نشریه آب و خاک
سال سی و دوم شماره 2 (پیاپی 58، خرداد و تیر 1397)

Evaporation takes place from vegetation cover, from bare soil, or water bodies. In the absence of a vegetation cover, soil surface is exposed to atmosphere which increases the rate of evaporation. Evaporation of soil moisture will not only lead to water losses but also increase the risk of soil salinity. The risk is increased under low annual rainfall, saline irrigation water and deep water table. Soil and water salinity is common in arid and semiarid regions where using saline water is common under insufficient fresh water resources. Evaporation is one of the main components of water balance in each region and also one of the key factors for proper irrigation scheduling towards improving efficiency in the region. On the other hand evaporation has a significant role in global climate through the hydrological cycle and its proper estimation is important to predict crop yield soil salinity, water loss of irrigation canals, water structure and also on natural disasters such as drought phenomenon. There are three distinct phases for evaporation process. Step Rate – initial stage is when the soil reaches enough moisture to transfer water to evaporate at a rate proportional to the evaporative demand. During this stage, the evaporation rate by external weather conditions (solar radiation, wind, temperature, humidity, etc.) is limited and therefore can be controlled, in other words, the role of soil characteristics will occur. In this case the air phase - control (at this stage the stage profile – control). Next step is to reduce the rate of evaporation rates during this stage of succession is less than the potential rate (evaporation, atmospheric variability). At this point, evaporation rate (the rate at which the soil caused by the drying up) can deliver the level of moisture evaporation in the area is limited and controlled. So it can be a half step - called control. This may be longer than the first stage.. Apparently when the soil surface is dry to the extent that, it is effectively cut off from water, this phase starts. This stage is often called vapor diffusion process where the surface layer so as to be able to dry quickly can be important.
This study was conducted to test the texture of sandy clay and four salinity levels (0.7, 2, 4 and 8 dS m-1 (the study used a PVC pipe with a diameter of 110 mm and a height of about 1 m (for the 90 cm soil profile). Evaporation measurements and weight measurements were performed using a water balance. Also the water out of the soil columns were carefully measured. Weight was measured in soil columns has been done with a digital scale with an accuracy of 5 g. The calculation of evaporation ,obtained by subtracting the weight of the soil column twice in a row, low weight and water out of the soil column.
Evaporation decreased with increasing salinity of the soil, even in the first stage mentioned earlier by external meteorological conditions (eg, radiation, wind, temperature and humidity) controlled, observed. It should be recognized that the ability of the atmosphere to evaporate completely independent of the properties of the object that is no evaporation occurs. Moreover, if we assume that the object is completely independent of the properties of water surface evaporation exactly equals, salinity reduced the water vapor pressure resulting in reduced evaporates. The first stage of evaporation decreases by increasing salinity, evaporation would be justified.

Soil is a key resource that contributes to the earth system functioning as a control and manages the cycles of water, biota and geochemical and as an important carbon reservoir. Soil organic matter is one of the most important factors in soil quality assessment and having relationship with physical, chemical and biological properties of soil. Carbon sequestration in plant biomass and soils is the simplest and the most economically practical solution to reduce the risks of atmospheric carbon dioxide. Little information is available about the effects of grazing management on sequestration of carbon in Khuzestan Province pastures. Therefore, this study was conducted to evaluate the effects of grazing exclusion on the amount and forms of carbon management and carbon sequestration with economic view in some pasture soils from Peneti Plain of Izeh area and Dimeh regions of Ramhormoz in Khuzestan Province.
This study was conducted in two regions including Izeh and Ramhormoz representing different climates, vegetation and soil types of southwestern Iran. We selected two grazing treatments including ungrazed and grazed pastures in each region. The first area includes rangeland ecosystem in Izeh city between 31° 57ʹ 8ʺ to 31° 58ʹ 20ʺ N and 49° 41ʹ 11ʺ to 49° 42ʹ 33ʺ E. The region has a typical temperate continental climate, characterized by dry summers and cold winters. The mean annual rainfall is 623mm. The mean annual temperature (MAT) is 19.2 °C, and the mean monthly air temperature varies from -0.6 °C in January to 42.4 °C in July. The second area (Ramhormoz) is located between 31° 7ʹ 44ʺ to 31° 9ʹ 11ʺ N and 49° 29ʹ 13ʺ to 49° 28ʹ 52ʺ E. The mean annual rainfall is 200 mm and the mean annual temperature (MAT) is 27.2 °C, and the mean monthly air temperature varies from 4.2 °C in January to 51.6 °C in July. For each climate region, grazed and ungrazed sites were located on the same soil series with similar aspect and slope. Then, random soil samples were taken from the surface and subsurface in 15 points. After air drying the soil samples and passing them through a 2 mm sieve, physical, chemical properties of the soils were measured.
The soil of both studied regions are non-saline, calcareous, and alkaline and have relatively heavy texture. The results showed that the studied characteristics in four study areas had low and moderate coefficients of variation. This suggests that the contribution of edaphic and environmental factors to explain variation in the data is not high. Also, grazing management has increased soil organic matter of surface and subsurface soil, but despite the increase in organic matter contents of subsurface soils the difference was not statistically significant. The effect of management practices, in order to have a significant effect to lower parts of the soil, it requires a longer period management. Comparing the biomass upon non-grazing (405 and 42 gm-2 in Izeh and Ramhormoz respectively) and grazed (117 and 17 gm-2) areas, indicates a good condition of vegetation in the non-grazing and the effectiveness of enclosure in rehabilitation of pastures in the study area. However, due to more rainfall rates, the amount of biomass produced in Izeh is higher.
