JWSS - Journal of Water and Soil Science

Determining the relative distribution of each chemical form of the elements and their relationship with the physical, chemical, and clay mineralogical properties of soils can help researchers to achieve the sustainable agricultural management. The present study was conducted to evaluate the chemical forms of four micronutrients (Zn, Cu, Fe and Mn) in some surface and subsurface soils of Kohgiluyeh and Boyer Ahmad province and their relationship with the physical, chemical and mineralogical properties of the soils. The results showed that the exchangeable and sorbed chemical forms of the studied elements were very low and negligible, but the residual, carbonate, and organic forms had the highest to lowest values of the chemical forms of these elements, respectively. Examination of the correlation of the chemical forms of these elements with soil properties showed the effective correlation of organic carbon values with the Zn chemical forms; also, there was a correlation between clay, silt, cation exchange capacity and calcium carbonate and the chemical forms of Cu, Fe and Mn. The correlation between the quantities of clay minerals and the chemical forms of these elements showed that the amounts of different forms of the studied elements were directly related to 2:1 clay silicate minerals (especially vermiculite). Evaluation of Fe and Mn chemical forms  also showed that the amounts of these elements were higher in the  soils with developed profiles (Alfisol and Mollisol), the  wetter climate and zeric moisture regime rather  than in soils with non-developed profiles (Entisols and Inceptisols) and a drier climate and a ustic moisture regime. In general, the results showed that variations of soil forming factors such as climate (as well as the  total amount of each micronutrients), could be effective on the chemical forms of micronutrients (especially on Mn and Fe);  these can be effective in the management of weakly to highly-developed soils orders.

Water resources are limited in many areas of the world; sometimes, even these limited resources are negligently contaminated. One of the polluting factors of water is oil and its derivatives. Oil absorption using textiles is one of the common ways to separate oil from water. In this study, we used three types of textiles with different properties in order to make the filter. The experiments were performed using three different concentrations of 10, 20 and 30% oil. In this study, three types of BC, PET and PP textiles in the presence of horizontal and vertical drainages were investigated. The PET and PP textiles were made of nonwoven polyester and polypropylene fibers, respectively, and the BC textile was a two-component nonwoven textile of both polyester and polypropylene fibers that was used for the first time. Flow through the textiles was turbulent. Coefficients of flow were calculated using non-Darcy flow relations and the optimization method. The results showed that at low oil concentrations, the oil absorption had an inverse relation with the porosity and turbulent flow coefficients, but at higher concentrations, the effect of these agents was less; instead, the effect of the concentration and the intrinsic ability of the non-woven fibers was greater.  The best performance was related to PP and PET with the horizontal drainage that had 95 and 91 absorption rates, respectively.

Optimization of artificial intelligence (AI) models is a significant issue because it enhances the performance and flexibility of the numerical models. In this study, scour depth around bridge abutments with different shapes was estimated by means of ANFIS and ANFIS-Genetic Algorithm. In other words, the membership functions of the ANFIS model were optimized using the genetic algorithm, finding that the performance of ANFIS model was increased. Firstly, effective input parameters on the scour depth around bridge abutments were defined. Then, by using the input parameters, eleven ANFIS and ANFIS-GA models were produced. Next, the superior ANFIS and ANFIS-GA models were introduced by analyzing the numerical results. For example, the correlation coefficient and scatter index for ANFIS model were calculated to be 0.979 and 0.070; for ANFIS-GA, these were 0.986 and 0.056, respectively. In addition, the average discrepancy ratio (DR_ave) for ANFIS and ANFIS-GA models was 0.984 and 0.988, respectively. Also, it was shown that the ANFIS-GA models had more accuracy, as compared to the ANFIS models. Moreover, a sensitivity analysis showed that Froude number (Fr) and ratio of flow depth to radius of scour hole (h/L) were the most influential input parameters for simulating the scour depth around bridge abutments.

