JWSS - Journal of Water and Soil Science

In general, rivers are one of the best and most accessible water resources at the disposal of mankind.  So, given the effect of the force of water and changes on the  flow patterns and consequently, on river morphology changes, the analysis of the flow in the river is important and necessary to organize projects, flood control and water supply structures downstream. In this study, by using numerical models CCHE2D hydraulic conditions Dimeh River Bridge between Oregon Bridge Sudjan was investigated. CCHE Model is a mathematical model capable of simulating the flow patterns and sediment transport in rivers and canals laboratory network. The numerical model in 1998, based on the calculations by the National Centre for Water Science and Engineering, University of Mississippi (NCCHE), was developed and has been applied in many research projects related to water engineering. At the outset, the input data required model provides and numerical model was implemented. In the next step, the results of the model were calibrated and validated using field data measurements; eventually, they were extracted and their model results were compared; it was confirmed that CCHE model could still simulate the flow pattern.

The purpose of this study was to determine the relative contribution of sub-basin resources to sediment production by using magnetic susceptibility data as the tracer in Chehelgazi catchment, Sanandaj. For this purpose, 20 samples of the output 5 sub-basins were measured by harvesting and magnetic susceptibility. Kruskal-Wallis test results showed that in all three trackings, frequency high, low and dependent, at least two sources had the ability to differentiate. In the second step, the three tracers were tested on the discriminant analysis by the sub-basin source and two tracers with different power splitters showed the high frequency of 88% and the frequency dependence of 12%; power splitters both tracers together in the sub-basin splitters was 90%, so they were selected as the optimal combination; therefore, they have the capability to determine the relative contribution model of sediment. The results of Bayesian uncertainty model also indicated Todarsamadi sub-basin with 44.4% of the largest contribution and Doveyseh, Chatan and Cherendo sub-basins with 35.5, 7.9 and 4.5, respectively, and Madian Dol sub-basin with 4/4 percent had the lowest contribution to sediment production. Based on the available results, Todarsamadi and Doveyseh sub-basins had the highest amount of sediment production; so these results could be used in soil conservation and management planning.

Occurrence of local scour is one of the most significant causes of damage to the pipes. Therefore, safe and economical design of pipes in the flow path requires a good estimate. In this study, based on the important and effective parameters in the scouring phenomenon, in order to develop educational patterns according to the data obtained in the laboratory of Ahvaz Islamic Azad University, models based on artificial neural networks were created with the NeuroSolution5 software. MLP, GFF and RBF were the models used in this study; after comparing, MLP was selected as the basis for our study. Finally, the effect of each parameter on scouring was determined using the  artificial neural networks technique, based on which the  shields parameter with a very high effect (more than 95 percent) was determined as one of the most effective causes of the local scour.

After Hamidieh Diversion Dam near the city of Hamidieh, Karkheh River is divided into two streams known as Hufel and Nissan. At the lower flow rates, Nissan makes up a greater share than Hufel due to the steeper slope of the former. This study attempted to construct a hydraulic structure to appropriately divide water flow in Hufel. In a laboratory experiment, a flume with a 90-degree bend was used at Islamic Azad University of Ahvaz. Various experiments were conducted at different widths and heights. Furthermore, this model was simulated through CCHE2D, the results of which were compared against those of physical and mathematical models. The results indicated that the weir height increased the deviation flow percentage to the Hufel stream due to rising water level. Moreover, the deviation flow percentage to Hufel was declined as the weir width was increased due to falling water level. At Hufel, the installation of rectangular weir in different dimensions yielded the minimum of 34.3% and the maximum of 61.5% increase in the flow rate. In the normal mode without any weirs installed, however, there would be an increase in the flow rate, as compared to the mode where a weir has been installed. This can be associated with the flow controlled by the weir. On average, the deviation flow rate was increased by 2.8% in the weir mode and 7.7% in the weir-less one. An increase in the Froude number from 0.21 to 0.38 led to a lower average deviation flow rate by 19.3%. Moreover, the results of the simulation through CCHE2D were demonstrated to be largely similar to those of physical model experiments. However, an increase in the Froude number did not lead to a decline in the deviation flow rate (i.e. it remained constant). This trend was inconsistent with the results of the physical model.