The carbon management index in the study areas, as well as the depths of the study is high, indicating recovery of soil carbon and improving its quality. Also, based on carbon sequestration in the study area, non-grazing was one of the most proper and efficient management practices, which improved soil quality. Accordingly, it seems that non-grazing practices should be considered as one of the major programs in renewable natural resources plans. On the other hand, estimation of the economic value of carbon sequestration in the pastures has been remarkable, and increased 17 and 12.7% of the value of carbon sequestration in Izeh and Ramhormoz regions under the management of the exclusion. Therefore, the management of rangelands should be directed to allow for their ecologic performance and capacity considering the environmental economy of rangelands so that in broad terms, the justification for the enhancement and maintenance of the economic equilibrium can be viewed as a guaranty of implementing the range managements resulting in sustained development.

One of the methods of increasing the water use efficiency is the application of water absorbent materials in Soil. Super absorbent polymer increases the water saving in soil and decreases the amount of water used for irrigation. By developing paths in public places creating green wall is very common. Green wall may have an efficient role in reducing cooling and heating energy of building and improving the thermal performance also it leads to biodiversity, reducing noise pollution and air pollution by absorbing CO2, dust and heavy metals. Irrigation requirement in green wall depends on the type of system, plant and climate condition. The plant used in this research was Osteospermum. The benefits of irrigation of capsule clay can be attributed to increase irrigation efficiency, yield and quality indices of products, the abundance of raw materials to make it and the lack of dependence on the currency for the pottery production Also simple and native technology doesn’t need power, reduced energy consumption and pests, diseases and weeds, thereby reducing the consumption of chemical pesticides insecticides, fungicides and herbicides, and the possibility of producing a healthier product, especially in cultivation. The other advantages of the greenhouse products are maintaining soil, preventing traps and the possibility of deploying in arid and semi-arid areas.
So far, many researches about application of superabsorbent polymer have been done increasing the water use efficiency, irrigation interval and production yield but there has been no research conducted on drip and capsule irrigation in green wall. Two methods of drip and capsule irrigation compared with current irrigation methods in the green wall and polymer to reduce the number of irrigation steps was used due to lack and importance of water and introduction of capsule irrigation method as a new method of irrigation in the green wall in order to facilitate the implementation of irrigation system.
This study was conducted in order to compare capsule and drip irrigation along with different levels of polymer on Osteospermum plant.
This research was done in Shahrekord University. The experiment region has a semi-arid climate. The study was carried out as a factorial experiment in the form of completely randomized design with 8 treatments and 4 replications. Treatments were consisting of two types of drip and capsule irrigation and four levels of super absorbent polymer consist of zero, 0.3%, 0.6%, 0.9%. The experiment was done in pots. In order to simulate planting conditions circumstance with green wall, a shelf with four floors and 8 pot capacity in each floor was made from iron. The shelves were embedded so that the plant had a proper and identical condition in terms of growths, receiving light and irrigation. In this study the analysis of obtained data was accomplished with SAS software and for average comparison the LSD test at 5 percent level was used.
The results of analysis of variance showed that clay capsule and drip irrigation with different levels of superabsorbent polymer have a positive and significant effect on water use efficiency, relative water content, total chlorophyll and growth indices of Osteospermum. The results also showed that fresh and dry shoot weight, leaf area, mean shoot length and relative water content are related to the treatment of 0.6% polymer in drip irrigation and maximum flowering therewith water use efficiency is related to 0.6% polymer in capsule irrigation. The treatment of 0.9% polymer in capsule irrigation had the highest root length and chlorophyll content. Water use efficiency in capsule irrigation (2 kg/m3) was higher than drip irrigation (1.8 kg/m3).
The results showed that using capsule irrigation in green wall is applicable, despite its limitations and it can be used an irrigation method in green wall. Water use efficiency and number of flowers in this method were more than the drip irrigation method which enhanced the importance of this method. Accompanying this method with super absorbent polymer, improve the growth and water use efficiency by increasing the air conditioning, porosity and maintaining nutrients in soil. In compare with conducted researches, drip irrigation which is considered as one of the green wall irrigation methods has acceptable water use efficiency; also the existence of polymer had a positive effect on the growth of Osteospermum plant. The results showed the application of 0.6% polymer along with capsule irrigation could be a proper method for Osteospermum in green wall.

Most part of Iran is located in an arid and semi-arid region, thus in most parts of a region; groundwater is the only water resource also Population growth, limitation of surface water resources and excessive water withdrawal from the aquifers, caused a sharp drop in groundwater level in many plains of Iran such as Shahrekord plain, So it is necessary to have suitable management plans to improve the aquifer and evaluate some indicators to see the effects of the methods. In this research, many management plans were assessed for the case study.
A groundwater numerical flow model (GMS 10.2) was established by using the monthly data including hydraulic heads, depletion volume of the wells, springs and qanats, precipitation values in Shahrekord aquifer. The model was prepared and calibrated for both status of steady (October 2010) and unsteady flow (November 2010-October 2012), and verified for the following year (November 2012- October 2013). The final values of hydraulic conductivity and specific discharge were obtained by trial and error and PEST method. The water level fluctuation was predicted for three years later (until October 2016) by applying management scenarios of 5% and 10% reduction in water withdrawal, underground dam and artificial recharge. After that, two indicators of Sustainability Index and modified Water Exploitation Index (WEI) were calculated to determine the effect of the scenarios. The Sustainability Index indicates the consumption ratio of natural resources to water demand. The optimal value of this Index is 1 and it may also have negative values. Low values of this index mean high usage of natural resources. The Water Exploitation Index shows to which extent the total water demand puts pressure on water resources. This index has positive values and its optimal value is close to zero. These two indicators were used for surface water resources in the past studies so in this article they were redefined for underground water resources.