Soil erosion is one of the most serious environmental issues in the world, causing soil degradation, reduction of land productivity, increasing flood, water pollution and pollutions transportation; it is also a serious threat to sustainable development in the world. Therefore, the soil conservation and the prevention of soil erosion and use of conditioners as the nanoclay can be considered as a solution to improve   land productivity and protect environment. The present study was, therefore, conducted to address the effect of the application of montmorillonite nanoclay with three rates of 0.03, 0.06 and 0.09 t ha^-1 on changing runoff and soil loss variables under laboratory conditions. The results showed that the nanoclay with the rate of 0.03 t ha^-1 could decrease the runoff coefficient, soil loss and sediment concentration with the rate of 40.65, 88.38 and 82.19 percent, respectively. The average of soil loss in control treatment and conservation treatments of nanoclay with various rates was measured to be 3.76, 0.44, 1.33 and 3.16 g, respectively. Also, the results showed that the most sediment concentration was the control treatment with the rate of 5.84 g l^-1 and the conservation treatments with nanoclay in the applied rates was 1.04, 3.47 and 2.96 g l^-1, respectively. Also, the results showed that the nanoclay effect was significant on changing the soil loss and sediment concentration at the level of 99 percent. Finally, due to the effect, the use of this conditioner in natural conditions and investigation of the effects on environment and aggregates stability are recommended.

In this research, the nitrate removal by beech leaves was investigated in batch and column systems. The batch experiment was performed to address the effect of pH, contact time, adsorbent dosage and initial nitrate ion concentration on the nitrate removal. The results showed that with an increase in pH, the removal efficiency and adsorption capacity were decreased and nitrate removal by millimeter and nano adsorbent beech leaves reached equilibrium 120 and 90 minutes after experiment, respectively. With an increase in the nitrate concentration, the removal efficiency was decreased from 59.2% to 39.7% and 82.1% to 69.9% for millimeter and the nanoparticles of Beech leaves, respectively. In fixed-bed column adsorption experiments, the flow rates of 5, 8 and 11 ml/min and the nitrate concentration of 15, 50 and 120 mg/L were studied. The results showed with an increase in the nitrate concentration from 15 to 120 mg/L, the saturation time was decreased from 240 to 150 and 360 to 270 minutes for millimeter and nanoparticles of Beech leaves, respectively. Thomas, Dose-response and Yoon-Nelson models were fitted to the results of the continuous experiments. The Thomas model fitted the experimental data with high accuracy. Compared to the adsorbents, nano-adsorbent had more adsorption capacity in the batch and column systems. 

In the present study, the spatial and temporal changes of climate variables such as pan evaporation (Ep), temperature (T), relative humidity (RH), sunshine duration (SD), wind speed (W) and precipitation (P), as well as their relationship with altitude, were investigated. For this purpose, 68 meteorological stations with 30 years of data (1987-2016) throughout Iran on both seasonal and annual time scales were selected. Trend analysis of climate variables showed that over the past 30 years, most areas of Iran have become warmer and drier although all trends have not been significant. Investigation of the relationship between the trend slope of climate variables and altitude illustrated that there was no significant relationship between them during the study period on the annual time scale (p>0.1). However, in winter, the rate of increase in T (minimum, maximum and mean temperatures) and SD (p<0.1), as well as the rate of decrease in P (p<0.01), was significantly enhanced by increasing the altitude. The increase in mean and maximum T (p<0.1) and SD rates (p<0.001) in summer were significantly lower in the highlands than in the lowlands. In autumn, the trend slopes of minimum and mean T (p<0.05) were negatively correlated with altitude; in addition, the rates of increase in P and RH (p<0.05) in the highlands demonstrated a sharper increase. It seems, therefore, that most changes in climate variables have occurred in both autumn and winter. The results also showed that in winter, the highest rates of increase in Ts were related to the altitude of 1500-2000 m; however, the highest decrease in P belonged to the altitude of 2000-2500 m. In autumn, the highest rates of decrease in minimum and mean Ts had occurred in the altitude of 2000-2500 m; as well, he highest rate of increase in P was observed in the altitudes of both 0-500 m and 2000-2500 m.

