Analysis of the surface water quality parameters in the Aji-Chai Watershed based on the multivariate statistical techniques

Kazemzadeh, Majid; Malekian, Arash

doi:10.22059/jrwm.2017.109430.779

Document Type : Research Paper

Authors

https://doi.org/10.22059/jrwm.2017.109430.779

Abstract

One of the most important dynamic ecosystems is river, awareness of spatio-temporal water quality changes of which is necessary. In this research, we studied the spatiotemporal water quality changes using three techniques of Cluster analysis (CA), Discriminant analysis (DA) and Principal Component analysis (PCA) in the Aji-Chai watershed over 1981-2010. Applying clustering, we identified three homogeneities clusters. Stations which were labeled in the first cluster showed that they are located in the upstream of Aji-Chi River. In comparison with other stations, these stations showed better water quality and the lowest changeability. DA methods significantly determined the three functions which described about 73.50, 20.30 and 3.40% of total variances. In the other word, in general three functions described the 97.20% of the total variances. Also the DA methods revealed the HCO-3, SAR, Na+, SO42- and Ca2+ were the most important parameters affecting upon water quality, based on which it's possible to seperate homogenous clusters. Finally, the results of PCA showed that the first two factors were the most important factors of water quality changes in the Aji-Chai River Watershed. These factors described about 78.75 and 14.71% of the variances, respectively.

Keywords

References

[1] Chen-Wuing, L., Kao-Hung, L. and Yi-Ming., B. (2003). Application of factor analysis in the assessment of groundwater quality in a Blackfoot disease area in Taiwan. Journal of the Science of the Total Environment, 313, 77-89.

[2] Erol, A. and Randhir, T. O. (2013). Watershed ecosystem modeling of land-use impacts on water quality. Ecological Modelling, 270, 54-63.

[3] Faryadi, S., Shahedi, K. and Nabatpoor, M. (2011). Investigation of Water Quality Parameters in Tadjan River using Multivariate Statistical Techniques. WatershedManagement Journal, 3(6), 75-92.

[4] Frid Gigloo, B., Najafinejad, A. and Moghani Bilehsavar, V. (2013). Evaluation of water quality variation of Zarringol river, Golestan province. Journal of Water and Soil Conservation, 20, 78-96.

[5] Gorji Anari, M. and Rafahi, H. GH. (1995). Study of saline surface water of Ajichai watershed and effect of erosion on its quantity. Iranian Journal of Agriculture Science, 26(4), 43-59.

[6] Karami, F. and Bayatieh Khatibi, M. (2011). Spatial monitoring of the groundwater quality in different geological formations (Case study: upstream of Aghi-Chi watershed). Journal of Geography and Regional Development, 17, 27-47.

[7] Mirzai, M., Riahi-Bakhtiar, A., Salman-Mahini, A. and Gholamalifard, M. (2013). Analysis of the physical and chemical quality of Mazandaran province (Iran) rivers using multivariate statistical methods. Mazandaran University of Medical Sciences, 23(108), 41-52.

[8] Murdoch, P. S., Baron, J. S. and Miller, T.L. (2000). Potential effects of climate change on surface water quality in North America. Journal of the American Water Resources Association, 36, 347-366.

[9] Noori, R., Khakpour, A., Omidvar, B. and Farokhnia A. (2010). Comparison of ANN and principal component analysis-multivariate linear regression models for predicting the river flow based on developed discrepancy ratio statistic. Expert Systems withApplications, 37(8), 5856-5862.

[10] Nosrati, K., Derafshi, Kh., Ghrachahi, S. and Rahimi, Kh. (2011). Assessment of Surface Water Quality in Haraz-Ghara Soo Watershed using Multivariate Statistical Techniques. Research Earth Science Journal, 5, 41-55.

[11] Ouyang, Y. (2005). Evaluation of river water quality monitoring stations by principal component analysis. Water Research, 39(12), 2621-35.

[12] Papatheodorou, G., Demopouloua, G. and Lambrakis, N. (2006). A long-term study of temporal hydro chemical data in a shallow lake using multivariate statistical techniques. Journal of Ecological Modeling, 193, 759-776.

[13] Rabia Koklu, R., Sengorur, B. and Topal, B. (2010). Water Quality Assessment Using Multivariate Statistical Methods—A Case Study: Melen River System (Turkey). Water Resources Management, 24, 959–978.

[14] Rasi Nezami, S., Nazariha, M., Baghvand, A. and Moridi, A. (2012). Karkheh River Water Quality Using Multivariate Statistical Analysis and Qualitative Data Variations. Journal of Health System Research, 8(7), 1280-92.

[15] Razmkhah, H., Abrishamchi, A. and Torkian, A. (2010). Evaluation of spatial and temporal variation in water quality by pattern recognition techniques: A case study on Jajrood River (Tehran, Iran). Journal of Environmental Management, 91, 852-860.

[16] Salajeghe, A., Razavi Zadeh, S., Khorasani, N., Hamidfar, M. and Salajeghe, S. (2010). Land use changes and their impact on the river water quality (Case study: Karkheh watershed). Journal of Environmental Studies, 58, 81-86.

[17] Singh, K., Malik, A., Mohan, D. and Sinha., S. (2004). Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)—a case study. Water Research, 38, 3980–3992.

[18] Zare Chahoky, M. (2009). Data analysis in natural resources research using SPSS software. University of Tehran press.

Journal of Range and Watershed Managment

Analysis of the surface water quality parameters in the Aji-Chai Watershed based on the multivariate statistical techniques

References

References

Volume 70, Issue 2
August 2017
Pages 465-478

Analysis of the surface water quality parameters in the Aji-Chai Watershed based on the multivariate statistical techniques

References

References

Volume 70, Issue 2August 2017Pages 465-478

Volume 70, Issue 2
August 2017
Pages 465-478