نشریه علوم آب و خاک (علوم و فنون کشاورزی و منابع طبیعی)
سال بیست و چهارم شماره 4 (پیاپی 94، زمستان 1399)

The purpose of this research was to investigate the trend of annual changes in Yazd stationchr('39')s meteorological parameters including minimum and maximum average daily temperature and average daily precipitation (1961-2005), as well as the predicted annual mean of these parameters in the three upcoming thirty years of the 2040s, 2070s and 2100s, by the SDSM model, under RCP2.6, RCP4.5, RCP8.5, A2, and B2 scenarios. Accordingly, by using the coefficient of determination and the MAE, R2, RMSE indicators, we evaluated the data generated by the SDSM model in comparison with the observed data in the base period. The lowest value of R2 based on the calibration and validation of the mean values of observed and simulated SRES was obtained for precipitation (86 and 80%). In terms of the R2 evaluation index, the accuracy of the small-scaled results of the minimum and maximum average temperature values was more than that of the average precipitation; however, in terms of the MAE and RMSE evaluation indicators, the accuracy of the small-scaled results of the average precipitation was higher than that of the minimum and maximum average temperature values. Subsequently, HadCM3 large-scale climatological data was used to predict the future periods (2010-2100). The results indicated that the temperature was raised in all months and seasons and the precipitation was decreasing in most of them, thereby confirming that the climate was changing in the studied region.

The present study was intended to improve the chemical properties of a saline-sodic soil using the individual application of alfalfa residue and two biochars produced from sugarcane bagasse and walnut shell, at the weighting ratio of 5%; their concomitant application with gypsum, aluminum sulfate and the mixture of these two chemical amendments was considered. The experiment was conducted in three replications using the factorial experiment in a completely randomized design. After four months of incubation, the soil samples were measured for their main chemical properties. The results showed that alfalfa residues were the most effective treatment to reduce the soil pH; so the concomitant application of this organic amendment with gypsum lowered the soil pH from 9.13 in the control (untreated soil) to 7.24. It was also observed that the addition of gypsum and/or aluminum sulfate to the soil led to the increase of the soil electrolyte concentration and consequently, the increase of soil electrical conductivity to three times greater than control, through an increase of ions, like calcium and sulfate in the soil solution. Increasing the soluble sodium concentration by replacing exchangeable sodium by other similar ions showed that the studied treatments enhanced the sodium adsorption ratio (SAR), which could be regulated by washing. Concomitant application of the walnut-shell biochar with gypsum had the most increasing effect on the soil SAR, enhancing it from 22.6 in the control to 54.3. Potassium was released from organic amendments, improving the soil general conditions; addition of chemical amendments elevated soil exchangeable potassium contents; however, the elevated soil available phosphorus contents were less influenced by chemical amendments application. As the conclusion, it seems that the positive impacts of the applied chemical and organic amendments would supplement each other; as a result, the concurrent use of both treatments not only improves the bad soil chemical properties, but also enhances the soil fertility.

Drilling material from the tunnel of the Tehran-Shomal highway was estimated to be about 2.5 Million Cubic Meters by the project authorities. Sadly, from the beginning, the drilling materials had been deposited on the open space in the floodplain of the Chaloos river with slightest environmental considerations. During the previous years, weathering and leaching from the drilled materials besides the discharge of drain water from the tunnel had led to seriouse contaminations and the deterioration of the water quality of the Chaloos river. In this paper, the ecological risk of nonorganic pollutants due to drilled materials was investigated. The sampling was done from the excavated materials and river sediment in five different locations throughout a complete year. From the many pollutants, Nickel, Cadmium and Copper were chosen to be investigated. The results showed that almost 15 percent of the samples had a high degree of pollution, while 60 percent of them were clean and the other 25 percent included the highly contaminated ones. All samples were also estimated to have a low to high ecological risk.