In areas with high rainfall distribution, proper irrigation management, including complementary irrigation, is one of the effective strategies to increase crop production. In order to investigate the effect of supplementary irrigation in different growth stages on the yield and water productivity of Autumn rapeseed, an experiment in the form of a complete randomized block design with five irrigation management treatments including rainfed (I1), single irrigation at flowering stage (I2), single Irrigation at pod filling stage (I3), two irrigation at pod filling stage and flowering (I4), three irrigation at flowering,  and pod filling and grain Filling stages (I5) was carried out at Lorestan University Research Field. Results showed that there was a significant difference between the effects of different irrigation treatments at 1% level. The lowest grain yield, biological yield and oil yield were obtained in I1 treatment with 44.62%, 50.95% and 53.58% decrease, as compared to I5 treatment. The results also showed that by applying irrigation at pod filling stage, grain yield and oil yield were increased by 13.22% and 20.23%, as compared to I1 treatment. The highest total productivity for the grain yield and oil yield was obtained in I5 treatment with 0.252 and 0.073 kg / m3. In general, due to the fact that drought stress in rapeseed calving stages reduces yield, the higher the number of irrigations in rapeseed calving stages, the more the yield.

Due to drought and climate change, estimation and prediction of rainfall is quite important in various areas all over the world. In this study, a novel artificial intelligence (AI) technique (WGEP) was developed to model long-term rainfall (67 years period) in Anzali city for the first time. This model was combined using Wavelet Transform (WT) and Gene Expression Programming (GEP) model. Firstly, the most optimized member of wavelet families was chosen. Then, by analyzing the numerical models, the most accurate linking function and fitness function were selected for the GEP model. Next, using the autocorrelation function (ACF), the partial autocorrelation function (PACF) and different lags, 15 WGEP models were introduced. The GEP models were trained, tested and validated in 37, 20- and 10-years periods, respectively. Also, using sensitivity analysis, the superior model and the most effective lags for estimating long-term rainfall were identified. The superior model estimated the target function with high accuracy. For instance, correlation coefficient and scatter index for this model were 0.946 and 0.310, respectively. Additionally, lags 1, 2, 4 and 12 were proposed as the most effective lags for simulating rainfall using hybrid model. Furthermore, results of the superior hybrid model were compared with GEP model that the hybrid model had more accuracy.

Changes in soil infiltration cause changes in irrigation efficiencies; therefore, estimating it in calculating irrigation efficiencies provides a more accurate estimate of irrigation performance indicators. In a study conducted on ARC2-7 farm in Amirkabir agro-industry in the 2010-2011 crop year, during four irrigations; two furrows were selected in terms of uniform infiltration and variable infiltration with a length of 140 and a width of 1.83 m. In the furrow assuming uniform infiltration two flume type II, at the beginning and end of it, were installed and the cumulative infiltration was determined by the volume balance method. The furrow with variable conditions was divided into four sections by installing five flumes. By examining the spatial variations of the mean cumulative infiltration, its value decreased from the first to the fourth section for the first irrigation by 15% and for the subsequent irrigations by 13%. Temporal changes of cumulative infiltration decreased by 27 and 30% for the first and second sections and by 26% for the third and fourth sections. An 11% increase in the average weight of the aggregate diameter and a 7% decrease in bulk density indicate physical changes in the soil. Surface runoff losses increased from 8 to 18.77% in the furrow assuming uniform infiltration and from 10.91 to 19.77% in the furrow with variable infiltration, and application efficiency decreased by 6%.

Land subsidence as a hydrogeomorphology event is currently occurring dangerously in many plains of the country due to uncontrolled groundwater extraction from water bearing layers, and accordingly monitoring and studying this phenomenon seems to be necessary. In this study, land subsidence rate of the Najafabad aquifer was determined through the Differential Radar Interferometry (DInSAR) processing of the ASAR and PALSAR radar data and the results were validated by comparying with the differential leveling and groundwater level drowdown data. Processing of the ASAR sensor data estimates the land subsidence in the Najafabad plain at an average annual subsidence rate of 6.7 cm and a total of 41 cm during 6 years period and processing of the PALSAR data suggests an annual rate of 7.7 cm and total subsidence of 30 cm during 4 years period. Most of the occured displacements are related to the Tiranchi, Koushk, Ghahderijan, Goldasht and Falavarjan cities. The simultaneous groundwater level data with acquisition date of the radar satellite images between 2002 and 2014 shows a drawdown ranging from 0.5 to 46.5 meters in the south and east to north of the Najafabad city consistent with the estimated land subsidence areas.The DInSAR processing of the PALSAR data has led to a more accurate results with higher spatial resolution. Results of the radar data processing can be employed for the hazard zonation directly utilized for management and planning of control and preventive measures.

