مجله محیط زیست و مهندسی آب
سال ششم شماره 1 (بهار 1399)

In order to increase water productivity at farm level and smart irrigation, appropriate systems are essential so that can measure the moisture content in a proper and acceptable accuracy. In this regard, the wetting front device was made at the Soil and Water Research Institute and was evaluated in 3 textures: light, medium, and heavy at 3 levels of water salinity: no salinity (S0), 5(S1), and 10 (S2) dS/m. Then, to evaluate and measure the device in the mentioned conditions, it was tried to simultaneously measure the device numbers and soil sampling at certain depths at intervals of 24 h. After collecting data on the time of arrival of the moisture front to the soil depth and changes in soil moisture, statistical analysis was performed by soil sampling and soil detection device. The results showed that the device reacts in different textures and salinities. Moreover, the sensitivity of its sensors to sudden changes in soil moisture due to the arrival of the moisture front to a certain depth of soil has acceptable accuracy. Statistical results showed that the device has about 6 to 9% normal error in determining soil moisture in non-saline conditions, 28 to 41% in terms of using water with salinity of 5 dS/m, and 31-37% when a water with salinity of 10 dS/m was used. The model efficiency index also showed that the device is very useful in non-saline conditions with an average efficiency of 0.75 and is not recommended in saline conditions with negative efficiency index.

In this study, 18 surface and groundwater samples and 5 wastewater samples were analyzed to assess water recourses and wastewater quality at Shahid Hashemi Nezhad Gas Refinery region in terms of corrosion and scaling. The parameters measured were pH, EC, temperature, and concentration of major ions, including K+, Na +, Ca2+, Mg2+, SO42, Cl, HCO3- and CO32,. Majority of the water samples showed Na+- SO42- and Na+-Cl- type and face by Piper diagram. To assess corrosion and scaling of the samples, various indices were calculated including LSI, RSI, PSI, AI and S&DSI for CaCO3 deposition, and L&SI and Skillman for sulfates deposition especially CaSO4. The results showed most of the water samples had scale forming due to high hardness and alkalinity, and the wastewater samples were often corrosive and therefore, all of the samples did not have favorable quality for industrial uses. The results of hydrogeochemical studies indicated evaporation, evaporative minerals such as gypsum and anhydrite in the water flow path, carbonate formations and their dissolution were the most important parameters in controlling ionic content of the water resources.

In order to protect the bank and prevent their erosion spur dike is used. Importance of these structures in the bend is more, because of secondary flows and consequently bank erosion. In this paper the flow pattern around series of vertical spure dikes in the 90° bend is investigated by a 3D RANS solver. In order to simulate the complex behavior of free surface and turbulent flow the volume of fluid method and realizable k-ɛ closure have been used, respectively. Two lengths spure dike (equal to 15 and 25 percent of width), two spacing (3 and 5 three times the length) and two depths (3 and 5cm) in constant discharge 25 lit/s in the mild bend flume with width 0.7m and depth 0.12 m has been examined. Comparison among the results with experimental data shows good agreement among them. Also, the results illustrate spure dike deviations maximum velocity to the inner bank in entrance of bend and then deviations to the middle flume. Increasing the length of the spure dikes increases the velocity but it has no effect on the location of the maximum velocity as in all arrangement occurrence in 71 to 81 degree of bend. In the case of shear stress, the maximum value is in the range of 71 to 81˚.

In this study, the effect of climate change on temperature and rainfall data in the Kermanshah Sanjabi basin was investigated. For this purpose, using climate and temperature data from 1979-2005 (observation period), the values ​​of these variables in 2041-2100 (forecast period) were predicted under three scenarios RCP8.5, RCP4.5 and RCP2.6 and CanESM2 atmospheric general circulation model. The SDSM model was used to fine-tune the survey data in the study area. The results showed that the mean annual precipitation, maximum and minimum annual temperatures in the squared Ravansar basin will increase in the forecast period of 2041-2100. The most predicted values ​​of these variables belong to the RCP8.5 scenario so that according to this scenario, the average increase in precipitation in December, in the forecast periods 2041-2070 and 2071 2100 is 153 and 159.6%, respectively, compared with the average rainfall in the observation period. Based on the results of this study, it is expected that in order to properly manage the water resources of the RWC due to the impact of climate change, a proper perspective on the future status of water resources in the watershed will be presented to water resource managers in the future.