In regard to wide piers, the pile group rather than single pile is used frequently to bear the loading of the structure in a particular arrangement; piles group composed of only one column of piles in the flow direction has a great effect on supporting the bridge deck. In this study, local scour at a single column arrangement of the piles group made up of four rows of piles characterized by different piles spacing was studied for clear-water conditions with two flow discharges of 20 and 35 l/s (the effect of increasing the flow depth with the same flow intensity). The results indicated that an increase in the flow depth not only greatly enhanced the scour depth and the width of the scour hole. Besides, the investigation of the relative flow depth on scour extent showed the need for revision in deep water conditions, as reported in the literature. The results of the pile group experiments revealed the noticeable impacts of piles spacing on the local scour. The bigger pile spacing caused a feeble interaction of wake-horseshoe vortices, leading to a decrease of the scour depth; the separate view of the scour holes was generated at individual piles. Finally, the results were compared with commonly used comprehensive models. The findings of this study can be applied for the appropriate selection and positioning for the countermeasure of the scour at bridge piers.

In order to study and evaluate the drought stress indices in surface irrigation by furrow method on grain yield, the yield components and water use efficiency, an experiment was conducted at Behbahan Agricultural Research Station in 2014-16. The experiment was conducted as a split plot in a randomized complete block design with 4 replications. Irrigation at two levels (irrigation after 100 and 200 mm evaporation from Class A pan, respectively) was evaluated as the main factor and corn cultivar was considered at 6 levels as the sub-factor. Comparison of the  mean water use efficiency in irrigation and cultivar interactions showed 100 mm evaporation from Class A pan and cultivars V4 (PH1), V5 (PH3) and V2 (SC Mobin) were ranked the first and foremost, respectively, with the  yields of 1.353, 1.299 and 1.296 kg of corn per kg of water consumed, respectively. The mean water consumed in 2014 of the experiment in 100 and 200 mm evaporation from Class A pan was 521.2 and 462.4 mm, respectively. Pearson correlation coefficient results  also showed that with increasing the  yield components, such as the  number of grains per row and number of rows, the  1000-grain weight was  increased due to  the highly significant correlation coefficient of 1000-grain weight with grain yield (r = 0.8776).  Consequently, grain yield was also increased. The highest values of SSI, STI, MP, TOL, GMP HM and YI indices were calculated in V4 (PH1). The higher values of the above indices in cultivar V4 (PH1) than other cultivars caused this treatment to be introduced as the superior one. The decreasing trend of corn yield, which was caused by water deficit stress, increased SSI, STI, MP, TOL, GMP and YI indices, while it decreased corn yield, leading to incremental changes in the YSI indices.

Wind erosion is one of the environmental problems worldwide, particularly in arid and semi-arid areas of Iran. Different methods and models have been proposed to measure and monitor wind erosion in the recent years. One of the accurate models for measuring f wind erosion is the USEPA model. The purpose of this study was to evaluate the quantification of wind erosion with the USEPA model and the comparison of different interpolation methods for drowsing high-precision soil erosion mapping. For this purpose, 50 samples from 0-30 depth were taken from the study area. Based on the analysis of the physical properties of the soil, including the distribution of the primary and secondary particle sizes, climatic parameters such as evaporation and transpiration, rainfall, wind speed and also, the vegetation and topography characteristics of the area, the erosion rates of Q, Q30 and Q50 were measured. Interpolation methods including general kriging, IDW, LPI and RBF were compared. The results showed that the highest erosion emission rate of Q50 was 39 ton ha-1. The highest and lowest erosion rates for the Q30 index were 0.060 and 2.694 ton ha-1, respectively; for the Q index, the highest and lowest erosion rates were 0.009 and 0.055 ton ha-1, respectively. The results also showed that the IDW method for the Q50 index with the minimum error rate (RMSE) values of 3.94 and the mean absolute error (MAE) with the valueof 1.89 had the best performance among the studied models. The LPI model Q had the best performance with the lowest error (0.0086) and absolute absolute error (0.0021).