The upcoming climate change has become a serious concern for the human society. These changes, caused and aggravated by the industrial activities of the international community and the increase in the concentration of greenhouse gases in the atmosphere, are seen as a threat to the food security and environment. Temperature change and precipitation are studied in the form of different probabilistic scenarios in order to have an outlook for the future. The present study was conducted to address the effects of climate changes on temperature and precipitation in Qazvin plain in the form of five AOGCMs including Hadcm3, CSIRO-MK3, GFDL, CGCM3 and MICROC3.2, and 3 greenhouse gas emission scenarios of A1B, A2 and B1, based on different possible scenario combinations in the next 30 years, 2021-2050 and 2051-2080 (near and far future). On basis of the study results, all 4 target stations, on average, will have experienced a change between two ratios of 0.5 and 1.4 of  the observed precipitation period  by the end of 2050, and the mean temperature will have had a change  between -0.1 to 1.6 °C, relative to the observed period.  By the end of 2080,  the  precipitation will also have fluctuated between the two proportions of 0.5 and 1.7 times of the observed precipitation period and the mean temperature will touch an increase between 0.6 and 2.6 °C. Both SPI and SPEI indices suggest the increment in the number of dry periods in the near and far future. However, the total number of negative sequences differed considering the 3, 12 and 24-month intervals at the stations level. Given the SPEI index, as compared to the base period, the total negative sequences of drought and number of dry periods will increase at 3 stations of Avaj, Bagh-Kowsar and Shahid-rajaei-powerhouse and decrease at Qazvin station in the future; however, SPI gives different results, such that  for Bagh-Kowsar, there will be an increase in both total negative sequences of drought and number of dry periods, as  compared to the baseline period; three other stations will have more dry periods, specifically, but less total negative sequences. The results reported that the drought events would become severe, and the wet events would become extreme in the future.

The reuse of treated wastewater in countries such as Iran that suffers from drought is considered an important challenge in water management programs. The application of modern wastewater treatment systems particularly attached growth systems, owing to the short time required for start-up, low land requirements, and the absence of problems associated with sludge handling may be a resolution. The objective of this study is to investigate the performance of the Moving Bed Biofilm Reactor (MBBR) in treating synthetic municipal wastewater and selecting an appropriate model. In this way, a bench-scale reactor possessing an effective volume of 15 liters, and synthetic wastewater with influent COD of 500 mg/l (similar to typical municipal wastewater) has been used and the experiments with media filling percentages of 30%, 50%, and 70% and hydraulic retention times (HRT) of 4, 8, and 12 hours have been carried out. The observed data show that the optimum bulk density and hydraulic retention time are 50% and 4 hours, respectively. Also, the kinetic study of reactor performance indicates that Grau second-order model has better conformation with Moving Bed Biofilm Reactor results. In addition, a regression model for predicting effluent COD based on the filling percentage and retention time is presented.

Characteristics of most soils in arid and semi-arid regions affected by carbonates. The study aimed to determine the distribution of carbonates in the size components of some soils in Khuzestan province. Upward to the bottom of Karun, Karkheh, and Jarahi rivers were studied at depths of 0-50, 50-100, and 150-100 cm. The results showed that the average amount of carbonates in the soils of the Jarahi river basin (37%) was significantly different from the amount in the soils of the other two rivers (33%). Carbonates were observed in all soil size components but the maximum was present in the clay component. The highest regression relationship between soil particles was in the clay component (0.375). The highest percentage of particle reduction after carbonate removal was related to coarse silt particles (0.75). Therefore, the soil texture changed from clay in Jarahi, from clay and silty clay in Karun, and silty clay in Karkheh due to the removal of carbonates to sandy loam. There was no significant difference in the distribution of carbonates at different depths for river soils and all studied soils. The relatively uniform distribution of carbonates in the four components studied in these soils from the surface to the depth showed that the carbonates originated from the parent material, namely alluvial flood sediments of these rivers.