The result of groundwater modeling shows that the hydraulic conductivity from 1 to 25 m/day and specific yield from 0.01 to 0.08 are varied also the result of prediction shows that the underground water level would be decreased about 1.34 meter per year in the next 3 years when it hadn’t any management plans in this area but after 5% and 10% reduction water withdrawal scenarios Decreasing of water level were, respectively, 1.33 and 0.71 meter for each year also, considering that there were more wells in the center of the aquifer, water level in this area increased more than other areas, after 5% and 10% Reduction scenarios. According to the results of the artificial recharge and underground dam storage prediction, groundwater head increased in upstream of underground dam and the area near the artificial recharge. Considering the results it was found that the current condition of the aquifer is inappropriate and the amount of withdrawal from the aquifer is more than its capacity. The amount of Water Exploitation Index for business as usual scenario equal to 1.068 and for underground dam, artificial recharge, 5% and 10% reduction water withdrawal, were, respectively, equal to 1.068, 1.061, 1.045 and 0.969. Also the amount of Sustainability Index for business as usual scenario equal to 0.071 and for the other scenario were 0.068, 0.071 and 0.114. , respectively.
Considering the values of the indicators, 10% reduction water withdrawal scenario improved both indicators and selected as the best scenario. After that, 5% reduction water withdrawal was in the second place, then the artificial recharge scenario and underground dam scenarios, respectively, were in the third and fourth place. The scenario of underground dam had any positive effect on these two indicate. Regarding the calculated values of the indicators, it can be seen that although management scenarios have improved these two indicators, the amounts obtained are also significantly different from their optimal values. Several management scenarios can be used simultaneously to bring the calculated index values closer to their optimal values. Used two indicators of sustainability and modified water exploitation can be used exploitation for other management scenarios and assess the performance of them for the other aquifers.

Soil pollution, i.e. elevated concentration of undesirable organic and inorganic matter such as trace elements higher than natural background concentration can be a consequence of indirect or intentional human activities. Evaluation of the effect of the agricultural operations and particularly using the wastewater on soil trace element concentrations is useful and required to manage the land and reduce the health risks of the food products. The aims of this study were: [1] The estimation of the mean concentration and max limit of the background concentration for Cd, Cr, Ni, Pb, Co and Hg in the surface soil samples of Boroujen-Faradonbeh plain; and [2] Evaluation of the effect of agricultural operation and farming by non-conventional water on background concentration and on accumulation, distribution and pollution load of the soil of this plain.
Boroujen-Faradonbeh is an agricultural plain loaced in the Chaharmahal and Bakhtiari mountainous province of Iran. Two hundered surface soil samples (0-20 cm) were taken from three types of land: never-uncultivated soil (20 samples), freshwater-irrigated (90 samples) and wastewater-irrigated (90 samples) soils. The total sampled area was about 2340 hectares. The exact position of the samples were recoded using a GPS device. The total concentrations of Pb, Co, Ni, Cd, Cr and Hg in the samples, and the background and upper limit concentrations were determined. In addition, pollution loading index (PLI) for the whole plain determined and delineated. To separate the affects of agricultural practices and wastewater application the analysis of variance of StatSoft Statistica 12 was used. Maping, and related operations were conducted inside ArcGIS 9.3.
Background concentrations of Ni, Cd, Cr, Hg, Co, and Pb, were determined as 1.13, 0.16, 1.56, 0.09, 0.80, and 1.52 mg/kg, respectively; while upper limit concentrations for the mentioned trace elements were respectively 1.3, 0.28, 1.6, 0.16, 0.9, 1.7 mg/kg. Conventional farming (application of fertilizer but not wastewater) increased the soil accumulation factor of Cd and Pb to 1.7 and 1.9 (p

Global warming is strongly linked to the increase in greenhouse gas emissions to the atmosphere. One of the most efficient ways to reduce the amount of atmospheric CO2 is to produce a lot of biomass and convert the biomass into a biochar. Biochar is an organic carbon-rich solid that can be obtained from pyrolysis of various organic materials. In other words, biochar can be produced via thermal degradation of many organic materials such as vegetation biomass, animal waste, sewage sludge, etc. in absence or lack of oxygen. Biochar is more resistant to microbial degradation than its feedstock and has a mean resistance time of several decades. In connection with the use of biochar, the most researches have been done in non-fertile and highly weathered soils. The most significant effects of biochar application, have been also observed in strongly acidic soils. In many arid and semi-arid regions of the world, including Iran, the soil organic matter content is low. The lack of organic resources and their instability in the soil are considered as some of the most important challenges in improving soil fertility and plant growth and yield. To improve soil fertility by using insufficient existing organic resources, stabilizing organic matter by converting it into the biochar can be a fundamental strategy. If this strategy is applied in our country with calcareous soils, it is necessary to study the effects of different biochars on calcareous soils from different aspects .In this regard, in the present study, the effect of three types of biochar in a calcareous soil has been investigated in comparison with their feedstock.
The effects of three types of biochar and their feedstock in a calcareous soil were investigated in a 6-months period of incubation. A completely randomized design in the form of split plot experiment, was carried out. The main plots were consisted of Control, Municipal Waste Compost (MWC) and its biochar (BMWC), Sewage Sludge (SS) and its biochar (BSS) and Cow Manure (CM) and its biochar (BCW). The sub plots consisted of five sampling times as 10, 30, 60, 120 and 180 days after the beginning of incubation. Application rate of each treatment per kilogram of soil was calculated based on having the same weight of organic carbon content. So that all treatments contained 2.2 grams of organic carbon. After mixing the treatment with soil and adjusting the humidity to the moisture content of the field capacity (FC), they were transferred to the cans (with 3 holes embedded on their doors) and kept at 25°C in the incubator. During the 6-month incubation period, soil moisture was set at FC levels at intervals of two to three days. Sub samples were taken at five times. After air drying the sub samples, the chemical parameters such as EC of 1:2.5 extract, pH of 1:2.5 suspension, available phosphorus (extracted with sodium bicarbonate 0.5N) and available potassium (extracted with ammonium acetate 1N) were measured. After data collection, statistical analysis was performed using SAS software.
