JWSS - Journal of Water and Soil Science

The study of flow patterns in front of intake has been attracted the attention of researchers during the past decades to explore the mechanism of flow and sediment entry to the intake. In this study, the separation and stream tube dimensions were investigated in water intakes installed to rectangular and trapezoidal main channel. These researches were carried out with experimental and fluent models. The results of experimental and fluent models have a good conformity. It was found that, in trapezoidal main channel, the stream tube width decreases near the bed and increases near the surface and separation dimensions reduced and led to reduction of sediment entry and increase of efficiency

Nowadays, greater recognition of drought and introducing its monitoring systems, particularly for the short-term periods, and adding predictability to these systems, could lead to presentation of more effective strategies for the management of water resources allocation. In this research, it is tried to present appropriate models to predict drought in city of Semnan, Iran, using time series, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (MLP and RBF). For these modeling processes, average monthly meteorological parameters of rainfall, temperature, minimum temperature, maximum temperature, relative humidity, minimum relative humidity, maximum relative humidity and SPI drought index were used during the period 1966 to 2013. The results showed that among the many developed models, the ANFIS model, with input data of average rainfall, maximum temperature, SPI and its last-month value, 10 rules and Gaussian membership function, showed appropriate performance at each stage of training and testing. The values of RMSE, MAE and R at training stage were 0.777, 0.593 and 0.4, respectively, and at testing stage were 0.837, 0.644 and 0.362, respectively. Then, the input parameters of this model were predicted for the next 12 months using ARIMA model, and SPI values were predicted for the next 12 months. The ANN and time series methods with low difference in error values were ranked next, respectively. The input parameters SPI and temperature had better performance and rainfall parameter had weaker performance.

The purpose of this research was source identification of aerosols in atmosphere using geochemical properties in the city of Kermanshah. The concentrations of twenty elements consisting of K, Na, Ca, P, Cu, Ni, Pb, Cd, Se, Zn, Fe, Mg, B, Cr, Co, As, Mo, V were analyzed by ICP for 55 soil samples (in the height range of 600-1600m) and 41 aerosols samples. Source identification of aerosels using geochemical tracers was performed in two steps. In the first step, appropriate combination of tracer elements with high ability in the resolation of aerosol sources was chosen using the means comparison test and discriminate analysis. In the second step, the multivariate mixing model was used to determine the contribution of aerosol sources (geological and geomorphology types) to the production of aerosols in the study area. The results obtained from determination of the contributions of sources of aerosols (geological and geomorphological types) showed the UF formation (consisting of red marl and sandstone), with the height of 0-1400 mand the slope of 0-5%, could be regarded as the main contributor to the production of aerosols located in the city of Qasreshirin.

Exploitation of dam reservoirs is one of the major problems in the management of water resources. In this research, Crow Search Algorithm (CSA) was used for the first time to manage the operation of reservoirs. Also, the results related to the exploitation of the single-reservoir system of Shahid-Rajaei dam, located in Mazandaran province, northern Iran, which meets the downstream water demands, were compared to those obtained by applying the Particle Swarm and Genetic algorithms. Time reliability, volume reliability, vulnerability and reversibility indices, and a multi-criteria decision-making model were used to select the best algorithm. The results showed that the CSA obtained results close to the problem’s absolute optimal response, such that the average responses in the Crow, Particle Swarm and Genetic Algorithms were 99, 75 and 61 percent of the absolute optimal response, respectively. Besides, except for the time reliability index, the CSA had a better performance in the rest of the indices, as compared to Particle Swarm and Genetic Algorithms. The coefficient of variation of the obtained responses by CSA was 14 and 16 times smaller than the Genetic and Particle Swarm Algorithms, respectively. The multi-criteria decision-making model revealed that the CSA was ranked first, as compared to the other two algorithms, in the Shahid-Rajaei Reservoir's operation problem.

