نشریه آب و خاک
سال سی و سوم شماره 1 (پیاپی 63، فروردین و اردیبهشت 1398)

Water is one of the most important factors limiting agricultural developments in arid and semi-arid regions in the world. One of the important issues of water management is assessment and determination of water requirement of plants. One of the main water management strategies in agriculture is to assess and determine the plants water requirement. Due to dry and semi-arid weather conditions in Iran the optimal use of water resources is crucial. Plants water requirements are the important parts of the hydrological cycle, and its precise estimation is essential for water budget studies, facilities, management, design of new irrigation systems and water resources management. The determination of behavior and characteristics nonreference vegetation compared to reference vegetation (grass) is the first step in estimating the evapotranspiration of crops. It is important to determine the crop factor in order to measure the water requirement of the crop at different stages of growth. The crop coefficient expresses the effects of crop and soil moisture on a non-reference plant species relative to the reference plant. Among the medicinal herbs, Hibiscus sabdariffa L. is an annual tropical and sub-tropical herbaceous plant belongs to Malvaceae family. Red calyces of Roselle are a source of anthocyanins (about 1.5 g/100 g dry weight), vitamin C and other antioxidants, such as flavonoids (gossypetin, hibiscetine, and sadderetine). Roselle is a medicinal plant that cultivated in Iran especially in Sistan and Baluchestan province. Regarding the long history of cultivation, and high consumption in Iran and the world so far, there has not been a scientific report about Roselle water requirement at different stages of growth. Therefore, this research was carried out with the aim of obtaining Roselle water coefficients and studying the pattern of its changes during the growing season in dry and semi-arid climates of Birjand using the lysimetric method. To determine the Roselle crop coefficient, as a valuable medicinal herb, a lysimetric experiment was conducted in faculty of agriculture, Birjand University during the growing season in 2017. The lysimeters used for this experiment have 20 cm diameter and 16 cm in height. Three lysimeters used for sowing Roselle and three lysimeters used for reference plant. There are six orifices as a water drain in the bottom of each lysimeter. Floor of lysimeter covered by 5 cm granule layer, then filled with soil and cow decayed fertilizer mixture. In each lysimeter, 25 seeds of Roselle were sown. To determine potential evapotranspiration, 12 centimeters height grass was used as the reference plant. Water requirement of Roselle was determined by water balance method. The Roselle growth period was divided into four stages included initial (10% plant growth after emergence), development (between 10% plant growth and before flowering), middle (between early flowering and end flowering), and end (between end flowering and seed ripening). Weed control was achieved by hand hoeing during the growth season. Drainage water was measured by weighting and soil moisture hold at field capacity during the growth season. Results of this study showed that Roselle plant in the initial stage due to slow growth and low transpiration have low Kc compared to middle and development stage. The average coefficient of Roselle was 1.26, 1.55, 1.81, and 0.96 in the initial, development, middle, and end stages respectively. Duration of growth stages for Roselle in Birjand region is 35, 75, 100, and 30 days after emergence. This results revealed an increasing trend from initial to development and middle stages. However, in the end stage of Roselle, Kc decreased. The result of this study showed that evapotranspiration of Roselle was 3819.57 mm whereas the reference plant evapotranspiration was 2420.3 mm. Due to water shortage in the arid and semi-arid region, this plant is not proper for sowing in this area. According to the results of this study, the annual average evapotranspiration rate of the Roselle was 3819.57 mm whereas the reference plant evapotranspiration was 2420.3 mm. Therefore, the water requirement of Roselle is very high during growth period. Finally, according to the high water requirement and water deficient in Birjand, Iran; it seems that Roselle is not a proper plant for sowing in this area.

Deficit irrigation is a management strategy for increasing water productivity. The yield loss can be compensated by saving water consumption under deficit irrigation. Increasing water productivity is a key factor in removing the biggest challenge facing the agricultural sector in water-limited areas, which means less water production. In order to achieve this, awareness of the relationship between water and yield, known as production functions, can be of great help in this regard. An experiment was carried out on a plot of 96 × 30 × 30 m2 based on a plot in a factorial arrangement in three replications. The main treatments consisted of six main hydrothermal treatments (0%, 33%, 66%, 85% 100% and 125% water requirement) and sub-treatments including four levels of fertilization (0%, 33%, 66% and 100% fertilizer requirement), and two cultivars named Golestan and B 557. Furthermore, the irrigation planning based on soil moisture discharge ranged from 5% to 70%. In this experiment, single branch sprinkler irrigation system was used, therefore 144 plots (6 water × 4 fertilizers × 2 digits × 3 repeats) were, created on the sides of the pipeline. On each cropping line, 20 cm spacing on each row and at a row spacing of 75 cm were cultivated. For each plot, the dimensions were 2.5 × 2.3 m (2.5 m in the direction of irrigation, and 3 m along the irrigation line). Soil samples were collected from each depth of 0-5, 20- 20, 20-40 and 40-60 cm before each irrigation. The moisture content was determined by weighing method. Based on the physical properties of the soil (bulk density, percentage of moisture content in field capacity and wilting point), effective depth of root and field management (MAD) 60-70% (based on previous studies), the depth of irrigation water was calculated. 40% of N-fertilizer application was carried out prior to sowing and the remaining N-fertilizer was applied from flowering stage with first irrigation and based on different treatments. The irrigation time was determined by dividing the irrigation water depth by the intensity of the sprinklers. 6I treatment due to the close proximity to the sprinklers received the largest amount of water and treatment 1I received the lowest amount of water (rain) as it was situated outside of the spray nozzle radius. From the beginning of planting, the irrigation program was carried out according to the amount of soil moisture at the irrigation time of the 5I treatment (100% water requirement). Therefore, it is expected that treatment 6I has received water more than water requirement. The total amount of water received by each row of crops during the growth period was measured by placing a water collecting canal mounted on a tripod to a height of 1 meter. After irrigation, by using cylinders the depth of water collected in the cans was measured. Due to wind blowing during the day, irrigation was carried out at night, to maintain the uniformity of water distribution. The final harvesting operation was performed for all treatments and replicates on first and second of November. a relationship and the corresponding regression coefficients were obtained between the irrigated yield and the each cultivar and fertilizer level separately, . The quadratic relationship was determined between the yield and the applied water. The coefficients values of the quadratic equation of production function were calculated for each fertilizer application and cultivars and were showed in Tables 5 and 6. The yield functions of cotton cultivars versus applied water were in the form of a second-order quadratic with a downward contraction. Initially, the gradient of the graph was high and then its intensity decreased indicating that water efficiency is much higher in irrigation. In addition, by increasing the amount of irrigation, the amount of the product reached to the peak value, and since then, a yield reduction was observed as applied water amount increased owing chiefly to Nleaching. The sensitivity coefficients for Golestan cultivars and 557 B were calculated at four levels of fertilizer according to the Doorenbos and Kassam formula. The average sensitivity coefficient for Golestan and B-557 was 1.18 and 1.27, respectively. It can be concluded that the Golestan cultivar is less sensitive to water shortage as compared with B-557. These results can be used to optimize water use under water constraints.