The soil texture was sandy loam with 21% of clay, 7% of silt and 72% of sand. Soil CaCO3 content and soil organic carbon content was 16% and 0.23% respectively. Available forms of potassium and phosphorous in soil were 76 and 6.3 mg kg-1, respectively. According to the results, under the influence of each treatment, the variation of soil available P, showed a significant increasing trend with the time. Changes in available potassium and soil pH were not significant over the time. Variation of soil salinity with time although showed an increasing trend but was not significant. Comparison of the effects of treatments showed that both biochars and their feedstock could significantly increase the available phosphorus and potassium in soil. In this regard, the effect of biochars was more pronounced than their feedstock. Among the feedstock, ranking for enhancing effect on available P, was SS > CM > MWC and among the biochars, it was BCM > BSS > BMWC. Ranking for enhancing effect on available K, was CM > MWC > SS and BCM > BMWC > BSS among the feedstock and biochars respectively. The increase in available phosphorus and potassium due to the use of biochars were much higher than that of total phosphorus and total potassium added by biochars. The soil pH decreased as a result of the application of each treatment compared to control. In this regard, the significant difference between biochars and their feedstock were not seen. Probable presence of some amounts of pyrogenic carbon with biochars can be one of the reasons for soil pH reduction. Electrical conductivity of 1:2.5 extract of soil was increased by all treatments compared to the control. Except for BSS, two other biochars significantly increased soil salinity more than their feedstock. This increasing effect on soil salinity can be partially due to the existence of some amount of ash accompanied with biochars.
Application of biochars derived from cow manure, sewage sludge or municipal waste compost in this experimental conditions, led to a significant increase in the amount of available phosphorus and potassium in soil compared to control and their feedstock. Therefore, the use of these biochars can have a high potential for reducing the consumption of some chemical fertilizers. From this point of view, the order of the superiority of the coal was as follows: biochar of cow manure > biochar of municipal waste compost> biochar of sewage sludge. The conversion of any of these feedstock to biochar did not have an effect on their potential for soil pH changes. Except for biochar of sewage sludge, in two other biochar, the potential for increasing soil salinity was higher than the feedstock. Considering that the durability of biochar in soil is much higher than that of its feedstock, it is possible to use suitable biochars such as those examined in this study as a great potential for the sustainable improvement of soil fertility and for reducing the use of chemical fertilizers in our country's agriculture. This requires extensive field researches for other soil properties in different soil and water conditions, with different kinds of biochars and crops.

Soil organic matter (SOM) is an important soil quality factor that affects physical, chemical and biological properties of soil. Accurate estimation of SOM variability provides critical information especially in precision agriculture. Geostatistics and geographic information system (GIS) are powerful tools for characterizing and mapping the spatial distribution and variability of soil properties. Kriging is a basic geostatistical technique that provides the best linear unbiased estimation for a spatially dependent variable. This method will produce satisfying results if enough sample points are available. Unfortunately, laboratory measurements of the SOM are costly and time-consuming. Artificial neural network-kriging (ANNK) is another geostatistical method that extends kriging of a primary variable to the readily available auxiliary variables based on their relationship with the primary variable. This relationship is captured using an artificial neural network (ANN) model. The residuals of the model were then interpolated using kriging, and added to the prediction obtained from the ANN model. Terrain attributes, derived from digital elevation models (DEMs), are useful for estimating SOM at landscape scale. Topographic indicators including slope, aspect, elevation, and topographic wetness index may be the dominant factors affecting SOM variability in an area with same parent material and climate. Hence, these factors can be used as auxiliary variables for estimating spatial variability of SOM using ANNK. The objective of this study was to estimate SOM spatial variability using ANNK and topographic indices and assess its status in hilly areas of Ghorveh in Kurdistan province (Iran).
A total of 150 soil samples from a depth of 0-15 cm were systematically collected in a grid spaced 2 Km × 2 Km. The SOM content of soil samples was measured in the laboratory. Topographic indicators including slope, aspect, elevation, and topographic wetness index were derived from the DEM. ANN was used to predict SOM variability based on topographic index combinations. The feed-forward network consisted of an input layer, one hidden layer with sigmoid neurons, and an output layer with linear neurons. The network was trained with Levenberg-Marquardt backpropagation algorithm. According to the Kolomogrov’s theorem, the number of nodes in the hidden layer was 2n, in which n is the number of input neurons. The optimal subset of topographic index combinations correlating best with the SOM was selected as the best ANN model. This model was used to generate an initial SOM surface. The residuals of ANN model were interpolated using ordinary kriging (OK) and combined with the initial SOM surface to produce the final ANNK SOM surface. The SOM status map was derived from overlaying of soil texture and SOM maps in four different levels (very low, low, medium and high).
The results of ANN suggested that elevation was the most important variable determining the distribution of SOM across the landscape. Further, aspect was the other variable which had a significant influence on SOM distribution. The selected two inputs ANN model (elevation and aspect) can explain about 33% of total variance of SOM. The cross-validation results indicated that the OK and ANNK techniques can explain about 37 and 89% of total variance of SOM, respectively. The ANNK technique performed better than the OK and ANN techniques since it was able to capture most of the small variations of SOM. The resulting SOM status map indicated a low and very low SOM content in relation with soil texture in most regions surveyed (79%). Low SOM level can be attributed to the erosive processes under Mediterranean climate on hills coupled with intensive and/or inappropriate agricultural practices. Based on the results of this study, proper agronomical and environmental planning such as soil conservation strategy is highly required in this area to restore and increase the SOM content in agricultural soils, combat soil erosion and maintain soil ecological functions and productivity. The SOM replenishment can be achieved in the degraded areas (i.e., low SOM content) by adopting conservative practices such as conservation tillage or no-tillage (e.g., direct seeding), improving land use rotations with forage crops, returning crop residues to soil, growing green manure crops, and supplying the soil with proper exogenous organic matter (compost, manure, sewage sludge, etc.). Furthermore, the results highlighted the potential of ANNK in combination with GIS to provide improved distribution patterns of SOM.