Quantitative description of the spatial variability of soil hydraulic characteristics is crucial for planning, management and the optimum application. Field measurement of infiltration is very expensive, time-consuming and laborious. Soil structure also important effects on water infiltration in the soil. The objectives of this study were to determine the spatial variability of water infiltration, to select the most appropriate infiltration model, to calculate the parameters of relevant models, and to quantify the soil structure by using the fractal geometry. Infiltration parameters were estimated by using some physical soil properties, as well as fractal parameters, in this research. To achieve these purposes, 161 sites were selected and their infiltration was measured by using the constant head double-ring infiltrometers method in a systematic array of 500*500 m. The observed infiltration data from all examined sites were fitted to three selected infiltration models. Soil bulk density (BD), soil water content, soil particle size distribution, soil aggregate size distribution (ASD), organic carbon content (OC), saturation percentage (SP), soil pH and electrical conductivity (EC) were also measured in all 161 sites. For the quantitative assessment of soil structure, the aggregate size distribution, fractal parameters of the Rieu and Sposito model as well as the mean weight diameters (MWD) and geometric mean diameter (GMD) were also obtained. The obtained results indicated that the infiltration rates of the studied areas had generally low basic infiltration rates (1.1-31.1 cm hr^-1) for most sites with the average of 6.69 cm hr^-1. According to all obtained results and based on the least-square method, the Philip model was selected as the best performing model to account for infiltration. The aggregate size distribution demonstrated a fractal behavior, and the infiltration parameters could be significantly correlated with the fractal parameters and other soil physical properties.

The aim of this study was to evaluate the spatial distribution of soil infiltration using geostatistics methods in a regional scale on 400 hectares of Mansour Abad Plain, in Larestan region, Fars Province. Sampling and parameters measurement were done for 78 points in a regular grid with a distance of 100*100 meters; for these variables, the best variogram model between linear, exponential, Gaussian and spherical models with the highest R2 and the lowest error was determined using GS+ and ArcGIS software. In this study, soil infiltration (cm/min) using the double ring method and some other soil properties including soil electrical conductivity (dS/m), pH, saturation percentage (%SP), particle size percentage (sand, silt and clay), and calcium (meq/lit), magnesium (meq/lit), sodium (meq/lit) were measured and determined. The spatial distribution of Kostiakov and Philip models parameters and theri zoning were determined using the geostatistic method. The results showed that, among different soil properties, the final infiltration rate had a high degree of variability in the study area, and the decision was based on the usual averaging methods, which could have a lot of error. Among applied infiltration models, Kostiakov model and Philip model were the best empirical and physical infiltratin models, respectively, in the studied area. The best semivariogram model for the steady state infiltration rate was Philip model, with the coeficients of S and A, and a coefficient of Kostiakove model was gaussian; for the b coefficient, Kostiakove model was exponential. Spatial structure of the final infiltration rate, a and b coefficients of Kostiakove model, and S and A coefficients of the Philip model, was strong. The best interpolation method for the final infiltration rate was cokriging with the cofactor of silt percentage, for the S coefficient of Philip model was inverse distance weighting (IDW); for a and b coefficients of Kostiakove model, kriging and IDW were suitable, respectively.

Due to unsuitable soil physical conditions, calcareous soils, and the existence of a huge amount of sulfur in the country, the study of sulfur effects on the soil structure and other soil properties is necessary. Therefore, the effects of different rates of sulfur including: 0, 750, 1500 and 3000 kg/ha, when accompanied by Halothiobacillus neapolitanus bacteria, on the soil properties in the corn-wheat rotation in two years were investigated. Parameters of soil pH, EC, sulphate, organic carbon, soil structure and wheat yield were measured. For the quantification of soil structure and quantity evaluation of sulfur effect on the soil structure, with measuring the aggregate size distribution, the mean weight diameter (MWD) and geometric mean diameter (GMD) of the aggregate indices, and the amounts of fractal dimension were determined. The r results indicated that with the progress of the experiment and further application of sulfur along with thiobacillus bacteria, aggregation and aggregate stability were increased. The effect of sulfur treatments on MWD and GMD was significant; based on quantification indices, it had 28 percent positive effect on the soil structure. Sulfur with 3 percent reduction of fractal dimension had a significantly positive effect on the soil structure. Application of sulfur decreased a small amount of soil pH and increased 12 percent of the soil EC and 40 percent of the soil sulphate. So soil structure improvement and reclamation of soil physical condition can be very effective on the soil conservation and sustainability of the production resources and the conservation of environment.

In this research, by using FLOW3D, the performance of non-linear (arced) piano key (PKW-NL) in plan and linear piano key weir (PKW-L), with equal length of weir, was compared. Results showed that nonlinearity of the weir caused 20% increase in the discharge coefficient. Investigating the velocity contours for these two weir models also showed that maximum velocity within the PKW-NL weir structure is about 30% lower than the PKW-L weir. Also, the performance of non-linear piano key weir was evaluated under inward (PKW-IC) and outward (PKW-OC) curvatures to the channel. Results showed that in the case of PKW-IC weir, the discharge coefficient was increased by 8% as compared to the PKW-OC weir. Investigating the pressure contours for these two weir models also shows that the average pressure within the PKW-IC weir structure is about 5% higher than the PKW-OC weir. This increase in pressure leads to a decrease in the speed and better distribution of flow over the weir keys.