Flow velocity measurement is an important hydrological factor in dam reservoirs, lakes, river and coastal planning/management, control of water resources and environmental conservation. A wide variety of techniques such as Current Meter and tracking float methods have been used to measure flow velocity. However, it is very difficult to measure cross-sectional average velocity in unsteady flows or during extreme hydrological events, such as flooding. Therefore, establishing the method and technology for flow velocity measurement is a crucial issue. Acoustic tomography systems offer powerful technique for measuring the flow velocity in oceans, seas, rivers and lakes. Ocean Acoustic Tomography (OAT) employs high-powered signals with frequencies less than 1 kHz to measure meso scale ocean currents. Coastal Acoustic Tomography System (CATS) applies OAT to coastal waters. Because CATS transmits signals at frequencies up to 10 kHz, it can be used in smaller water areas. To use this technique in shallow aquatic environment and in the shorter ranges as much as hundred meters, these systems must transmit sound at much higher frequencies. As a result, Fluvial Acoustic Tomography System (FATS) uses a second-generation - CATS that transmits sound at a frequency of 30 kHz to measure flow velocity and water temperature. Although, FATS is widely used to measure flow features in rivers and estuaries, it has never been used in the lakes. This study shows the result of first acoustical tomography experiment in one of the freshwater Haftbarm Lakes, located western part of Shiraz. This study shows the first acoustical tomography experiment in a lake to measure the flow velocity. Reciprocal sound transmissions were performed between the two acoustic stations located diagonally on both sides of the lake during the period of July 7, 2017. The air temperature ranged from 32 °C to 33 °C and there was not meaningful wind. Sound pulses of the FATS were simultaneously transmitted from transducers every 40 second at a timing synchronized with a GPS clock. The length of sound transmission line was 262 m and the central frequency was set to 30 kHz. The velocity data was successfully collected. FATS uses travel-time tomography approach. Based on the arrival time of acoustic signals at the upstream and downstream stations, the sound speed and flow velocity along the sound ray path are computable. To accurately identify the arrival time of a traveling acoustic signal mixed with noise, the transmission signal was phase- modulated by applying a pseudo-random sequence called an M-sequence. The FATS transmission signal was modulated with a 9th-order M-sequence (511 digits). A three cycles per digit (Q-value) was also selected as a suitable value to transmit the phase-modulated sound from the broadband transducers. The arrival times of the acoustic data were 176.96 and 177 msec at station 1 and station 2, respectively. Therefore, the differential of -0.004 msec was observed. The minus value shows the existence of an insignificant flow to the station 1. The results of calculations showed the speed of sound in water was about 1481 m/s during the experiment period. The flow velocity was estimated as much as 1.5 cm/s. Since, the flow velocity resolution of FATS is 0.1 cm/s, the measured value was meaningful. However, other instruments such as mechanical current meter cannot measure the flow velocity under the 3 cm/s. Therefore, the results of acoustic tomography experiment did not compare with other methods. There are two possibilities for observing the flow in the lake: 1) the effect of wind on the Lake Surface or 2) alluvium aquifer recharge where is located under the lake. Continuous measurements of the flow velocity were conducted in a shallow lake using Fluvial Acoustic Tomography System (FATS), a state-of-the-art acoustic system. The FATS was equipped with a couple of 30-kHz broadband transducers with horizontally omnidirectional and vertically hemispherical beam patterns which can be used to estimate the cross-sectional average velocity from multiple ray paths that cover the cross-section of a water body. This study shows the recharge of alluvium aquifer located under the lake. This outcome is confirmed by the previous studies that investigated about the hydrogeological situation of the aquifer located under the lake. In conclusion, this study shows the possibility of determination of ground flow inflow/outflow (discharge/recharge) into or out of the lakes.

Recharge estimation is one of the major issues in management of groundwater resources. Many methods have been applied to calculate the groundwater recharge, among which the water table fluctuation, chloride mass balance and water balance methods have been widely used. In this study the recharge quantity into alluvial unconfined aquifer of Aleshtar in Lorestan province with an area of about 128 km2 was estimated using three methods of water table fluctuation, chloride mass balance and water balance. The aquifer is more important, as it supplies the water for agricultural consumptions. The aquifer is discharged by 322 pumping wells. It is also drained by the gaining river of Aleshtar which crosses the plain in a general trend of the north to the south. Three methods of water table fluctuation (WTF), chloride mass balance (CMB) and water balance were used to calculate the recharge to Aleshtar aquifer in Lorestan province.
In water table fluctuation (WTF) method, water table data from 18 piezometers installed in Aleshtar aquifer during an 11-year period (2003-2014) were collected and analyzed. The values of groundwater rise () which is equal to the difference between the peak of the rise and low point of the extrapolated antecedent recession curve at the time of the peak were calculated and then multiplied by the specific yield to determine the value of recharge based on the following equation:
Δh/Δt   (1)
In which R is recharge, Sy is the specific yield and Δt stands for the time.
Recharge value was also calculated by chloride mass balance (CMB) method. In this regard chloride concentrations were measured in 33 groundwater samples and 5 rainfall samples and then recharge was calculated by the following equation: (2)
Where R is annual groundwater recharge (mm), P is annual precipitation (mm),  is mean chloride concentration in rainfall (mg/l) and   is average chloride concentration of groundwater (mg/l).
