نشریه آب و خاک
سال سی و هفتم شماره 1 (پیاپی 87، فروردین و اردیبهشت 1402)

Evaluation of plant models in agriculture has been done by many researchers. The purpose of this work is to determine the appropriate plant model for planning and predicting the response of crops in different regions. This action is made it possible to study the effect of various factors on the performance and efficiency of plant water consumption by spending less time and money. Since the most important agricultural product in Iran is wheat, so proper management of wheat fields has an important role in food security and sustainable agriculture in the country. The main source of food for the people in Iran is wheat and its products, and any action to increase the yield of wheat is necessary due to limited water and soil resources. Evapotranspiration is a complex and non-linear process and depends on various climatic factors such as temperature, humidity, wind speed, radiation, type and stage of plant growth. Therefore, in the present study, by using daily meteorological data of Urmia, Rasht, Qazvin, Mashhad and Yazd stations, the average daily evapotranspiration values based on the results of the FAO-Penman-Monteith method are modeled and the accuracy of the two methods temperature method (Hargreaves-Samani and Blaney-Criddle) and three radiation methods (Priestley-Taylor, Turc and Makkink) were compared with FAO-56 for wheat.

The present study was conducted to evaluate the accuracy and efficiency of the AquaCrop model in simulation of evapotranspiration and biomass, using different methods for estimation reference evapotranspiration in five stations (Urmia, Qazvin, Rasht, Yazd and Mashhad). Four different climates (arid, semi-arid, humid and semi-humid) were considered in Iran for wheat production. The equations used to estimate the reference evapotranspiration in this study are: Hargreaves-Samani (H.S), Blaney-Criddle (B.C), Priestley-Taylor (P.T), Turc (T) and Makkink (Mak). Then, the results were compared with the data of the mentioned stations for wheat by error statistical criteria including: explanation coefficient (R2), normal root mean square error (NRMSE) and Nash-Sutcliffe index (N.S).

The value of the explanation coefficient (R2) of simulation ET and biomass in the Blaney-Criddle method is close to one, which shows a good correlation between the data. The NRMSE and Nash-Sutcliffe values for both parameters and the five stations are in the range of 0-20 and close to one, respectively, which indicates the AquaCrop model's ability to simulate ET and biomass. On the other hand, the value of R2 in the Hargreaves-Samani method for biomass close to one, NRMSE in the range of 0-10 and Nash-Sutcliffe index is more than 0.5, which indicates a good simulation. The NRMSE index in the evaluation of ET and biomass wheat is excellent for the Blaney-Criddle method and about Hargreaves-Samani for ET is poor and for the biomass is excellent.The Turc method with NRMSE in the range of 0-30, explanation coefficient close to or equal to one and a Nash-Sutcliffe index of one or close to one can be used to simulate ET and biomass at all five stations. Also, for biomass simulation, Priestley-Taylor and Makkink methods have acceptable statistical values in all five stations.Based on the value of explanation coefficient (R2) of estimation ET and biomass wheat for radiation methods, the correlation between the data in all three radiation methods is high. Percentage of NRMSE index of Makkink method for wheat in ET evaluation in Qazvin station is poor category and in Urmia and Rasht is good and in Mashhad and Yazd is moderate and about biomass in all five stations (Qazvin, Rasht, Mashhad, Urmia and Yazd) is excellent category, the error percentage of Priestley-Taylor method for wheat in ET evaluation in Yazd station is good and the rest of the stations is poor, about biomass is excellent in all five stations (Qazvin, Rasht, Mashhad, Urmia and Yazd). The error rate of Turc method for wheat in ET evaluation in Urmia, Rasht and Mashhad stations is good and in Qazvin and Yazd is poor and about biomass is excellent in all five stations (Qazvin, Rasht, Mashhad, Urmia and Yazd).

According to the results obtained using Blaney-Criddle method with R2 value close to one, NRMSE in the range of 0-20% (excellent to good) and Nash-Sutcliffe index close to one and Turc method with R2 value close to one, NRMSE in the range of 0-10% (excellent) and Nash-Sutcliffe index close to one was showed a good accuracy of AquaCrop model in simulation of evapotranspiration and biomass with these methods of estimation of evapotranspiration compared to other methods.

Determining the capture zone of water resources is a strategic approach proposed at the national level of water resources management in Iran. One of the important actions for this purpose is protection of karst water resources, which are considered one of the vital sources for supplying water due to the widespread karst formations in this country and the limitation of groundwater resources in alluvial aquifers. Generally, water flows out through the springs in the karst system. The land area where the water contributes to the spring is called the spring's capture zone. The study and analysis of the recession curve of the springs, the area extending from a discharge peak to the base of the next rise, along with the other physical characteristics of springs such as electrical conductivity is a useful indicator for getting knowledge about the condition of the catchment area and other properties of the heterogeneous karst terrain. In estimating the water budget, unlike the non-karst areas where the surface runoff or the outflow is considered the main factor in the estimated water budget, the recharge component is an important factor in the karst domain. The difference between hydrogeological and hydrological (topographic) catchments is one of the obvious features in karst landscapes. The identification of these basins or their boundaries is possible by combining geology and topography information. Soufiyan Cement Company in the vicinity of Chelleh Khanehe Olya spring located in Moro Mountain is associated with the creating social problems due to the expansion of mining activities and the negative impact on spring water in this area. Therefore, this study aims to determine the catchment area and the capture zone of the Chelleh Khanehe Olya spring by determining the protective boundary for the extraction of limes by the Soufiyan cement factory to prevent the negative impact of this factory on the spring.