River discharge is among the influential factors on the operation of water resources systems and the design of hydraulic structures, such as dams; so the study of it is of great importance. Several effective factors on this non-linear phenomenon have caused the discharge to be assumed as being accidental. According to the basics the chaos theory, the seemingly random and chaotic systems have regular patterns that are predictable. In this research, by using methods of phase space mapping, correlation dimension, largest Lyapunov exponent and Fourier spectrum power, a period covering 43 years of Zayandehrud River discharge (1971-2013) was evaluated and analyzed based on the chaos theory. According to the results, the non-integer value of the correlation dimension for Eskandari and Ghale Shahrokh stations (3.34 and 3.6) showed that there was a chaotic behavior in the upstream of Zayandehrud-Dam Reservoir. On the other hand, in the Tanzimi-Dam station, the correlation dimension curve was ascending with respect to the embedding dimension, showing that the studied time-series in the downstream of Zayandehrud-Dam Reservoir was random. The slope of the Lyapunov exponent curve for Eskandari, Ghale Shahrokh and Tanzimi-Dam stations was 0.0104, 0.017 and 0.0192, respectively, and the prediction horizon in the chaotic stations was 96 and 59 days. The non-periodical feature of time series was studied by using the Fourier spectrum power. The wide bandwidth, besides other indices, showed that river discharge in the upstream stations of Zayandehrud Reservoir was chaotic.

In general, engineering designs need to optimize the factors affecting the under-study phenomenon; however, this is often a costly and time-consuming process. In this regard, new methods have been developed to optimize with fewer tests; thus, they can make the whole process more affordable. In this study, Taguchi and Taguchi-GRA methods were used to design the geometric parameters of the protective spur dike in order to optimize their efficiency in reducing the scouring in a series of spur dikes. The results of both methods showed the optimal ratio of the length of the protective spur dike to the length of the first spur dike was 2.5 and the angle of the protective spur dike was 90 °. However, the ratio of the length of the protective spur dike to the length of the main spur dike in the Taguchi method was 0.8 and in the Taguchi-GRA method, it was 0.6. In addition, using variance analysis showed that the distance between the protective spur dike from the first spur dike, the protective spur dike angle, and the length of the protective spur dike were, respectively, the most effective on the performance of the protective spur dike. The results of this study, therefore, indicate that both methods are highly effective in optimization and, therefore, can be useful in the hydraulic engineer studies.

Given the various advantages of applying conservation tillage methods in the agriculture, including reducing the effects of climate change by decreasing the carbon dioxide emissions to the atmosphere caused by carbon sequestration in soil, this study was conducted with two wheat-cotton and wheat-sesame rotations at Agricultural Research Station Bakhtajerd, in Darab, the southeast of Fars Province, which had a warm and dry climate; this work was carried out in a loam soil during four years. The aim of this investigation was to compare the carbon sequestration (CS) in the soil after application of different conservation tillage methods with the conventional method. The results showed that in wheat-cotton rotation, the maximum and minimum amount of CS in the 0-20 cm depth of soil with the average 17.160 and 13.810 t/ha could be obtained by using no-till and conventional tillage, respectively. Therefore, no-till increased CS by 24.26% in wheat and cotton cultivation, as compared to the conventional tillage. The economic value of this CS increment for the environment was $2459 per hectare. In the wheat-sesame rotation, the highest and lowest CS was obtained with an average of 25.850 and 12.505 t/ha in no-till and conventional tillage, respectively. Namely, direct seeding of wheat and sesame increased the CS at the 0-20 cm depth of soil by 107%, as compared to the conventional tillage with the economic value of $9809.5 per hectare. Under similar conditions, in wheat-cotton and wheat-sesame rotations, the conventional methods could be replaced by no tillage.

