مجله تحقیقات آب و خاک ایران
سال پنجاه و سوم شماره 8 (پیاپی 80، آبان 1401)

The impact of dust phenomenon in Iran is so vast that it has involved more than half of the country's provinces in some way with the issues and limitations of this natural phenomenon. In addition to the environmental effects, it has disrupted the implementation of national sustainable development plans and so far, it has had many negative consequences. This research tries to present a new hybrid model using artificial intelligence hybrid metamodels as well as Box Jenkins hybrid metamodels to predict and model the FDSD index (frequency of days with dust storms), in seven synoptic stations of Khuzestan province with length The statistical period has been 40 years (1981-2020). The hybrid prediction algorithms used in this research include W-ANFIS, AF-SVM, ARIMA-NARX and SARIMA-SETAR. The prediction results showed that the decrease in the performance of hybrid models to predict the FDSD index has a direct relationship with the decrease in the frequency of days with dust storms. So that the correlation coefficient for experimental data in AF-SVM and W-ANFIS hypermodels from 0.991 and 0.985 to 0.985 and 0.958, respectively, and Nash Sutcliffe coefficient has also decreased from 0.977 and 0.960 to 0.973 and 0.952, respectively. Also, the RMSE coefficient from Abadan station to Dezful for the two metamodels from 0.135 and 0.151 to 0.140 and 0.179 respectively, And the MAE coefficient has also increased from 0.054 and 0.068 to 0.060 and 0.093, respectively. Correlation coefficient for test data in Box Jenkins SARIMA-SETAR and ARIMA-NARX hypermodels also from 0.967 and 0.951 to 0.958 and 0.941 respectively and the Nash Sutcliffe coefficient has also decreased from 0.945 and 0.923 to 0.938 and 0.913, respectively, which indicates the weakening of the performance of hybrid metamodels with the decrease in the frequency of dust storms in Khuzestan province. Also, by fitting four hybrid hypermodels on the FDSD index, it was shown that AF-SVM hybrid hypermodel had better performance than other methods. In a way, in all studied stations, the correlation coefficient and Nash-Sutcliffe coefficient are higher and the root mean square error coefficient and the mean absolute value of the error are lower, which shows the superiority of this hybrid meta-model over other meta-models for predicting the FDSD index in Khuzestan province. The results of this study can be used to model dust storms in other western regions of the country.

Today, in order to increase the efficiency of fertilizer use and reduce environmental pollution, the production and consumption of slow-release fertilizers is considered. The objective of the current study was to apply three methods of rotary drum (A), insitu hydrogel synthesis (B) and two-stage (C) to reduce the solubility rate of urea fertilizer using starch as a cheap and environmentally friendly source and evaluation the comparative efficiency of these samples on the growth and nutritional responses of tomatoes. At first, fertilizers were synthesized in three methods. Then, the effects of synthesized samples (A,B and C) were compared with un-coated urea granules on morphological characteristics of tomatoes. A factorial based on completely randomized blocks design were utilized with three replications in 2020 in greenhouse conditions, at 180 and 420 kg/ha of each fertilizer treatment. The results showed that urea release rate after 6 hours from synthesized (A, B and C) fertilizers was reduced 87.33, 32.08 and 29.22%, respectively compared to un-coated urea. Comparison of coating methods showed that the highest amount of dry weight (roots and shoots), stem length, chlorophyll content and number of leaves and lateral branches were observed in C fertilizer treatment. Nitrogen use efficiency and apparent nitrogen recovery in C fertilizer treatment increased 36.54 and 27.04% compared to urea, respectively. The use of starch as a natural biopolymer in the structure of these fertilizers reduces nitrogen loss and environmental pollution.

Engineers in recent decades have come to the conclusion that the design of bridges should be based not only on structural considerations but also on the impact of flow on bridges due to the long-term experience of building bridges over rivers. In this study, we investigated the effects of the longitudinal development of the pier, the vertical angle of the pier, the pier thickness, and the shape of the base nose for sediment with an average diameter of 1.2 mm. Experiments were performed on piers with angles (45, 60, 75 and 95). The results showed that the angle was different from different points along with the distance between the hole and the pier, and the scour depth was above the maximum depth created. At an angle of 45 degrees without a nose, the scour depth was reduced by 51% for the base with a thickness of 30 mm, 79% for the pier with a thickness of 15 mm, and 89% for the triangular nose with a thickness of 30 mm. Among the triangular and long noses, the triangular nose in all the studied conditions was better reduced by 96.4% scours depth. In addition, as the thickness of the pier decreased, the pressure applied to the pier decreased and, as a result, scouring decreased by 8.3%.

