scholarly journals Spatio-Temporal Variation of Total Nitrogen and Ammonia Nitrogen in the Water Source of the Middle Route of the South-To-North Water Diversion Project

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2615
Author(s):  
Guoquan Dong ◽  
Zhenqi Hu ◽  
Xuan Liu ◽  
Yaokun Fu ◽  
Wenjing Zhang
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Total Nitrogen ◽  
Ammonia Nitrogen ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Water Diversion ◽  
Mountainous Area ◽  
Danjiangkou Reservoir ◽  
N Concentration

The quantitative inversion of the concentrations of water quality parameters could clarify the temporal and spatial distribution characteristic, migration, and conversion of water quality parameters. This study took the Danjiangkou Reservoir as the research object, and established an inversion model based on the reflectance of different band combinations of remote sensing analyses on Sentinel-2 images, combined with the water quality monitoring data of total nitrogen (TN) and ammonia nitrogen (NH3-N) of the sampling sites in February 2016. The inversion results of TN and NH3-N in 2020 were obtained, the variation of TN and NH3-N concentrations in the reservoir area were analyzed, and the factors accounting for the variation were discussed. The results indicated that the fitting accuracy using the established model was high for both TN and NH3-N, and R2 was 0.782 for TN and 0.851 for NH3-N, respectively, showing high predication accuracy, which could be suitable for remote sensing inversion of TN and NH3-N concentrations in the Danjiangkou Reservoir. The NH3-N concentration of the Danjiangkou Reservoir was in line with Class I from 2016 to 2020, while the TN concentration was between Class III and IV. The inter-annual changes indicated that the overall water quality had an upward trend. The main tributary in the northern of the Danjiangkou Reservoir had a heavy load of TN, and after entering the reservoir, the flow velocity decreased, which caused nitrogen to accumulate at the river entrance, leading to a high TN concentration. The large slope of the mountainous area cause soil erosion. The lost soil and water carried a large amount of pesticides and fertilizers, and the ground runoff carried a large amount of nitrogen into water body, which could account for the high NH3-N concentration on the east and west sides of the southern part of the Danjiangkou Reservoir.

scholarly journals The in situ remediation of aquaculture water and sediment by commercial probiotics immobilized on different carriers

2021 ◽  
Author(s):  
Mengmeng Yi ◽  
Chun Wang ◽  
He Wang ◽  
Xi Zhu ◽  
Zhigang Liu ◽  
...  
Keyword(s):  
Water Quality ◽  
High Throughput Sequencing ◽  
Relative Concentration ◽  
Ammonia Nitrogen ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Treatment Groups ◽  
Walnut Shells ◽  
Water And Sediment ◽  
Aquaculture Water

Abstract In the present study, we investigated the effect of probiotics immobilized by oyster shells (Os), vesuvianite (Ve) and walnut shells (Ws) on the remediation of aquaculture water and sediment by analyzing the variation of ammonia-nitrogen (NH4–N), nitrate-nitrogen (NO3–N), nitrite-nitrogen (NO2–N), total nitrogen (TN), total phosphorus (TP) and chemical oxygen demand (CODCr), as well as the microbiota of the water and sediment. The positive or negative effects of the treatment groups on the water quality parameters were both observed. Compared with their effects on water quality parameters, the treatment groups had better effects on sediment parameters. Group Ve had the best remediation effect of NH4–N and NO3–N in the sediment (decreased by 5.22 and 1.66 times, respectively). Group Os showed a lower relative concentration of TN and CODCr (decreased by 3.77 and 0.95 times, respectively). The high-throughput sequencing results revealed that the immobilized probiotics increased the relative abundances of functional bacteria in the treatment groups at the phylum and genus level. The above results showed that probiotics immobilized by oyster shells, vesuvianite and walnut shells positively affected the aquaculture environment's remediation, especially the sediment.

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 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.

scholarly journals Stress response in transport of juvenile cobia Rachycentron canadum using the anesthetic benzocaine

2017 ◽  
Vol 44 (3) ◽  
pp. 638-642
Author(s):  
Janaína S. Pedron ◽  
Denise S. Miron ◽  
Ricardo V. Rodrigues ◽  
Marcelo H. Okamoto ◽  
Marcelo B. Tesser ◽  
...  
Keyword(s):  
Water Quality ◽  
Blood Glucose ◽  
Stress Response ◽  
Stocking Density ◽  
Ammonia Nitrogen ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Blood Samples ◽  
Total Ammonia Nitrogen ◽  
Total Ammonia

This experiment evaluated the efficacy of benzocaine to reduce stress response during transport of juvenile cobia. Fish (30 g) were packed in bags and transported for 8 h (stocking density = 10 g L-1). Three concentrations of benzocaine were evaluated: 0, 2, and 6 mg L-1. Blood samples were taken for glucose and hematocrit before transportation, and then at 0, 2, 24, and 48 h after. Water quality parameters were verified. No mortality was observed. Total ammonia nitrogen was higher (2.46 mg L-1) and pH was lower (6.92) at 2 mg benzocaine L-1. There was an increase in blood glucose for all treatments on arrival, and it was higher for those exposed to benzocaine at 6 mg L-1, although at 48 h they were all similar. The hematocrit did not differ among treatments. The results suggest: 1) the density 10 g L-1 is considered safe for juvenile cobia transport; 2) benzocaine did not mitigate stress response on cobia during transport, therefore its use is not recommended for this purpose.

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