JWSS - Journal of Water and Soil Science

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.

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.

To prevent demolishing bridge piles due to developing the scour hole under the foundation of these piles some solution has been proposed in the literature. One of the important approaches could be installing different geometric of roughness at the downstream and upstream piles sections. This causes the downward flows which are performing the main role in developing scour holes to be marginally decreased. The present study explores the effect of geometric roughness and also, continuity and un-continuity of roughness length on maximum scour holes around bridge pile. Results indicate that due to increasing the length of roughness the developed scour holes were formed by less scour hole depths. Furthermore, continuity of roughness increases the scour hole depths; however, un-continuity causes the height of scour holes to be developed by fewer values. Also, the comparison shows that the length of installed roughness in maximum value is decreasing the scour hole depth constitute 34 percent. Based on the non-linear regression technique an equation has been proposed to predict the maximum scour hole due to different conditions. Comparison between experimental and proposed values shows that the accuracy of the proposed equation has an acceptable error which has been calculated less than 11 percent.

In this study, the hydraulic characteristics of the flap gates are installed at the end of the trapezoidal channels were investigated by laboratory study. In the physical model, three trapezoidal channels and four gates with different weights were used (12 gates for three channels). Based on several experiments, equations for estimating of flow rate for each side slope (each channel) were developed using dimensional analysis. In this research, five forms of discharge-stage relationship were used to obtain relationships for each side slop to estimate flow rate, separately. The results show that none of the discharge-stage relationships forms as a single relationship for all flap gates in a certain channel are suitable for estimating discharge. But the first, second, and third forms of the discharge-stage relationship are very suitable for estimating the flow rate in a certain channel for a certain flap gate. In other words, for each gate with a specific weight, a separate (unique) relationship is obtained to estimate the flow rate in the form of the first to the third discharge-stage relationship in a certain channel. To estimate of flow rate by using the first form of the discharge-stage relationship, the maximum values of statistical parameters of RMSE, ME, and MARE, among all three channels, are 0.0001 m³/s, 0.00022 m³/s, and 0.22 percent, respectively. The values of all the above statistical parameters for the first, second, and third forms of the discharge-stage relationship are presented in the article.

Snow cover is one of the important climatic elements based on which climate change may have a special effect. In general, climate change may be reflected in different climatic elements. Therefore, it is very important to study and measure changes in snow level as one of the important sources of water supply. Ardebil and Sarein cities are located at 48° 18׳ east longitude and 38° 15׳ north latitude. In this study, Sentinel-2 optical satellite was used to monitor the snow cover surface in 2018, and NDVI, S3, NWDI, NDSI, Cloud mask indices were applied to detect snow-covered surfaces using ArcGIS and Snap software. Next, to validate the snow maps extracted from the images, it was compared with the snow data in terrestrial stations using linear regression in MATLAB software and to evaluate the accuracy of the model statistical indices including RMSE, MSE, BIAS, CORR were used. The present study showed that according to Ardabil city climatic conditions, maximum-snow covered area in January with an area of 356.52 km2 and minimum snow-covered area in March with an area of 96.10 km2. The highest snow cover is observed in the high slope areas in the western slopes (Sabalan Mountain Heights) and the lowest snow cover is observed in the lower eastern slopes. The results of linear regression with generalization coefficient are 85% and the results of statistical indices of error are equal to MSE: 0.086, BASAS: 0.165, CORR: 0.924, and RMSE: 0.03. Correlation relationships between terrestrial data and estimated snow maps showed a high degree of correlation. This result is statistically significant at the 99% level. The use of optical images in estimating snow levels is very cost-effective due to the size of the areas and the high cost of installing snowmobiles. The results obtained in the present study indicated that traditional radar images with high spatial resolution and good correlation with terrestrial data can be a good alternative to snowmobiling ground stations at high altitudes or in passable areas.

Water hammer is one of the unsteady flows in urban water distribution networks, which has been of great importance due to the damage caused to the pipeline and has always been of interest to researchers. In this study, the phenomenon of water hammer due to the sudden closure of the valve in the downstream end has been investigated in a laboratory and using a numerical model. In the laboratory section of the study, the effect of flow changes with control equipment and without control equipment on the maximum and minimum height of pressure wave head was investigated. The results showed that the proper performance of the surge tower pipe in reducing the maximum pressure wave as well as improving the negative pressures in the system. In a maximum discharge of 35.75 liters per minute, surge tower pipe reduced pressure wave head by a maximum of 70.40%. In a minimum discharge of 7.70 liters per minute, the surge tower pipe reduced the height of maximum pressure by 34.82%. Also, in minimum discharge, surge tower pipe has improved the minimum pressure wave head by more than 78%. AFT Impulse numerical model was used to analyze the water hammer. The results of the numerical model were examined in a benchmark problem using a characteristic method and its validity was confirmed. Simulation of laboratory model with numerical software showed that this software only predicts the first wave properly when water hammer produces negative pressures, but in the next cycles it does not show the depreciation rate of the pressure wave, properly.