In this research, the improvement of a clay soil contaminated with MTBE using GGBS activated by magnesium oxide and slaked lime was studied. Contaminated soil with MTBE was artificially prepared in the laboratory with a concentration of 2.25 g (MTBE)/kg (soil) and activated GGBS with slaked lime was added to it with different percentages. Experiments including Atterberg limit, compaction, uniaxial strength and SEM were conducted on samples of natural soil, contaminated and those which were mixed with the mentioned additives. The results showed that the used additives increase the strength of natural and contaminated soil and this improvement is a function of  percentage of the used materials and the curing time. In general, adding the used additives increases the strength by 14-22% by increasing the mixing percentage and curing time. In addition, the strength of natural soil with a same percentage of additives and the same processing time is about 3 to 7% higher than contaminated soil. Comparison of the effect of two additives clarified that lime has a greater effect in improving than activated GGBS. The SEM results also clarified that the hydration of the additives cause producing the cementitious materials which improves the mechanical behavior of the soil.

The most common method to supply phosphorus for plants is the use of phosphate chemical fertilizers that have low efficiency, high cost and harmful environmental effects. If the availability of phosphorus can be increased by using phosphorus-soluble bacteria and mycorrhiza, the phosphorus concentration and plant growth parameters may also increase and make a major change in the phosphorus nutrition of plants. The aim of this study was to investigate the possibility of using superior strains of phosphate-solubilizing bacteria isolated from rhizosphere of pistachio trees, mycorrhiza and phosphate sources on the growth and phosphorus uptake of pistachio seedlings in greenhouse conditions. The experiment was performed as a factorial experiment in a completely randomized design with three replications in 2019. Treatments included four sources of phosphorus (control, monocalcium phosphate, tricalcium phosphate, and soil phosphate), four levels of bacteria (control, Serratia odorifera, Pseudomonas fluorescens and Pseudomonas brassicacearum) and two levels of mycorrhiza (control and mycorrhiza (Funneliformis mosseae, Rhizophagus intradices, Rhizophagus irregularis and Glomus caledonium)). Analysis of variance of the data showed significant interactions between phosphorus-soluble bacteria, phosphate sources and mycorrhiza on pistachio growth indices. All three bacterial isolates had positive effects on increasing vegetative indices. Also, mycorrhiza inoculation along with bacterial inoculation showed a significant increase of 44% in root dry weight. The highest shoot to root ratio was observed with application of soil phosphate and tricalcium phosphate which increased by 19% and 37% compared to control respectively. Inoculation of pistachio seedlings by mycorrhiza increased root, stem and leaf P concentration by 90%, 104% and 122% respectively. Therefore, phosphate-solubilizing bacteria especially Pseudomonas SP and mycorrhizal fungi played an important role in increasing the efficiency of phosphorus fertilizers and reducing fertilizer use, increasing growth and phosphorus uptake of pistachio seedlings.

Supplemental irrigation is considered as a beneficial economic mechanism in the situation of water constraint and increase water use efficiency of canola. The aim of this study was to evaluate the effect of supplemental irrigation on yield, yield components and water use efficiency. This research was carried out at split plots in a randomized complete block design with three replications at Gachsaran Agricultural Research Station in 2017-18 and 2018-19. Irrigation regimes applied in four levels (without irrigation (I1), supplemental irrigation at flowering stage (I2), supplemental irrigation at grain filling stage (I3), supplemental irrigation at flowering stage + grain filling (I4)) in main plot, Hyola and Shirali cultivars were sown in the subplot. The studied traits including number of pods per plant, number of seeds per pod, 1000 seed weight, biological yield, grain yield, harvest index and water use efficiency. Results of ANOVA showed that the number of pods per plant increased from 88 in rainfed conditions to 120 with two supplemental irrigations, which increased by 36%. The supplemental irrigation increased the harvest index from 24.1 to 27.9 percent, which was an increase of 12.4 percent. Increasing the frequency of supplemental irrigation increased the grain yield and biological yield, so that the two supplemental irrigations increased the average grain yield from 782 in rainfed conditions to 2378 and increased biological yield from 3228 to 8350 kg ha-1. The highest water use efficiency (0.73 kg m3) was obtained from treatment I4 and the lowest (0.39 kg m3) was obtained from treatment I1. Overall, the results showed that supplemental irrigation increased grain yield, oil yield, harvest index and water use efficiency 83, 12, 7, and 23 percent, respectively. In case of canola cultivation in rainfed conditions, high yield can be achieved by supplemental irrigation in two stages of flowering and grain filling.

