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Hossein Babazadeh
Associate Professor, Department of Water Sciences and Engineering, Science and Research Branch, Islamic Azad University, Tehran,
Civil Engineering, Building, Construction & Architecture

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Journal : Civil Engineering Journal

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Investigated of Desalination of Saline Waters by Using Dunaliella Salina Algae and Its Effect on Water Ions Asma Moayedi; Bahman Yargholi; Ebrahim Pazira; Hossein Babazadeh
Civil Engineering Journal Vol 5, No 11 (2019): November
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/cej-2019-03091423

Abstract

Nowadays, due to augmentation of population and expansion of cities and the limitation of fresh water sources in the world, existing water resources cannot meet the human needs. Desalination or reduction of salinity of water through biological methods involves the use of plant species, microorganisms, algae or a combination of them, which can be effective in reducing water salinity. The objective of this study was to investigate the desalination of saline waters by using Dunaliella salina algae. For this purpose, the experiments were carried out as factorial based on completely randomized design. The expected tests were conducted in a laboratory controlled condition for humidity, light and temperature (90 days). During this research, the Electrical Conductivity (EC) was measured daily. The results showed that salt absorption in Dunaliella salina algae was significantly different. High salt absorption was observed in Dunaliella salina at a concentration of 130mS.cm-1. Due to the constant humidity, light and temperature, salt removal from saline water was observed in laboratory conditions. The results of this study indicate that significant reduction of chlorine, sodium and bicarbonate levels were observed using Dunaliella salina algae. According to the results of this study, it seems that reducing salt absorption in algae is due to the use of salt in the metabolism and the growth and proliferation of algae. The absorption process in this study showed that the catch of Dunaliella salina has a good ability to remove salt and can be used as an appropriate suggestion for salt removal from saline water.
Forecasting by Stochastic Models to Inflow of Karkheh Dam at Iran Karim Hamidi Machekposhti; Hossein Sedghi; Abdolrasoul Telvari; Hossein Babazadeh
Civil Engineering Journal Vol 3, No 5 (2017): May
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (718.733 KB) | DOI: 10.28991/cej-2017-00000095

Abstract

Forecasting the inflow of rivers to reservoirs of dams has high importance and complexity. Design and optimal operation of the dams is essential. Mathematical and analytical methods use for understanding estimating and prediction of inflow to reservoirs in the future. Various methods including stochastic models can be used as a management tool to predict future values of these systems. In this study stochastic models (ARIMA) are applied to records of mean annual flow Karkheh river entrance to Karkheh dam in the west of Iran. For this purpose we collected annual flow during the period from 1958/1959 to 2005/2006 in Jelogir Majin hydrometric station. The available data consists of 48 years of mean Annual discharge. Three types of ARIMA (p, d, q) models (0, 1, 1), (1, 1, 1) and (4, 1, 1) suggested, and the selected model is the one which give minimum Akaike Information Criterion (AIC). The Maximum Likelihood (ML), Conditional Least Square (CLS) and Unconditional Least Square (ULS) methods are used to estimate the model parameters. It is found that the model which corresponds to the minimum AIC is the (4, 1, 1) model in CLS estimation method. Port Manteau Lack of fit test and Residual Autocorrelation Function (RACF) test are applied as diagnostic checking. Forecasting of annual inflow for the period from 2006 to 2015 are compared with observed inflow for the same period and since agreement is very good adequacy of the selected model is confirmed.
Co-Authors Abdolrasoul Telvari Asma Moayedi Bahman Yargholi Ebrahim Pazira Hossein Sedghi Karim Hamidi Machekposhti