Soil quality is defined as the capacity of a soil to function within different land uses and ecosystem boundaries, sustain biological productivity, maintain environmental quality and promote plant, animal, and human health. Soil quality cannot be directly measured but can be evaluated on the basis of several parameters; the type of parameter to be used depends on research scale and goals. Soil quality indicators (SQIs) are used to evaluate the effect of different management and types of land use on soil quality and can be achieved by easily-measured soil physicochemical properties. Soil quality indicators are measurable characteristics of the soil affecting the soil capacity for crop production or environmental performance. Air capacity (AC), relative field capacity (RFC) and plant available water (PAWC) are the most important indicators. Selection of appropriate input parameters is the first and most important step in predicting SQIs. Feature selection can be defined as the identification and selection of a subset of useful features among the primary data collected. One of the methods for choosing the features is the Pearson coefficient, which shows the correlation between the input variables and target variable. When the coefficient is close to one, there is a strong relationship between the input and the target variable. The features having a correlation coefficients of greater than or equal to 0.9 are considered important and less than that are considered non-important. Decision tree algorithm is one of the prediction approaches in statistics and data mining literature. This algorithm can select the property with the highest separation capability. Working with this algorithm and interpret its results is very straightforward. The aims of this study were to select the best set of input properties influencing SQIs using Pearson correlation coefficient and then model the effect of the input properties by decision tree and multiple linear regression.
In this study, the Pearson correlation coefficient was used for selecting effective soil properties influencing SQIs and these indices were modeled and predicted by the decision tree algorithm with selected input properties. For this purpose, 104 soil samples were collected from the soil surface (0-15 cm depth) of four land uses including a garden with 20 year-old walnut trees, pasture, agriculture and a mountain almond in a semi-arid area in Iran (Rabor region, 29 27′ N to 38 54′ N and 56 45′ E to 57 16′ E). A multiple linear regression (MLR) model was constructed as the benchmark for the comparison of performances. Sensitivity analysis of decision tree model was performed with input variables using StatSoft method. The predictive capabilities of the proposed models were evaluated by the mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) between measured and predicted SQIs values.
The soil properties including porosity, bulk density, clay and sand content for air capacity, porosity and sand, clay and silt content for relative field capacity, and bulk density, electrical conductivity, porosity, and sand, clay and silt content for plant available water were selected as important input parameters. In addition, the values of r2 for the decision tree model for air capacity, relative field capacity and plant available water were 0.95, 0.84 and 0.85, respectively, while the r2 values for multiple linear regression for AC, RFC and PAWC were 0.63, 0.62 and 0.61, respectively. According to the evaluation indices, it appears that the conventional regression model was poor in predicting SQIs. Therefore, conventional regression techniques (i.e., multiple-linear regression) may not be reliable for predicting the SQIs. The results of sensitivity analysis for decision tree model showed that porosity and bulk density for air capacity, porosity for relative field capacity and bulk density for plant available water had the greatest influence.
This research work provided a basis for predicting soil physical quality indicators and identifying important parameters impacting these indicators in agricultural soils, grassland and forests in semi-arid regions which can be generalized to other areas. Further studies are needed to assess the effects of selected input variables under different conditions.

Cadmium is considered to be one of the heavy metals with the highest toxicity, because it has high activity and a relative high dissolution rate in water and in living tissues. In recent years, due to the high volume of natural resources pollution and the inefficiency of conventional physicochemical methods for refining these resources and the occurrence of environmental crisis, bioremediation process has been at the forefront. Microbially induced calcite precipitation (MICCP) has been considered as a novel solution for these problems, and several bacterial species have been already utilized for MICCP. MICCP based degradation of urea occurs through the ureolytic pathway. Urease (urea amidohydrolase) is an enzyme that hydrolyzes urea into one mole of carbonate and two moles of ammonia per mole of urea. In this aspect, microbial mineral precipitation products such as calcite can strongly adsorb heavy metals on their surfaces and incorporate heavy metal ions into their crystal structure. Some studies have reported MICCP-based sequestration of soluble Cd via coprecipitation with calcite was useful for Cd bioremediation. Several bacterial species have been utilized for MICCP. The endospore forming bacteria Sporosarcina pasteurii have been shown to produce high levels of urease and have therefore been extensively studied. Sporosarcina pasteurii has attracted significant attention for its unique feature of calcium carbonate precipitation, which can be easily controlled. So, In the present study the ability of Sporosarcina pasteurii bacterium has been investigated in the remediation of Cd(II) in Cd-contaminated sandy soil based on MICCP method.