Recharge estimates were also performed by the water balance method based on the following equation:  (3)
In which R denotes groundwater recharge,  is groundwater outflow,  is groundwater inflow, is groundwater drainage, is evapotranspiration from the groundwater table,  is groundwater pumping and   is change in groundwater volume storage. Investigating 11-year groundwater hydrograph of Aleshtar aquifer shows a decreasing trend against time. In the current situation, the annual rate of water table decline is about one meter. In order to estimate recharge value using water-table fluctuation method, the value of 0.05 was considered for specific yield based on dominant soil texture in drilling logs and the value of annual recharge into the aquifer was estimated at 28.3 million cubic meters. Temporal variations of recharge showed an increasing trend with time. This is probably related to capacity increase of the aquifer to receive recharging water due to the decline in water table. It was further confirmed by investigating the upstream and downstream hydrographs of the Aleshtar River which showed a decreasing trend in contribution of the groundwater (base flow) at the river discharge with the time. The average concentration of chloride ion in groundwater and rainfall samples were measured as 40.23 and 6.4 mg/l, respectively. Then, recharge value was calculated about 10 million cubic meters using chloride mass balance method. The annual water balance of the Aleshtar aquifer was investigated considering the main components of groundwater inflows (32.46 million cubic meters), groundwater outflows (6.25 million cubic meters), groundwater drainage by the Aleshtar river (15.76 million cubic meters), discharge by pumping wells (49.22 million cubic meters) and change in aquifer storage (-6.41 million cubic meters). The evapotranspiration was not considered as the depth to water table is more than 5 meters, anywhere. Then, the amount of annual recharge using water balance method was estimated about 32.4 million cubic meters. The similarity of the recharge values calculated by water table fluctuation and water balance methods confirm the accuracy of the calculated total recharge by the both rainfall and irrigation return flows to the Aleshtar aquifer. By subtracting the irrigation return flows, the annual rainfall recharge is estimated at 18.5 and 22.6 million cubic meters by the water table fluctuation and water balance methods, respectively. Due to the uncertainties in recharge estimation by different methods, rainfall recharge to the aquifer was determined in the range of 10 to 22 million cubic meters per year and the rainfall recharge coefficient of 28% was introduced for Aleshtar aquifer.

Increasing the production rate became considerable for farmers in various ways. Modern technologies, such as biotechnology and nanotechnology could play an important role in increasing the production and improving the quality of agricultural products. Research into the direct application of nanotechnology into agriculture is set to increase in the future. One of the most remarkable plant growth factors is its nutrition. Titanium plays a beneficial role in increasing and stimulating plants growth. Titanium's usage in nutrition solution or spraying on the plant will increase the biomass and growth of different plant species. With respect to Nano technology enhancement in recent years the application of nano-particles is increasing. All the positive effects of titanium dioxide depend on its ability to absorb light and the main disadvantages of this combination are the low ability to absorb visible light from the sun and absorbing more UV light.  It is possible to improve its effectiveness due to the high proportion of sunlight in the visible range by absorbing the visible light of nano-particles. To achieve this goal a layer of color will be added on the surface of the nanoparticles, which is called the nanoparticle sensitization by color. Due to the absorption of light by titanium dioxide nano-particles, especially ultraviolet radiation, it is assumed that the creation of a color layer on these nano-particles increases the antibacterial and fungal properties of these nanoparticles. As a result, the goal of this experiment is to investigate the possible increase in light absorption and increase the yield of the sorghum plant by titanium dioxide nano-particles of Dye-Sensitized, which, some of the parameters were investigated by treating the seeds of the plant with both nanoparticles. This research was performed in three replications in a completely randomized design with factorial arrangement and with 12 treatments containing 6 concentrations of titanium dioxide nano-particles (0, 1, 10, 50, 100 and 500 mg.L-1), 6 concentration of titanium dioxide nanoparticles of Dye-Sensitized (0, 1, 10, 50, 100 and 500 mg.L-1). Fresh and dry weight of plants, plant nutrients content (Phosphorus, Potassium, Manganese, and Zinc), activity of ascorbate peroxidase and guaiacol peroxidase and chlorophyll content parameters  have been measured. The saffron compounds have significant peaks in the UV-Vis spectrum. The spectrum of titanium dioxide nanoparticles has a specific peak in the ultraviolet range (Area between wavelengths of 200-400 nm) however there is no trace of absorption in visible areas. The spectrum of the saffron solution has two identifiable peaks at 328 and 258 nm, and a double peak at 466 and 442 nm. The observed peak at 258 nm is related to the combination of Picrocrocin, which is the same colorless bitter substance found in saffron. The dual peaks range between 400-500 nm and the peak appearing at 328 nm are related to the carotenoids found in saffron. Crocin also has similar peaks which are likely to be overlapping with trans-isomeric peaks and not separable. The Spectrum of titanium dioxide nano-particles covered with saffron color also represents two peaks at 322 and 260 nm, and a peak at 430 nm with a specific shoulder at 458 nm. What comes from the comparison of two saffron peaks alone and saffron coated on titanium dioxide nano-particles is that the Crocin molecules contained in saffron are attached to nano-particles. According to the results, dry weight and enzymatic activity of Guaiacol peroxide and Ascorbate peroxide showed a significant increase compared to the control and had the highest performance respectively at concentrations of 10, 100 and 500 mg.L-1of titanium dioxide nano-particles of Dye-Sensitized, and showed 1.25, 2.7 and 3.28 fold. The amount of plant nutrients such as phosphorus, potassium, manganese, and zinc at concentrations of 10, 100, 500 and 50 mg.L-1titanium dioxide nanoparticles of Dye-Sensitized had a 72.34, 42.85, 73.95 and 28.17 percent increase, except fresh weight and chlorophyll a. Chlorophyll a at a concentration of 500 mg.L-1of both nano-particles showed the highest amount, but the fresh weight, unlike other parameters, showed the best performance with normal nanoparticles. It seems that these nano-particles, by coloring, intensify light-related reactions compared to normal nano-particles, which results in better performance.

