scholarly journals An Algorithm for Tracking Multiple Fish Based on Biological Water Quality Monitoring

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 15018-15026 ◽  
Author(s):  
Xiaoqiang Zhao ◽  
Sheng Yan ◽  
Qiang Gao
Keyword(s):  
Water Quality ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Biological Water ◽  
Biological Water Quality

scholarly journals Assessment of Water Quality by Bioindication of Algae and Cyanobacteria in the Peshawar Valley, Pakistan

2021 ◽  
Vol 22 (3) ◽  
Author(s):  
Izaz Khuram ◽  
Nadeem Ahmad ◽  
Cüneyt Nadir Solak ◽  
Sophia Barinova
Keyword(s):  
Water Quality ◽  
Industrial Effluents ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Nutrient Runoff ◽  
Biological Water ◽  
First Time ◽  
Biological Water Quality ◽  
Significant Factors

In purpose to assess the water quality in Peshawar Valley, the diversity of algae and cyanobacteria were studied in 41 sites during 2018-2019. A total of 361 species indicators of 7 Phyla were revealed. Algae and cyanobacteria in the studied sites preferred benthic and plankton-benthic lifestyle and mesotrophic waters. Indicators characterized water as moderate in temperature, medium oxygenated, low alkaline, and low saline. Algae and cyanobacteria inhabited medium-polluted and good water quality of Classes 2-3. The statistical maps were constructed for the first time to visualize the spatial distribution of diverse environmental and biological water quality variables and their relationship. The statistical maps and CCA revealed Water Temperature, Electrical Conductivity, Salinity, and Total Dissolved Solids as significant factors influenced freshwater algal and cyanobacteria communities. Statistical maps reflected an increase of dissolved substances from the foothills to the Kabul and Indus rivers' confluence. Acidification was revealed in the northeast of the valley. The bioindication results allowed us to propose that the algae and cyanobacteria communities were influenced by nutrient runoff from the surrounding foothills, agriculture, domestic and industrial effluents. The bioindication method combined with statistics can be recommended as a productive instrument for future water quality monitoring in the Peshawar Valley.

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