Land Surface Temperature (LST) is an important parameter in weather and climate systems. Satellite remote sensing is a unique way to estimate this important parameter. However, satellite products have either low spatial resolution or low temporal resolution that limits their potential use in various studies. In recent years, the use of Spatio-temporal fusion techniques to produce high resolution simultaneous spatial and temporal images has been extensively investigated. In this study, a Flexible Spatio-temporal Data Fusion (FSDAF) was used to produce Landsat-like LST images with Landsat spatial resolution and MODIS temporal resolution. The quantitative and qualitative validation of the images was performed by comparing them with the Actual Landsat LST images. The results showed that the FSDAF algorithm has high accuracy in estimating daily LST data both qualitatively and quantitatively. The RMSE and MAE parameters of the images produced compared to the actual Landsat images were 1.18 to 1.71 and 0.88 to 1.29°C, respectively. The correlation coefficient above 0.87 and bias between -0.6 to 1.45°C also confirms the high accuracy of the algorithm in estimating Landsat-like land surface temperature on a daily time scale.

Due to the limitation and scarcity of water supplies, it is essential to identify and reuse alternative water sources, particularly in the arid and semi-arid regions according to environmental conditions. Reuse of runoff is an adaptive management philosophy and approach to balance efforts and provide sustainable water services and manage hazards. The present study is aimed to design a suitable model of water resource management with an emphasis on crisis management. In this study, indices and dimensions of the water resources management model were determined via the Delphi method (based on Schmidt, et al.). Delphi panel members were identified and selected in three stages using random sampling. The faculty members of water resources and watershed management university specializing and passive defense experts of water organization were selected as the Delphy panel members. Initially, panel members identified the most important effective items on water resources security, based on their inference of the model. Based on the first evaluation and after eliminating duplicates, 43 items remained. Finally, 36 items remained in the analyses, when the items with low and medium significance coefficients were eliminated. The final model of water resources management was approved by the expert opinion based on the crisis management approach. According to the results, designing rainwater collection and storage systems in different parts of the city and installing tanks for roof rainwater collection in each home were selected as the best approach in the critical condition (with an average grade of 4.94), whereas the installation of the sensors in different parts of water pipe with an average grade of 2.10 was ranked in the 33rd selection. Finally, the items identified by the Delphi panel were classified into four general indices: retrofit, safety, culture, and planning. In general, it is necessary for the officials of urban water resources, as well as crisis management, must prepare for crisis conditions as well as the correct, principled, and scientific use of available water resources to extract and store rainwater and runoff to use it in crises and disrupt the general water supply system.

World climate change is an accepted important subject but its negative effects are severe in arid and semi-arid areas of Iran. So, in the present study, two climate scenarios including RCP 8.5 (critical scenario) and RCP 4.5 (moderate scenario) during 2020, 2030, and 2040 decades and their effects on temperature changes in the wheat growth period in five cities of Isfahan province including Isfahan, Najaf Abad, Chadegan, Burkhar, and Meimeh have been investigated. The survey of temperature changes during wheat growth in the next decades showed that Burkhar, Isfahan, Najaf Abad, Chadegan, and Meimeh, respectively will experience more days with a temperature higher than 30°C in 2020, 2030, and 2040 decades than the mean of two recent years (2017-2018). Furthermore, in comparison with present conditions, the most changes in the number of days with a temperature higher than 30°C in next decades climates (2020, 2030, and 2040 decades) will be in Burkhar, Meimeh, Chadegan, Najaf Abad, and Isfahan, respectively. The range of changes percent in the number of days higher than 30°C in next climate conditions rather than present condition will be varied between 5 percent (Isfahan) till 97 percent (Burkhar). The changes percent in all studied cities were more in RCP 8.5 than RCP 4.5. During wheat growth, the number of days less than zero°C will be less in Isfahan, Burkhar, and Meimeh while will be more in Najaf Abad and Chadegan. The evaporation- transpiration will be increased in the next decades during wheat growth. As a result, planning and using compatibility strategies for each city is important to guarantee wheat production.

