Assessment of Physico-Chemical Water Quality Parameters of the Brahmani River
DOI:
https://doi.org/10.5281/zenodo.15115537Keywords:
Brahmani River, Physico-Chemical Parameters, pH, Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD)Abstract
This research analyzes the Brahmani River water quality in terms of the important physicochemical parameters. The river is exposed to huge industrial effluents and impacted by extensive agricultural and human practices. To assess the effect of these activities, water samples were gathered from nine points over the river basin between August 2014 and September 2015, with sampling done on the first working day of every month. Parameters like pH, Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), and Conductivity were examined. It is found from the results that the water quality of the river remains within acceptable ranges. The physicochemical parameters play a significant role in evaluating the overall water quality of the river. The research highlights the need for constant monitoring to make the river a sustainable resource for both ecological and human purposes.
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Ahmad, S., Khan, I. H., & Others. (2001). Performance of stochastic approaches for forecasting river water quality. Water Research, 35(18), 4261-4266. https://doi.org/10.1016/S0043-1354(01)00167-1
Akkaraboyina, M. K., & Raju, B. S. N. (2012). Assessment of water quality index of River Godavari at Rajahmundry. Universal Journal of Environmental Research and Technology, 2(3), 161-167.https://www.cabidigitallibrary.org/doi/full/10.5555/20123418194
Alam, M. J., Islam, M. R., Muyen, Z., Mamun, M., & Islam, S. (2007). Water quality parameters along rivers. International Journal of Environmental Science & Technology, 4, 159-167. https://doi.org/10.1007/BF03325974
Baban, S. M. J. (1993). Detecting water quality parameters in the Norfolk Broads, UK, using Landsat imagery. International Journal of Remote Sensing, 14(7), 1247-1267. https://doi.org/10.1080/01431169308953955
Bhadra, A. A., Bhunya, N. K., & Others. (2015). Assessment of the water quality standard of Brahmani River in terms of physico-chemical parameters. International Journal of Scientific Research and Management (IJSRM), 2(12), 1765-1772.
Bhatt, S., Mishra, A. P., Chandra, N., Sahu, H., Chaurasia, S. K., Pande, C. B., ... & Hunt, J. (2024). Characterizing seasonal, environmental and human-induced factors influencing the dynamics of Rispana River's water quality: Implications for sustainable river management. Results in engineering, 22, 102007. https://doi.org/10.1016/j.rineng.2024.102007
Bhattacharya, A. K., Basack, S., & Others. (2008). Saline water intrusion in Bhadrak and Balasore districts of Orissa, India. EJGE, 13, 1-7.
Boyacioglu, H., Boyacioglu, H., & Others. (2005). Application of factor analysis in the assessment of surface water quality in Buyuk Menderes River Basin. European Water, 9(10), 43-49.
Champely, S., & Doledec, S. (1997). How to separate long-term trends from periodic variation in water quality monitoring. Water Research, 31(11), 2849-2857. https://doi.org/10.1016/S0043-1354(97)00136-X
El Kholy, R. M. S., Khalil, B. M., & Others. (1997). Assessment of the National Water Quality Monitoring Program of Egypt.
Emad Am, S., Ahmed M, T., & Others. (2012). Assessment of water quality of Euphrates River using cluster analysis. Journal of Environmental Protection, 2012. http://dx.doi.org/10.4236/jep.2012.312180
Hadi, G., & Shui, L. (2012). Neuro-fuzzy modeling and forecasting in water resources. Scientific Research and Essays, 7(24), 2112-2121. DOI: 10.5897/SRE11. 2164
Ishaq, S. E., Agada, O. P., & Others. (2012). Spatial and temporal variation in water quality of River Benue, Nigeria. Journal of Environmental Protection, 2012. http://dx.doi.org/10.4236/jep.2012.328106
Jha, R., & Singh, V. P. (2008). Evaluation of river water quality by entropy. KSCE Journal of Civil Engineering, 12(1), 61-69. https://doi.org/10.1007/s12205-008-8061-3
Juahir, H., Zain, S. M., & Others. (2004). Application of artificial neural network models for predicting water quality index. Malaysian Journal of Civil Engineering, 16(2).
