JWSS - Journal of Water and Soil Science

In the vast majority parts of the Earth, a prospect now visible is the mostly synthetic thinking and fabrication by the human hand. Collision and impact of humans on the natural environment in the short and long-term courses for obvious geographical features have changed a variety of spaces. One of the consequences of human impact on the natural environment during the current period is the phenomenon of climate change. One of the climatic parameters that plays an important role in agriculture, energy, urban, tourism and road transport is the minimum temperature. In this study, an attempt was made using the minimum temperature data from 5 meteorological stations in the West Mazandaran province, as well as HADCM3 model data, to show how to change this parameter in the future periods based on simulation by the SDSM model. Accordingly, after selection of the suitable climate variables and model calibration, the accuracy of the created model in the base period was evaluated; after ensuring the sufficient accuracy of the model according to A2 and B2 scenario, data minimum temperature in 2100 was simulated. Based on the simulation results showed that the values of minimum temperature in the region over the coming years would increase. This parameter was such that the average seasonal periods 2016 to 2039, 2040 to 2069 and 2070 to 2099, as compared to the baseline period would increase, on average, by 1.8, 3.5 and 6 percent. The largest increases in the minimum temperature in the western and southern parts of the region could occur. It was also found that unlike other months of the year, the minimum temperature in January would be a decreasing trend.

Infiltration is the most important characteristic in the design and management of any surface irrigation system. Since the hydraulic of flow in meandering furrows is different from the standard furrows, the accuracy of infiltration function parameter estimation methods should be examined for the optimal design and management of meandering furrow irrigation. The main objective of this study was to compare Elliot and Walker’s two-point and two-time methods for estimating the empirical infiltration function parameters of meandering furrow irrigation using four sets of field data. The estimated infiltration functions, as obtained by the two methods, were validated by performing the unsteady flow simulations and using the Slow-change/slow-flow (SC/SF) model. The results showed that Elliot and Walker prediction of the advance trajectories (with a mean RMSE of 0.68 minutes) was comparable to the two-time method (with an average RMSE of 0.66 min). The Nash–Sutcliffe efficiency coefficient for the simulated outflow hydrograph by the two-time and two-point methods was 0.89 and 0.50, respectively, indicating the excellent predictive power of the two-times method. In addition, the two-time method predicted the total volume of infiltration with the less relative error (-1.5%), in comparison to the two-point method (-47.2%). Therefore, the use of post-advance data (such as a two-time method) for infiltration function parameters estimation improves the flow simulation in the meandering furrows.

In this study, drought characteristics of Arak, Bandar Anzali, Tabriz, Tehran, Rasht, Zahedan, Shiraz and Kerman stations during the statistical period of 1956 to 2015 were studied by Reconnaissance Drought Index (RDI) and Standardized Precipitation Index. Precipitation and temperature data were needed to calculate RDI. Precipitation data was also required to estimate SPI. In this study, Drinc software was used to calculate RDI, SPI and potential evapotranspiration (PET). The software calculated PET by the Thornthwaite method. One of the main challenges in drought monitoring is to determine the indicator that has a high reliability based on its monitoring purpose. Therefore, in this research, two methods used for selecting the appropriate index based on the minimum rainfall and normal distribution were evaluated. The results of the evaluation of the minimum rainfall method for selecting the appropriate index showed that most drought indices with the occurrence of minimum rainfall level indicated severe or very severe drought situations; in most cases, it could not lead to selecting an exact and unique index. Based on the results of the normal distribution method for the stations of Arak, Tabriz, Rasht, Zahedan, Shiraz and Kerman, SPI index, and for the stations of Bandar Anzali and Tehran, RDI index were selected as the most appropriate ones.

In recent years, a lot of research has been done on the Aquacrop model, the results show that this model simulates the product performance for deficit irrigation conditions. But this model, like other models, is sensitive to values of independent variables (model inputs). In this research, the sensitivity of the Aquacrop model was analyzed for 4 input parameters of reference evapotranspiration, normalized water productivity, initial canopy cover percentage and maximum canopy cover for barley. Irrigation treatments included full irrigation and two deficit irrigation treatments of 80% and 60%, the experiment was done in 2014-15 growing season in the field of Abourihan College. The values of measured biomass were used as the base values for treatments. The Beven’s method (Beven et al., 1979) was used for sensitivity analysis of Aquacrop model. The results showed that the model is most sensitive to the reference crop evapotranspiration, So the sensitivity coefficient for this parameter for full irrigation treatments, 80% full irrigation and 60% full irrigation were -1.1, -1.2 and -2.3 respectively. The negative sign indicates that if the value of reference evapotranspiration input is exceeded the actual value into the model, Yield performance is simulated less than actual value. In the meantime, the higher the degree of deficit irrigation, the greater the sensitivity of the model.