In this research, the hydrograph of the recession curve related to a rainfall event has been analyzed by taking into account the mean monthly discharge rate of spring to determine the sub-regimes of diffuse and conduit flow by employing the following equation:Qt=Q0e-αt (1)Where Qt is the discharge rate at time t, Qo reveals the discharge at the initial time, and α is a recession coefficient.In addition, The Qmax/Qmin ratio has been calculated to estimate the flow type and the degree of karstification in the catchment area.In the next step, to determine the Chelleh Khanehe Olya spring catchment area and its capture zone, spring hydrogeological boundaries were determined and investigated using the SCS method and estimating the area's water budget. Due to the lack of sufficient rainfall and groundwater discharge information in this region, the water budget for a given period (2019-2020) has been computed indirectly by measuring the monthly discharge rate from the selected stations. After collecting the required data, the following equation developed by Milanovich (1989) has been used to estimate the water budget as follows:P=E+R+I   (2)Where P, E, R, and I denote precipitation (P), evaporation at the basin level (E), runoff (R), and recharge to the aquifers (I). All the parameters are in mm units.

Analyzing the variation of electrical conductivity along with the discharge rate indicates that by decreasing the discharge rate from 2.5 l/s to 8.1 l/s, the electrical conductivity increase from 463 µs/cm to 500 µs/cm, reflecting an increase in the volume of the reservoir, the dilution of the aquifer. The hydrograph recession curve during 2019-2020 indicated two laminar and turbulent sub-regimes. Micro regimes α1 (01.002) and α2 (0.013) represented that the dominant system of karst development in the region is diffuse. The high density of fractures and the lack of purity of lime are the main reasons for the weak development of the karst fracture in the region, which the Chelekhaneh Alia spring recession curve analysis,  maximum to minimum ratio of discharge, and karstification coefficient confirmed this issue. Determining the catchment basin using geological, hydrogeological information, and water budget showed that the hydrological and hydrogeological boundary of the spring is different. The protected zone of Chelekhane Alia spring, which includes the total hydrogeological basin and the Cretaceous limestone area below the level of the spring, was estimated to be about 184,000 square meters (18 hectares). According to the findings of this research, Sufian Cement Factory does not have the right to enter the hydrogeological boundary to extract limes, and on the other hand, to prevent the water level from decreasing due to the excessive extraction of lime as a result of the excavation depth reaching the level of the water table, it suggests to extract from the unsaturated part of the aquifer (unsaturated limes) to prevent the flow rate of Chele Khana spring from decreasing and even drying it up.

Analyzing the discharge rate, electrical conductivity, hydrograph recession curve, and its recession coefficient(α=0.002), revealed that the dominant flow in the system is diffuse, which results from the high density of fractures and region lithology consisting of impure cretaceous limestone. Since the result revealed the inconsistency between hydrological and hydrogeological boundaries, the geological profile of the site was prepared and the spring of the catchment was estimated. Based on the findings of this research, the Chelle Khanehe Olya capture zone consists of the hydrogeological area, obtained from the groundwater budget estimation, and the protective boundary for the limestone below Cheleh Khaneh Olya spring (the unsaturated zone of the area's limestones), which covers an area of about 18 hectares.

Crude oil is a complex combination of many hydrocarbon and non-hydrocarbon compounds, including heavy metals, which affect the physical and chemical properties of the soil, cause the soil particles to stick and connect and then cause the soil to become stiff and impenetrable. Contamination of soil with petroleum hydrocarbons is a significant environmental problem, which has received remarkable attention in recent decades. Petroleum hydrocarbons are resistant and hazardous pollutants. Some petroleum hydrocarbons such as benzene are mutagenic and carcinogenic materials for humans. There are many physical and chemical methods to remediate oil-contaminated soils. Phytoremediation is a relatively new technology for refining contaminated soils in which resistant plants are used to remove or reduce the concentration of inorganic, radioactive, and organic pollutants, especially petroleum compounds, from the environment.

Sufficient amounts of about 50 kg of soil contaminated with petroleum hydrocarbons were collected from regions (0-30 cm soil depth) adjacent to the oil wells west of Kermanshah province. Uncontaminated soil samples were also taken from sites at the lowest distance to the contaminated sites. The aim of this study was to compare the efficiency of different plants to remove total petroleum hydrocarbons from oilfield soils. In this study, after determining the total amount of petroleum hydrocarbons, the contaminated and uncontaminated soils were mixed in 4 treatments with different weight ratios (0, 10, 25, and 35%). This experiment was established as completely randomized design with 3 replications for 6 different plants (Barley, Grass, Alfalfa, Hemp, Camelina, and Vicia ervilia). One treatment without plant was considered to remove soil matrix effects on petroleum hydrocarbon concentrations. Plants were harvested at the end of their growing season (90-120 days). Soils and plant samples from the experimental pots were analyzed for their important properties (including some physiological characteristics of the plants, as well as the percentage of reduced petroleum hydrocarbons in the soils). The gravimetric method was used to determine the concentration of petroleum hydrocarbons in the soil. After measuring the properties of the soil and plant, the normality of the data was checked by the Anderson–Darling test, and the homogeneity of the variance of the treatments was checked by using Levene's test. Analysis of data variance was done using ANOVA and average data comparison was done using LSD test at 5 and 1 percent probability levels (SAS 9.4 and SPSS 26).

