightness 38 to 46 cm, pH 7.20 to 8.48 mg /L, dissolved oxygen from 7.20 to 8.48 mg / L, alkalinity 100 to 150 mg /L, carbon dioxide from 25.90 to 28.95 mg / L, BOD from 0.20 to 0.38. Refers to the standards of water quality according to the PP. 82, 2001, it could be concluded that water physical-chemical qualities in fish farming locations in the Village Klamalu were still in good condition. Keywords: Water physical-chemical quality, aquaculture, waduk Embung Klamalu

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 GIS-Based Modelling of Water Quality in Different Hilsha Spawning Grounds and Sanctuaries of Bangladesh

2018 ◽  
pp. 1-11
Author(s):  
Rumana Yasmin ◽  
Mehady Islam
Keyword(s):  
Water Quality ◽  
Present Status ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Total Alkalinity ◽  
Total Hardness ◽  
Quality Model ◽  
Spawning Grounds ◽  
Temporal Modelling ◽  
Spatio Temporal

The current study was performed to monitor in situ condition and spatio-temporal modelling of the present status of water quality parameters of different spawning grounds and sanctuaries of Hilsha. The study was conducted in nine sites in lower Padma River (Maowa) to lower Meghna River (Bhola, Patuakhali) from 1 August 2015 to 31 January 2016. This study demonstrates surface water temperature, salinity, conductivity and transparency were ranged from 19.00-33.00°C, 0.10-2.90 ppt, 125.60-4720.00 µS/cm and 6.60-74.00 cm respectively. The values of pH, DO, free CO2, total alkalinity, total hardness and free NH3 were varied from 6.00-9.50, 4.50-11.60 mg/L, 3.46-24.00 mg/L, 33.00-172.50 mg/L, 34.20-1291.00 mg/L and 0.20-1.40 mg/L respectively. Moreover, water quality model reveals that the present status of some water quality parameters (free CO2, free NH3, transparency) deviated from optimum condition suitable for the normal physiological process and spawning of Hilsha.

scholarly journals Monitoring Water Quality of the Haihe River Based on Ground-Based Hyperspectral Remote Sensing

Water ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 22
Author(s):  
Qi Cao ◽  
Gongliang Yu ◽  
Shengjie Sun ◽  
Yong Dou ◽  
Hua Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Real Time ◽  
Training Model ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Hyperspectral Remote Sensing ◽  
Water Quality Parameters ◽  
Quality Monitoring ◽  
Haihe River

The Haihe River is a typical sluice-controlled river in the north of China. The construction and operation of sluice dams change the flow and other hydrological factors of rivers, which have adverse effects on water, making it difficult to study the characteristics of water quality change and water environment control in northern rivers. In recent years, remote sensing has been widely used in water quality monitoring. However, due to the low signal-to-noise ratio (SNR) and the limitation of instrument resolution, satellite remote sensing is still a challenge to inland water quality monitoring. Ground-based hyperspectral remote sensing has a high temporal-spatial resolution and can be simply fixed in the water edge to achieve real-time continuous detection. A combination of hyperspectral remote sensing devices and BP neural networks is used in the current research to invert water quality parameters. The measured values and remote sensing reflectance of eight water quality parameters (chlorophyll-a (Chl-a), phycocyanin (PC), total suspended sediments (TSS), total nitrogen (TN), total phosphorus (TP), ammonia nitrogen (NH4-N), nitrate-nitrogen (NO3-N), and pH) were modeled and verified. The results show that the performance R2 of the training model is above 80%, and the performance R2 of the verification model is above 70%. In the training model, the highest fitting degree is TN (R2 = 1, RMSE = 0.0012 mg/L), and the lowest fitting degree is PC (R2 = 0.87, RMSE = 0.0011 mg/L). Therefore, the application of hyperspectral remote sensing technology to water quality detection in the Haihe River is a feasible method. The model built in the hyperspectral remote sensing equipment can help decision-makers to easily understand the real-time changes of water quality parameters.

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