The scour around the bridge piers is one of the main causes of bridge failure and the extraction of aggregates may aggravate this phenomenon. The present study comprehensively investigated the scour around the groups of bridge piers in the presence of aggregate extraction pits, using different discharges. The bridge piers roughened by gravel had been compared with the simple bridge piers; so, the results showed that the roughening caused the reduction of the scour depth. Scour depth change rate led to an increase in the equilibrium time. The results also showed that the reduction of the scour depth at the downstream groups of piers was more than that in the upstream. For the lowest discharge, the aggregate extraction pits had a considerable effect on the scour depth difference for the groups of piers in the downstream and upstream. On the other hand, the effects were decreased when the rate of discharge was increased. The experimental results obtained by the rough surface models showed that as the discharge was increased, the local scour was increased too; at the same time, the bed profile was posed at the low level. Generally, the scour depth of the groups of piers in the downstream of the extraction pit was more than that in the upstream. The results of the current research, therefore, demonstrated that the surface of the bridge pier roughened by gravel reduced the scour depth.

Today, the use of organic wastes as fertilizers to improve the physical, chemical and biological properties of soil is common. In this study, to investigate the effect of the sewage sludge on the growth and concentration of chlorophyll, nitrogen, phosphorus and potassium in quinoa plant, a factorial experiment was conducted based on a completely randomized design with three replications in a calcareous soil with electrical conductivity of 13.1 dS m-1. Treatments included three genotypes of quinoa (Red carina, Titicaca, Q29) and three levels of sewage sludge (0, 20 and 40 t ha-1). The results showed that the effects of the quinoa genotype, different levels of sewage sludge and the interaction of treatments on the root dry weight, shoot P concentration and chlorophyll concentration were significant. Also, the sewage sludge had a significant effect on the shoot length, shoot dry weight and shoot nitrogen concentration. By increasing the level of the sewage sludge, root length, shoot length, shoot dry weight and shoot N concentration were increased, on average, by 44.7 %, 48.8%, 42.0% and 46.6%, respectively. Also, application of 40 t ha-1 sewage sludge significantly increased the chlorophyll concentration and shoot P concentration in Q29 and Titicaca genotypes. According to the results of this study, application of sewage sludge can increase the growth of quinoa by improving its nutrition.

Optimal use of water resources seem to be necessary due to climate change and the recent drought conditions. One of the most important and effective management strategies is increasing water productivity in agriculture. Irrigation method and the use of different levels of nitrogen fertilizer are the effective factors in increasing the water productivity. Therefore, this study was conducted to investigate the effect of the irrigation method and nitrogen fertilizer on the harvest index and water productivity of two wheat cultivars with 36 treatments as a split-split plot based on a completely randomized design with three replications in the research farm of Natural Resources and Agricultural Research Center of Kashmar, during the 2018-2019 time period. The treatments were two irrigation methods including end blocked border and drip irrigation (tape) as  the main plots, three levels of the nitrogen fertilizer from urea source including 0, 50 and 100 kg/ha as the  sub plots and two cultivars of wheat including Pishgam and Sirvan as the sub-sub plots. The results showed that by changing the border irrigation method to the drip irrigation (tape) method, the harvest index and water productivity were increasesignificantly. The results also showed that grain yield and its components, including harvest index and water productivity, had no significant difference in 50 and 100 kg/ha nitrogen levels. On the other hand, grain yield and its components, harvest index and water productivity, were significantly higher in the Sirvan cultivar rather than the Pishgam one (P<0.01). According to the results obtained from this study, the drip irrigation method, 50 kg/ha nitrogen level and Sirvan cultivar could be recommended for the study region.

Optimizing the water resources operation, especially in the agricultural sector, which has the largest share in the water resources operation, is extremely important. Therefore, in this research, while introducing Whale, Gray Wolf and Crow Search Optimization Algorithms, their performance in the optimum operation of Golestan single-reservoir system Dam was evaluated with the aim of providing water demand for the downstream lands based on reliability, Reversibility, and vulnerability indices. In this optimization problem, the objective function was defined as the minimization of the total deficiency during the operation period. Meanwhile, the constraints of continuity equation, overflow, storage and reservoir release volume were applied to the objective function of the problem. Then, the results were compared with the absolute optimal value based on the nonlinear programming method obtained from GAMS software; finally, a multi-criteria decision-making model was developed to rank the optimization algorithms in terms of performance. The absolute optimal response obtained by the GAMS software based on the nonlinear programming method was 19.41. The results showed that the Gray Wolf algorithm performed better than the other algorithms in optimizing the objective function, so that the average responses in Gray Wolf, Crow Search and Whale algorithms were 92, 84 and 67% of the absolute optimal response, respectively. Furthermore, the Gray Wolf optimization algorithm performs better than the Whale and Crow Search algorithms in all parameters. In addition, the coefficient of variation of the responses obtained by the Gray Wolf algorithm is 2 and 1.43 times smaller than that in the Whale and Crow Search Algorithms, respectively. Finally, the results of the multi-criteria decision-making model showed that the gray wolf algorithm had the first rank, as compared to the other two algorithms studied in solving the problem of the optimal operation of the Golestan dam reservoir.