In general, the growth of most plants showed a decreasing trend in proportion to the increase in soil pollution levels. However, the growth decline rates of different plants were not similar. Camelina was very sensitive to oil pollution and the plant could not tolerate pollution even at 10% level. After camelina, alfalfa was highly sensitive to oil pollution. The highest dry weight of the aerial parts of the hemp plant in the soil without oil contamination was observed at the rate of 111.22 grams in the pot. The leaf area of all studied plants in contaminated soils decreased compared to the control treatment (without contamination) so with the increase in the percentage of contamination, the leaf area of the plants was significantly reduced. The highest amount of leaf surface was observed in unpolluted soil and in the hemp plant. Except for the Camelina plant, which was completely destroyed at different levels of pollution, the rest of the plants showed a noticeable decrease in growth. The total petroleum hydrocarbons in soil were measured again 120 days after the start of cultivation, and its difference with the total amount of petroleum hydrocarbons at the beginning of cultivation was determined as the reduction of petroleum hydrocarbons and reported as a percentage. According to the mean comparison results, the percentage of reduced petroleum hydrocarbons was not significantly different among cultivated and non-cultivated treatments, although, it was significantly affected by soil pollution levels. Since all the studied soils contained natural bacteria and were not sterilized, the eliminated part of petroleum hydrocarbons is probably decomposed and removed by native bacteria in the soils. Therefore, the strengthening of native bacteria in these soils may increase the decomposition and degradation of petroleum hydrocarbons.

The results of this research show that the presence of petroleum hydrocarbons in the soil caused a decrease in growth and other physiological characteristics in all studied plants. Although the Camelina was able to germinate in soils contaminated with petroleum hydrocarbons, the presence of these pollutants in the soil prevented the optimum growth of the plant, so its use in subsequent studies of phytoremediation of oil-contaminated soils, was not recommended. The results showed that there is no statistically significant difference between cultivated and non-cultivated treatments at different pollution levels, and the reduction of the total petroleum hydrocarbons in the soil was probably done by native microorganisms in the soil. It is recommended to take into consideration the efficiency of the plant species used, the type of polluting hydrocarbons, and the duration of contamination in future research to obtain better results.

Land suitability analysis and land use mapping are one of the most practical applications of Geographic Information Systems in land resource management. Complexities in soil have briefly limited studies on how it functions (Karlen, 2008). There are many methods from different centers including food and agriculture organizations (FAO), to evaluate land suitability. These methods are based on the characteristics of the land and the needs of the plant. Soil quality indicators are a set of measurable soil characteristics that affect crop production or the environment and are sensitive to land use change, management or conservation operations. (Brejda, 2000; Aparico and Costa, 2007). As a result, there is a global need for environmental issues, improvement of soil quality assessment methods for sustainable agricultural development and recognition of the sustainability of soil management and land use systems. Until now, various methods have been used to collect data, measure and evaluate soil quality, and laboratory analysis is the most common method, which has the advantage of being easy to use and characterizing and the quantitative characteristics of the test on different soil quality indicators (and Wang, 1998 Gong). Criteria for soil quality indicators should be a set of physical, chemical, biological characteristics or a combination of them (Doran and Parkin, 1997).

In the present study, the qualitative assessment of land suitability was investigated using fuzzy and parametric hierarchical analysis process models for the irrigated wheat and alfalfa crops. Soil characteristics, climatic conditions, topography and accessibility were selected based on the Food and Agriculture Organization framework and expert opinions. The interpolation function was used to plot values to points in terms of quality/ terrain characteristics for the type of operation and the evaluation was performed based on parametric and fuzzy analytical hierarchy process models. The process of evaluation is based on the FAO qualitative land evaluation system (FAO 1976a, b, 1983, 1985), which compares climatic conditions and land qualities/characteristics including topography, erosion hazard, wetness, soil physical properties, soil fertility, and chemical properties, soil salinity and alkalinity with each specific crop requirements developed by Sys et al. (1991a, b, 1993). Based on morphological and physical/chemical properties of soil profiles some 10 land units were identified in the study area.Climate data related to different stages of wheat growth were taken from ten years of meteorological data of the region (2007-2017) and the climatic requirements of the crop were extracted from the Table developed by (Sys et al., 1993). An interpolation technique using the ArcGIS ver 10.3 helped in managing the spatial data and visualizing the land index results in both models for preparing the final land suitability evaluation maps. The FAHP method and (Chang, 1996) method, which is a very simple method for generalizing the hierarchical analysis process to the fuzzy space, was used in order to assign weight to the criteria through. This method is based on computational mean of the experts’ opinion and the time normalization method and the use of triangular fuzzy numbers. A pairwise comparison matrix has been made fuzzy based on the experts’ opinion and using the triangular fuzzy numb. After calculating the weights of the criteria in the present research through the FAHP method, the entire criteria maps were overlaid through the use of the GIS function and the suitability maps were prepared for the main criteria. The main suitability maps went through weight overlaying eventually and the final map of suitability for wheat and alfalfa cultivation was produced.

The results of this study showed that the FAHP was an efficient strategy to increase the accuracy of weight allocation to criteria that affect the analysis of ground fit. The inability of conventional decision-making methods to account for uncertainty paves the way for the use of fuzzy decision-making methods. One of the drawbacks of the AHP is its inability to account for the uncertainty of judgments in pairwise comparison matrices. This defect is compensated by the FAHP method. Instead of considering a specific number in a pairwise comparison, a range of values in the FAHP is used for uncertainty for decision makers. The present research method can be useful for prioritizing lands, improving exploitation, conserving resources, and creating sustainable management. The results of this study, considering the main criteria of cultivation in the study area and the opinion of domestic experts, can provide useful insights into choosing the appropriate cultivation pattern in the region. The use of different fuzzy AHP methods as well as comparing the results of different fuzzy AHP methods in future research is recommended.