In the last few decades, the use of porous concrete to cover the sidewalks and pavements as an interface to collect the urban runoff has been increased. This system is economically more efficient than other runoff-pollution reduction methods. To design a runoff control system and reduce its pollution, it is necessary to determine the hydraulic and dynamic properties of the porous concrete (with and without additives). In this research, the effects of cement type (2 and 5), water to cement ratio (0.35, 0.45 and 0.55), fine grains percent (0, 10 and 20%), the type of additive (pumice, industrial pumice, perlite and zeolite), and the added additive percent (5, 10, 15 and 20%) on the physical properties of the porous concrete (porosity, hydraulic conductivity and compressive strength), each with three replications,  were  investigated using robust design. Qualitek-4 software was also used to discuss the results. The results showed that to obtain the highest porosity in the mixing scheme of the porous concrete, no fine grains, cement type 2 and 15% industrial pumice should be used, and water to cement ratio should be 0.35. Also, the water to cement ratio of 0.55, 0% fine grains, type 2 cement and 15% industrial pumice resulted in the highest value of hydraulic conductivity in the porous concrete. Finally, the water to cement ratio of 0.55, 20% fine grains, type 2 cement and 5% zeolite led to the maximum compressive strength. In general, it was not possible to reach a logical conclusion in this research with the least costs without employing the robust design.

Today, one of the biggest challenges facing the world is the lack of water, especially in the agricultural sector. In this research, we investigated the effects of irrigation method and deficit irrigation with the urban refined effluent on biomass, grain yield, yield components and water use efficiency in single grain crosses 704 maize. This research was carried out in a randomized complete block design with two irrigation systems (furrow irrigation (F) and drip irrigation (T)) and three levels of deficit irrigation treatments of 100 (D₁), 75 (D₂) and 55 (D₃) percent of water requirements in three replications, in 2017, at the collage of Abourihan Research field, University of Tehran, in Pakdasht County. The results showed that the highest yield of biomass was 2.426 Kg m^-2 for full drip irrigation treatments; also, there was no significant difference between D₁ and D₂ treatments. The highest grain yield was 1.240 kg m^-2 for the complete drip irrigation treatment. The highest biomass water use efficiency was obtained for the treatment of 75% drip irrigation, which was equal to 5.3 kg per cubic meter of water. Therefore, a drip irrigation system with 75% water requirement is optimal and could be recommended.

The impact of different management options on the region and the existing conditions can be evaluated with minimal cost and time to select the most practical case using various tools including mathematical models. In this study, the SWAT hydrological model was performed from 2009 to 2019 using climatic, hydrological, and hydrometric data in the Malayer catchment, and the final model was validated by SWAT-CUP. To reduce the amount of uncertainty in the input parameters to the MODFLOW model, using the values of surface recharge from the implementation of the SWAT hydrological model, quantitative modeling of Malayer aquifer was performed more reliably in GMS software by using MODFLOW model. After modeling the study area in the 2009-2018 period and calibrating the model in the years from 2018 to 2019, the mean values of absolute error (MAE) were 0.35-0.65 m, and root means square error (RMSE) was 0.62-0.94 m, which seems acceptable considering computational and observational heads equal to 1650 m. Results of water level changes in observation wells located in the Malayer region indicate that the groundwater level in the aquifer has decreased by an average value of 9.7 m in the 10-year study period.

Runoff is formed by spending some time after rain and significantly depends on rainfall intensity, soil moisture, and slope. One of the fundamental questions about runoff is the time that it starts to create. In this research, the runoff start time in sandy loam soil was evaluated experimentally under different conditions using a precipitation simulator machine. The rainfall intensity parameters of (60, 80, and 100 millimeters per hour) and the slope of (0 and 5 percent) were investigated. The rainfall was created in the three soil treatment types completely dry (S_dry), the dry soil that had been saturated 24 hours before the test (S_24hrlag), and the dry soil that had been saturated 48 hours before the test (S_48hrlag). Eighteen tests were conducted on this soil. At the end of each test, the soil moisture was measured. The experimental results were compared with the numerical model of Green-Ampt. According to the Kendall and Spearman correlation test results, as the rainfall be intense, the start time of the runoff is lower. Also, the runoff starts at a faster time in the slope of 5 percent for every three types of soil. Also, the results of starting time of the runoff in the soil with a delay of 48 hours in the rain compared to the soil with a delay of 24 hours in the rain are closer in all of the rainfall intensity and slopes compared to the case of dry soil. Therefore, in the experiments related to a delay of 24 hours, the time of the start of runoff decreases. While in tests with a delay of 48 hours, it was not much different from completely dry soil. Also, the Green-Ampt results are close to the experimental results (R²=0.9775), and the maximum difference between the two mentioned methods is 4.8 minutes. Therefore, it can be used with the Green-Ampt method to calculate the start time of runoff in sandy loam soil in different states of rainfall intensity and bed slope.