In this paper, the ability and performance of two unsaturated soil constitutive models are compared. One constitutive model is in the context of classical plasticity, and the other constitutive model is in the context of generalized plasticity. The selected models consider the effect of water retention curve on the unsaturated soil behavior. First, a program in FORTRAN language is written for each constitutive model. In the next step, the written program is validated with the experimental results. Finally, eight different suction-stress paths are modeled to identify the strengths and weaknesses of the constitutive models. The results showed that both models could simulate the loading at constant suction, increasing the yield stress and decreasing the soil deformation with an increase of suction. In drying–wetting cycles, the variation of the yield stress of the Sun et al., 2007 model is less consistent with experimental data than the variation of the yield stress of the EBSZ model, and Sun et al., 2007 Model cannot simulate some important properties of unsaturated soils. The EBSZ model cannot simulate a sudden volume reduction (failure) under decreasing suction in unsaturated soils. Using the EBSZ model in the deformation analysis of unsaturated soil may not be reliable.

Leaf area index is an important parameter in controlling different processes between atmosphere-plant-soil and due to its importance in various modeling, its rapid measurement at different scales has been considered. The use of vegetation indices (VIs) is one of the common methods for estimation leaf area index and each of these indices shows different sensitivities in various values of leaf area index during plant growth period. The aim of this study was to estimate leaf area index using Normalized Difference Vegetation Index (NDVI), Difference Vegetation Index (DVI), Weighted Difference Vegetation Index (WDVI), Soil Adjusted Vegetation Index (SAVI), Green Normalized Difference Vegetation Index (NDVIg), Normalized Difference Water Index (NDWI), Optimized Soil Adjusted Vegetation Index (OSAVI), Enhanced Vegetation Index (EVI), Wide Dynamic Range Vegetation Index (WDRVI) and Green Difference Vegetation Index (GDVI) and comparison with measured leaf area index during the growth period of maize under different crop densities and the application straw mulching during 2020 growing season in the Karaj. Based on the results, the sensitivity of vegetation indices to leaf area index weren't same at different growth stage and indices such as DVI, WDVI and GDVI at the initial growth stage and NDVIg, NDWI and EVI at the mid growth stage showed high sensivity to estimation of leaf area index. Finally, OSAVI index With R2, RMSE and average noise equivalent (NE) of 0.91, 0.98 (m2/m2) and 1.8, respectively, considered as the best index for leaf area index estimation.

One of the important goals of the development of greenhouses in the country is to improve production efficiency and increase water and fertilizer efficiency. Bell pepper is also one of the most important greenhouse products around the world and has a high economic value. This research was carried out to provide irrigation and fert fertigation scheduling for greenhouse peppers through monitoring soil moisture and salinity in the root zone in 1400 in Alborz province, Chaharbagh city. The treatments include three irrigation treatments I1, I2 and I3 (100, 80 and 60% of the plant's water requirement) and three fertigation treatments F1, F2 and F3 (150, 100 and 50% of the plant's fertilizer requirement, respectively) in the form of a randomized complete block design in three replications. The total amount of irrigation measured for treatments I1, I2 and I3 was 397, 318 and 238 mm, respectively. The irrigation requirement values simulated by the irrigation requirement system of agricultural and garden plants were compared with the measured values, and the statistical indices RMSE, NRMSE, MBE, d and EF were calculated to be 38.55, 0.21, and -21.1, 0.99 and 0.95 respectively. The results showed that the effect of irrigation, fertigation and their mutual effect on the yield of greenhouse pepper was significant. The maximum yield of pepper in the I1F1 treatment was 114.38 tons/ha and the minimum in the I3F1 treatment was 40.96 tons/ha. Also, the maximum water productivity in the I2F2 treatment was 31.05 kg/m3 and the minimum in the I3F1 treatment was 17.19 kg/m3. Although the maximum yield was obtained in the I1F1 treatment, the maximum water productivity was obtained in the I2F2 treatment, and the product yield was not significantly different in these two treatments. The general conclusion shows that 20% deficit irrigation is recommended by monitoring the moisture of the root zone in greenhouse pepper production, but the fertilizer should be controlled by monitoring the salinity of the root zone.