Conventional cropping systems, dependent on heavy application of chemical fertilizers, are not ecologically and environmentally sustainable; they are a threat for soil and water quality and, in consequence, for plant and human health. Nitrogen fertilizers are heavily applied in conventional leaf vegetable production systems to obtain maximum growth and yield. However, the excess nitrogen tends to accumulate in leaf vegetables in the form of nitrate, which pose serious human health hazards. Therefore, to supply nitrogen from non-chemical sources, such as organic amendments, is a sustainable practice for production of leaf vegetables. Spent mushroom substrate (SMS), which is the remaining material after the harvest of mushroom, is produced in large quantities (5 kg SMS for 1 kg of mushroom) and is enriched with organic carbon, N, P, K, and micronutrients. Therefore its reuse as a soil amendment not only provides essential elements for plants but also improves soil quality. Similarly, incorporation of green manures, especially legume green manures, into cropping systems is a sustainable practice for soil fertility and soil quality management. In this study, we aimed to investigate the short-term effects of two soil organic amendments (spent mushroom substrate and alfalfa residues) and their combination, in comparison to inorganic N fertilizer (urea), on soil fertility, and selected essential nutrients, and nitrate accumulation in a leaf vegetable, test plant (spinach).    

A one-season pot experiment was led in a randomized complete block design with three replications in experimental greenhouse of Bu-Ali Sina University. Treatments were comprised of two levels of spent mushroom substrate (SMS-1: 2% SMS, and SMS-2: 5% SMS), two levels of alfalfa green manure (AGM-1: 1% AGM, and AGM-2: 3% AGM); two levels of the mixture of SMS and AGM (SMS+AGM-1: 1% SMS plus 0.5% AGM; and SMS+AGM-2: 2.5% SMS plus 1.5% AGM);  two levels of urea fertilizer (U-1; 120 kg/ha, and U-2: 360 kg/ ha); and control. Selected properties of the initial soil and both organic amendments were determined. Spinach (Spinacea oleracea L.) was seeded as leaf vegetable, test plant in early autumn 2017. After ten weeks, spinach were harvested and the aboveground and root dry weights were determined. Moreover, the content of NO3-, P, Fe, Cu, Zn, and Mn in edible parts were measured. Soil samples were analyzed for EC, pH, total organic carbon, available P and K, and alkaline phosphatase activity.

All soil quality indicators were significantly affected by the treatments. TOC was significantly increased in all of the organic treatments compared to the chemical and control treatments. The maximum increase in TOC was observed in SMS-2, SMS+AGM-2, and AGM-2 treatments, compared to the control (134, 130 and 107%, respectively). A decreasing trend in TOC was detected in the high level of urea treatment (U-2) compared to the control which can be explained by the faster decomposition of soil organic matter in the presence of higher inorganic N inputs. Both organic amendments (in both levels) and the higher level of urea (U-2) decreased soil pH compared to the control. The initial low pH of SMS (5.6) and AGM (6.2), in the first case, and oxidation of urea to nitrate, in the latter, may justify this observation. In contrast, soil EC increased under the both organic amendments relative to the control and U-1 treatments. Moreover, the adverse effect of SMS on soil salinity was greater than AGM due to the initial differences in their corresponding source materials (5.8 vs. 3.0 ds/m). Available K was significantly increased in the second level of all organic treatments compared to the chemical and control treatments. As for available P, all organic treatments, except AGM-1, led to the significantly higher P than the chemical and control treatments. It is reported that organic materials compete with mineral particles for P adsorption and increase its availability. Moreover, all organic treatments, except SMS-1, significantly increased phosphatase activity compared to the chemical and control treatments. This could contribute to the mineralization of organic materials and increase available P.   Spinach yield was affected by the experimental treatments. The highest increase in shoot dry weight occurred in SMS+AGM-2 and AGM-2 treatments by 235 and 230%, respectively, compared to the control. Moreover, the second level of all organic treatments as well as the first level of SMS plus AGM treatment significantly increased yield compared to the chemical treatments. Spinach P content was significantly higher in all organic treatments, except SMS-1 and AGM-1, compared to the chemical and control treatments. Organic amendments, by decreasing the surface adsorption of P and increasing soil microbial biomass, promote the availability of P for plants. Spinach nitrate content ranged from 265 (in control) to 7807 mg/kg (in U-2). According to the critical limit of nitrate in spinach (4000 mg/kg) presented by European Union, only U-2 treatment led to over-accumulation of NO3-. The two levels of AGM treatments and SMS+AGM-2 resulted in the comparable amounts of nitrate as the recommended amount of urea (U-1). A narrow variation in spinach Cu content (from 6.1 in SMS+AGM-2 to 9.8 mg/kg in AGM-2), all within the standard range reported for plants (5-20 mg/kg), was observed among the treatments. Spinach Fe content was increased under all organic treatments relative to the control, although some disparities were not significant. The lowest Fe was detected in U-2. It is reported that excessive N may diminish root growth and, in turn, reduce nutrient uptake. Spinach Zn content varied from 44.8 (in control) to 71.5 mg/kg (in SMS-2), which was close to the higher limit of standard range (20-50 mg/kg) reported for vegetables, but lower than toxic concentration range (200-400 mg/kg). Spinach Mn content varied from 17.4 (in control) to 32.1 mg/kg (in SMS-2), which was close to the lower limit of the standard range (40-400 mg/kg) reported for plants.