Chemical fertilizers can supply all the nutrients required by plants, but their high consumptions cause environmental pollution and increased agricultural production costs. Organic fertilizers can improve the biological, physical, and chemical properties of soil and improve soil fertility and productivity. However, these fertilizers alone cannot provide all the requirements of plants for different nutrients. In addition, these fertilizers are not sufficiently available to farmers everywhere. So, in order to increase effectiveness of organic and chemical fertilizers, to decrease environmental pollutions and to achieve sustainable agriculture, integrated application of organic and chemical fertilizers is recommended. Nitrogen (N), phosphorus (P) and potassium (K) are essential elements for plant nutrition and growth. Wheat as a strategic crop is the most important cereal and plays a very important role in human and animal nutrition and health. The deficiencies of N, P and K in the most agricultural soils often reduce the growth and yield of wheat. Therefore, the appropriate concentrations of these nutrients in wheat seed, leaf and stem are important not only for the optimum growth of the wheat plant and its quality improvement but also for the health of humans and animals. This research work was carried out to study the effects of combining farmyard manure (FYM), municipal solid waste compost (MSWC) and municipal sewage sludge compost (MSSC) with different levels of urea on seed, leaf and stem yields of wheat (Triticum aestivum L.) cultivar Alvand and concentrations of N, P and K in seed, leaf and stem in a randomized complete blocks design with 15 treatments and three replications under field conditions at Khalatposhan Agricultural Research Station, University of Tabriz, Tabriz, Iran. The treatments included were: 1) control (without fertilizers), 2) 150 kg urea/ha, 3) 300 kg urea/ha, 4) 30 ton MSWC/ha, 5) 30 ton MSWC/ha + 150 kg urea/ha, 6) 60 ton MSWC/ha, 7) 60 ton MSWC/ha + 150 kg urea/ha, 8) 30 ton MSSC/ha, 9) 30 ton MSSC/ha + 150 kg urea/ha, 10) 60 ton MSSC/ha, 11) 60 ton MSSC/ha + 150 kg urea/ha, 12) 30 ton FYM/ha, 13) 30 ton FYM/ha + 150 kg urea/ha, 14) 60 ton FYM/ha, 15) 60 ton FYM/ha + 150 kg urea/ha. The size of each plot was 2.0m × 1.9m. At the end of growth period, the plants were harvested and different sections of wheat plant (seed, leaf and stem) were separated and the yield of each section was determined. The concentration of N in seed, leaf and stem were then measured by Kjeldahl method. After dry ashing of the seed, leaf and stem samples, the concentrations of P and K in their extracts were measured by spectrophotometer and flame photometer instruments, respectively. The results showed that application of 300 kg urea/ha increased the wheat grain yield and concentrations of N, P and K in seed, leaf and stem but it decreased the stem yield. Application of 150 kg urea/ha had no significant effect on the leaf yield but its integration with 60 ton MSWC/ha significantly increased the leaf yield of wheat. The combining of 150 kg urea with 30 and 60 ton FYM, MSWC and MSSC per hectare increased yields of wheat stem and seed and their N and P concentrations as compared with the control and application of solely organic fertilizers. The use of FYM, MSWC and MSSC significantly increased the wheat grain yield and concentrations of N, P and K in seed, leaf and stem relative to the control but their effects on yields of leaf and stem depended on the type and rate of organic fertilizer. The highest yields of grain, stem and leaf and the highest concentrations of N, P and K in wheat grain, stem and leaf were observed under combined application of 150 kg urea and 60 ton FYM, MSWC and MSSC per hectare. The minimum yields of seed, leaf and stem and the minimum concentrations of N, P and K in different organs of wheat plant were observed in the control treatment. The average wheat yield component was in the order of seed > stem > leaf. The mean concentrations of N, P and K in different sections of wheat were in the order of seed > leaf > stem, seed > leaf > stem and stem > leaf > seed, respectively. The grain yield of wheat had positive and significant correlations (p<0.01) with concentrations of N, P and K in different organs of wheat, which indicates the role of N, P and K nutrition of wheat plant in increasing its seed yield. The wheat seed had higher concentrations of N and P and lower concentration of K compared to leaf and stem. In general, in order to decrease nitrogen fertilizers use, enhance N, P and K nutrition of wheat plant, improve wheat seed quality, decline environmental pollution and increase wheat yield, application of 150 kg urea and 60 ton manure per hectare is recommended. However, if there is not enough manure, 150 kg urea and 60 ton municipal solid waste compost or municipal sewage sludge compost per hectare can be applied at similar conditions.

Wind erosion is one of the most important destructive phenomena leading to land degradation and desertification, which occurs due to blowing of erosive winds over a susceptible soil surface or a smooth land. Iran is mostly located in arid and semiarid climates; consequently, wind erosion dominates large parts of the country due to the climate and land mismanagement. In this regard, Kerman as the largest province in Iran has been under influence of erosive winds with high damaging potential. Wind erosion is a function of two agents including erosivity and erodibility. As wind velocity increases, the rate of wind erosion increases as well, while an increase in threshold friction velocity results in sand drift potential reduction. On the other hand, soil properties can control wind erosion rate through affecting both soil erodibility and threshold velocity. In addition, wind erosion is directly influenced by the direction and velocity of wind. Therefore, for better understanding of this phenomenon, analysis of wind erosivity based on meteorological data is of importance. The aim of this study was to analysis wind erosivity in Kerman province and the wind erosion potential in different parts of the province. This study was conducted to investigate the potential of wind erosion in different parts of Kerman province based on seasonal wind data obtained for the period from 2006 to 2010. For this purpose, eight synoptic stations were selected and wind rose and sand rose were plotted for each station using WR Plot View.8 and Sand Rose Graph 3. For each season and for the whole period, erosive wind speed classes, prevailing wind direction, and the sand rose components including drift potential, sediment load and uni-directional index were obtained for each station. This study results indicated that the intermediate wind speed class i.e. 7.7 to 9.8 m s-1 with the west and southwest directions had the highest frequency at most stations. The most erosive winds occurred during winter and summer, while the lowest ones were found in autumn. In winter, the highest wind speed class i.e. >13 m s-1 was the most frequent class. However, precipitations mostly occurring during winter can moderate the sand transport potential, since the higher precipitation causes a higher soil moisture level and enhanced threshold velocity. In addition, Jiroft station had the most frequent calm winds, whereas Lalehzar station exhibited the least frequency of these winds as this site is located in a mountainous region. Among the stations, the highest potential of sand transport (1637 vector unit) and the greatest sediment discharge (102.62 kg m-1 s-1) were observed at Rafsanjan station. However, the lowest sediment discharge was found at Jiroft station with 22.40 kg m-1 s-1. In all stations, the values of DPt were more than 400 indicating high wind erosion potentials in most areas of the province. The assessment of the uni-directional index illustrated that the investigated wind properties varied for different seasons and regions. Analysis of this index showed that Zarand and Jiroft had multi-directional winds, while other stations with a uni-directional index ranging from 0.3 to 0.8 experienced bi-directional winds with moderate variations. Furthermore, the analysis of resultant drift direction implied that the sand transport direction in Kerman, Jiroft, Sirjan, Rafsanjan and Shahrbabak sites was from west to east, at Lalehzar station was from southwest to northeast, at Bam station was from north to south, and at Zarand station was from northwest to southeast. The highest values of total drift potential in Bam, Jiroft and Zarand were obtained in summer season, while the maximum total drift potential was recorded in wintertime for Kerman, Rafsanjan, Shahrbabak, Sirjan and Lalehzar locations. The findings of this study revealed the significance of wind erosivity analysis in order to make a better understanding of wind erosion processes and achieve a more suitable strategy to combat this environmental threat. It was concluded that due to climate conditions, Kerman province as the largest province of Iran has experienced high potentials of wind erosion and sand transport. In addition, the prevailing direction and most frequent velocity classes of winds differ among different parts of the province demonstrating the possibility of the formation of different features of wind erosion. Finally, the high values of DPt (> 400) were obtained for most stations, showed a high wind erosion potential in the province.

