مجله محیط زیست و مهندسی آب
سال پنجم شماره 1 (بهار 1398)

The water body of Urmia Lake in recent years has been faced with a significant reduction in surface area and volume due to various reasons such as successive droughts. Therefore, in this study, the situation of drought was evaluated at the synoptic station of Tabriz as one of the important stations of Urmia Lake basin in different time scales using the standardized precipitation-evapotranspiration index (SPEI) and the gene expression programming (GEP) model. For this purpose, the SPEI index was used for drought monitoring at 1, 3, 6, 12, 24, and 48 months during the 53-year statistical period. The results showed that three long periods of drought related to the years 1961-1963, 1986-1992, and 1997-2009 are available during the statistical period. According to the results, the prediction accuracy is directly related to increasing the scale of SPEI and increased by increasing the scale of SPEI, so that the correlation coefficient in the test stage in the one-month scale (SPEI1) increased from 0.203 to 0.988 at 48-month scale (SPEI48) and the overall accuracy of the model increased from 57.1 in SPEI1 to 94.2 % in SPEI48.

Investigating the spatial variation of groundwater quality parameters is important in identifying the quality of the aquifer and contaminating resources, and determining the most appropriate management solutions. Geostatistical and GIS methods can be useful tools in this regard. The aim of this study was to evaluate the geostatistical methods in order to investigate and analyze the spatial amount of salinity, nitrate, and total dissolved solids of subsurface waters of Sistan Plain in northern Sistan and Baluchestan province. For this purpose, ordinary Kriging (OK) and simple Kriging (SK) and certain methods such as inverse distance weigthing (IDW), local polynomial interpolation (LPI), global polynomial interpolation (GPI) and radial basis function (RBF) were used. First, the normality of the data was investigated and the non-normal data were normalized by logarithmic method. Then analysis of variograms was performed. The results were evaluated using a cross-evaluation method. The fitting results of the models showed that the EC and TDS indices follow the Gaussian model and the nitrate index follows the spherical model, and simple kriging method is suitable for salinity and nitrate mapping and ordinary kriging for zoning maps of TDS. Moreover, based on the Schuller's diagram, in terms of TDS, sub-surface waters of the region are classified as good to acceptable and in terms of salinity for agricultural use in the moderate to severe problem class.

Among the various natural hazards, floods may be considered as the most devastating factor that inflicts great damage on human societies. Therefore, the importance of estimating flood damage and its scope in planning to reduce damages and determine points with high risk is very important. The aim of this study is to determine the extent of flood hazard using OLI satellite data. For this reason, a window of OLI satellite images of Landsat 8 was acquired before and after the Dezful flood of April 25, 2016. First, preprocessing operations include radiometric and atmospheric corrections of images were done, and the principal component analysis was then used to reduce the correlation of the data. Data processing was performed using a Support Vector Machine algorithm with linear and polynomial kernels. In order to train the Support Vector Machine algorithm, training samples for each class (agricultural land, flood extent, water resources, settlement areas, and recreational areas along the river boundary) were harvested at the user level. In order to evaluate the similarity of the classes and the degree of correlation between the samples, the quantitative assessment method of the Jeffries Matusita was performed. The results showed that the flood area was 11593.26 ha, the highest damage was due to agricultural land with a destruction of 8467.45 ha and recreational and tourist areas along the riverbank with a destruction of 2659.14 ha.

Urban green space has always faced challenges to estimate the actual water requirement of plants due to the diversity of different plant species, their dispersal, and the different densities. In this research, we have tried to estimate the need for the University of Science and Research Branch with an area of 10.59 hectares. First, it has been necessary to identify and categorize existing species and finally 77 plant species were identified on the site of Science and Research Branch. In addition, due to the diversity in trees and green spaces, the California Journal’s method was used to calculate crop coefficient. The meteorological data required from the meteorological stations in Tehran was then obtained by the Iran Meteorological Organization and processed by the CROPWAT program. In the next step, the potential evapotranspiration was calculated using Penman Monteith method. Finally, the water requirement for green space was determined by the California University method. The results of this study indicate that the maximum water requirement is 246033.7 cubic meters in July. Also, in January, February, November, and December, due to the long-term average rainfall, this amount provides the water requirement of the site and there is no need for irrigation during this period.

