نشریه تحقیقات کاربردی خاک
سال دهم شماره 3 (پاییز 1401)

Heavy metals pollution is one of the major environmental concerns in the world, as these metals are a threat to humans, animals, and plants due to their toxicity. Clay minerals which are a major component of the soil, play an important role in the absorption of various contaminants in soil and water. Bentonite (B) and its modified forms have a much higher capacity to adsorb toxic metals than other clays. This experiment was accomplished in a completely randomized design in a factorial arrangement with three replications. The experimental treatments consisted: time (5, 10, 20, 30, 60, 120, 240 min), B and nanobentonite (NB) adsorbents (2 g l-1) and humic acid concentrations (0, 100 and 500 mg l-1). The results showed that humic acid increased Cd adsorption by B and NB in different times. The highest amount of Cd adsorption by B adsorbent was 4370 mg kg-1 recorded in 500 m l-1 humic acid treatment and the lowest amount of adsorption was observed in the absence of humic acid 1134 mg.kg-1 by bentonite adsorbent. Semi second-order kinetic model was significantly fitted to Cd adsorption by B and NB in all of the humic acid concentrations (R2 for all three levels of humic acid in bentonite adsorbent and treatment of 100 mg.l-1 humic acid in nano bentonite adsorbent was 0.99,  for treatment of zero and 500 mg l-1 humic acid was 0.97 and 1.00, respectively). The results of current study showed that humic acid could markedly promote the Cd adsorption by adsorbents, which had a greater effect on the adsorption of B than NB.

To study the effect of enriched biochar (EB) by phosphate solubilizing bacteria (PSB) on soil phosphorus (P) fractionation and explain the change in soil phosphorus availability by determining changes in different forms of phosphorus, a factorial incubation experiment in a randomized complete design with six treatments (fertilizer treatments (control (count), biochar (BC), phosphate fertilizer (TSP), Biochar-Rock phosphate (BC-RP), biochar- PSB (BC-PSB) and enriched-biochar with rock phosphate and PSB (BC-RP-PSB) and two soil types with different EC (2 and 15 dS m-1) was studied in saline soils around Lake Urmia. Olsen-P, pH and different forms of inorganic P were determined by sequential extraction method at 7, 30 and 60 days of incubation. The results showed that on average, the BC-PSB-RP and BC-PSB treatments reduced the pH of soils S1and S2 0.1 and 0.4 unit, respectively. BC-PSB-RP treatments reduced Olsen-P of S1 and S2 soils from 6 to35.3 mg.kg-1 and 7 to 41.7 mg.kg-1, respectively. Microbial treatments significantly (p <0.01) altered the distribution and amount of inorganic P forms. BC-PSB-RP reatment increased the amount of Ca2-P fraction in S1 soil by 10 and in S2 soil by 5.2 time. However, the amounts of Ca8-P, Al –P and Ca10-P fractions reduced significantly. Olsen P positively and significantly correlated with Ca2-P, Fe-P, and Ca10-P fractions and suggesting that in the extraction of Olsen-P, phosphorus is released from these mineral fractions. The results showed that the use EB by PSB can provide long-term P supply to plants and had a better effect on increasing the availability of P in saline conditions.

Tillage and puddling are important operations of paddy field. Puddling is an important and common method in bed preparation for rice seedling cultivation in paddy lands, which is done with rotavator. To investigate the changes in soil physical and hydraulic parameters, an experiment was conducted as a split plot based on a randomized complete block design with three replications in Ghaemshahr, Iran. In this study, the rice field was under two main treatments, T1 (without tillage) and T2 (with tillage) and four sub-treatments of passing the rotavator, P1 (once), P2 (twice), P3 (three times) and P4 (four Times). Different levels of puddling on the paddy field with loam texture were applied and the parameters of infiltration, hydraulic conductivity, gravimetric water contents and dry soil bulk density were measured. Also, at the end of the cultivation season, 1000-grain rice weight was calculated for each treatment. The results showed that in both parameters of permeability and hydraulic conductivity, the T2 treatments had the lowest amount of infiltration and hydraulic conductivity. Also, in both parameters, with increasing the intensity of puddling, the rate of infiltration and hydraulic conductivity decreased significantly.  By applying tillage and increasing the intensity of puddling, a decreasing trend in the bulk density and an increasing trend in soil water content were observed. So that, the tillage treatment with high puddling (P4) had the maximum weight moisture (28.67 %). Different tillage methods did not show any effect on the weight of 1000-grains rice. In contrast, different puddling treatments had a significant effect on the weight of 1000-grains rice and in high puddling treatment the highest weight of 1000-grains rice (28.38 g) was observed showing the positive effect of high levels of puddling on this parameter. Finally, it can be concluded that tillage and puddling reduce water loss and thus increase water productivity in the rice cultivation.