Over the last few years, due to the depletion of Lake Urmia located in the northwest of Iran, the proportion of surrounding saline agricultural lands increased at a fast pace. Digital mapping of regional soils affected by salt is essential when monitoring the dynamics of soil salts and planning land development and reclamation schemes. The soil hydraulic and mechanical parameters are very important factors that affect water and chemical transport in soil pores. In the salt-affected soils, saturated hydraulic conductivity (Ks) is very low due to the high contents of sodium and weak aggregate stability. Penetration resistance (PR) indicates soil mechanical strength to penetration of a cone or flat penetrometer; it is important in seedling, root growth and tillage operations. Generally, PR values exceed 2.5 MPa, while root elongation is significantly restricted. The analysis of spatial variability of Ks and PR is essential to implement a site-specific soil management especially in the salt-affected lands. The objective of this study was to evaluate the influence of two different bare and agricultural land uses on the spatial variability of Ks and PR in the salt-affected soils around Lake Urmia.   This study was conducted in the agricultural and bare lands of Shend Abad region located at the 15 km of Shabestar city, northwest of Iran (45° 36ʹ 34ʺ to 45° 36ʹ 38ʺ E and 38° 6ʹ 37ʺ to 38° 7ʹ 42ʺ N). Totally, 100 geo-referenced samples were taken from 0-10 cm soil depth with 100×100 m intervals (80 ha) in agricultural (n=49) and bare (n=51) land uses. Sand, silt, clay, organic carbon (OC), mean weight diameter of aggregates (MWD), sodium adsorption ratio (SAR) and electrical conductivity (EC), were measured in the collected soil samples. The EC and SAR were measured in 1:2.5 (soil: distilled water) extract. Ks was measured using constant or falling head method. Bulk density (BD) and field water content (FWC) were measured in the undisturbed soil samples taken by steal cylinders with 5 cm diameter and height. Total porosity calculated from BD and particle density (PD). PR was directly measured at the field using a cone penetrometer. The best fit semivariograms model (Gaussian, spherical and exponential) was chosen by considering the minimum residual sum of square (RSS) and maximum coefficient of determination (R2). Ordinary Kriging (OK) and inverse distance weighting (IDW) interpolation methods were used to analyze the spatial variability of Ks and PR. Spatial distribution maps of soil variables were provided by Arc GIS software. The accuracy of OK and IDW methods in estimating Ks and PR was evaluated by mean error (ME), mean absolute error (MAE), root mean square error (RMSE) and concordance correlation coefficient (CCC) criteria.The CCC indicates the degree to which pairs of the measured and estimated parameter value fall on the 45° line through the origin.     According to coefficient of variation (CV) from the study area, the most variable soil indicator was Ks (CV=155.6%), whereas the least variable was PD (CV= 3.05%) both in bare land use. The Lognormal distribution was found for Ks data in the studied region. The Pearson correlation coefficients (r values) indicated that there are significant correlations between Ks and OC (r=0.36), sand (r=0.60), SAR (r=-0.35), EC (r=-0.22), BD (r=-0.52), TP (r= 0.31), silt (r=-0.60), and clay (r=-0.43). Also, significant correlations were obtained between PR and FWC (r=-0.32), BD (r=0.21), and TP (r=-0.21). The spatial dependency classes of soil variables were determined according to the ratio of nugget variance to sill expressed in percentages: If the ratio was >25% and <75%, the variable was considered moderately spatially dependent; if the ratio was >75%, variable was considered weakly spatially dependent; and if the ratio was <25%, the variable was considered strongly spatially dependent. The strong spatial dependences with the effective ranges of 2443m were found for Ks. The PR and PD variables had the least (335 m) and the highest (2844 m) effective range, respectively. The range of influence indicates the limit distance at which a sample point has influence over another points, that is, the maximum distance for correlation between two sampling point. The models of fitted semivariograms were spherical for Ks and exponential for PR. According to RMSE and CCC criteria, there was not found significant difference between Ks estimates by OK and IDW interpolation methods. The high CCC and low RMSE values for OK compared with IDW indicated the more precision and accuracy of OK in estimating PR in the studied area. Generally, the spatial maps showed that from agricultural to bare land use by nearing to Lake Urmia, the BD and PR increased and consequently TP and Ks decreased. The results showed that Ks negatively related to the SAR, EC, BD, silt and clay and positively related to the OC, sand, MWD and TP in the study area. Also, PR negatively related to the FWC and TP and positively related to the BD and silt. The spatial dependency was found strong for Ks. The PR revealed the smallest effective range (335 m) among the studied variables. As a suggestion, for subsequent study, soil sampling distance could be taken as 335 m instead of 100 m in order to save time and minimize cost.

Although the soil salinity as an effective factor on soil and water management is typically assessed by measuring the soil electrical conductivity (ECe), this conventional laboratory method is time-consuming and costly. Therefore, near-infrared spectroscopy (NIR) as a fast, cheap and non-destructive method to assess soil salinity level can be considered as a valuable alternative method. Reviews of literature on the application of NIR spectroscopy for soil salinity prediction have shown that there is no sufficient information about the effect of soil texture on results accuracy; therefore, in this study the soil salinity was predicted under different soil salinity levels and various soil textures. The effect of different pre-processing methods was also investigated to improve the predicted soil salinity. Twenty three surface soil samples were collected from different places in Fars province, then; some soil properties such as percentage of particles size and ECe were measured. These samples were artificially salted by adding the water in different salinity levels to the soil samples. The ECe of these soils were between 2.1 to 307.5 dS/m and then all samples dried to reach the field capacity level. Soil reflectance spectra were obtained in 350-2500 nm wavelength range. The absorbance and derivative of reflectance spectra were calculated based on the reflectance spectra. In order to determine the effect of smoothing technique, as a pre-processing method, 4 various methods (moving average, Gaussian, median and Savitzky-Golay filters) in 12 different segment sizes (3,5,7,9,11,13,15,17,19,21,23 and 25) were applied and the processed spectra introduced to Partial Least Square Regression (PLSR) model to predict soil salinity in two calibration and validation steps. At the first step, the soil salinity was predicted for all samples using of reflectance, absorbance and derivative of reflectance spectra under 4 pre-processing methods and 12 segment sizes. According to the R2 and RMSE indices, the best type of spectra, the effect of various pre-processing methods and the best segment size in prediction of soil salinity were determined as absorbance spectra, moving average and Savitzky-Golay filters for segment size of 25 and 15, respectively. In the second step, the effect of soil texture on prediction accuracy was investigated. For this purpose, soil samples were divided into the coarse and fine textures and soil salinity was predicted for each of these groups using different pre-processing methods and different segment sizes. In prediction of soil salinity by absorbance, reflectance and derivative of reflectance spectra, the R2 values in validation step were 0.742, 0.706 and 0.670; and RMSE values were 29.92, 31.96 and 33.9 (dS.m-1), respectively. The absorbance spectra were the best spectra type in prediction of soil salinity. Therefore, in next step, absorbance spectra were used only for predicting the salinity in fine and coarse soil textures. Results showed that the prediction in coarse texture was better than that of the fine texture (R2= 0.836 and R2=0.756, respectively). It was also revealed that the highest R2 occurred in coarse texture and the accuracy of prediction was reduced in fine textures. The results showed that the performance of different pre-processing methods is related to the spectrum type. Although the pre-processing methods had no positive effect in using of reflectance spectra, but it improved the predicted values which were obtained using of absorbance and derivative of reflectance spectra. The best results were occurred when the absorbance spectra were used. Moving average method increased the accuracy of prediction more than the other pre-processing methods, and according to the results this method, for the segment size of 25, was the best technique in soil salinity prediction. According to the R2 and RMSE indices, the prediction of soil salinity by absorbance spectra was more accurate than the prediction using reflectance and derivative of reflectance spectra (R2= 0.742, 0.706 and 0.670, respectively). Although the predicted soil salinity in coarse soils were more accurate than that in fine soils. Using of absorbance spectra to predict the soil salinity in all soil textures was efficient. The results showed that using of pre-processing methods improved the soil salinity prediction by absorbance and derivative of reflectance spectra, and the moving average and Savitzky-Golay filter were the best pre-processing methods.