Iran is located in the dry belt of the earth and is predicted to face water stress in the next half-century. Currently, the area of sugarcane cultivation in Khuzestan is over 85,000 hectares and due to the high water needs of sugarcane and drought conditions, optimization of water consumption and irrigation management is necessary to continue production. Therefore, in this study, the values of soil moisture, canopy cover, biomass yield in five treatments and irrigation levels (start of irrigation at 40%, 50%, 60%, 70%, and 80% soil moisture discharge) during 2 planting dates in the crop year 2015-2016 on sugarcane cultivar CP69-1062 in Amirkabir sugarcane cultivation and industry located in the south of Khuzestan was simulated by AquaCrop model. The measured data on the first culture date (D1) and the second culture date (D2) were used to calibrate and validate the model.  The results of NRMSE statistics in canopy cover simulation in calibration and validation sets with values of 2.1 to 15.6% and 3.8 to 18.3%, respectively, and in biomass simulation with values of 6.2 to 15.2%, and 9.5 to 12.6%, respectively and coefficient of determination (R2), range 0.98 to 0.99 indicated that the high ability of the AquaCrop model in simulation canopy cover and biomass yield. whereas, the values of NRMSE of soil depth moisture in the calibration and validation sets ranged from 11.6 to 23.8, and 12.2 to 22.7, respectively, with a coefficient of determination (R2), 0.73 to 0.96 (calibration) 0.8 to 0.93 (validation) showed less accuracy of the model in the simulation. The best scenario is related to the third proposal that water consumption, water use efficiency, and yield are 1710 mm, 1.53, and 42.27 tons per hectare, respectively, which shows a reduction in water consumption of 360 mm.

The present study is investigated the earth dam stability during drawdown based on both numerical and experimental aspects. To validate the numerical model, a model was performed experimentally. Some soil mechanic tests were carried out through the hydraulic experiments to attain the usage factors of the numerical investigation. To investigate the effect of hydraulic conductivity on the rapid drop of water level and the use of hydraulic parameters of materials, seepage flow in the model was modeled by seep/w software. The input information to the software including hydraulic conductivity and water volume were measured by performing a constant load test and using a disc penetration meter, respectively. After validation of hydraulic conductivity with the experimental model, the results were compared with observed data. Comparison between numerical and laboratory discharge illustrated that the numerical model with laboratory model is well confirmed. In addition, saturated and unsaturated simulations demonstrated that the unsaturated model is highly consistent with the experimental model. It is assumed that due to the drawdown conditions, unsaturated models can achieve high accuracy for simulating the flow through a homogeneous earth dam.

Soil salinity and its development are the main problems that should be prevented by correct management methods. Recognition of saline districts and the preparation of salinity maps are the first steps in this way. Nowadays, the application of auxiliary data in digital soil mapping is increasing due to the current associated problems in the preparation of traditional maps. The objectives of this study were to map soil salinity by the Regression Kriging (RK) method,  to identify areas with high salinity, and to investigate the relationship between soil salinity and soil-forming factors in Khuzestan Province. For this purpose, 291 surface soil samples (0-10 cm) were randomly collected in April 2014. Auxiliary variables or soil-forming factors were included in the land parameters such as slope, watershed and wetness index, OLI and TIRS images of Landsat 8, and the category maps (soil, land use, and geological maps). Also, kriging approaches were used to compare the precision of different mapping methods. The results indicated that the Regression Kriging method has a higher precision compared with other methods so that the coefficient of determination, Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) were estimated as 0.84, 0.41, and 6.21, respectively. The Decision Tree Regression method could also create a good relationship between soil salinity and auxiliary variables. The results showed that some auxiliary variables were more effective on the prediction of soil salinity including 2, 4, 5, and 7 bands of Landsat 8, Brightness Index, Wetness Index, Multiresolution index of Valley Bottom Flatness (MrVBF), Channel Network Base Level (CNBL), NDVI, SAVI and soil map. A Digital map of soil salinity was prepared by the obtained rules, and then it was assimilated with the map of error of variance to prepare the final soil salinity map. Accordingly, soil salinity was found to have an increasing trend from north to south in Khuzestan Province which indicates a salinity problem in the south of the Province. The main reasons for the high salinity in the south and southwestern parts of the area could be attributed to the high water table levels, differences in topography, capillary movement of salt to the soil surface, the difference in the type of land uses, and also groundwater quality and irrigation water which is altered by the frequent application of wastewaters and animal manures.