The most appropriate treatments in view of improving yield and soil quality (i.e., optimum TOC, P, and K; and lower EC) as well as tolerable nitrate accumulation were SMA+AGM-1 and SMS-1 in decreasing order. These treatments are preferred over the chemical treatments (U-1 and U-2).

One of the most fundamental global environmental challenges in the past two decades has been the issue of soil pollution and degradation. Soil, as an important environmental element, has played a significant role in food production, human health, and living organisms, but various factors, by both human and naturally have destroyed it. The exploitation of natural resources with activities such as mining and quarrying, as an anthropogenic action (caused by human activities), is one of the most important factors of human intervention in nature and also one of the environmental hazards of soil degradation, which has caused the spread of desertification. Sangan iron mines in Khaf city are the largest mines in the northeast of Iran. According to the geomorphological disturbances caused by the activity of Khaf iron ore mines and the geological composition of the region, there is a potential for causing pollution and destroying the soil around the mine. This research was conducted with the aim of evaluating the impact of mining activity on concentration of some heavy metals such as lead, iron, nickel, copper, and arsenic in the soil around the iron ore mine in Sangan area of Khaf city in Khorasan Razavi province. Realizing the polluted hotspots due to the concentration of heavy metals, as one of the important signs of soil pollution and the spread of desertification, is one of the goals of this research, and the results can be effective in making appropriate management decisions to prevent soil pollution and further destruction.

In order to conduct this research, 60 soil samples were systematically taken from a depth of 0-20 cm from two areas adjacent to the mine and control. The concentration of aqua regia extracted heavy metals was measured using an inductively coupled plasma-optical emission spectroscopy (ICP-OES). In the first stage, the results were descriptive, and in the second part, after performing tests related to the normality of the data, they were inferential using the parametric independent t-test and Pearson's correlation coefficient in the statistical environment of the SPSS software. In order to quantify the level of soil contamination with heavy metals, geochemical indices including contamination factor, pollution load index, and enrichment factor were used. The pollution load zoning map of the area adjacent to the mine as well as the average enrichment map of lead and arsenic elements were prepared using the inverse distance weighting interpolation method in the ArcGIS environment.

The results of this research showed that the average concentrations of arsenic, copper, nickel, lead, and iron elements in the area near the mine were 12.71, 25.54, 34.59, 48.64, and 38860 mg/kg and in the control area were 8.57, 15.97, 32.13, 16.96, 29110 mg/kg, respectively. The comparison of the coefficient of variation (dispersion criterion) of heavy metals showed that the highest coefficient of variation among the metals is related to the lead with a value of 42.8%, as well as the coefficient of variation for other metals in the area adjacent to the mine also has a relatively high dispersion compared to the control area. In addition, it was found in all elements except for nickel (p<0.05), which indicates a significant difference in the average concentrations between the control area and the area adjacent to the mine. The correlation between lead element and nickel, copper and arsenic variables was inverse and there was a positive and very strong correlation between iron and copper and nickel with values of 0.8 and 0.76 respectively and nickel and copper with values of 0.82. The pollution coefficient of the lead elements in the area adjacent to the mine showed moderate to significant pollution levels, which is more polluted than other elements. The pollution load in the area near the mine showed that the value of this index was greater than one in the samples closer to the mining areas, which indicates the high contamination of the surface soil with these elements. Lead and arsenic elements in the area adjacent to the mine showed moderate to relatively intense enrichment. From the examination of all the pollution indicators used in this research, as well as the positive and very strong correlation between copper and nickel, the presence of these two elements in the soil of the study area showed no pollution. The comparison of the results obtained from the analysis of soil samples in the two areas of the control and adjacent to the mine showed an increase in the concentration of heavy metals (iron, lead, and arsenic, copper) in the area adjacent to the mining.

The results obtained from the analysis of soil samples and pollution indicators in the two control areas adjacent to the Sangan iron ore mine in Khaf city showed that the presence of iron ore industrial and mining sites in the study area and the spread of its wastes and tailings by seasonal and local winds, as well as the activities of humanity and the spread of these pollutants to other areas, can be one of the main reasons for the increase in the concentration of metal pollutants in the soils of this region.

Monitoring the changes in physical and hydraulic properties and stability of growth media due to root growth effects and wetting and drying cycles is important. Wetting and drying cycles can probably change physical characteristics, availability of water, air and nutrients for the plant and, as a result, might affect the growth and yield of the greenhouse plants. The growth period greatly affects the physical characteristics of the growth substrates; therefore, the watering of growth substrates should be managed according to these changes to avoid improper irrigation.

In this study, 14 growth media were prepared from individual substrates with different volumetric ratios. In order to evaluate the changes of growth media over the time (i.e., during consecutive irrigation events) in the greenhouse, 10 wetting and drying cycles were applied on the growth media in the lab. Several physical indicators including easily available water (EAW), air after irrigation (AIR), water buffering capacity (WBC) and water holding capacity (WHC) of the growth media were determined before and after the wetting and drying cycles. Besides, the subsidence, decrease of mass and decomposition of the growth media were determined over the time. Total porosity (TP), bulk density (BD), particle density (PD), pH and electrical conductivity of the mixtures were measured as well.