Iron (Fe) is an essential micronutrient for plants and its deficiency occurs in calcareous soils. However, a suitable extractant for the estimation of plant-available Fe and its critical level in calcareous soils depends on the type of soil and plant. The objective of the present study was to evaluate several chemical extractants to estimate available Fe and its critical level for corn growing in calcareous soils from Chaharmahal-Va-Bakhtiari Province. The amount of available Fe was measured by DTPA-TEA, AB-DTPA, 0.01 M calcium chloride, Mehlich IІ, and Mehlich ІІI extractants. At the end of the experiment, corn was harvested, and dry weight, Fe concentration in the plant, and the amount of Fe uptake by corn were determined. Extracted Fe had a significant correlation with all extractants used with maize indices. . The highest correlation coefficients were determined between the DTPA-TEA (0.32-0.94) and AB-DTPA (0.43–0.96) methods and the plant indices. The results of this research showed that the DTPA-TEA and AB-DTPA methods were the most suitable extractants for predicting available Fe content in these soils and the critical level of Fe extracted by these extractants was 2.81 and 3.67 mg kg^-1.

The simulation of the rainfall-runoff process in the watershed has particular importance for a better understanding of hydrologic issues, water resources management, river engineering, flood control structures, and flood storage. In this study, to simulate the rainfall-runoff process, rainfall and discharge data were used in the period 1997-2017. After data qualitative control, rainfall, and discharge delays were determined using the coefficients of autocorrelation, partial autocorrelation, and cross-correlation in R Studio software. Then, the effective parameters and the optimum combination were determined by the Gamma test method and used to implement the model under three different scenarios in MATLAB software. Gamma test results showed that today's precipitation parameters, precipitation of the previous day, discharge of the previous day, and discharge of two days ago have the greatest effect on the outflow of the basin. Also, the P_t Q_t-1 and P_t P_t-1 Q_t-1 Q_t-2 Q_t-3 combinations were selected as the most suitable input combinations for modeling. The results of the modeling showed that in the support vector machine model, the Radial Base kernel Function (RBF) has a better performance than multiple and linear kernels. Also, the performance of the Artificial Neural Network model (ANN) is better than the Support Vector Machine model (SVM) with Radial Base kernel Function (RBF).

Delineation of gully erosion susceptible areas by using statistical models, as well as optimum usage of existing data and information with the least time and cost and more precision, is important. The main objective of this study is to determine the areas accuracy to gully erosion and susceptibility mapping by using data mining of the bivariate Dempster-Shafer, linear multivariate statistical methods and their integration in Semirom watershed, southern Isfahan province. First, the geographical location of a total of 156 randomly gullies were mapped using preliminary reports, satellite imagery interpretation and field survey. In the next step, 14 conditioning parameters of the gullies in the study area were selected including the topographic, geomorphometric, environmental, and hydrologic parameters using the regional environmental characteristics and the multicollinearity test for modeling. Then, the Dempster-Shafer statistical, linear regression, and ensembled methods were developed using 70% of the identified gullies and 14 effective parameters as dependent and independent variables, respectively. The remaining 30% of the gully distribution dataset were used for validation. The results of the multivariate regression model showed that land use, slope and distance to drainage network parameters have the most significant relation to gully occurrence. The gully erosion susceptibility maps were prepared by individual and ensemble methods and they were divided to 5 classes of very low to very high rate. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to validate gully erosion susceptibly maps. The verification results showed that the AUC of ensemble method (0.948) is higher than Dempster-Shafer (0.924) and Multivariate regression (0.864) methods. Also, the the seed core area index (SCAI) value of the ensembled model from very low to very high susceptible classes have a decreasing trend that indicating a proper separation of susceptible classes by this model.

One of the crucial problems that exist in the irrigation networks is the fluctuation of the water surface flow in the main channel and changes in the flow rate of the intake structure. One of the effective methods to decrease these fluctuations is increasing the weir crest length at the given width of the channel with the use of the labyrinth weirs can be achieved for this purpose. The labyrinth weir is the same linear weir that is seen as broken in the plan view. In this study, a labyrinth weir with a length of 3.72 m, three different heights of 15, 17, and 20 cm, three different shapes of dentate (rectangular, triangular, and trapezoidal), and a linear weir were used in a recirculating flume with 15 m length and 1 m width. The result showed that for a given length and height of weir, with the increasing of the upstream water head to the weir height ratio (), the discharge coefficient decreases. The results showed that by increasing weir height, the discharge coefficient decreases for a given length of the weir. Linear weir and labyrinth weir without dentate create more water depth at the upstream by 3.3 and 1.2 fold compared with dentate labyrinth weir.