Simulation of water and salt transfer in soil is very effective in managing optimal water and fertilizer use in the field. In this study, the HYDRUS-1D model was used to simulate the transfer of water and bromide in a laboratory column of soil with clay loam texture. Soil hydraulic parameters (including air entry point) α, (saturated hydraulic conductivity) ks, (residual moisture content) θr (saturation moisture content) θs, (pore and particle joint parameter) l (parameter of moisture curve shape) n through measurement and using Retc software was obtained Solubility transfer parameters including difiusion coefficient and actual velocity were estimated using soil hydraulic parameters and bromide concentration data by reverse modeling method. According to the target coefficients, the sensitivity analysis of the physical model was performed .The results showed that the correlation coefficient of observation and simulation bromide concentration in optimal mode was 0.84%. accordingly, the diffusion coefficient was estimated to be 4.9 cm. based on the results of the sensitivity analysis, the saturation hydraulic conductivity had the greatest effect on the variation of this parameter, so that the amount sensitivity coefficient of this parameter was 2.64 The RMSE coefficient with a value of 0.04 was the lowest and ME coefficient with the value of -0.0001 had the most parameter variations.

Lack of the proper conjunctive use of surface and groundwater resources causes large water stresses in one of these resources. Conjunctive use of surface and groundwater, especially in arid and semi-arid regions, is a scientific and practical solution for sustainable water resources management. The aim of this research was to prepare some mathematical modeling to apply the conjunctive use of surface and groundwater in the Dehloran plain aquifer. In this study, the mathematical model of the Dehloran plain aquifer was developed using GMS 9.1 and the river data were entered. For the steady state condition, the time series data in the average year 2010-2011 were utilized. In the next step, the time series data from October, 2010, to September, 2011, were used for the unsteady state analysis. In the unsteady state, four stress periods were taken; then the model calibration was carried out in three steps for each stress period; after the optimization of the hydrogeological parameters of the model, its verification was done for the period of 2011-2012 period. After the calibration of the model in the unsteady state, the values of the mean error (ME), the mean absolute error (MAE) and the root mean squared (RMS) errors measured in piezometers were obtained to be -0.24, 0.46 and 0.65, respectively. The results of verification confirmed the ability of the model in simulating the natural conditions of the aquifer. Finally, applying different scenarios to the model showed that the proper conjunctive use of surface and groundwater could increase the volume of water at a rate of 2.23 million cubic meters per year.

This study focused on proposing a new operational perspective within main and lateral irrigation canals based on the economic value of water. To achieve this objective, the operation-economic framework offered in this study consisted of two main components of the PMP model and Operation model. The estimated economic values of water in different regions of the network were employed as the starting point for connecting the economic model with the operation model. It is worth mentioning that the technical perspective targeting adequacy of water distribution within the canals was modified in this study to be applied for the operation-economic framework since the original forms of the indicator were based on physical inherent of the water. Roodasht Irrigation District, located at Zayandeh-Rud basin, was selected as the case study, and the proposed framework was tested on the district. The obtained results revealed that in response to implementing the proposed framework in water distribution within the canal under the water shortage condition, alfalfa and safflower were the two crops those cultivation was decreased drastically in comparison with the other crops. The primary reason for the decrease was the lower values of the economic value of water for these two crops. Also ,the results of the canal operation appraisal from the adequacy of water delivery revealed that for the traditional operating system (without considering the economic perspective), the maximum values of the adequacy indicator were obtained for the upstream four canal reaches. On the other hand, the off-takes numbers of 1, 6, 5, and 12 got the maximum values of the adequacy indicator when the proposed operation-economic framework was applied for the canal system.

Rainfall may be considered as the most important source of drinking water and watering land in different areas all over the world. Therefore, simulation and estimation of the hydrological phenomenon is of paramount importance. In this study, for the first time, the long-term rainfall in Rasht city was simulated using an optimum hybrid artificial intelligence (AI) model over a 62 year period from 1956 to 2017. The gene expression programming (GEP) and wavelet transform (WT) were combined to develop the hybrid AI model (WGEP). Firstly, the most effective lags of time series data were identified by means of the autocorrelation function (ACF); then eight various GEP and WGEP models were defined. Next, the GEP models were analyzed and the superior GEP model as well as the most influenced lags was detected. For instance, the variance accounting for (VAF), correlation coefficient (R) and scatter index (SI) for the superior GEP model was calculated to be 0.765, 0.508 and 0.709, respectively. Additionally, lags (t-1), (t-2), (t-3) and (t-12) were the most influenced. Then, the different mother wavelets were examined, indicating that the demy mother wavelet was the most optimal one. Moreover, analyzing the numerical simulations showed that the mother wavelet enhanced the performance of the GEP model significantly. For example, the VAF index for the superior WGEP model was increased almost three times after using the mother wavelet. Furthermore, the R and MARE statistical indices for the WGEP model were computed to be 0.935 and 0.862, respectively.

