Microalgae play an important role during the tertiary treatment of municipal wastewater. Cell immobilization techniques have been developed in order to improve the quality of the treated wastewater and avoid wash out of the biomass. Since cell immobilization method may affect the nutrient removal efficiency, ten strains of microalgae were immobilized in sodium alginate gel in differentdiameter circular screens, and orthophosphate removal efficiency from municipal wastewater was studied. Results indicate that the alginate immobilization screen size and contact surface with wastewater affects the microalgae synthesis activity and thus orthophosphate removal efficiency. Increasing the contact surface by making smaller alginate screens will increase the cation exchange rate and reduce the orthophosphate concentration in the medium. Among all microalgae treatments, Scenedesmus rubescens MCCS 018, Chlamydomonas sp. MCCS 026, and Chroococcus dispersus MCCS 006 had the highest PO 4 3--P removal efficiency of 68.8%, 71.9%, and 72.3% within 12 days.

This research investigated the quality of groundwater of 298 wells during 10 years, in Fars province, southern Iran, to survey spatial variation of groundwater quality and also major sources of hydro-chemical components for drinking and agricultural uses. To classify the sampling stations in each year, hierarchical cluster analysis, using the Euclidean distances and "Ward" method, was used. According to the results of cluster analysis, there were three quality groups in groundwater of the research area: first group of 170 wells with type of Ca-HCO3, second group of 98 wells with type of Ca-HCO3, and third group of 30 wells with type of Na-Cl. Hydro-chemical parameters were increased from the first to the third group, and on the basis of Schoeller and USSL diagrams, the water of wells of the third group was considered unsuitable for irrigation and drinking. Principal component (PC) analysis and factor analysis reduced the complex and voluminous data matrix into three main components, accounting for more than 80 % of the total variance. The first PC contained TDS, EC, TH, Na(+), Cl(-), Mg(2+), SO4 (2-), Ca(2+), and SAR parameters. Therefore, the first dominant factor was salinity. In PC2, HCO3 and pH were the dominant parameters, which may indicate weathering of silicate minerals. The PC3 contained high loadings for NO2 (2-) and NO3 (-). This factor indicates anthropogenic contaminants that may be caused by improper disposal of domestic wastes or the use of chemical fertilizers in agriculture and leaching of them.

Salinization is a gradual process that should be monitored. Modelling is a suitable alternative technique that saves time and cost for the field monitoring. But the performance of the models should be evaluated using the measured data. Therefore, the aim of this study was to evaluate and compare the SALTMED and HYDRUS-1D models using the measured soil water content, soil salinity and wheat yield data under different levels of saline irrigation water and groundwater depth. The field experiment was conducted in 2013 and in this research three controlled groundwater depths, i.e., 60 (CD60), 80 (CD80) and 100 (CD100) cm and two salinity levels of irrigation water, i.e., 4 (EC4) and 8 (EC8) dS/m were used in a complete randomized design with three replications. Soil water content and soil salinity were measured in soil profile and compared with the predicted values by the SALTMED and HYDRUS-1D models. Calibrations of the SALTMED and HYDRUS-1D models were carried out using the measured data under EC4-CD100 treatment and the data of the other treatments were used for validation. The statistical parameters including normalized root mean square error (NRMSE) and degree of agreement (d) showed that the values for predicting soil water content and soil salinity were more accurate in the HYDRUS-1D model than in the SALTMED model. The NRMSE and d values of the HYDRUS-1D model were 9.6% and 0.64 for the predicted soil water content and 6.2% and 0.98 for the predicted soil salinity, respectively. These indices of the SALTMED model were 10.6% and 0.81 for the predicted soil water content and 11.0% and 0.97 for the predicted soil salinity, respectively. According to the NRMSE and d values for the predicted wheat yield (9.8% and 0.91, respectively) and dry matter (2.9% and 0.99, respectively), we concluded that the SALTMED model predicted the wheat yield and dry matter accurately.

In this research, four methods of in situ measurement of saturated hydraulic conductivity (Ks) including the Guelph permeameter (GP), auger hole (AH), original Porchet (OP), and saturated Porchet methods were compared for a silt loam soil. The representative Ks in a drainage system was also determined as a reference value. The mean values of Ks for the GP, AH, OP, SP, and drainage system methods were 1.18, 1.06, 1.85, 1.18, and 1.08 m d−1, respectively. Furthermore, the GP and OP methods had the highest and lowest coefficients of variation at 42.1 and 24.2%, respectively. The difference in Ks values among all methods except SP and GP and the difference in CV values between GP and OP were statistically significant at the 0.01 level of probability. The direct measurement from the drainage system resulted in Ks values of 0.584, 0.915, 1.019, and 0.915 times that of the OP, SP, AH, and GP methods, respectively. The results of the SP, GP, and AH methods were very similar to that obtained from direct measurement of the drainage system. Results showed that the AH and GP methods are the best methods for measuring Ks in the presence and absence of a water table, respectively, with −1.85 and 9.26% difference, respectively, compared with the reference method. Therefore, in regions with a high water table, the AH method is suitable, and for a low water table, the GP method is recommended.

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