Liu, L., Zhou, J., & Others. (2009). Using fuzzy theory and information entropy for water quality assessment in Three Gorges region, China. Expert Systems with Applications, 37(3), 2517-2521. https://doi.org/10.1016/j.eswa.2009.08.004
Maier, H. R., & Dandy, G. C. (1996). The use of artificial neural networks for the prediction of water quality parameters. Water Resources Research, 32(4), 1013-1022. https://doi.org/10.1029/96WR03529
Malviya, A., Diwakar, S. K., & Others. (2010). Chemical assessment of Narmada River water at Hoshangabad city and Nemawar as the navel of a river in Central India. Oriental Journal of Chemistry, 26(1), 319.
Nath, T. K., Tripathy, B., & Das, A. (2018). A study of water quality of River Brahmani, Odisha (India) to assess its potability. International Journal of Engineering Research & Technology, 7(7), 301-311.
Prathumratana, L., Sthiannopkao, S., & Others. (2008). The relationship of climatic and hydrological parameters to surface water quality in the Lower Mekong River. Environment International, 34(6), 860-866. https://doi.org/10.1016/j.envint.2007.10.011
Qian, Y., Migliaccio, K. W., & Others. (2007). Surface water quality evaluation using multivariate methods and a new water quality index in the Indian River Lagoon, Florida. Water Resources Research, 43(8). https://doi.org/10.1029/2006WR005716
Ramsay, J. O., & Silverman, B. W. (2007). Applied functional data analysis: Methods and case studies. Springer.
Saatsaz, M., Suliman, W. N. A. B., & Others. (2013). Multivariate statistical techniques for the evaluation of spatial and temporal variations in groundwater quality of Astaneh-Kouchesfan Plain, Sefid-Rud Basin, North of Iran. 9th International River Engineering Conference, Ahwaz.
Sahoo, M. M. (2014). Analysis and modeling of surface water quality in river basins. http://ethesis.nitrkl.ac.in/6551/
Sahu, M., Mahapatra, S. S., & Others. (2011). Prediction of water quality index using neuro-fuzzy inference system. Water Quality, Exposure, and Health, 3(3-4), 175-191. https://doi.org/10.1007/s12403-011-0054-7
Samantray, P., Mishra, B. K., & Others. (2009). Assessment of water quality index in Mahanadi and Atharabanki Rivers and Taldanda Canal in Paradip area, India. Journal of Human Ecology, 26(3), 153-161.
Şener, Ş., Şener, E., & Davraz, A. (2017). Evaluation of water quality using water quality index (WQI) method and GIS in Aksu River (SW-Turkey). Science of the total Environment, 584, 131-144. https://doi.org/10.1016/j.scitotenv.2017.01.102
Shraddha, S., Rakesh, V., & Others. (2011). Evaluation of water quality of Narmada River with reference to physio-chemical parameters at Hoshangabad city, MP, India. Evaluation, 1(3).
Simeonov, V., Stratis, J. A., & Others. (2003). Assessment of the surface water quality in Northern Greece. Water Research, 37(17), 4119-4124. https://doi.org/10.1016/S0043-1354(03)00398-1
Singkran, N., Yenpiem, A., & Others. (2010). Determining water conditions in the Northeastern rivers of Thailand using time series and water quality index models. Journal of Sustainable Energy & Environment, 1, 47-58.
Sutadian, A. D., Muttil, N., Yilmaz, A. G., & Perera, B. J. C. (2016). Development of river water quality indices—a review. Environmental monitoring and assessment, 188, 1-29. https://doi.org/10.1007/s10661-015-5050-0
Telanga, S., Saxena, Y., & Others. (2009). Effect of mass bathing on the water quality of Narmada River at district Hoshangabad, (MP) India.