The main purpose of the study is the operational simulation of main irrigation canal and evaluation of water delivery and distribution locally, regionally and overall using adequacy, efficiency, and equity indicators and “Desirability of water delivery and distribution” indicator. To achieve this goal, the hydrodynamic model of Roodasht irrigation network’s main canal was developed. The results of the calibration and validation of the hydrodynamic model showed that the two processes were satisfactory. All available scenarios including normal, water shortages and fluctuations were considered for water delivery and distribution in different conditions. In the local assessment, the adequacy varied from 7 to 85%, and the efficiency in all scenarios was 100%. The adequacy, efficiency, and equity indicators in the regional evaluation varied from 6 to 89, 91 to 100, and 13 to 46%, respectively. The overall evaluation of the canal showed that the most desirable situation is related to a harsh fluctuation increasing with the adequacy, equity and efficiency indicators equal to 82, 23 and 91%, respectively. Calculation of the “Desirability of water delivery and distribution” indicator showed poor performance in all operational scenarios except harsh fluctuation scenario with 82% of which, the canal performance was estimated in fair level.

The construction of irrigation network and the water transfer from Karkheh Dam to Dashte-Abbas, due to neglecting the groundwater resources has increased groundwater level and waterlogging of the agricultural land in the recent years. The aim of this study was, therefore, to optimize the conjunctive use of surface and groundwater resources in Dashte-Abbas to minimize waterlogging problems and achieve the maximum net income. For this purpose, the behavior of groundwater was simulated using the system dynamics (SD) approach. The conjunctive use of surface and groundwater resources was then optimized using the Vensim multi-criteria optimization method with the objective function of maximizing the net income of the plain. The SD model calibration was done using climatic, hydrological, agricultural, and environmental data from the 2001-2009 time period; then it was validated based on the information from the 2009-2016 period. Evaluation of the developed SD model showed that the model had high accuracy in simulating key variables such as groundwater levels (ME=60cm, R²=97%, RMSE=47cm) and groundwater salinity (RMSE=100μS/cm, R²=74%, and ME=123μS/cm). Furthermore, the results of the optimization model showed that the optimum use of surface and groundwater resources for the agricultural demand was 65% and 35%, respectively. To sum up, it could be concluded that with the optimization of the conjunctive use of surface and groundwater resource, s about 10 MCM of water consumption could be annually saved to irrigate almost 800 ha of the new lands.

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.

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.

Investigating and understanding river change issues is one of the important factors in sediment hydraulic sciences and river engineering. These studies can be done with the help of physical, mathematical models, or both, but due to financial and time constraints, mathematical models are more general and often used. In this study, the GSTARS model was used to investigate erosion and sedimentation and select the most appropriate function in 12.5 km in length from the Talar river in Mazandaran Province. Simulation using the 55 sections taken in 2006, the daily flow data of the hydrometric station of the Shirgah, located at the beginning of the rich and characteristics of the river sediment, was done. The calibration and validation of the model with cross sections taken in 2012 showed that Yang's sediment transport equation has the highest correlation with reality and can be used to predict river change. The amount of sediment depleted from the case study using the Yang equation is estimated at 8590 tons per year. Also, the study of longitudinal profiles of the river with different sediment transfer functions showed that the study reach at the end range has an erosion trend and is not capable of sand and gravel mining.