Soil salinity is caused by natural or human processes and is a major environmental hazard. There is also a lack of soil moisture which has a negative impact on agricultural activities in mountainous areas where most of the climate is semi-humid. The main purpose of this study is to map soil salinity and moisture located in the western part of Lake Urmia in Iran using Sentinel 1 and 2 satellites along with five neural network algorithms to model soil salinity and moisture. Learning models are multilayer neural networks (MLP-NN), radial basis radiation performance (RBF-NN), Gaussian processes (GP), support vector regression (SVR), and random forests (RF). First, different salinity and soil moisture indices were obtained using different algorithms, then using 60 soil samples at a depth of 5 to 15 cm during a field survey on 06/18/1398 along with the image time. Sentinel 1 and 2 were harvested, precision was performed. In the soil salinity indices used in optical images, the salinity index with an accuracy of 0.96 was the best indicator for estimating soil salinity according to comparison with terrestrial data. The NDWI index also had the highest accuracy for estimating moisture in optical images with an accuracy of R2= 0.89. The accuracy of estimating soil moisture and salinity in radar images was R2=0.80 and R2= 0.89, respectively. The performance of five algorithms for modeling was also evaluated and compared using mean square error (RMSE) and correlation coefficient (R2). The results showed that the GP model had the highest predictive performance (RMSE = 2 and R2 = 0.82) and was better than other machine learning models.

The aim of this study was to evaluate the effect of sulfur fertilizer accompanied by thiobacillus inoculation on canola yield and yield components and some soil chemical properties by maize cropping during three consecutive years. This study was performed based on randomized complete block design consisting of seven sulfur treatments (0, 750, 1500 and 3000 kg ha-1) replicated three times. The treatments were added to soil two weeks before cultivation. Two and four-months soil samplings were done to determine EC, pH and SO4-2 content, as well as EC, pH, SO4-2, Fe, Zn, Mn, P, N, K contents and agronomical traits (1000-seed weight, plant height, number of seed in capsule, number of capsule) after harvesting in plant and plant yield. The results showed that increasing of sulfur fertilizer caused enhancement of seed yield, number of seed in capsule and number of capsule in plant during three consecutive years. In addition, the trend of changes in sulfate, potassium and nitrogen was improved and resulted in changes reduction of these elements in soil. The increasing trend of soil salt and acidity content were observed due to the effect of different sulfur treatments during consecutive years in two and four months sampling while these traits showed no significant variation after canola harvest. According to the obtained results, it could be suggested that the cropping system and sulfur fertilizer application would cause positive effect on chemical properties of soil and main agronomic product yield.

At the present study, the effectiveness of organic fertilizer produced from poultry wastes was evaluated on corn and pistachio plants. Treatments included: T1 (Control), T2 (Fertilizer recommendation based on soil test), T3 (Application 0.71 g kg-1 organic fertilizer from poultry slaughterhouse wast), T4 (Use of 1.06 g kg-1 of organic fertilizer from Poultry slaughterhouse waste), T5 (use of 0.07 g kg-1 N from urea + 0.53 g kg-1 slaughter wastes fertilizer, T6 (use of 0.035 g kg-1 urea + 0.8 g kg-1 slaughter wastes fertilizer), T7 (use of 1.33 g kg-1 vermicompost). The experiment was conducted as completely randomized design in four replications. The highest maize shoot dry weight belonged to T2 (fertilizer recommendation based on soil test) while the lowest one was related to T1 (control). In terms of total nitrogen content of maize, treatments T1 (0.35), T4 (0.41,) T5(0.41) and T7(0.40) have a significant difference with other treatments. While treatments T2 (0.66%), T3 (0.56%) and T6 (0.6%) were in a statistical group, control treatment (T1) and treatment T7 had the highest nitrogen concentration in pistachio leaves. Leaf Fe content in the different treatments was more than twice the optimum level (more than 200 mg kg-1), but Zn content in all treatments was severely low (less than 15 mg kg-1) and the plant was deficient in zinc. In terms of copper content, except the T5 and T6, the other treatments were optimal. Manganese content of all treatments was about 30% to 50% lower than optimum. In general, the results indicated that integrated plant nutrition (application of organic fertilizer along with chemical fertilizers) is a suitable solution to manage plant nutrition and reduce the use of chemical fertilizers.