This research tried to provide a sustainable solution for the allocation of water resources of Zayandehrood basin in a way ensuring minimal conflicts and tension between the stakeholders in use of the water resources, four main decision makers of the basis, comprising Regional Water Company, conflicts among Agricultural Jahad Organization, and Department of Environment of Isfahan Province and Chaharmahal and Bakhtiari Province, were reviewed and 128 possible cased  according to 7 scenarios were constructed and applied in the  GMCR model. According to the GMCR approach, 6 balanced sustainable scenarios in different climatic periods of the basin were presented. Finally, the results were generalized for choosing the best mode in the form of a scenario within the WEAP model; also, the results obtained from these scenarios were presented using the criteria of system performance assessment. On the basis of the findings, Scenario II was developed, comprising the application of new simultaneous management of demand and supply, restrictions in drawing water from water tables, new prioritization in stakeholder allocation and new water portion plans in the basin as the best scenario with 81.4% sustainability index.

Hydrodynamic models proposed for simulating flow hydraulic in rivers assume the flow in one direction and simulate the hydraulic parameters based on the one-dimensional Saint-Venant equations. In this research, a two-dimensional HEC-RAS model was used to simulate the flow in the Karun River, between Mollasani and Farsiat stations. Geographic information system (GIS) and river cross sections were used to prepare the altitude map using the satellite image of the study area. Modeling results in river bends showed that the maximum velocity occurred in the outer bend, which coincided with the flow mechanism in the bends. Based on the results, grid type and density have little effect on flow depth modeling. However, the characteristics of the mesh used had a great influence on the velocity distribution, so that the regular high-density mesh had the best accuracy in simulating the flow velocity. Statistical analysis showed that the RMSE for the flow discharge and flow depth were 17.95 m³/s and 0.05 m, respectively. In addition, the Nash–Sutcliffe efficiency index was calculated to be above 0.9 for the discharge and flow depth, which could be considered as a desirable value.

Flood is a natural disaster making the heavy humanistic and economic damages each year in most parts of Iran. In this research, the SWAT model performance in flood prediction and sub-basin priority was investigated in terms of flooding in Araz-Kose watershed in Golestan province. To calibrate the model, SUFI2 was applied. The calibration and validation were done for the 1991-1998 period based on the data of 2001-2009. After validation, the indices (R2, bR2, and NS) were estimated. They were equal to 0.81, 0.81 and 0.73 for calibration and 081, 0.78 and 0.64 for validation, respectively. The sensitivity analysis results showed 13 effective parameters. The curve number (CN2) was determined as the most effective parameter. For studying the flooding in a watershed, the Araz-Kose watershed was divided into six parts. Based on the obtained results from the SWAT model with different CN and F indexes (with/without considering the sub-watershed), the sixth sub-basin with 22.4% decrease in discharge was chosen as the most effective region in flooding. Meanwhile, the other sub-basins including 4, 1, 3, 5 and 2 had more flood potential, respectively.

The evaluation of climate change impact on hydrological cycle includes uncertainty. This study aimed to evaluate the uncertainty of climate change impact on the Zayandeh-Rud Reservoir inflow during the future period of 2020-2049. The outputs of 22 GCM models were used under the three emission scenarios including RCP2.6, RCP4.5 and RCP8.5. The Bayesian Model Averaging (BMA) was used as the uncertainty analysis for weighting the 22 GCM models based on their ability to simulate the baseline 1990-2005 period. Results showed that different GCM models had different abilities in estimating climatic and hydrological variables and the application of uncertainty analysis in climate change studies could be necessary. The monthly temperature in the upstream of Zayandeh-Rud reservoir could be raised by 0.85 to 1 ◦C; also, the precipitation might be increased by 2 to 3 percent. The high flow during winter season will increase under climate change, while the spring and autumn seasons’ low flows are expected to reduce. Additionally, the annual reservoir inflow may decrease by 1 to 8 percent, showing the necessity for change in Zayandeh-Rud reservoir’s rule curve and allocation of water resources.