Sporosarcina pasteurii (PTCC 1645) was procured from Microbial Bank of Iran (Central Collection of Industrial Fungi and Bacteria, Karaj, Iran). The bacterial strain was inoculated into NB (nutrient broth) media containing 2% urea and 25 mM CaCl2 (NBU media) and then incubated at 37◦C for 6 days. The urease activity was determined at regular time intervals by measuring the amount of ammonia released from urea according to the phenol-hypochlorite assay. Minimum inhibitory concentration (MIC) test was performed to determine the lowest concentration of cadmium chloride, which prevents the growth of bacteria. Sporosarcina pasteuriiwas inoculated into NBU media supplemented with 0.5, 1,2,4,8 and 10 mmol l-1 Cd and incubated at 37◦C, 130 rpm for 50 hours. Control flasks without adding Cd were also incubated. Bacterial growth was determined in terms of optical density (OD) by measuring absorbance at a wavelength of 600 nm at regular time intervals (0, 10, 20, 30, 40 and 50 hours) and colony-forming units (CFU) were also counted. The cadmium removal in 0.5, 1 and 2 mM cadmium solutions (based on MIC) was measured.A sandy soil from a depth of 0 to 30 cm was sampled. The soil was polluted with 10, 20, 40 and 50 mg/kg of cadmium and incubated in room temperature for two weeks. After incubation time, the cadmium remediation studies were performed at 30◦C in the beakers containing 100 g of sterilized dried contaminated soils and 200 mL of overnight grown of Sporosarcina pasteurii (~ to 107cfu ml−1) in NBU media. For each treatment corresponding control were included with the same condition but without bacteria.After 7 days of incubation, urease and dehydrogenase enzymes activity and concentration of cadmium in soluble exchangeable and carbonate fractions were measured. The concentration of cadmium in iron-manganese oxides, organic matter and residual fractions in concentration of 50 mg/kg cadmium was also determined according to the continual extraction procedure of Tessier et al. (1979).
The amount of released ammonia by ureolytic activity of Sporosarcina pasteurii increased up to fourth day and then became almost constant.Optical density in different concentrations of cadmium decreased in comparison to control treatment after 48 hours. The minimum inhibitory concentration of cadmium for bacteria growth was 2 mM as determined by colony counting after 48 hours of incubation. Cadmium removal efficacy from solutions containing 0.5, 1 and 2 mM of cadmium was 99.6, 99.8 and 99.8%, respectively. The amounts of urease and dehydrogenase activities in the presence of bacterium were significantly higher than control treatments (P≤0.05). The results of the fractionation of contaminated soils in the absence of Sporosarcina pasteurii showed the distribution of cadmium as organic matter.

Assessing the soil quality of agricultural land is essential for the economic success and sustainability of the environment in developing countries. Recently, there are many types of methods for assessing soil quality, each of them uses different criteria. Considering that Qazvin plain is one of the most important regions of agricultural products in Iran as well as Middle East, so the assessment of the soil status using quantitative models of soil quality can be used as an indicator of the status of soils in relation to sustainable agriculture, optimal utilization of resources Natural and better land management. Among the quantitative models of soil quality index, cumulative model integrated quality index (IQI) and Nomero (NQI) index can be mentioned. Therefore, this study intends to evaluate the best quantitative and quality index model by examining and comparing two methods of selecting the appropriate criteria, Total data set (TDS) and Minimum (MDS) and the second order soil quality index, integrated quality index(IQI) and Nomero (NQI) index in Qazvin plain lands.
Material and The study area with 25220 hectares is located in east of Qazvin Province. The average annual precipitation is 275 mm and the soil moisture and temperature regimes are Thermic, Dry xeric and Weak Aridic, respectively. A total of 76 samples from the depth of 0-20 cm of the soil surface were studied and based on uniformity, soil type and land use. In this study, four types of criteria that affect the quality of soil in terms of their performance, including: upper limit, lower limit, optimal limit and descriptive function were selected. To qualify (normalize), the upper limit, lower limit and peak limit were selected. In the following, the Total Data Set (TDS) and the Minimum Data Set (MDS) set of data were used. In the TDS method, all of the measured characteristics (a total of 19 physicals, chemical and biological properties of the soil) were considered. Then, the degree of soil quality indices was determined based on the combination of TDS and MDS criteria and the final NQI and IQI quality indices.
Result and Dissection: Comparison of soil types in the region showed that the Aridisols had good, moderate and poor quality (19.35% of soil with good quality, 67.76% with moderate quality and 12.94% with poor quality), Entisols have good and medium quality (53.21% of the soil with good quality and 46.79% with moderate quality) and Inceptisols have very good, good, moderate and poor quality (96.9% Soils with very good quality, 66.73% with good quality, 15.85% with moderate quality and 13.44% with poor quality).
According to the TDS standard and the NQI model, the soils with qualities I, II and III were 30.67%, 66.86%, 47.2% of the total soils of the area (lands with poor quality soil quality were not observed in TDSNQI method). Therefore, according to this method, Aridisols has a very good, good and medium quality (13.26% of the soil with a very good quality rating, 73.88% with a good quality and 12.84% with a moderate quality grade), Entisols with The good quality (100% of the soil with good quality degree) and Inceptisols have a very good and good quality (28.11% of the soil with a very good quality grade, 71.88% with a good quality grade). The results of quantitative soil quality by using the MDS standard method and IQI model were showed, soils with very good, good, moderate and poor degree are 2.45, 16.45, 48.93 and 46.3 percent of total land area respectively.
The results of the combination of the MDS and the NQI model also showed that the soils with a very good, good and average grade are 30.67%, 66.86% and 47.2% of the total land, respectively. Also, the results of the combination of the MDS and NQI model showed that the soils with very good, good and average quality are 30.67%, 66.86% and 47.2% of the total land area respectively. The results of the evaluation based on 4 indicators showed that good quality (II) was prevalent in the studied soils and accounted for about 47% of the total area studied in Qazvin plain lands. The map of distribution of soil quality degrees, the distribution of soil degrees is relatively similar to all of four combination methods, the choice of criteria and model. By examining the linear relationship between the indices obtained from TDS and MDS criteria and the IQI and NQI indexes, it is observed that the correlation coefficient is more and more reliable than the NQI model when used in the IQI model (R2 = 0.77). So the highest correlation coefficient we observed two methods for selecting the TDS and MDS criteria when using the IQI model. In general, the results of this study indicate a better performance of the MDS criteria than TDS.