The soil-water retention curve (SWRC) is the relationship between the soil water content and matric potential of soil water. The SWRC is a fundamental soil characteristic, which is essential to determine parameters of numerous processes in the soil such as infiltration, drainage, solute movement and water availability for plants. It is also a key parameter in the study of the strength and compression of unsaturated soil. Direct field or laboratory measurement of soil water retention is costly, laborious and time-consuming. During the past four decades many models have been introduced to describe soil water retention curve, but their fitting capability in different textural groups have rarely been investigated. A good mathematical representation is the model that reduces the discrepancy between the observed and predicted data.  Therefore, the aim of this study was to evaluate the ability of 10 SWRC models in fitting to the experimental data and determine the best model among them for the SWRC of all soil samples and for each soil textural groups in the entire soil water range, near saturation to near oven dryness. In this study, 145 disturbed and undisturbed soil samples were taken from top soils and subsoil's of Guilan, Hamedan and Kermanshah provinces from different depths and were classified into textural groups after textural measurements. Water content were measured at 12 matric potentials. The SWRC models were fitted to the observed SWRC data of 145 soils using an iterative nonlinear optimization procedure. The latter finds the values of the fitting parameters giving the best fit of the model to the data. The optimization procedure was applied using the least square curve fitting toolbox of the MATLAB software to find the values of the fitting parameters. The coefficient of determination (R2) and root mean square error (RMSE) were used as relative measures of the goodness-of-fit of the SWRC models to the experimental data. Corrected Akaike information criterion (AICc) that imposes penalties for additional fitting parameters was used to compare the quality of models fitting. The results showed that the Fredlund and Xing model in all soil samples and as well as in the coarse-textured group, the Libardi model in the fine-textured group and the Brutsaert model in the moderate-textured group had the most accurate fitting results, but their differences were not significant P <0.05 in the all soil samples and each of textural groups. The Brutsaert and Fredlund and Xing models provided a continuous mathematical function for the entire SWRC. The better performance of these models may be due to their physical basis that could describe the SWRC accurately. On the other hand, the parameters of the Libardi model can affect and control the slope and the position of the SWRC in all three areas, including the capillary saturation, de-saturation and residual saturation and the effect of one parameter can be easily distinguished from the effect of the another parameter. Also, according to parametric study of the Libardi model, it can well simulate the break point of the air entry value. Although the fractal models have physical and mathematical basis, they do not have the adequate flexibility to describe the SWRC. A poor performance of fractal models in the present study may be was due to terms of “3-D” (the result of this term was less than one). Therefore, fractal models were not successful in predicting the sigmoid shape of the entire SWRC. Fermi and Tani models with exponential functions had weakest performance. The poorer performance of the Fermi and Tani models in the present study may be due to lack of convergence of their parameters. It is generally accepted that the lack of convergence of parameters is an indication that the data cannot be fitted to the model well. Comprehensive comparisons of SWRC models will be of value to future model users, but it is important to note that such comparisons will remain dataset dependent. In other words, these results can help the users to choose SWRC models for fitting to the experimental data accurately in case there are limitations to the number of matric potential-water content measured points. Finally, the Libardi model is introduced as the best model for representing the wide range of the soil matric potentials due to the lower number of parameters, the physical concept of the parameters, and the simple form of its equation.

Nowadays pollution of sand columns and water resources with hexavalent chromium is enhancing due to the increase of industrial and agricultural activities. In recent years nanoscale zerovalent iron particles (nZVIP) have been used according to special properties comprising of high surface area, high reaction sites, non-toxic, non-expensive and high potential for removal of pollutants such as hexavalent chromium from sand columns and water. The size range of Zerovalent iron nanoparticles is less than 100 nm. So they could potentially be transported into the subsurface and finally be mixed with the target pollutants. Chromium is one of the steely-grey, lustrous and toxic heavy metals with high toxicity potential. Upon chromium (VI) toxicity this element is classified as a primary contaminant. Chromium (III) compounds is not toxic and hazardous and are grouped as one of the beneficial elements for human and other animals, while the toxicity and carcinogenic properties of hexavalent chromium have been realized for a long time in all over the world. Application of polymers as nZVIP stabilizers diminishes flocculation and sedimentation of nanoparticles. So usage of such polymers may lead to decreasing of particle size, enhancing reactivity and increasing particle transport in column and continuous medium studies. The objectives of this study were: (1) synthesis and characterization of different surface modified nZVIP with some polymers including Polyacrylamide (PAM) and Guar gum (GG), (2) the removal of hexavalent chromium ions from sand columns by application of different stabilized nZVIP, (3) investigation the impacts of different experimental situations on hexavalent chromium removal from sand columns including primary nZVIP dosages and primary hexavalent chromium dosages, and (4) evaluation nZVIP transportation in sand columns. In this research, nZVIP were synthesized using chemical reduction of ferrous sulfate by sodium borohydride. Guar gum (GG) as a green and environmentally friendly coating and polyacrylamide (PAM) as an anionic and biodegradable polymer were applied for stabilizing of nanoparticles. Zeta potential values were determined by a ZetaPlus zeta-potential analyzer from Brookhaven Instruments Corporation and the measured values were gathered from a suspension containing 5 mg zero valent iron nanoparticles in 100 mL of 1 mM NaCl solution, at room temperature. The hydrodynamic diameter of nanoparticles was determined using a ZetaPlus zeta potential analyzer and the Brownian movement of particles was related to nanoscale zerovalent iron particles hydrodynamic diameter. The morphology of zerovalent iron nanoparticles was determined by scanning electron microscope (SEM). Furthermore, the size of the synthesized nanoparticles was considered using a transmission electron microscope (TEM) via image measuring software. The results showed by increasing of nanoparticle and hexavalent chromium dosage the removal efficiency of chromium increased and decreased from sand columns, respectively. Increasing of hexavalent chromium dosage from 40 to 80 mg/L in sand columns lead to more excessive chromium ions at sand columns and diminishing of hexavalent chromium removal efficient from sand particles. When the dosage of nanoscale zerovalent iron particles raised from 1 to 3 g/L and while the concentration of Cr (VI) was on a constant value of 100 mg/L, the effective reaction sites for hexavalent chromium removal would increase and so the removal performance would enhance according to the nanoparticle dosages. The findings of the current study also revealed when ionic strength and nZVIP dosage enhanced, the transportation of nZVIP decreased in sand columns. By enhancing the concentration of nZVIP, the surface reaction sites of nZVIP increased and hence the efficiency of chromium removal raised from sand columns.Zeta potential is a good parameter for evaluating the colloidal stability. This parameter is an index of stability that reflects the electrostatic repulsion forces between charged particles. By shifting the zeta potential values to the higher records (more negative) the magnitude of repulsion forces among the particles will increase and the stability of them will enhance as a result. In this research the achieved zeta potential records for synthesized nZVIP showed that PAM-stabilized nZVIP and non-stabilized nZVIP had the most and the least stability values respectively. The final results of this study revealed that increasing dosages of synthesized zerovalent iron nanoparticles enhanced the removal efficiency of nitrate and hexavalent chromium from sand columns. When dosages of Cr (VI) increased the removal efficiency of current pollutants decreased. TEM results showed the order of particle sizes were upon to the following trend: PAM-nZVIP < GG- nZVIP < Bare- nZVIP. So PAM stabilized zerovalent iron nanoparticles and the bare nanoparticles were the smallest and largest sizes of all. The efficiency of hexavalent chromium removal and nanoparticle transormation were according to the following trend:  polyacrylamide (PAM)- nZVIP> Guar gum (GG)- nZVIP> Bare- nZVIP

