Increasing Water Quality Modeling Efficiency by Separating the Year into Hot and Cold Months (Case of Study: Watershed of Sanandaj Gheshlagh Dam)

Subject Areas : Water Resource Management

Seyed Pedram Nainiva ¹ (M.Sc. Student, Department of Watershed Management Engineering, Faculty of Natural Resources, Sari University of Agricultural Sciences and Natural Resources, Sari, Iran. *(Corresponding Authours))
Kamran Chapi ² (Assistant Professor, Department of Rangeland and Watershed Management, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran.)

Received: 2017-01-07 Accepted : 2017-05-10 Published : 2019-10-23

Keywords: Sanandaj Gheshlagh Dam, Modeling, Water Qualitative Parameters, discharge,

Abstract :

Background and Objective: Nowadays, water is considered as one of the factors for improvement and economic growth of societies. The hot and cold seasons of the year and its comparison with the non-segregation of the hot and cold seasons are 26 years. Method: In this study, after studying the accuracy of discharge data, electrical conductivity, soluble matter, chlorine, calcium, sodium, magnesium, acidity and sodium uptake ratio of the two stations, it was tried to find appropriate regression relationships between discharge parameter and qualitative parameters. Provide water. Findings: The results showed that the Chehelgazi sub-watershed in cold months, the liner relationship between discharge with electrical conductivity, dissolved solids, chloride and sodium and also the exponential relationship was suitable between discharging with calcium. In warm months for this sub-watershed, the linear relationship presented the suitable relationship between discharge with dissolved solids, electrical conductivity, magnesium, calcium, sodium and the sodium adsorption. Also, the linear relationship was suitable between discharge with dissolved solids, electrical conductivity, chloride and sodium whereas the exponential relationship was better between the discharging with calcium in Khalifehtarkhan sub-watershed. In this sub-watershed, for warm months, the linear relationship was suitable for the relationship between discharge with dissolved solids, electrical conductivity, chloride, sodium and sodium adsorption. The separation comparison of cold and warm months with non-separation showed that non-separation of cold and warm months is not possible the chloride and magnesium estimation (in Chehelgazi sub-watershed) and calcium estimation (in Khalifetarkhan sub-watershed). Discussion and Conclusion: using obtained relationships and seasonal changes of surface waters quality, with discharge rate can create modeling water quality, extraction and recovery of water quality data.

References:

1. SolaimaniSardo, M ., Vali, A.A., Ghazavi, R., Saidi Goraghani, H.R. 2013. Trend Analysis of Chemical Water Quality Parameters; Case study Cham Anjir River, Journal of Irrigation and Water Engineering, 3(12), 95-106 (In Persian).


2. Shekohifar, M., Izadpanah, Z. 2013. Relationship between TDS, EC, HCO3 and CL with Karun River discharge in cold and hot seasons using regression analysis, First National Conference on Water and Agricultural Resources Challenges, Irrigation and Drainage Association of Iran Islamic Azad University Khorasgan Branch (In Persian).


3. Mosaedi, A., Zanganeh, M.E., Karimi, I. 2010. Investigating the Relationship between Chemical Parameters in Water and Flow Rate by Regression Analysis, 6th National Conference on Watershed Management Science and Engineering and 4th National Conference on Erosion and Sedimentology, Tarbiat Modares University, Mazandaran (In Persian).


4. Karami, O., Hoshmand, A.R. 2013. Validation and estimation of correlation between TDS and EC of Karun River water, In high water and low water seasons, 4th National Conference on Irrigation and Drainage Network Management, Shahid Chamran University of Ahwaz, Faculty of Water Science Engineering (In Persian).


5. Nainiva, S.P., Hamidi, SH., Yarahmad, S. 2014. Linear Regression Model of Electrical Conductivity (EC) and Total dissolved solids (TDS) for Water Quality Management in Two Hydrometric Stations of Qeshlagh Dam, Sanandaj, Third National Conference on Environmental Research in Iran, University of Kurdistan, Sanandaj (In Persian).


6. Nainiva, S.P., Chapi, K., Yarahmad, S., Hamidi, SH.  2014. Relationships of Chemical Parameters of Water with Water Discharge in the Gheshlagh Watershed, The First Electronic Conference on New Findings in the Environment and Agricultural Ecosystems, Institute of New Energy and Environment, University of Tehran, Tehran (In Persian).