Eutrophication is a global environmental problem that poses a serious risk to the conservation of dams lake water quality, human health and aquatic ecosystems. Indicators for determining the nutritional status of water bodies allow to make decision and to implement management strategies for controlling eutrophication. TSI and TLI indices and statistical analysis on phosphorus (TP), nitrogen (TN), chlorophyll.a (Chl.a) and Secchi depth (SD) parameters were used to assess the Eutrophic state of Alaviyan Dam Reservoir during 1394 to 1398. The results of parameter analysis showed that the values of total TSI and total TLI index for the lake in 1398 were 53.5 and 4.8, respectively, and thus the lake was placed in the eutrophic category. TN was the main cause of worsening water quality in spring, while in autumn TP had a greater portion in declining water quality. In addition, the differences between the indices indicate that during the study period, phosphorus is not a factor that limits algal productivity and the mean value of 8.8 for the TN / TP ratio emphasizes that TN is the limiting factor of primary production. Studies also showed that in addition to algae, which block light from passing to lower levels of the lake, non-algal turbidity can also affect the growth of phytoplankton. The parameters of total nitrogen, total phosphorus, and chlorophyll-a. showed increased trend, which requires input nutrient controls into Alaviyan reservoir to preserve the water quality.

Although the use of fertilizer in poor soils is essential for increasing soil fertility and optimal growth of plant, but in recent years, chemical fertilizers have caused a lot of environmental damages. Thus, this study was conducted to investigate the effect of organic matter (Rice Husk) and mineral modifiers (Clinoptilolite Zeolite) on some soil properties. For this purpose, an experiment was performed in 2020 in the greenhouse faculty of the agricultural and natural resources of lorestan university. Test treatments include: 1- organic modifiers with three level (1, 3, 5 wool weight) and mineral modifiers with three level (3, 5, 10 wool weight) and control treatment 2- three different incubation time (30 as control, 60, 90 days). Before starting the proposed times, one month incubation was applied to the soil to adjust the soil material. The result showed that the use of both modifiers increased average weight of the aggregate diameter, porosity, weight moisture, electrical conductivity, total nitrogen, acidity, carbon ratio to nitrogen and microbial respiration compared to the control. The average weight of aggregate diameter increased by 26.7% compared to the control. But, the amount of bulk density and the hydrophobicity of the samples were decreased as compared to the control treatment. 10% weight of zeolite and 3% weight of rice shell treatment reduced hydrophobicity by about 37.8% compared to the control. Over time, the amount of bulk density, porosity, electrical conductivity, organic carbon, total nitrogen and microbial respiration showed a reduction trend, but the soil acidity and carbon ratio to nitrogen had an increasing trend. The carbon/nitrogen ratio during the incubation period of 60 and 90 days, significantly increased by 7.04 and 17.32% compared to the control. The result of data analysis showed that the effect of time on hydrophobic and average weight of the aggregate diameter and weight moisture was not significant.

Water quality forecasting plays an important role in environmental monitoring, ecosystem sustainability and aquaculture. Traditional forecasting methods cannot show the non-linearity and instability of water quality well. In the present study, the water quality parameter of dissolved oxygen was modeled using intelligent Support Vector Machine (SVM), Gaussian Process Regression (GPR) and Long Short-Term Memory (LSTM) methods on three consecutive stations on Savanah River located in USA. For this purpose, six different flow hydraulic and hydrological parameters including water temperature, turbidity, discharge, mean water velocity, pH and specific conductivity were used daily for seven years (2021-2015) as input parameters to model dissolved oxygen. The results showed the complete superiority of the deep learning method over the machine learning methods. According to the results, the long short-term memory method for the last model, which included all parameters, in the third station with correlation coefficient, coefficient of determination and root mean square error, respectively R = 0.981, DC = 0.956 and RMSE = 0.034 for test data performed better. Finally, by performing sensitivity analysis, by removing the water temperature parameter, it was found that DC evaluation criteria decreased by 14% and RMSE increased by 100%. Therefore, water temperature was introduced as the most influential parameter in predicting dissolved oxygen in water.