The pH values in the growth media varied from 5.72 to 6.94. The maximum pH value was related to sawdust- sugarcane bagasse biochar produced at 300◦C vermiculite-zeolite, and wheat straw-vermiculite substrates, and the minimum value was related to the cocopeat-perlite substrate. The values of EC in the growth media varied from 0.21 to 1.43 dS m-1. The highest and lowest EC values among the growth substrates were related to date palm bunches-vermiculite-rockwool and rockwool (0.2)-perlite substrates, respectively. The bulk density (BD) values of the growth media varied in the range of 0.163-0.401 Mg m-3. The values ​​of total porosity (TP) of the growth media varied in the range of 64.8-82.8%v/v. The highest TP was related to the cocopeat-perlite substrate. The TP values ​​of most of the substrates were greater than 70%v/v. The average values of EAW in the growth substrates ranged from 0.123 to 0.272 cm3 cm-3. The highest EAW was related to the sawdust-sawdust biochar produced at 500 ◦C vermiculite-zeolite substrate. The application of wetting and drying cycles increased EAW in most of the growth media. Therefore, it can be stated that the time had a positive effect on the EAW in most of the growth media. The average values of AIR before and after the application of wetting and drying cycles for the growth media varied in the range of 0.063-0.240 cm-3 cm3. The highest value of this indicator was observed in the sawdust-date palm bunches biochar produced at 300◦C vermiculite substrate. In all substrates (with the exception of the sawdust-sawdust biochar produced at 500◦C vermiculite-zeolite), the AIR increased after wetting and drying cycles. The range of WHC values before and after applying wetting and drying cycles was 0.453-0.699 cm3 cm-3. The highest WHC belonged to the wheat straw-vermiculite substrate. The WHC values of five growth media, including cocopeat-perlite, decreased due to the application of wetting and drying cycles, and the WHC values of nine growth media decreased. The most stable substrate after the wetting and drying cycles was rockwool-sawdust-vermiculite. The effect of time on the quantity of WBC was positive, so that with the application of wetting and drying cycles, the WBC values of most of the substrates increased. In all substrates, subsidence and dry weight reduction were observed after the wetting and drying cycles. These changes were low for the substrates with a high volumetric ratio of inorganic materials. The least change among the growth substrates in terms of decomposition (dry weight reduction) was related to the completely inorganic substrate rockwool (0.1)-perlite (%0.17). The most stable substrate in terms of subsidence after wetting and drying cycles was the rockwool-sawdust-vermiculite, which has a large volumetric ratio of individual inorganic substrates. The highest subsidence was observed in the substrates containing wheat straw (wheat straw-vermiculite and date palm bunches biochar produced at 300◦C wheat straw-vermiculite). The organic matter content in all the growth substrates decreased over time (after wetting and drying cycles). The decrease of organic matter in the substrates can be related to the decomposition of organic materials as a result of wetting and drying cycles.

The BD, TP, EAW and WHC of the majority of growth media were in the optimal ranges and for some mixtures even better than cocopeat-perlite. Wetting and drying cycles could affect the growth media through several processes such as decomposition of organic compounds, displacement and rearrangement of particles, fragmentation of particles, shrinkage, hardening and subsidence. The growth media with a high percent of organic substrates were unstable as compared with those containing a high proportion of inorganic substrates. In general, the wetting and drying cycles increased the frequency of micropores in the growth media. The wetting and drying cycles positively affected EAW, WHC, AIR and WBC of most growth media. These findings imply that wetting and drying cycles may improve the growth media according to the studied extensive variables. However, it is necessary to study the intensive variables such as hydraulic conductivity, oxygen diffusion and pore tortuosity in the growth media for better evaluation of the impact of wetting and drying cycles as well.

The relative preference and the cation exchange capacity of the exchanger are among the important and determining factors in the adsorption and retention of cations. Studies have shown that factors such as valency, the size of the hydrated radius or the relative hydration energy of ions, the type of clay mineral, the concentration of the solution phase, the amount of organic matter, the structural characteristics, and the charge density of the exchanger determine the preferential adsorption of cations in the soil. The aims of this study were: 1) to investigate the effect of contact time, adsorbent dose, and pH on potassium selectivity by bentonite in binary systems including K-Ca, K-Mg, and K-Na based on Gapon, Vanslow, and Gaines-Thomas equations and 2) to investigate the potassium adsorption isotherms by bentonites saturated with calcium, magnesium, and sodium.

To saturate bentonite, 1 M solutions of calcium, magnesium, and sodium chloride were separately used. The effects of contact time (10-1440 min), adsorbent dose (0.1-2 g), and pH (3-9) on potassium adsorption and selectivity by bentonites saturated with calcium, magnesium, and sodium in binary systems were investigated. In these experiments, 20 mL of a solution containing 24 meq L-1 of potassium and 6 meq L-1 of the competing cation (Ca, Mg, or Na) were added to the adsorbent. The selectivity coefficients of Gapon, Valselow, and Gaines-Thomas were calculated. Isotherm experiments were also performed to evaluate the effect of different equivalent fractions of potassium (0.1, 0.2, 0.4, 0.6, 0.8, 0.9, and 1) and the competing cation in the solution phase on potassium adsorption. Simple linear, Freundlich, and Temkin equations were fitted to the isotherm data.