Integrated assessment of the watershed is critical in arid and semi-arid areas due to the severe water stress in these regions. Data and information are an essential part of decision making and water governance to obtain integrated water resources management at the watershed scale. Water accounting is a helpful tool to organize information and present them as the standard indicators to achieve this goal. Therefore, the objective of this study is to implement the Water Accounting Plus framework (WA+) in the Ferizi watershed located in the Khorasan-e Razavi Province. In this study, water accounting indicators of the Ferizi watershed for a period of 28 years (1990-2017) and wet (1990-1997) and dry (1998-2009) periods were calculated using the SWAT model. The calculated indicators showed that the amount of manageable water and usefulness of consumption (transpiration) is low in the watershed and a large part of the share of irrigation in the watershed is provided by groundwater resources. Generally, the results of this study showed that the use of the SWAT model, WA+ framework, and analysis of water accounting indicators play a significant role in assessing the agricultural and hydrological conditions of the watershed. The proposed approach in this study can help managers make enlightened decisions to keep the sustainability of the watershed.

Biochar as an efficient strategy for the improvement of soil properties and organic waste management may reduce the potential effects of abiotic stresses and increase soil fertility. However, the effects of this organic amendment on soil microbial indicators under combined salinity and pollution have not been studied yet. Therefore, the objective of this study was to evaluate the influence of sugarcane bagasse biochar on some soil bioindicators in a Cd-polluted soil under saline and non-saline conditions. A factorial experiment was carried out with two factors, including NaCl salinity (control, 20 and 40 mM NaCl) and sugarcane bagasse biochar (soils unamended with biochar, amended with uncharred bagasse, 400 ^oC biochar, and 600 ^oC) at 1% (w/w) using a completely randomized design. Results showed that salinity increased the mobility of Cd (12-17%), and subsequently augmented its toxicity to soil microorganisms as indicated by significant decreases in the abundance and activities of the soil microbial community. Conversely, sugarcane bagasse biochar application reduced the concentration of soil available Cd (14-18%), increased the contents of soil organic carbon (89-127%), and dissolved organic carbon (4-70%), and consequently alleviated the effect of both abiotic stresses on soil microbial community and enzyme activity. In conclusion, this experiment demonstrated that the application of sugarcane bagasse biochar could reduce the salinity-induced increases in available Cd and mitigate the interaction between salinity and Cd pollution on the measured soil bioindicators.

In the present study, a model was developed using a system dynamics approach to simulate and optimize the profitability of crops of the Jofeyr (Isargaran) Irrigation and Drainage Network located in Khuzestan Province. To validate the results, the statistical indicators of root mean square error (RMSE), standard error (SE), mean biased error (MBE), and determination coefficient (R²) were used. To validate the simulation results of the benefit-cost ratio, the values of these indicators were obtained 0.25, 0.19, 0.005, and 0.96, respectively. Then, to determine the optimal cultivated area of the network and increase the profitability, the cropping pattern was determined both non-stepwise and stepwise in 2013 to 2017 cropping years. In the non-stepwise, the cultivated area of each crop changed from zero to 2 times of current situation. In stepwise, due to social and cultural conditions of inhabitants, this change was slow and 10% of the current situation every year. The analysis of the results showed the success of the model in optimizing and achieving the desired goals and the total benefit-cost ratio increased in all years both non-stepwise and stepwise. For example, in 2017 compared to 2016, production costs decreased by 7.1 percent and sales prices increased by 5.8 percent, and increased the benefit-cost in 2017 compared to the previous year. The results showed that the present model has good accuracy in simulating and optimizing the irrigation network, its cropping pattern, and defining other scenarios.

Accurate prediction of pore water pressure in the body of earth dams during construction with accurate methods is one of the most important components in managing the stability of earth dams. The main objective of this research is to develop hybrid models based on fuzzy neural inference systems and meta-heuristic optimization algorithms. In this regard, the fuzzy neural inference system and optimizing meta-heuristic algorithms including genetic algorithms (GA), particle swarm optimization algorithm (PSO), differential evolution algorithm (DE), ant colony optimization algorithm (ACOR), harmony search algorithm (HS), imperialist competitive algorithm (ICA), firefly algorithm (FA), and grey wolf optimizer algorithm (GWO) were used to improve training system. Three features including fill level, dam construction time, and reservoir level (dewatering) obtained from the dam instrumentation were selected as the inputs of hybrid models. The results showed that the hybrid model of the genetic algorithm in the test period had the best performance compared to other optimization algorithms with values of R2, RMSE, NRMSE, and MAE equal to 0.9540, 0.0866, 0.1232, and 0.0345, respectively. Also, ANFIS-GA, ANFIS-PSO, ANFIS-ICA, and ANFIS-HS hybrid algorithms performed better than ANFIS-GWO, ANFIS-FA, ANFIS-ACORE, and ANFIS-DE in improving ANFIS network training and predicting pore water pressure in the body earthen dams at the time of construction.