7. Hojati, M., Bostani, F., Aboverdi, J. 2009. Correlation of discharge and electrical conductivity of rivers in Bakhtegan basin using two methods of Pearson and Kendall,  Journal of Water Engineering, 2, 83-94 (In Persian).


8. Ouyang, Y., P. Nkedi-Kizza, Q.T. Wu, D. Shinde, C.H. Huang. 2006.Assessment of seasonal variations in surface water quality. Water Research, 40(20), 3800-3810.


9. Meybeck, M. 2002. Riverine quality at the Anthropocene: propositions for global space and time analysis, illustrated by the Seine River. Aquat. Sci. 64: 376-393.


10. Kay, D., M. Wyer, J. Crowther, C. Stapleton, M. Bradford, A. McDonald, J. Greaves, C. Francis and J. Watkins. 2005. Predicting faecal indicator fluxes using digital land use data in the UKs sentinel Water Framework Directive catchment: the Ribble study. Water Res. 39: 3967-3981.


11. Dawe, P. 2006. A statistical evaluation of water quality trend in selected water bodies of Newfoundland and Labrador. J. Eviron. Eng. Sci. 5: 59-73.


12. Chang, H.J. 2008. Spatial analysis of water quality trend in the Han River basin, South Korea, 1993_2002. Water Resour. 42: 3285-3304.


13. Li, S., Gu,S., Tan,X., Zhang,Q. 2009. Water guality in the upper Han River. China: The impacts of land use/land cover in riparian buffer zones, Journal of Hazardous Materials, 195, pp 317-324.


14. Loukas, A. 2010. Surface water quantity and quality assessment in Pinios River, Thessaly, Greece. Desalination, 250(1), 266-273.‏


15. Sun, W., Xia, C., Xu, M., Guo, J., and Sun, G. 2016. Application of modified water quality indices as indicators to assess the spatial and temporal trends of water quality in the Dongjiang River. Ecological Indicators, 66, 306-312.‏


16. Gorji, M., Refahi, H. 1994. Investigating the causes of salinity of Ajji River and its optimal use of water, Seventh Seminar of the National Committee on Irrigation and Drainage (In Persian).


17. Karami Moghadam, A., Hji MashHadi, S. 2006. Investigating the role of Gorganrood River discharge changes in the process of influence of chemical foundations of its water quality (Case Study on Gorgan, Ghoraqoli and Gorgan Dam Stations), Seventh International Seminar on River Engineering (In Persian).


18. Ghovhi, J.H., Habibnezhad, M., Vahabzadeh. G., Khaledi Darvishan, A. 2012. Efficiency of Different Data Separation Methods to Increase the Accuracy of Sediment Rating Curve; Case Study A Part of the Sefidrood Watershed, Journal of Irrigation and Water Engineering, 2(7), 97-111 (In Persian).


19. Mohamadi, H., Kalantari, N., Pahlavanzadeh, S. 2014. Investigation of the Impact of Jarra Dam Construction on Yellow River Water Quality Using Statistical and Hydrochemical Methods, Second National Conference on Water Crisis, Shahrekord University, 116-122 (In Persian).


20. Grum M., R. H. Aalderink, L. Lijklema and H. Spliid. 1997. The underlying structure of systematic variations in the event mean concentrations of pollutants in urban runoff. Water Sci. Tech. 36(8-9): 135-140.


21. Vervier P., A. Pinheiro, A. Fabre, G. Pinay and E. Fustec. 1999. Spatial changes in the modalities of N and P inputs in a rural river network. Water Res. 331: 95-104.


22. Miller, J. D. D. Hirst. 1998. Trends in concentration of solutes in an upland catchment in Scotland. Science of the Total Environment 216: 77-88.


23. Naddafi, K., H. Honari, and M. Ahmadi. 2007. Water quality trend analysis for the Karoon River in Iran. Journal of Environ Monitor Assessment 134: 305-312.


24. Jacovides, C. P., 1997, Reply to comment on Statistical procedures for the evaluation of evapotranspiration models. Agricultural water management 3:95-97.