A ‘spillway’ is a structure used to provide the controlled release of flood water from upstream into downstream area of a dam. As an important component of every dam, a spillway should be constructed strongly, reliably and efficiently to be used at any moment. Labyrinth and stepped spillways are presented as appropriate modifications to those spillways hardly capable of managing the maximum potential discharge. Owing to their nonlinear crests for a given width, labyrinth and stepped spillways have a larger discharge rate than linear- crest spillways at an identical height. Compared to other energy dissipaters, the combination of stepped and labyrinth spillways is known as a very strong energy dissipater. In the following part, the combination of these two structures and their dimensional change for increasing the water- energy dissipation are addressed. To conduct this study, an experimental flume with a 90- degree bend in the Islamic Azad University of Ahwaz was used. In total, 90 experiments were conducted on three different labyrinth- shape stepped spillway models with two different lengths, three different widths, and five different discharges. Analysis of the results showed a greater energy loss reduction in triangular rather than rectangular or trapezoidal labyrinth- shape stepped spillways. In addition, energy loss was greater in labyrinth spillways with two cycles than those with one cycle. Energy loss was increased by raising the Froude number from 0.05 to 0.1; in contrast, energy loss was decreased with increasing the Froude number from 0.1 to 1.0, which was due to the submergence of steps, a decrease in the roughness of steps and an increase in the intensity of aeration.

Nowadays, with the increasing population in Iran, especially in arid and semi-arid areas, as a result of the growing importance of the quality of water resources, including groundwater, field experiments and many simulations have been conducted for the development of groundwater contamination through powerful and up- to- date software. However, in most cases, there is a tangible difference between the measured data in laboratories and the data produced with software; this is why the scientific validation and verification of the research results could be declined. In this study, in order to justify and correct these data, the calibration principle was used to minimize the error of testing and modeling. The purpose of this study was to validate and verify the SUTRA model for different scenarios of the solute transport in a sand tank with heterogeneous hydraulic conductivity to evaluate transverse dispersivity. In this study, coding was initially performed for the configuration and calibration of the SUTRA numerical model to simulate different scenarios of the solute transport in a heterogeneous sand Tank in the Hydraulic Laboratory of the University of Kassel, Germany, until acceptable values were obtained. Then the results were compared with the experimental model. In order to validate and verify the data obtained from the simulation with the SUTRA model, the relevant concentration profiles were compared with the results of the experimental model. The results of the numerical and laboratory models revealed the density effects by sinking the geometric center of the mixing zone for the low concentrations of salt, C₀ = 250 ppm. The results also showed that the width of the mixing zone between salt and fresh water depended on the amount of longitudinal dispersivity, especially the transverse dispersivity. By analyzing the results of simulation and experiment, it was observed that with increasing the velocity, reducing the amount of sinking and raising the input concentration, the time needed to achieve the steady dispersion was decreased.

Drought as a natural hazard is a gradual phenomenon, slowly affecting an area; it may last for many years and can have devastating effects on the natural environment and in human lives. Although drought forecasting plays an important role in the planning and management of water resource systems, the random nature of contributing factors contributing to the occurrence of and severity of droughts causes some difficulties in determination of the time when a drought begins or ends. The present research was planned to evaluate the capability of linear stochastic models, known as multiplicative Seasonal Autoregressive Integrated Moving Average (SARIMA) model, in the quantitative forecasting of drought in Isfahan province based on the Standardized Precipitation Index (SPI). To this end, the best SARIMA models were chosen for modelling the monthly rainfall data from 1990 to 2017 for every 10 synoptic stations in Isfahan province to forecast their monthly rainfall up to five years. The monthly time scale SPI values based on these predictions were used to assess the drought severity of different stations for the 2018- 2022 time period. The station results indicated a weak drought at the 2019- 2022 period for Isfahan, Kashan and Naeen, a severe drought in 2019 for Ardestan and Golpaygan, and a weak one in 2019 for the East of Isfahan, KabootarAbad and Shahreza stations. All other stations, except Golpayegan, Isfahan, Kashan and Naeen, faced a severe drought in 2018.

This study was conducted to evaluate AquaCrop for the simulation of potato yield and water use efficiency (WUE) under different water stress values at five levels (E0, E1, E2, E3 and E4, indicating 100, 85, 70, 50 and 30 percent of crop water needed, respectively) in three times during growth cycles (T1, T2, and T3, indicating 50, 100, and 150 days after sowing, respectively). The results showed that AquaCrop had overestimated and underestimated error for the simulation of yield and WUE, respectively. Based on RMSE and NRMSE values, the errors for yield and WUE were acceptable. The maximum and minimum error were also 0.3 (E1T3) and 3.15 (E1T2), respectively. The results obtained for WUE showed that the maximum and minimum were 0.53 (E3T2) and 0.03 (E4T2), respectively. The average differences between simulated and observed results (ADSO) of WUE for E1, E2, E3 and E4 were 0.24, 0.25, 0.19, and 0.44 ton.ha^-1, respectively; the ADSO of yield for T1, T2, and T3 was 0.19, 0.36, and 0.22 ton.ha^-1, respectively. Therefore, AquaCrop showed a high error for WUE when water stress was increased and crop was in its initial crop growth.