Treatment of municipal wastewater and its proper disposal is one of the most critical needs for urban services. Stabilization pond method is one of the simplified methods, low cost, and easy maintenance and operation. For evaluation of the Qorveh County Wastewater Treatment Plant, 54 samples were taken from the raw wastewater and the effluent in winter and spring seasons and 12 factors including: BOD, COD, TDS, TSS, pH, TC, FC, temperature, phosphate, nitrate, ammonia and the inlet and outlet turbidity of wastewater were measured according to Standard Methods. ANOVA and t-Test were used to analyze the data and to compare them with the national standards. The results showed that removal efficiency of BOD, COD, TSS, TDS, TC, FC, nitrate, phosphate and ammonia by Qorveh treatment plant were 81.56, 82.44, 70.81, 24.12, 99.91, 92.23,79.34, 56.51, and 96.16% respectively. The results of ANOVA aslso showed that the treatment plant performance was not affected by the season change. Comparing the amount of parameters with discharge standard determined that the values ​​of BOD, COD, TSS, TDS, TC, and FC were higher than the standard and the effluent could not be discharged into surface waters. Based on the grey water reuse for agricultural purposes, although all parameters except biological parameters were lower than the permitted level, the reuse of this wastewater without disinfection and supplementary purification is not possible due to the sensitivity and importance of health of agricultural products.

In this study, in order to simulate the current climate (1970-2016) for calculating the drought index in Fars Province, the data used include daily rainfall, minimum temperature, maximum temperature, and sunny hours at Shiraz station in a period of 46 years (1970-2016) as the entry for the LARS-WG statistical model. To simulate the climatic parameters at the Shiraz station basin, the data of HADCM3 model were downscaled using WG-LARS model under two scenarios A2 and A1B. The results showed that the average annual rainfall will increase under A2 scenario by about 1.5% and under A1B scenario by about 5.5% during 2020-2066 periods. Moreover, sunshine hours in the study period will be reduced under both scenarios. With high precision, the model could simulate maximum temperature, minimum temperature, and radiation parameters, but more error in simulating was presented in the precipitation parameter than other parameters. The highest increase, with about 80%, was due in September under scenario A2, which occurred in the upcoming period of the study period. Based on the SPI drought index, the most severe droughts occurred in 2008 in Shiraz station showing an index value of -2.89. Moreover, SPI shows that the most precipitation was recorded in 1995 with an index value of 1.91.

Today, the phenomenon of flooding is one of the most complex hazardous events that, more than any other natural disaster, causes deaths and finances every year in different parts of the world. Therefore, flood susceptibility mapping is the first step in a flood management program. The purpose of this study was to identify flood susceptible areas using two methods of random forest (RF) and Bayesian generalized linear model (GLMbayesian) machine learning in the Tajan watershed in Mazandaran province, Sari. Past flood distribution maps were prepared to predict future floods. Of the 263 flood locations, 80% (210 flood locations) was used for modeling and 20% (53 flood locations) was used for validation. Based on previous studies and surveying of the study area, 13 conditional factors were selected for flood zoning. The results showed that three factors of elevation (21.55), distance from the river (15.28) and slope (11.18) had the highest impact on flood occurrence in the study area, respectively. The results also showed that the AUC values for RF and GLMbayesian models were 0.91 and 0.847, respectively, indicating the superiority of the RF model and the accuracy of this model in flood susceptibility mapping in the study area. The highest flood susceptibility area in the RF model is in the very low class and the high class in the GLMbayesian model.