عنوان مقاله [English]
Background and purpose: The present study was performed to investigate trend and prediction of changes in some quality parameters of Gamasyab river water using multivariate statistical methods and time series.
Materials and methods: In this research, the annual means of some qualitative parameters related to a 6-year statistical period in two Pol-Chehr and DoAb stations were used. At first, the factors controlling chemistry of Gamasyab river were determined using Ternary and Gibbs diagrams. Then, to determine a linear relationship between multidimensional variables, Canonical correlation coefficients were used. Finally, the changing trend of water quality parameters in next 5-years was predicted.
Results: At Pol-Chehr station, qualitative parameters show an upward trend except for pH. While at DoAb, all qualitative parameters show a downward trend except for Mg and SO4. Based on Ternary and Gibbs diagrams, water dominant facies are Ca-Mg-HCO3 and the main factor controlling water chemistry is water-rock reaction at both stations, respectively. Results showed that the chemical parameters of HCO3 and Mg at Pol-Chehr with canonical coefficients of 0.938 and 0.933 are in the first group and Na with coefficient of 0.845 is situated in the second category. While in DoAb station, chemical variables HCO3 and Ca with coefficients of 0.945 and 0.0789 are placed in the first group, and Na and Cl with the coefficients of 0.930 and 0.800 are in the second group, respectively. First and second group origins of canonical variables can be related to dissolution of limestone and evaporative deposits. Prediction results of the water quality parameters changes in Gamasyab river for the next 5 years showed that an increase in all the parameters except for pH at Pol-Chehr station. While except for Mg and SO4, all quality parameters will decrease at the DoAb station.
Conclusion:Water-rock reaction is the most important factor affecting Gamasyab river water chemistry.
Document Type: Research article
1. Mirzaei R, Abbasi N, Sakizadeh M. Water Quality Assessment of Rivers in Bushehr Province by Using Water Quality Index During 2011-2013 Years. ISMJ. 2017;20(5):470-80.(In Persian)
2. Kalaji M, Ebrahimi A, Hasheminejad H, Motaghi A, Asadolah S. Water quality assessment of lake Zayandehrood Dam using WQI index. Isfahan University of Technology.2017;21(1):265-77.(In Persian)
3. Bricker OP, Jones BF. Main factors affecting the composition of natural waters. Trace elements in Natural Waters; Eds Salbu B & Steinnes E. 1995:1-20.
4. Khosravi Fard A, Vahabzadeh G, Gholami L. The Study and Classification of Water Quality of Ghorbaghestan and Doab Merk Stations in Gharasoo River Basin. Journal of Research in Environmental Health. 2017;2(4):299-310.
5. Khadempour F, Shahidi A. Qualitative assessment of surface water using the CWQI method and with the Aquachem software(Case study: Qaen River in South Khorasam). Iranian Jornal of Research in Environmental Health. Autumn 2017; 179-186. (In Persian)
6. Sharma P, Meher PK, Kumar A, Gautam YP, Mishra KP. Changes in water quality index of Ganges river at different locations in Allahabad. Sustainability of Water Quality and Ecology. 2014;3:67-76.
7. Sun W, Xia C, Xu M, Guo J, Sun G. Application of modified water quality indices as indicators to assess the spatial and temporal trends of water quality in the Dongjiang River. Ecological Indicators. 2016;66:306-12.
8. Qishlaqi A, Kordian S, Parsaie A. Hydrochemical evaluation of river water quality—a case study. Applied Water Science. 2017;7(5):2337-42.
9. Daou C, Salloum M, Legube B, Kassouf A, Ouaini N. Characterization of spatial and temporal patterns in surface water quality: a case study of four major Lebanese rivers. Environmental monitoring and assessment. 2018;190(8):485.
10. Sauerbrei W, Royston P, Schumacher M, Austin PC, Tu JV. Austin, PC, and Tu, JV (2004)," Bootstrap Methods for Developing Predictive Models,"" The American Statistician," 58, 131-137: Comment by Sauerbrei, Royston, and Schumacher and Reply. The American Statistician. 2005;59(1):116-8.
11. Nash MS, Chaloud DJ. Multivariate analyses (canonical correlation and partial least square (PLS)) to model and assess the association of landscape metrics to surface water chemical and biological properties using savannah river basin data. US Environmental Protection Agency Las Vegas, Nevada, USA. 2002.
12. Noori R, Sabahi MS, Karbassi AR, Baghvand A, Zadeh HT. Multivariate statistical analysis of surface water quality based on correlations and variations in the data set. Desalination. 2010;260(1-3):129-36.
13. Waxman MF. The agrochemical and pesticides safety handbook: CRC Press; 1998.
14. Bouwer H. Simple derivation of the retardation equation and application to preferential flow and macrodispersion. Groundwater. 1991;29(1):41-6.
15. Kumar M, Kumari K, Ramanathan A, Saxena R. A comparative evaluation of groundwater suitability for irrigation and drinking purposes in two intensively cultivated districts of Punjab, India. Environmental Geology. 2007;53(3):553-74.
16. Tabachinck B.L, Fidell S. Using multivariate statics. A pearson education company. Needham.2000. 966.
17. Fink G, Alcamo J, Flörke M, Reder K. Phosphorus loadings to the world's largest lakes: sources and trends. Global Biogeochemical Cycles. 2018;32(4):617-34.
18. Banerjee M. Impact of environmental factors on maintaining water quality of Bakreswar reservoir, India. Computational Ecology and Software. 2015;5(3):239.