The flow fields over a trapezoidal labyrinth weir (two-cycle) and a piano key weir were simulated using Flow3D, studying the impact of each model on the flow field in the weirs and the coefficient of discharge in comparison with the available experimental data. Moreover, the models were investigated experimentally in a 12.5 m long, 0.3 m wide, and 0.4 m high rectangular flume under clear-water conditions. The results showed good agreement between the data from the numerical and experimental models. The piano key weirs had a higher coefficient of discharged compared with labyrinth weirs. The coefficient of discharge was observed to increase by 26 percent as the height of the PKW was increased by 50 percent (from 5 to 7.5 cm). This increase was 24 percent for labyrinth weirs.

Given the climatic changes and threats to food security in recent years, they have have become a major issue in agricultural climatology. The present study aimed to investigate the status of agricultural climate suitable for the cultivation of rice in the light of the influential climatic conditions in the past. Given the effect of temperature and the amount of precipitations on rice growth and the sensitivity of rice to these two variables, the study examined the predicted future temperature and rainfall and their effects on rice. Data related to the temperature and rainfalls were obtained from the Meteorological Organization. Additionally, the temperature and agricultural potential of the region were considered. By preparing the agricultural calendar for the cultivation of rice, the correlation between temperature, precipitation and rice productivity was calculated using the Spearman Correlation coefficient. By using the SDSM model, future data and temperature and precipitation return period were determined in the SMADA software. The results demonstrated that minimum spring temperature tended to be late spring. The minimum temperature had the highest impact in April, the maximum temperature had the highest impact in July and the maximum rainfall had the highest effect in both June and July. Based on the results of the prediction models, the studied region would experience an increase in temperature and rainfall by providing favorable conditions for the cultivation of rice. However, delays in the cold season and shortness of the growth period increased the risks associated with the cultivation of rice in this period.

In this study, the discharge coefficient of sharp-crested weirs located on circular channels was modeled using the ANFIS and ANFIS-Firefly (ANFIS-FA) algorithm. Also, the Monte Carlo simulations (MCs) were used to enhance the compatibilities of the soft computing models. However, the k-fold cross validation method (k=5) was used to validate the numerical models. According to the input parameters, four models of ANFIS and ANFIS-FA were introduced. Analyzing the numerical results showed that the superior model simulated the discharge coefficient as a function of the Froude number (Fr) and the ratio of flow depth over weir crest to the weir crest height) h/P(. The values of the mean absolute relative error (MARE), root mean square error (RMSE) and correlation coefficient (R) for the superior model were calculated 0.001, 0.002 and 0.999, respectively. However, the maximum error value for this study was less than 2%. 

The interaction of population growth, technological improvement and climate change have impacted severely on agricultural and environmental sustainability. In Iran, conventional tillage practice has resulted in soil erosion and loss of soil organic matter. In this regard, Conservation Agriculture (CA) forms part of this alternative paradigm to agricultural production systems approaches and can be regarded as a means to enhancing food productivity, reducing poverty, and mitigating the consequences of climate change in rural households. The objectives of this study were to examine the determinants and impacts of CA technology on wheat yield, poverty gap and water use. To this end, an endogenous switching regression (ESR) model was employed to estimate the impacts of CA technology on continuous variables such as wheat yield, poverty gap and water use. A sample of 260 farmers from Zarghan district was selected for interview collection of necessary farm level data. The results indicated that in the select equation of ESR model, ten coefficients (out of 12) are significant at the 5% level or higher. Knowledge of soil quality, access to credit, access to information, education, farm size, ownership of machinery, participation in agricultural extension activities and farmer’ perception have positive and significant effects on the probability of adopting CA. In contrast, variables such as the distance to shopping center and number of land parcels have negative and significant influence on adoption. Also, the results of ESR model and counterfactual analysis showed that wheat yield would increase by 1.05 tons and poverty gap and water use would decrease by 20% and 910 cubic meters per hectare respectively if farmers adopt CA technology.

