Citations in impact factor journals
Prediction of heavy metals in acid mine drainage using artificial neural network from the Shur River of the Sarcheshmeh porphyry copper mine, Southeast Iran Environmental Earth Sciences |
Heavy metal pollution assessment using support vector machine in the Shur River, Sarcheshmeh copper mine, Iran Environmental Earth Sciences |
Citation to this article as recorded by
Alipour, M. and R. Derakhshani, 2010. Identification of hydrogeological properties using the results of the groundwater modeling. Res. J. Environ. Toxicol., 4: 67-76. CrossRefDirect Link |
Rahnama-Rad, J., M.Y. Bavali and R. Derakhshani, 2010. Optimization of hydraulic parameters of iranshahr alluvial aquifer. Am. J. Environ. Sci., 6: 477-483. Direct Link |
Citation to this article as recorded by
Prediction of toxic metals concentration using artificial intelligence techniques Applied Water Science |
Data on arsenic contamination in groundwater of Rafsanjan plain, Iran Data in Brief |
Evaluation of the Phytoextraction Potential at an
Acid-Mine-Drainage-Impacted Site Soil and Sediment Contamination: An International Journal Vol. 21, Issue 8, 970, 2012 |
Specification and prediction of nickel mobilization using artificial intelligence methods Central European Journal of Geosciences |
Optimization of Hydraulic Parameters of Iranshahr Alluvial Aquifer American Journal of Environmental Sciences Vol. 6, Issue 6, 477, 2010 |
Identification of Hydrogeological Properties Using the Results of the Groundwater Modeling Research Journal of Environmental Toxicology Vol. 4, Issue 2, 67, 2010 |
How to cite this article
R. Derakhshani and M. Alipour, 2010. Remediation of Acid Mine Drainage by using Tailings Decant Water as a Neutralization Agent in Sarcheshmeh Copper Mine. Research Journal of Environmental Sciences, 4: 250-260.
DOI: 10.3923/rjes.2010.250.260
URL: https://scialert.net/abstract/?doi=rjes.2010.250.260
DOI: 10.3923/rjes.2010.250.260
URL: https://scialert.net/abstract/?doi=rjes.2010.250.260