The importance and the presence of spatial variability in soil properties is inevitable, however, the understanding of causes and sources of the variability is not complete. Spatial variation of soil attributes can affect the quality and quantity of plants. Investigation of the soil variability at the small scale can be evaluated by classic statistics and geospatial statistics. The present study was conducted to investigate the spatial variability of yield characteristics of rose (Rosa Damasceneea Mill) and soil characteristics in two main cultivated fields of rose (Negar- Golzar) with different climatic and topographic characteristics located in Bardsir city, Kerman Province. In order to achieve the objectives of the present study, 100 soil and plant samples were collected from each farm. The soil samples were taken from 0 to 25 cm depth and analyzed. The measured soil properties at each location were including fragment, clay, silt, sand, and organic matter contents, CEC, calcium carbonate equivalent, EC, pH, total nitrogen, available phosphorus, and available potassium. Moreover, some plant characteristics (yield, plant height, and plant crown diameter) were measured at each point. Then, maps of soil properties and plant induces were prepared using Geoeas, Variowin, and surfer software. Descriptive statistics were applied using Statistica software (version 20). Kolmogorov-Smirnov test was also used to test the tolerance of variables distribution. The results of Kolmogorov-Smirnov test showed that all characteristics of the plant and soil in both farms follow the normal distribution. Statistical analysis showed that coefficient of variation of soil properties was as follows: total nitrogen (54.47%) and pH (3.16%) in Negar farm, and EC (46.09%) and pH (35.3%) in Golzar farm. The variability of nutrients in both farms had similar trends, so that total nitrogen, phosphorus and potassium have the highest to lowest coefficients of variation, respectively. Analysis of variograms indicated that all of the variables in both fields have a strong and moderate spatial variability. Ranges for variograms were from 122.16m (for yield) to 218.46 m (for silt) in Negar farm and from 115.1m (for available K) to 228 m for (total nitrogen) in Golzar unit. The distribution conditions and spatial variations of the soil properties in the study area were not uniform due to variation of the range of the variograms. The results also showed that the yield characteristics of the rose with some soil characteristics have a closer spatial relationship. About this, in the Negar farm, the range of the rose flower yield was close to the clay, available potassium and calcium carbonate contents. In the Golzar farm, the range of rose flower yield was close to the range of clay, silt, fragments and available phosphorus contents. The spatial correlation ratio showed that all plant characteristics including plant yield, plant height and plant diameter had a strong spatial correlation in the Golzar farm, and all characteristics of the soil were in the medium spatial correlation. Also, in the Negar farm, the product yield characteristics were in a strong spatial correlation class, and all other characteristics were in the medium spatial correlation. Kriging maps showed that soil characteristics and product yield in the study area had spatial distribution. The similarity of the spatial distribution pattern of some variables was one of the important features that these maps showed. The results of this study showed the characteristics of plant yield and soil characteristics have a moderate to strong spatial dependency even in small scales. Kriging maps illustrated that the pattern and distribution of soil properties even within a farm can be varied. However, the spatial pattern of some soil characteristics such as organic matter and total nitrogen with the spatial pattern of plant characteristics and the dimensions of the farms showed conformity. This indicates that the variability of these characteristics is mainly under the management of farmers, and in order to optimize the use of nutrients, inputs should be re-evaluated by farm managers. In general, the results of this study indicated geostatistical method can be used to recognize of control factors of plant production and use its information in order to improve management.

Sustainable management of natural resources is one of the main goals of land use planning and is quite complicated due to various interactions in any given ecosystem. Therefore soil as the bed for interactions of main ecosystem components can be a good indicator candidate as the main requirements of sustainable land use management. Soil classification is a valuable technique for transferring a large set of data along with soil history and is a necessary tool for zoning and soil management plans. This indicates efficiency and potential of classification for showing inner and outer soil properties and stimulating for achieving the best possible soil classification system. Among various existing soil classifications, the World Reference Base for Soil Resources (WRB) as an international soil classification system and USDA Soil Taxonomy (STus) are more globally accepted and applied. In both systems soil orders are similar and their classifications are based on acceptable rules. However each one of them has its own characteristics and reflects its potentials. Also the relationship between soil and landscape and the necessity of sustainable nature management convert soil classification to a tool which is essential for appropriate management decisions about utilization and conservation of natural resources. This study was conducted to investigate the efficiency of Soil Taxonomy and WRB for classification of developed soils of Zayandeh-rud River’s upper terrace. This study applied on the current pathway of Zayandeh-rud River.  Several pedons were studied in a semi-detailed scale study. Finally, four different pedons were selected. Routine physical and chemical analyses Selected physicochemical properties of the soil samples were determined according to the Soil Survey Laboratory Manual and soils were classified according to Soil Taxonomy (2014) and WRB (2015) systems. Argillic (Argic), and Cambic diagnostic horizons were investigated after field and laboratory work. Based on both field and lab studies, for these soil pedons due to lithologic discontinuity, presence or absence of Cambic horizon and accumulated clay horizon, four different sequence of horizons are realizable. Calceric matrix of soil pedons is also another prominent property of them. Due to aridity condition of the region and presence of Argilic horizon based on STus, all soil pedons were classified in great group of Haplargids. According to WRB, all pedons considered as reference group of Luvisols. As the results show, the difference between these two systems of classification was originated at family level for STus and qualifiers for WRB. In fact the difference is due to environmental qualifiers and intrinsic soil profile propertie. STus is performing better than WRB indefining the environmental conditions. Such pattern reflects the climate conditions in any given soil name. Moisture regime (Aridic) at order level (Argids) and temperature conditions (Thermic) at family level have been realized for all soil pedons. However WRB not only at first level but also for second level of classification (qualifiers) was not able to indicate. On the other hand this study results showed that main qualifiers have enhanced WRB efficiency compared to STus and was also able to define the variety of horizon sequences. STus did not show such potential even at family level and all four soils were classified under one name.