In this study, we used the ARIMA time series model, the fuzzy-neural inference network, multi-layer perceptron artificial neural network, and ARIMA-ANN, ARIMA-ANFIS hybrid models for the modeling and prediction of the daily electrical conductivity parameter of daily teleZang hydrometric station over the statistical period of 49 years. For this purpose, the daily data for the 1996-2004 period were used for model training and data for the 1996-2006 period were applied for testing. In order to verify the validity of the fitted ARIMA models, the residual autocorrelation and partial autocorrelation functions and Port Manteau statistics were used. PMI algorithm were   then used to model and predict electrical conductivity for selecting the effective input parameter of the neural fuzzy inference network and the artificial neural network. The daily parameters of magnesium (with two days delay) and sodium (with one day delay), heat (with one day delay), flow rate (with two months delay), and acidity (with one day delay) were obtained with the lowest values of Akaike and highest values of hempel statistics as the input of the neural fuzzy inference network and the artificial neural network for modelling daily electric conductivity predictions; then predictions were made. Also, models evaluation criteria confirmed the superiority of the ARIMA-ANFIS hybrid model with the trapezoidal membership function and with two membership numbers, as compared to other models with a coefficient of determination of 0.86 and the root mean square of 29 dS / m. Also, the Arima model had the weakest performance. So, it could be applied to modeling and forecasting the daily quality parameter of the tele Zang hydrometer station.

Knowledge about the spatial distribution of soil organic carbon (SOC) is one of the practical tools in determining sustainable land management strategies. During the last two decades, the utilization of data mining approaches in spatial modeling of SOC using machine learning algorithms have been widely taken into consideration. The essential step in applying these methods is to determine the environmental predictors of SOC optimally. This research was carried out for modeling and digital mapping of surface SOC aided by soil properties ie., silt, clay, sand, calcium carbonate equivalent percentage, mean weight diameter (MWD) of aggregate, and pH by machine learning methods. In order to evaluate the accuracy of random forest (RF), cubist, partial least squares regression, multivariate linear regression, and ordinary kriging models for predicting surface SOC in 141 selected samples from 0-30 cm in 680 hectares of agricultural land in Khorramabad plain. The sensitivity analysis showed that silt (%), calcium carbonate equivalent, and MWD are the most important driving factors on spatial variability of SOC, respectively. Also, the comparison of different SOC prediction models, demonstrated that the RF model with a coefficient of determination (R2) and root mean square error (RMSE) of 0.75 and 0.25%, respectively, had the best performance rather than other models in the study area. Generally, nonlinear models rather than linear ones showed higher accuracy in modeling the spatial variability of SOC.

The objective of this research was the development of a hydraulic-economic simulation-optimization model for the design of basin irrigation. This model performed hydraulic simulation (design of basin irrigation), using Volume Balance model, economic simulation through calculating sum of four seasonal costs and optimization using NSGAII multi-objective meta-heuristic algorithm. For programming, MATLAB programming software was applied. The optimizations of functional, multi-dimensional, static, constraint, continuous, multi-objective and meta-heuristic were applied for the optimization of the objective functions. Decision variables selected from simulation inputs were calculated in such a way that the  hydraulic objective function (minimizing linear combination of seven performance indicators) and economic objective function (total seasonal cost based on sum of water cost, labor cost, basin preparing cost and channel drilling cost) were minimized. Data of one the experimental field was used for the purpose of simulation. After initial simulation, optimization of the experimental field was done using NSGAII multi-objective meta-heuristic algorithm with tuned parameters. Optimization using the suggested model shoed the decrease (improvement) of objective functions rather than initial simulation performance. As a result, the suggested model could be regarded as is a specialized tool for basin irrigation, showing a good performance, despite its simplicity.

Water is the most crucial factor for agricultural development. Therefore, the economic evaluation of water resources is critical. The purpose of this paper was to determine the economic value of water resources, to evaluate the financial efficiency and to decide on the price of agricultural water in Arak plain. For this purpose, the economic value of water resources for wheat, barley, alfalfa and corn was identified in 2015- 2016, using the mathematical model developed in this research. The results showed that the financial efficiency was calculated for three alternatives: free-cost water, water cost equal to the 10% of the calculated price and water cost equal to the exact calculated price.  The irrigation efficiency of 40% financial efficiency was 2.38%, 1.68% and 0.47% , respectively, for the  aformentioned methods, and  the irrigation efficiency of 70% financial efficiency was 2.07, 1.92 and 0.71, respectively. Also, the sensitivity analysis of the financial efficiency was performed, with 10% change in the farmers income and costs. The results also revealed that irrigation efficiency and financial efficiency were not aligned when farmers had free water; however, they were aligned when the farmer paid 10% of the calculated price. Financial efficiency was more sensitive to changes in the farmers income when compared to the changes in costs.