The Khanmirza plain is one of Iran’s fertile plains that is located in Chaharmahal Bakhtiari province. Agriculture in the area is very prosperous, but the lack of rain and over-harvesting from consumption wells has led to a reduction in groundwater levels, even causing land subsidence. Moreover, the high usage of chemical manures, especially nitrate manures, has increased the number of solutes and chemical materials in the groundwater. Thus, for this plain, making artificial ponds is important to modify the storage of the aquifer. In this study, to define the optimum locations of the artificial ponds, the effect of 12 factors was considered. The analytic hierarchy process (AHP) method was used to introduce the weight of each parameter in comparison to other factors. Afterward, the spatial priority of all factors was derived using the Geographic Information System (GIS) technique. The produced GIS layers were laid on each other and the optimum locations were obtained. Agricultural drainage was an effective index for recharge purposes. The results of the study demonstrated that groundwater level decline got the maximum weight (40%), while the land slope had the minimum weight, since the vicinity to available floodways was considered as an independent criterion. The results also showed that regions with a total area of 18 km2 in north and north-west of the Khanmirza plain could be the optimum and most suitable places for artificial ponds construction.

The prediction of local scouring as a dynamic and nonlinear phenomenon using methods of acceptable predictive capability has always been of interest to researchers. The shape of the bridge pier is one of the important factors in the formation and magnitude of the scour hole. In this paper, the scour depth of three bridge piers with cylindrical, sharp nose and rectangular shapes was predicted in two scenarios using the support vector machine algorithm with 395 field data obtained from the US Geological Survey and Froehlich (1988), based on different combinations of dimensionless parameters as the water attack angle (α), Froud number (Fr), the ration of pier length to width (l/b), and the ratio of mean sediment size to pier width (D50/b). The results of the study, while confirming the acceptable performance of the SVM algorithm for all piers in both scenarios, showed that in the first and second scenarios, the most optimal performance was related to the rectangular pier shape with correlation coefficient of 0.8702 and 0.8838, with and maximum Ds (DDR) values of 0.854 and 1.229 respectively, during the testing phase. The positive effect of increasing the number of data on the performance of the SVM algorithm was also confirmed by further probing the evaluation indicators. The results of the comparison pointed out the overestimation of the predicted scour depth values of absolute error between 11% to 35%.

Earthworms are soil organisms commonly used in environmental studies and biological toxicology. Therefore, the present study aimed to investigate the role of Eisenia Fetida  earthworms on the bioavailability of zinc and copper in the  contaminated soils. This study was carried out on a contaminated soil sampled from the Ahangaran mine 26 kilometers far from the city of Malair and its surrounding areas. In this experiment, 12 earthworms with  the average weight of 0.3 -0.6  g were selected for each soil sample. The worms were exposed to a  metal contaminated soil for 42 days. After the test time, Zinc (Zn) and Cupper (Cu) concentrations were measured in different fractions of the soil. The results showed that cow manure, carrot pulp and vermicompost significantly reduced (at the level of 5%) 62.2, 80 and 65.2 mg / kg of the metal zinc concentration in carbonate, respectively,  as compared to the treatment control. Earthworms significantly increased zinc (81.45 mg kg) in the  carbonate fraction. On the other hand, there was a significant increase in the amount of exchangeable copper with the addition of organic fertilizer to  worm, as compared to the control sample. This increase  was significant (at the level of 1%) in the treatment of Vermicompost (1.27 mg / kg) and carrot pulp (1.32 mg / kg), as compared to control.