Based on the findings of the research, using qualifiers and little laboratory data requirement by WRB caused this system to be more successful than Soil Taxonomy to describe internal attributes in the pedons. WRB was more flexible in reflecting described properties in soil nomenclature. But WRB was not able to reflect soil variability in this semi-detailed study, completely. Also results showed that Soil Taxonomy couldcharacterize environmental properties of soils using soil moisture and temperature regimes. On the other hand, the presence or absence of Cambic diagnostic horizon in the four pedons can indicate a difference in their evolutionary pathway, but the presence or absence of Cambic horizon has been disregard in the names of both systems. The efficiency of each system is vary according to the aims of soil survey, and both systems have advantages and disadvantages in relation to displaying the internal features and the soil environment. The WRB was more succeed than STUS in displaying variety of the characteristics of developed soils in this study, due to its advantages such as Clayic, Cutanic, Ochric, Ruptic, Endocalcaric and also requires less laboratory data. On the other hands, WRB is facing a serious challenge to management objectives related to climatic conditions and vegetation. Therefore, it can be concluded that purpose and scale of a study affects the efficiency of Soil Taxonomy and WRB classification systems to describe soil properties.

Laccases are potent enzymes that are capable of oxidizing various phenolic and non-phenolic compounds as well as resistant environmental pollutants. One of the most effective methods for improving their properties, such as increasing the stability of these enzymes and even increasing their activity, is the immobilization of laccases on different carriers. In the process of immobilization, the enzyme is bonded to a solid carrier which is insoluble in the reaction mixture. In this process, the movement of the enzyme in space is severely restricted, while its catalytic activity is still maintained. One of the carriers used to create recyclable biocatalyst systems is mineral. Minerals as inorganic carriers are inexpensive, abundant in nature, readily available, and also have high biocompatibility. The objective of the present study was to investigate the adsorption properties of Laccase enzyme from T. versicolor fungus on montmorillonite K10 and zeolite minerals using Langmuir, Freundlich, Temkin and Dubinin–Radushkevich isotherms. For this study, the pure laccase enzyme (> 10U mg-1), 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid (ABTS) substrate and montmorillonite K10 mineral (with a specific surface area of 220-270 m2/g and a cation exchange capacity (CEC) equal to 30 meq 100 g-1) were purchased from Sigma-Aldrich. Zeolite mineral was provided from a mine located in southeast Semnan province. Scanning electron microscopy (SEM) images of both minerals, CEC of zeolite with sodium acetate solution (pH=8.2) and zeolite surface area were determined. X-ray Diffraction (XRD) and X-ray Fluorescence (XRF) analyzes of zeolite mineral were also done. In order to immobilize laccase on the minerals, 200 mg of both minerals were activated by shaking with 0.5N HNO3 for 2 hours and a solution of 2% 3-aminopropyltriethoxylane in acetone. The activated minerals were treated by a 5% solution of glutaraldehyde in a 0.1M sodium acetate buffer (pH=5) and were shaken for 24 hours with 0.25-2.0 mg of the laccase dissolved in the buffer. Langmuir, Freundlich, Temkin and Dubinin–Radushkevich isotherms were determined. The experiment was carried out at a constant temperature of 20°C. The results were analyzed using the MSTATC software and the means of the data were compared using Duncan’s multiple range test. Based on the results, the zeolite type was clinoptilolite with a chemical formula of (Na,K,Ca)2.5Al3(Al,Si)2Si13O36.12H2O. Moreover, BET Surface Area, Langmuir Surface Area, t-Plot Micropore Area and t-Plot External Surface Area of zeolite were 40.2712, 645.4780, 3.5188 and 36.7524 m2/g, respectively. Laccase absorption on montmorillonite K10 showed the highest compliance first with the Dubinin–Radushkevich model (R2=0.97) and then with the Langmuir adsorption isotherm model (R2=0.96). Based on the D-R model, the theoretical monolayer sorption capacity (qm) and the constant of the sorption energy (ß) of montmorillonite K10 were 3 mg/g and 0.62 (×103 mol2/J2), respectively. According to the Langmuir isotherm, there was probably a homogeneous distribution of active sites on the montmorillonite K10 mineral surface. On the other hand, laccase adsorption on zeolite showed the best compliance with the Freundlich model (R2=0.87). Accordingly, sorption capacity (KF) of zeolite was 0.05 mg/g (L/mg)1/n. The amount of n parameter as an indicator of the favorability of sorption process was 1.49 demonstrating favorable absorption condition. The values of R2 obtained for Temkin isotherm model were, however, equal in both minerals (R2=0.62 for montmorillonite K10 and R2 = 0.61 for zeolite), and based on this model, the adsorption process was likely to be exothermic. According to the values of the equilibrium parameter (RL) of montmorillonite K10, the absorption was favorable. However, with increasing the initial concentration of laccase, the amount of RL approached zero indicating the laccase adsorption on the mineral is more favorable at higher initial concentrations of laccase. Based on % Removal parameter, the highest percentage of laccase adsorption on montmorillonite K10 and zeolite was related to concentrations of 250 and 125 mg/L, respectively, which showed a statistically significant difference with other concentrations. In general, laccase absorption on montmorillonite K10 showed the best fit with Dubinin–Radushkevich and Langmuir adsorption isotherm models. On the other hand, adsorption of laccase on zeolite mineral showed the best fit with Freundlich model. A higher degree of steric hindrance and conformational changes in the enzyme structure is likely to occur and subsequently, the catalytic efficiency of the enzyme complexes may decrease. Therefore, montmorillonite is more suited to be used as a carrier of laccase enzymes. However, complementary studies such as kinetic tests will help to make final decisions.