In this study, chitosan-coated magnetically nanoparticles were used to remove the Reactive Red 120 dye from aqueous solution. Chitosan is one of the most famous biological polymers that can be used as adsorbent in the removal of color pollutants. Magnetic Fe3O4 nanoparticles synthesized by mixing FeCl3.6H2O and FeCl2.4H2O were coated on low molecular weight chitosan polymer. Magnetic nanoparticles coated with chitosan were then characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier transform infrared (FTIR), X-ray diffraction (XRD) and vibrating sample magnetomer (VSM) analysis. The effect of three parameters of pH, dye concentration, and the adsorbent dosage on adsorption was investigated. Under these conditions, the optimal adsorption was obtained ​​at pH = 4, initial dye concentrations = 150 mg/l, and the adsorbent dosage of 2 g/l. Adsorption data were adapted to Langmuir and Freundlich isothermic models. The results showed that the data obtained from the dye adsorption on the chitosan-coated magnetically nanoparticles fit better with Langmuir model.

The erosion of bed and river banks and sediment transport is one of the reasons for migration and changes in river morphology, which causes changes in the quality and quantity of flow. Groins are among the rivers' structures that extend from the coast to the river's axis. One of the important issues in their design is the localized scouring phenomenon on the nose, which appears due to changes in the pattern of flow and the presence of strong vortices. In recent years, most of the research on single-row open and closed open spray guns has been carried out and has been performed in a laboratory. Therefore, in this research, scouring and three-dimensional flow patterns were simulated near the open two-row openings with two zigzag and parallel formations with Flow-3D model and using the RNG turbulence model and compared with experimental results. The results showed that the scour area and the dimensions obtained from numerical simulation as well as flow patterns are in good agreement with experimental results.

In recent years determination of different components of water balance has been the focus of many hydrological modeling techniques. In most basins, it is not feasible to measure all the different quantities for a detailed and enhanced hydrological modeling. Therefore, it is necessary to select a model capable of simulating hydrological events with the least number of variables; while being simple to use. Hence, in this paper the monthly runoff of Ravansar Sanjabi basin, Kermanshah, Iran was simulated through AWBM and SWAT models. AWBM is a lumped model simulating the runoff in basins using rainfall and evaporation variables. On the other hand, SWAT model is a continuous and semi-distributive model, which can simulate the hydrological processes in basins through a wide range of information such as physical information of basins (soil, land use, slope) as well as weather data such as precipitation, temperature, wind, relative humidity, and solar radiation. Simulation results during the calibration and validation periods were evaluated through two statistical indices: Nash–Sutcliffe efficiency (NSE) and coefficient of determination, R2. Comparison of calculated statistical coefficients showed that SWAT model has better results in simulating monthly runoff in calibration and validation periods so that the calculated NSEcoefficient was equal to 0.7 and 0.81 respectively and 0.63 and 0.5 for AWBM model respectively.

Many studies have projected increasing the temperature with decreasing precipitation for future decades in different regions of Iran. But, few studies have evaluated the effect of climate change on the dynamics of soil organic carbon (SOC) sources. One of the obstacles is the lack of recognition of carbon models and the lack of sufficient information on the required data and how to supply the data. The purpose of present study was to investigate the structural and practical application of the RothC model as the most widely used model worldwide for assessing the effects of climate change on soil carbon sources. In this study, the model’s function for calculating SOC and the factors affecting SOC decomposition, including temperature correction coefficient, moisture correction coefficient, and vegetation correction coefficient were completely investigated. Then, in the application section of the model, the required data and how to provide them in the conditions of Iran, and finally validation and implementation of the model for future climate conditions were discussed. Results showed that the RothC model is now the best carbon model for Iran conditions due to the simplicity and availability of the required data to its implementation. Generally, the present study provides useful information needed in implementation and validating the RothC model to simulate and predict the effects of climate change on the dynamics of soil carbon sources.