This study results showed that the adsorption of potassium by Ca-, Mg-, and Na-bentonites increased with increasing contact time and reached its highest value in 24 hours. The pseudo-second-order kinetic equation was better able to describe the process of potassium adsorption by bentonites over time than the pseudo-first-order equation. Potassium adsorption by Mg- and Na-bentonites had a downward trend with increasing the absorbent dose in the range of 0.1-2 g, while Ca-bentonite showed the highest adsorption of potassium in the dose of 0.2 g. With increase in pH, the percentage of potassium adsorbed from the solution phase increased; and reached its maximum value at pH 9. The amount of potassium adsorption by Mg- and Na-bentonite in all pHs was almost the same and at the same time more than Ca-bentonite. The interesting result of this research was that the behavior of Mg-bentonite was more similar to Na-bentonite than to Ca-bentonite. An increase in the negative charge of aluminosilicates with an increase in pH can occur due to the loss of protons by silanol and aluminol groups. The selectivity coefficients of Gapon, Vanslow, and Gaines-Thomas changed under the influence of contact time, adsorbent dose, and pH. Comparing the results of the investigation of the mentioned factors with the results of the selectivity coefficients showed that these coefficients cannot be a definitive criterion for judging the preference of one cation over another cation for adsorption in exchange sites. The isotherm experiment indicated that the amount of potassium adsorption in the solid phase increased with the increase of the potassium equivalent fraction in the solution phase; so the maximum adsorption was observed at the highest initial concentration of potassium (30 meq L-1, which corresponded to the equivalent fraction of 1). The linear adsorption coefficient in the simple linear equation (Kd) showed that potassium adsorption by Na-bentonite was higher than the two others. The highest amount of Kd, 56.0 L kg-1, and the lowest value, 11.9 L kg-1, were obtained for bentonites saturated with sodium and calcium, respectively. The parameter bT, the heat of exchange in the Temkin equation, was estimated to be 4.5, 5.0, and 19.1 (J mol-1) for bentonites saturated with sodium, magnesium, and calcium, respectively. Three simple linear equations, Freundlich, and Temkin were able to describe the adsorption process well. However, based on the highest value of the coefficient of determination (R2) and the lowest value of the standard error (SE), it can be said that the Freundlich equation showed the best fit to the data.

The highest adsorption of potassium occurred at a contact time of 24 h, a dose of 0.1 g for Mg- and Na-bentonite and 0.2 g for Ca-bentonite and pH 9. The pseudo-second-order equation described well the kinetics of potassium adsorption by bentonites over time. The results showed that the behavior of Mg-bentonite was more similar to Na-bentonite than Ca-bentonite. The selectivity coefficients of Vanslow, Gaines-Thomas, and Gapon changed under the influence of contact time, adsorbent dose, and pH. The results revealed that it is not possible to definitely determine the preference or non-preference of a cation based only on selectivity coefficients. The isotherm experiment showed that the amount of potassium adsorption increased with the increase of the initial equivalent fraction of potassium in the solution. The highest value of R2 and the lowest value of SE were obtained for simple linear and Freundlich equations, respectively.

Nowadays, climate change is one of the human challenges in the exploitation and management of water resources. Temperature along with precipitation is one of the most important climatic elements and is one of the main factors in zoning and climatic classification. Due to location of Iran within the drought belt and proximity to the high-pressure tropical zone, this country has an arid and semi-arid climate and suffers from drought in majority of years. Therefore, temperature fluctuations and variability are important issues, and make the study of temperature changes a necessity. In the current study, four data mining algorithms in selecting predictors for downscaling of maximum temperature in Birjand synoptic station have been studied, compared and the superior algorithm has been introduced. As the number of large scale features are high, selection of machine learning algorithm will play as an important role in statistical downscaling of climatic variables such as maximum temperature. 

Today, the data set is such that many variables are used to describe the climatic phenomenon in environmental studies. As the number of data is huge, choosing the predictors is one of the most important steps in preprocessing machine learning. In this study, four machine learning methods including stochastic approximation of simultaneous turbulence (SPSA), Least Absolute Shrinkage and Selection Operator (LASSO), Ridge and Gradient Boosting Method (GBM) in selecting important features in downscaling of maximum temperature in Birjand synoptic station during the statistical period of 1961-2019 were studied and compared. It is a mechanism to find a combination of predictors that with a minimum number of predictors can produce an acceptable evaluation index in estimating the variable under study. For the present study, the weather information of Birjand Synoptic Meteorological Station has been prepared by the Meteorological Organization of Iran. In order to calibrate and validate the machine learning algorithms, 70% and 30% of the available monthly data, respectively, were allocated for this purpose. To conduct this research, coding in R-Studio environment and Caret and Fscaret packages were used. In this study, to evaluate the performance of the algorithms, three indices includes relative Nash-Sutcliffe Efficiency (rNSE), Volume Efficiency (VE) and Kling-Gupta Efficiency (KGE) were used.

Before using the algorithms in selecting large-scale predictors, the correlation between these variables and the maximum observational temperature at Birjand station was investigated. Large scale variables mslp, P1_v, P8_v, P8_u, P850 Temp, with a maximum correlation temperature of 0.6 showed that the correlation is acceptable given the complexity of the climate change phenomenon. In addition, these results show that all the algorithms used the important factors including F1, F2, F15, F16, F18, F20 and F26 by more than 50% and the first variable (mean pressure at the ocean surface) was the most important parameter in downscaling of maximum temperature. Also, the highest importance was for P1_v and the lowest value related to P5_u, as 73.2% and 15%, respectively. Violin plots of downscaled maximum temperature in validation step of different algorithms along with the observed maximum temperature in Birjand synoptic station in each of the algorithms showed that the values of the first and third quartiles in the output data of SPSA algorithm compared to other algorithms were closer to the observed data. According to the evaluation criteria, SPSA algorithm has a higher performance than other algorithms in reproducing the maximum monthly temperature values in Birjand synoptic station. Also, based on the volumetric efficiency evaluation criteria and relative Nash-Sutcliffe, GBM algorithm was more successful in selecting predictors than Ridge and LASSO algorithms. It is also observed that SPSA algorithm shows different results than other algorithms. In comparison of mean and variance of downscaled and observed maximum temperature, the results of t-test and F-test showed that SPSA algorithm has higher efficiency than other algorithms in regenerating mean and variance of observed maximum temperature in Birjand synoptic station at the 5% significance level.