Therefore, the main results of this study suggest using the IQI model with the MDS selection method as the starting point in the global standard path for future studies. Special attention should be paid to the criteria chosen by the MDS. In addition, conducting a series of research into the future in order to modify the MDSIQI model can make it more relevant to international standards.

Soil is a key resource that contributes to the earth system functioning as a control and manages the cycles of water, biota and geochemical and as an important carbon reservoir. Soil organic matter is one of the most important factors in soil quality assessment and having relationship with physical, chemical and biological properties of soil. Carbon sequestration in plant biomass and soils is the simplest and the most economically practical solution to reduce the risks of atmospheric carbon dioxide. Little information is available about the effects of grazing management on sequestration of carbon in Khuzestan Province pastures. Therefore, this study was conducted to evaluate the effects of grazing exclusion on the amount and forms of carbon management and carbon sequestration with economic view in some pasture soils from Peneti Plain of Izeh area and Dimeh regions of Ramhormoz in Khuzestan Province.
This study was conducted in two regions including Izeh and Ramhormoz representing different climates, vegetation and soil types of southwestern Iran. We selected two grazing treatments including ungrazed and grazed pastures in each region. The first area includes rangeland ecosystem in Izeh city between 31° 57ʹ 8ʺ to 31° 58ʹ 20ʺ N and 49° 41ʹ 11ʺ to 49° 42ʹ 33ʺ E. The region has a typical temperate continental climate, characterized by dry summers and cold winters. The mean annual rainfall is 623mm. The mean annual temperature (MAT) is 19.2 °C, and the mean monthly air temperature varies from -0.6 °C in January to 42.4 °C in July. The second area (Ramhormoz) is located between 31° 7ʹ 44ʺ to 31° 9ʹ 11ʺ N and 49° 29ʹ 13ʺ to 49° 28ʹ 52ʺ E. The mean annual rainfall is 200 mm and the mean annual temperature (MAT) is 27.2 °C, and the mean monthly air temperature varies from 4.2 °C in January to 51.6 °C in July. For each climate region, grazed and ungrazed sites were located on the same soil series with similar aspect and slope. Then, random soil samples were taken from the surface and subsurface in 15 points. After air drying the soil samples and passing them through a 2 mm sieve, physical, chemical properties of the soils were measured.
The soil of both studied regions are non-saline, calcareous, and alkaline and have relatively heavy texture. The results showed that the studied characteristics in four study areas had low and moderate coefficients of variation. This suggests that the contribution of edaphic and environmental factors to explain variation in the data is not high. Also, grazing management has increased soil organic matter of surface and subsurface soil, but despite the increase in organic matter contents of subsurface soils the difference was not statistically significant. The effect of management practices, in order to have a significant effect to lower parts of the soil, it requires a longer period management. Comparing the biomass upon non-grazing (405 and 42 gm-2 in Izeh and Ramhormoz respectively) and grazed (117 and 17 gm-2) areas, indicates a good condition of vegetation in the non-grazing and the effectiveness of enclosure in rehabilitation of pastures in the study area. However, due to more rainfall rates, the amount of biomass produced in Izeh is higher.
The carbon management index in the study areas, as well as the depths of the study is high, indicating recovery of soil carbon and improving its quality. Also, based on carbon sequestration in the study area, non-grazing was one of the most proper and efficient management practices, which improved soil quality. Accordingly, it seems that non-grazing practices should be considered as one of the major programs in renewable natural resources plans. On the other hand, estimation of the economic value of carbon sequestration in the pastures has been remarkable, and increased 17 and 12.7% of the value of carbon sequestration in Izeh and Ramhormoz regions under the management of the exclusion. Therefore, the management of rangelands should be directed to allow for their ecologic performance and capacity considering the environmental economy of rangelands so that in broad terms, the justification for the enhancement and maintenance of the economic equilibrium can be viewed as a guaranty of implementing the range managements resulting in sustained development.

Organic matter is considered as the main element for soil fertility by improving the condition of agglomeration, porosity and soil permeability. One of the most useful ways to use plant debris is to turn it into Biochar and Hydrochar. Biochar is a kind of coal produced from plant biomass and agricultural waste that is burned in the presence of low oxygen content or its absence. The hydrothermal process involves heating the biomass or other materials in a pressurized in the presence of water at a temperature between 180 and 250 C, and the result of this reaction is coal (Hydrochar) and soluble organic matter. Biochar and Hydrochar have several advantages such as climate change mitigation through carbon sequestration, soil cation exchange capacity (CEC) increasing, soil fertility, plant growth and root development, improved soil structure and stability, increased soil moisture storage capacity and soil pH adjustment. Coarse soils have large pores and they have low ability to absorb the water and nutrient. The aim of this research was to determine the optimum temperature of wheat straw Biochar and Hydrochar production, and to investigate the effect of these materials on bulk density, total porosity and moisture curve of Sandy Loam soil.
In order to produce biochar, at first the wheat straw was washed and dried in the oven. Then it was grinded and was made at different temperatures (200 to 600 C) inside a furnace for four hours. Similar to biochar, for producing hydrochar, after washing and drying the wheat straw it was grinded into particles ranges from 0.5 to 1 mm. Then it was placed in a stainless steel autoclave with deionized water. The autoclave was heated at different temperatures between 140-230 C for four hours. The optimum temperature for producing of biochar and hydro-char was determined by using stable organic matter yield index (SOMYI), and it was used in this study. The pH and EC of the biochar and hydro-char samples were measured by combining 1 g of a sample with 20 mL DI water. The cationic and anionic exchange capacity were determined by replacing sodium nitrate with hydrochloric and potassium chloride (Chintala et al., 2013). Surface area was obtained using methylene blue method. A CHNSO Elemental Analyzer (Vario ELIII- elementar- made in Germany) was used to determine the content of C, N, H, S and O in the samples. Potassium and sodium content were measured by flame photometer and calcium and magnesium were measured by titration with EDTA. Biohchar and hydrochar treatments were applied at three levels of 2, 5 and 10 mg / kg soil in three replications in 21 lysimeter. The bulk density, total porosity and moisture curve of soil were measured after four-month irrigation period.
