Comparative Water Quality Analysis in Beso River in District Jaunpur, Azamgarh and Ghazipur Uttar Pradesh
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2021.12.1.11Keywords:
ppm, significant data, site of sampling (S1, S2, S3), μ S/cm,Dimensions Badge
Issue
Section
The Beso River originates from village Shahapur in District Jaunpur and enters in District Azamgarh after Jaigaha and finally merges into river Ganga in District Ghazipur Uttar Pradesh. It flows south-eastward for almost 95 km only through three districts of eastern Uttar Pradesh. The sample has been collected from three sites indicated by S. S1 from Lakhmapur Jaunpur, S2 from Lalganj Azamgarh, and S3 from Jakhania Ghazipur. The sample has been collected five times i.e. in May, August, November, January, and March on the second Sunday of the month in the year 2020-2021. During tabulation of data five reading from each sample have taken and bio statistically analyzed by students T-test for all parameters for all times and only significant data have been considered. The mean value for the pH as 7.4 Ammoniac Nitrogen as 66.0 ppm, Temperature as 28.660C, B.O.D 235.33 C.O.D 271, Free CO2 260 ppm TDS as 543.33ppm, Cu 2.47 ppm, Iron Total as 2.09 ppm Zinc 6.46 ppm, Cr 3.58ppm, Phenolic Compounds as 5.36 ppm and Conductivity as 373.73 μ S/cm. have been measured by implication of different techniques. During the investigation, only Cu and total Iron values are measured lower to normal while other parameters reported high to normal values. Overall all physiochemical data indicate the water quality tends to be increased polluted as river move to Sangam from Ganga. Yet the water quality of Beso is many times better than River Sai and GomatiAbstract
How to Cite
Downloads
Similar Articles
- Neha Verma, Beyond likes & clicks: Empowering role of social media marketing in value creation , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Anli Suresh, Sandhiya M., Investment model on the causation of inclining attributes towards bank investment options in the investor’s portfolio , The Scientific Temper: Vol. 16 No. Spl-2 (2025): The Scientific Temper
- Shaik Abdulla P., Abdul Razak T., Retrieval-Based Inception V3-Net Algorithm and Invariant Data Classification using Enhanced Deep Belief Networks for Content-Based Image Retrieval , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Theophilus Deenadayal, Tarun Jain, Floristic composition in Paramananda Devara Gudda A sacred grove at Lingadahalli Village Devadurga Taluk Raichur District Karnataka, India , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Ayalew Ali, Determinants of banks profitability: Do capital structure and dividend policy matters? , The Scientific Temper: Vol. 16 No. 04 (2025): The Scientific Temper
- A. K. Chaubey, Vidhi Tyagi, Tanu Vatsa, Chhavi Kaushik, EVALUATION OF VIRULENCE OF ENTOMOPATHOGENIC NEMATODE ISOLATES AGAINST HELICOVERPA ARMIGERA AND SPODEPTERA LITURA , The Scientific Temper: Vol. 1 No. 01 (2010): The Scientific Temper
- Kunwar Ananad Singh, Poonam Pandey, ROLE OF ANTHROPOGENIC EMISSIONS IN CLIMATE CHANGE , The Scientific Temper: Vol. 1 No. 01 (2010): The Scientific Temper
- Sachin V. Chaudhari, Jayamangala Sristi, R. Gopal, M. Amutha, V. Akshaya, Vijayalakshmi P, Optimizing biocompatible materials for personalized medical implants using reinforcement learning and Bayesian strategies , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Archana Bansal, On the Biology of Chrysomya megacephala (Fabricius) (Diptera: Calliphoridae) , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper
- Abhishek Dwivedi, Shekhar Verma, SCNN Based Classification Technique for the Face Spoof Detection Using Deep Learning Concept , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper
<< < 20 21 22 23 24 25 26 27 28 29 > >>
You may also start an advanced similarity search for this article.