In determining the allocation of water resources, the probable conditions of water resources and water demands are considered as the water allocation scenarios in the basin scale. Then, these scenarios are evaluated in the context of integrated water resources management and from the perspective of sustainable development indicators. The best scenario is selected in order to determine the water allocations. In these evaluations, there are spatial distributions and their interactions are simultaneously the key charaterictics in the decision matrix. These features are not often considered in the evaluation process. In the present study, distributed indicators and simple and integrated multi-criteria evaluation models, including ANP and CP methods, were used to evaluate the water allocation scenarios in the Aras Basin. The results showed that modeling of the spatial distribution and interactions of water allocation impacts was not possible through any of the simple multi-criteria evaluation methods. Simplifying and discarding one or two key features in the evaluation process can lead to significant uncertainties on rankings with a Spearman coefficient of -0.1. By implementing the integrated spatial decision-making approach and applying two features simultaneously, the fourth scenario was ranked first. The proposed approach was compared with the individual models, showing more accurate, with the correlation coefficients of 0.5, 0.6 and 0.7.

Identification and investigation of changes in the area under cultivation of various crops seem to be essential for the management supply of crop production. In this study, r to identify and investigate change of the area under cultivation in major crop Hoseynabade Mishmast region in Qom province, we used the time series images of OLI and ETM sensors of landsat 8 and 7satellites, according to the crop calendar of this region. By using the vegetation index (NDVI) in the decision tree algorithm, the thresholds of this index were adjusted according to the major crops of this region; then a map of the cultivation pattern of the crop of this region was prepared. In order to evaluate the results, the statistics of the provinces agricultural jihad were used during 2005, 2009, 2014 and 2019 crop years. The results showed that by using the threshold of NDVI index, crops in this region in 2005 included wheat and barley and alfalfa, and their areas had an error of 17/1 and 6/1 percent in comparison with the statistics of agricultural Jihad, respectively; in 2009, wheat and barley, alfalfa and corn had an error of 0/5, 9/6 and 0/1 percent. Also, in 2014, wheat and barley, alfalfa, corn and sophie crops had an error equal to 4/9, 0.4, 11/4 and 2/4 percent, and the same crops in 2019 had an error 0/04, 11/6, 1/4 and 17/5 percent; that error was not significant. According to the results, the appropriate efficiency NDVI index in estimating crop cultivation area was determined by their phenology. Also, in 2009 and 2014, corn and sophie crops were added to the regions crops, and the area under crops cultivation in 2019 was increased, as compared to 2014.

In the present study, the SWAT hydrological model was developed for the upstream of the Zayandehrood dam to evaluate the inflow to this dam. Accordingly, after entering the meteorological and hydrometric information of the region, the runoff simulation was performed. Due to the high volume of entrances to the Zayandehrood Dam, Shahrokh Castle hydrometric stations were selected as the base station for calibration and validation during the statistical period of 1990-2015. After hydrological simulation and accuracy of results, climate prediction was performed using the fifth model of the climate change for the RCP scenarios. According to the forecast, by using climate change models, the temperature could be assumed to increase in all models and the highest rate of increase would occur under the RCP 8.5 climate scenario. After evaluating climate change in different diffusion scenarios, the runoff of the basin was simulated in the SWAT model. The simulation results of runoff in the catchment area showed that although the amount of rainfall was increased in the region, increasing the temperature had a greater effect, reducing the amount of runoff in the basin. Based on the results of climate change, hydrological simulation was performed using the SWAT model. The results showed that the effect of diffusion scenarios in the region was different, causing an increase in temperature and precipitation. The highest increase was observed in the RCP8.5 scenario, which was consistent with the nature of this emission scenario, with the highest emission of greenhouse gases and carbon dioxide. Then, the evaluation of the hydrological model was done; the results showed that although the amount of rainfall in the region had been increased, the increase in temperature of this basin had a greater effect and efficiency in reducing the amount of runoff.

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

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

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.

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.