In the present study, CanESM2 climate change model and stormwater management model (SWMM) were employed to investigate the climate change effects on the quantity and quality of urban runoff in a part of Karaj watershed, Alborz Province. The base period (1985-2005) and future period (2020-2040) are considered for this purpose. Based on the existing main and lateral drainage system and to be more accurate, the watershed was divided into 37 sub-watersheds by ArcGIS software. To simulate rainfall-runoff, the intensity-duration-frequency (IDF) curve has been prepared for a 2-hour duration and 10-year return period, for the base period and RCP2.6 and RCP8.5 climate change scenarios based on the obtained precipitation data from Karaj synoptic station. Results showed that mean 24-hour precipitation values in RCP2.6 and RCP8.5 scenarios will increase by 21% and 11%, respectively, and maximum 24-hour precipitation values will decrease by 17% and 23%, respectively, as compared to the observed values in the base period. Also, based on the results of quantitative and qualitative runoff modeling in the study watershed, and according to the outflow hydrograph in the RCP2.6 and RCP8.5 scenarios, the outlet runoff discharge will decrease by 5.8% and 7.1%, respectively. Also, the flooded areas in the watershed will decrease by 13% and 15.28%, respectively. The concentration of pollutants in the RCP2.6 and RCP8.5 scenarios, compared to the base period, including total suspended solids (TSS), will increase by 7.48% and 9.24%, total nitrogen (TN) will increase by 6.93% and 8.48%, and lead (Pb) will increase by 7.32% and 8.91%, respectively.

The application of simulation-optimization models is a valuable tool for selecting the appropriate cropping pattern. The main objective of this research is to develop a two-objective simulation-optimization model to determine the pattern of cultivation and water allocation. The model performs the optimization with the multi-objective metamorphic algorithm (MOALO) after simulating different states of the cultivation pattern. The decision variables including land and water allocated to ten-day periods of plant growth were designed in a way that the minimum utilization of water resources and economic maximization were identified as target functions. The developed model was used to simulate and optimize the cultivation pattern with an area of ​​5500 hectares and water allocation of Semnan plain with renewable water at the rate of 60.8 million cubic meters. Harvesting scenarios of 80 (GW80) and 100 (GW100) percent of renewable groundwater and scenarios of change in existing cropping pattern of 30 (AC30) and 60 (AC60) percent were considered and each scenario was simulated with the MOALO algorithm. Optimization using the proposed model in four scenarios improved the water and economic objective functions compared to the initial simulation performance. The results showed that the four proposed scenarios were obtained by minimizing the water objective function and maximizing the economic objective function relative to the current situation (simulation). In general, the proposed model had a good performance despite its simplicity, which is a specialized tool to optimize the crop pattern with water allocation.

At present, the occurrence of dust storms is one of the most important environmental problems in Khuzestan Province, and the south and southeast regions of Ahwaz have been recognized as one of the interior dust sources and are the priority of corrective operations. Given that land use change is one of the desertification factors in the mentioned region, therefore, modeling its changes is necessary and provides useful information for planners to control and revive the degraded lands. The objective of this study was to evaluate the efficiency of the CA-Markov model in predicting land use changes in the dust source of south and southeast of Ahwaz based on two long-term and short-term approaches. In the long-term approach, land use maps of 1986 and 2002 years and in the short-term approach, land use maps of 2002 and 2007 years have been used to predict land use for the year 2016 and then the simulation results were validated. The results showed that the values ​​of allocation error, quantity error, and kappa coefficient for the long-term approach were 42.55%, 13.95%, and 0.08 respectively, and for the short-term approach were 12.56%, 10.42%, and 0.22 respectively, which indicates the weak ability of the CA-Markov model to evaluate the desertification trend in the dust Source of south and southeast Ahwaz. Use of uniform transition rule throughout the simulation period without considering the factors and processes affecting land use change, the non-same trend of land use change during study periods, changes due to human activities, drought, and long forecast period can be the reasons for the poor performance of the CA-Markov model to predict the desertification trend the dust Source of south and southeast Ahwaz.

The study of annual damage statistics due to floods in Iran and the world shows the extent of flood damage to natural and human resources in different regions. Determining the flood zone of rivers in order to protect national resources and reduce flood damage provides the possibility of protecting the river from encroachment and the construction of any unauthorized facilities in it. Therefore, in the present study, the capability of numerical models in simulating the flood zone of rivers was evaluated in the range of Azarshahr Qushqura river and the two-dimensional hydraulic model HEC-RAS 5.0.7 and one-dimensional HEC-RAS model were compared. Changes in the hydraulic characteristics of the flood flow including depth and velocity of the flow at different cross sections of the models were evaluated. The results showed that the water surface level (flow depth) of the two-dimensional model HEC-RAS compared to the one-dimensional model had the lowest error as compared to other hydraulic parameters of flood flow. The two-dimensional HEC-RAS model showed the highest error rate in the flow velocity parameter in comparison to the one-dimensional model. The results indicated that two-dimensional HEC-RAS model V5.0.7 determined the surface of the flood zone 12.46 % more than the one-dimensional HEC-RAS model. The confirmation of the resulting zones on the current state of the river and comparison with the river aerial photo of 1346 indicated the higher accuracy of the two-dimensional HEC-RAS model in estimating the flood zone of the river.