The data used in this study included large scale atmospheric variables and the maximum observed temperature at Birjand station. The algorithms were used to select important predictors and the performance of these methods in the validation part. According to the results of this study, the highest importance among large-scale variables is related to P1_v and the lowest value is related to P5_u, the values of which were 73.2% and 15%, respectively. The SPSA algorithm also performs better than other algorithms in selecting predictors and consequently the maximum temperature.

Heavy rains often occur in small areas, but they may be the result of large-scale systems and their energy and moisture are provided from distant areas (Mohamadei et al., 2010). Therefore, identification of synoptic systems is of great importance in order to predict precipitation. Although rain has many positive effects on human life, heavy rain can cause one of the most dangerous and damaging natural disasters, namely floods. Every year, floods cause many human and financial losses in different regions of the world. Floods are more effective in vulnerable areas and cause the loss of human lives, damage to property and products, disruption of transportation and services, and other economic losses (Kheradmand et al., 2018). In March 2019, heavy rains occurred in Golestan province, which caused flooding in parts of this province, especially in the cities of Gonbad-Kavus and Aqqala. Most of this heavy rain and flood occurred in the Gorgan River basin. According to meteorological reports, the rain started from the night of 03.17.2019 and continued until 03.21.2019, although the heaviest rainfall occurred from the 03.18.2019. The volume of the flood was so great that the dams on the Gorgan River could not accommodate it. According to the reports of the regional water company of Golestan province, the flood entered the Bostan dam at 1 am on 03/19/2019, and after passing through it, entered the Vashmgir dam at 6 am, and then on 03.21.2019 entered the city of Aqqala. The damage of this flood was estimated at about 4800 billion Tomans, which includes damage to 17800 residential units, damage to farms, transportation infrastructure, 40% reduction in tourism, damage to industrial units, unemployment of about 3000 people, and damage to the nomads of the province. (Islamic Republic News Agency, 04.09.2019). Considering the heavy damage caused by the mentioned heavy rain and flood in Golestan province, it is necessary to identify and analyze the causes of its occurrence in order to plan and take the necessary measures to prepare and deal with such incidents.

The study area is Gorganrood watershed, most of this area is located in Golestan province. Golestan province is one of the northern provinces of the country and is located in the southeast of Caspian sea. In this research, in order to identify and analyze the heavy rain that occurred in Golestan province in March 2019, which led to severe flooding, several types of data were used (data from meteorological stations, NCEP/NCAR reanalyzed data, MODIS satellite images, GPM precipitation products). First, using the rainfall data of the synoptic stations located in the Gorgan River watershed, the time of heavy rainfall was identified, and then using the data of the aforementioned stations and several stations outside the basin, a rainfall zoning map was prepared. MODIS satellite images were also used to check the position of precipitation system and cloudiness of region. Using GPM satellite rainfall products called IMERG, which were extracted on a half-hourly basis, as well as the main synop reports of meteorological stations, which are reported on a six-hourly basis, the intensity of rainfall was investigated. In addition, the physical conditions of the basin were investigated using the topography and slope map of the basin prepared from the DEM layer of the region. In the following, using the reanalyzed data of the NCEP/NCAR database (National Center for Environmental Prediction - National Center for Atmospheric Research of the United States), synoptic maps including maps of land surface pressure, geopotential height of the upper atmosphere, Omega (indicates the speed of vertical movements of the atmosphere), wind direction and speed, moisture flux convergence function, frontal function, specific humidity, atmospheric precipitable water and Hoff-Müller diagram were drawn to identify the synoptic and dynamic factors of the mentioned precipitations.

The results of the present research in the analysis of flood factors can be summarized as follows:Survey of the topography and slope of the Gorganrood basin revealed that the physical conditions of the basin are such that the potential for flooding is high.The amount of rainfall in 24, 6 and a half hour intervals in the study area were investigated and it was shown that the rainfall occurred on March 17, 18 and 19, especially on March 18, in terms of the intensity of rainfall were very intense.Investigation of the state of the middle troposphere showed that the formation of the Rossby wave and the meridional expansion of one of its troughs, along with the creation of a positive vorticity that dominated the studied area on the seventeenth of March, are the main factors in the creation of a baroclinic atmosphere and the dynamic ascent of air.Investigation of the synoptic-dynamic conditions of the lower levels of the troposphere showed that in the lower levels of the low-altitude synoptic system with closed meters, at the same time as the deep trough reigns over the region, it has been formed and strengthened during peak rainfall times and has led to a strong rise of air.Investigating the state of atmospheric humidity in the study area and identifying sources of moisture supply using special humidity maps, moisture flux convergence function and atmospheric flow paths were carried out.Investigating the omega variable in the vertical profile of the atmosphere using the Hoff-Mueller diagram showed that during the times of precipitation events, upward movements prevailed in all levels of the troposphere, especially during the peak of precipitation, the upward movements became more intense in the lower levels.Identifying the type of clouds using MODIS products showed that during heavy rains, especially on March 18, deep convective clouds with a high density of water were formed in the region, which extended up to a height of 300 hectopascals and were very thick.