In this study, a fuzzy multi-objective planning model was used for the optimal allocation of irrigation water and land use under multiple uncertainties. The effect of effective rainfall for determining the irrigation requirement of cultivated crops and also the limitation of surface water and groundwater resources were taken into account in the developed model in the Talash study area, which is located outside the Sefidroud irrigation and drainage network. The study area of Talesh was divided into three irrigation areas: Astara, Talesh, and Rezvanshahr. Then, the results of the optimal model were investigated at different levels of α-cut (0, 0.2, 0.4, 0.6, 0.8, and 1). Allocated amounts of surface water and groundwater showed that maximum shortages occurred in June and July in Talash area, So that the shortage of Talash area in the upper and lower bounds of a-cut=0.8 was 1.7 and 2.7 times more than Astara area as well as 1.2 and 1.8 times more than Rizvanshahr area, respectively. The optimal ratio of groundwater consumption to the total allocated water in Astara, Talesh, and Rezvanshahr areas were 13.4%, 58.1%, and 28.5% respectively. Also, 100% of the allowable groundwater is consumed in most of the dry months of the year. Due to the unavailability of surface water resources to many farmers in this area, proper approaches should be given to the farmers for more access to surface water. Therefore, the results of this study could be a warning for the regional manager and planners to consider this issue in future planning to select the best decision regarding the use of the type of irrigation water resource.

System simulation is done with different structures and by using different approaches and algorithms. Algorithms are intelligent methods of data processing in machine learning that can identify unknown factors in a time-dependent phenomenon. In the analysis of random phenomena, among the methods that can make decision-making easier is the ensemble algorithms. With the help of this method, more accurate data management and more knowledge of the studied system is obtained. Since, investigation of the trend component can be effective in simulating hydrological phenomena and help in interpreting the relationship between hydrological processes and environmental changes in the study areas; State space models have the advantage of analyzing the system flexibly and dynamically. Therefore, this article aims to improve the efficiency of Kalman Filter, ETS, BATS, and TBATS state space time series models with the help of an ensemble method and by comparing with the Box-Jenkins model, to show which of these models has a better capability in simulating the monthly discharge of the river. This comparison has been done in three water measuring stations of Sepiddasht Cesar, TangPanj Bakhtiari and Telezang in Dez catchments located in Khuzestan province since 1386 to 1399. The results of this study, based on the model evaluation criteria (RMSE, MAE and R2), showed that the state space performed better than the Box-Jenkins model (classical), and among the state space models, the local level model (Kalman filter) performed better. So that in the validation stage, RMSE = 39.21and R2 = 0.79 in Sepiddasht Cesar water measuring station, RMSE = 57.89 and R2 = 0.76 in TangPanj Bakhtiari station and RMSE = 113.41 and R2= 0.73 in Telezang station were obtained.

This study was done in Sefidrood Irrigation and Drainage Network. Paddy rice and tea gardens were selected as agricultural products. The environmental performance of the system was evaluated by selected environmental impacts categories such as climate change, Eutrophication, etc. Economic performance was also determined by using the total added value of the system's final products, according to water use and the adopted management practices. Finally, the value of area vulnerability was evaluated by assessing the eco-efficiency of these categories. The results showed that the most important environmental impact categories were climate change, human toxicity, aquatic eco-toxicity, and fossil fuels depletion because of high use of fertilizers and chemical pesticides, the combustion of diesel fuels in agricultural machinery and water pumps. So that the ratio percentage of the mentioned parameters were 48.9, 47.9, and 2.4% of the impact values of the climate change group, respectively. Furthermore, type I, II, and III indexes were defined for the environmental impact assessment of tea and rice, by which the tea indices were accordingly higher than those of rice due to their higher environmental impacts. For example, in the climate change group, the ratio of type I, II, and III indexes of tea to rice was calculated to be 1.4, 4.2, and 2.7, respectively. In addition, the economic performance of rice per hectare was approximately 70% more than the one of tea, however, the economic performance per cubic meter of water consumption in rice was only 8% more than the one in tea, due to high water consumption. Finally, the comparison of eco-efficiency indexes of different groups showed that the lowest eco-efficiency was obtained for climate change and fossil fuels depletion. In addition, the analysis showed that despite of the greatest environmental impacts of rice, the highest eco-efficiency index was related to rice due to higher economic performance compared to tea.