Soil entities depends on its physical, chemical, and biological characteristics. Soil organic carbon (SOC) stocks is one of the main factors whose variations affect all these parameters. So, this study was performed for mapping the coefficient of variations (CV) of SOC stocks in some parts of the Simineh Roud watershed. Soil sampling performed using the Latin Hypercube method (cLHm) at 210 points from 0 to 30 cm of the soil surface, and the organic carbon was measured, then SOC stocks was calculated. In the next step, using Random Forest (RF) model the effective parameters were calculated (in this step, to model the SOC stocks, standardized spectral reflectance index and extracted data from digital elevation model were used). Finally, RF model was performed 100 times, as well as mapping of the values of upper (95th %), lower (5th %), and average SOC stocks for each pixel with a spatial resolution of 30 × 30 m was obtained. To obtain the CV with a confidence coefficient of 90%, the percentile of 95% and 5% were subtracted. The CV was obtained by dividing it by the mean. The results showed that the accuracy coefficient (R2) for modeling SOC stocks by the RF model was 0.81 and the mean accuracy coefficients including RMSE and MAE were 0.44 and 0.34 (kg/m2), respectively. Also, the results of CV mapping for the amount of SOC stocks in the study area showed that the amount of variation of this parameter varies between 3.9- 55%. Based on the results of the CV mapping of the study area, the most and lowest variations were observed in dry farming and grasslands, respectively. Probably, continuous cultivation and low return of organic matter in dry farming have increased the CV of SOC stocks in dry farming use.

Nowadays, given the human need for water, efforts to reach sustainable water resources are essential and important. The purpose of this study was to investigate the effect of water structures construction on the conservation and optimal management of water resources in Nashar basin. For this purpose, by field survey, the specifications of the construction structures and information on water resources in the area, including wells, springs and qanats, were collected. Information on water resources was obtained from the Hamedan Regional Water Department before the construction of the structures. The results showed that 856 small water structures were constructed in the watershed, of which 660 were mortar-clad inland structures, 4 were inland-china structures and 192 were gabion structures. The volume of reservoirs created by the implementation of these structures is equal to 50936 cubic meters, of which 29502 cubic meters have been filled and the empty volume that can currently reduce floods is 2143434 cubic meters. The total discharge of the three springs control watershed before the construction of the structures was 1.8 liters per second, which after construction has reached 2.15 liters per second. The average water height of wells in the region has decreased from 11 meters before ground construction to 9 meters after construction. Also, the total discharge of active qanats in the area before construction was 32.5 liters per second, which has reached 38.5 liters per second after construction. Therefore, the impact of the construction of water structures is positive and has led to an increase in water resources in the region.

Awareness about spatial distribution of soil properties plays an important role in the system of crop growth and yield in the agricultural field. In this regard, genetic algorithm was used to increase the accuracy in spatial distribution of soil pHwhich combines the estimates of linear regression, gene expression programming (GEP) and geostatistics (kriging interpolation) with data related to some parts of East Azerbaijan province (Bonab,Maragheh and Ajabshir). The linear model of kriging interpolation had the minimum error. Gene expression programming and linear regression had the lowest and highest error for soil pH spatial distribution estimation, respectively, for example the mean square error, root mean square error, relative root mean square errordecreasing from linear regression to geostatistics was 47.67%,27.58%, 26.47% and scatter index and adopted mean absolute percentage error decreasing from linear regression to GEP was 23.8% and 37.03%, respectively. The use of genetic algorithm in combination method reduced the error of spatial distribution compared to the tree types of models, for example mean square error, root mean square error, relative root mean square errordecreasing from GEP to combination method was 23.33%, 11.76%,10%, respectively. The estimates of soil pH with combination method are in the alkaline range, which is consistent with the obtained data.  The minimum and maximum value of the absolute difference between measured and estimated data were at point in Bonab (0.09) and Ajabshir(0.25), respectively. The mean absolute percentage error of combination method was in acceptable range and this shows the efficiency of combination method for soil pH spatial distribution estimation.

Understanding the factors, conditions of occurrence, and development of landslides in order to assess and zoning the risk of its occurrence provides the possibility of achieving methods by which the dangers and damage caused by landslides can be prevented. The purpose of this study is to prepare a landslide risk potential map with AHP and Shannon entropy models in the Cherikabad watershed of Urmia. Initially, ninety-five landslide points were recorded using GPS through field visits and Google Earth. Layers of mean annual rainfall, slope degree, slope Aspect, elevation classes, land use, Lithology, distance to River, distance to road, distance to fault, distance to village, and normalized index of vegetation difference (NDVI) As factors affecting the occurrence of landslides in the basin were selected and maps of these layers were prepared in the GIS environment and digitized. After combining the layers of factors affecting the occurrence of landslide, the landslide risk potential map was prepared for two models of Analytic hierarchy process (AHP) and Shannon entropy. The results of preparing risk maps using the Areas Under the Receiver Operating Characteristic Curve with the area below the 99% significance curve showed that both models have good performance in evaluation. Shannon entropy model with 87.9% AUC and very good performance compared to AHP model with 70.6% AUC and a good performance class, has a higher accuracy in preparing the maps. According to Shannon's entropy model, 32% of the basin is located in high and very high-risk classes, which should be considered by the relevant authorities to implement relief measures.