According to the calculated value of stable organic matter yield index (SOMYI) at various temperatures in this study, the maximum thermal constancy of wheat straw biochar was 16.20 at temperature of 300 C and for hydro-char was obtained as 6.13 at the temperature of 200 C. So, the temperatures of 300 and 200 ̊C were determined as the optimum temperature of sustainable carbon biochar and hydro-char production and were used to continue the experiments of this study. The results showed that addition of HW2, HW5, HW10, BW2, BW5 and BW10 to soil compared to control treatment significantly decreased the bulk density of the soil, 8.97, 11.77, 15.17, 7.9, 10 and 13.10 percent respectively. Also, results showed that addition of HW2, HW5, HW10, BW2, BW5 and BW10 to the soil as compared to control treatment increased soil porosity by 8.8, 11.48, 15.77, 6.48, 9 and 22.13 percent, respectively. The reason for reducing the soil bulk density and increasing the total porosity of soil can be due to the mixing of the soil with materials with a lower bulk density and the effect of increasing the organic matter of the soil due to the use of Biochar and Hydrochar. Based on statistical analysis, wheat straw Biochar and Hydrochar had a significant effect (P

Glomalin is a specific glycoprotein produced by the fungi belonging to phylum Glomeromycota and plays a key role in soil carbon and nitrogen storage. This also has a significant role in the stable aggregates formation and establishment of microbial communities in soil. Assimilated plant C which is allocated to the mycorrhizal fungus, appears as a recalcitrant glycoprotein (glomalin) in cell walls of hyphae and spores. Considering global warming due to increasing greenhouse gases, this phenomenon cab be important in carbon sequestration and reducing CO2 in atmosphere. Chemical fertilizers can affect symbiotic relations of these fungi, which in turn affect glomalin production.
In a factorial completely randomized design with three replication, clover plants (Trifolium repense L.) were included with Rhizophagus irregularis and/or Rhizobium leguminosarum bv. Trifolii. Four levels of nitrogen (0, 2, 6 and 10 mM as nitrate) in Newman & Romheld nutrient solution were applied to the pots containing 1.5 kg sterile sand. The pots were daily irrigated with nutrient solution containing the above-mentioned levels of nitrogen. Clover plants were excised after 12 weeks of growth. Fine roots were cleaned with %10 KOH and then stained using lactoglycerol trypan blue. Root colonization percentage was determined by grid line intersections method (GLM) described by Norrif et al (1992). For glomalin extraction, hyphal or root samples were autoclaved at 121 ⁰C with 50 mM sodium citrate buffer for 60 min in three cycles. Sand glomalin (SG) and root glomalin (RG) were measured by Bradford method after extraction. Nitrogen concentration in shoot and root was measured according to the standard method.
By increasing nitrogen level, the SG significantly decreased (p Carbon sequestration via glomali synthase by AM fungi is an important pathway for capturing CO2 from atmosphere. Field management measures help AM development of glomalin production. Based on our results, co-inoculated plants with AM and rhizobuim seem to positively affect the production of this glycoprotein. On the other hand, SG decreased significantly by increasing nitrogen concentrations in the nutrient solution. RG, however, increased significantly as a result of increased nitrogen in both fungal inoculations. The highest amount of RG was recorded in the co-inoculated plants with 10mM level. Glomalin synthesis by the fungi is positively affected by the soil nitrogen availability. Nitrogen is the main constituent of this glycoprotein. Plant photosynthates are translocated to the fungal organs via roots and mainly utilized for glomalin synthesis in hyphal and spore cell walls. During this process, nitrogen plays an important role as a constituent of the glycoprotein. The Bradford method was used for glomalin determination in this study. The method is not specific for glomalin and can also measure other glomalin related proteins and glycoproteins. Other proteins increased by N fertilization can hence be measured based on Bradford method. Once plant assimilates are translocated to the fungi, they may be transformed to the nitrogenous compounds if sufficient nitrogen sources are available. Accordingly, a considerable amount of fixed carbon is assimilated in fungal organs and soil particles. It can be concluded that carbon sequestration by arbuscular mycorrhizal symbiosis in terrestrial ecosystems can be improved by N fertilization at optimum level. In addition, the presence of rhizobium bacteria can meet the nitrogen requirement of plants through biological stabilization of nitrogen.

Estimating crop water requirement, crop yield and their temporal and spatial variability using crop simulation models are essential for analysis of food security, assessing impact of current and future climates on crop yield and yield gap analysis, however it requires long-term historical daily weather data to obtain robust predictions. Depending on the degree of weather variability among years, at least 10–20 years of daily weather data are necessary for reliable estimates of crop yield and its inter-annual variability. In many regions where crops are grown, daily weather data of sufficient quality and duration are not available. In this way, gridded weather databases with complete terrestrial coverage are available which require comprehensive validation before any application. These weather databases typically derived from global circulation computer models, interpolated weather station data or remotely sensed surface data from satellites. The aims of this study were to evaluate differences between grided AgMERRA weather data and ground observed data and quantify the impact of such differences on simulated water requirement and yield of rainfed wheat at 9 different locations in Khorasan Razavi province.
AgMERRA dataset (NASA’s Modern-Era Retrospective analysis for Research and Applications) was selected as the girded weather data source for use in this study because it is publically accessible. We evaluated AgMERRA weather data against observed weather data (OWD) from 9 meteorological stations (Torbat Jam, Torbat Heydarieh, Sabzevar, Sarakhs, Ghoochan, Kashmar, Gonabad, Mashhad, and Neyshabour) in Khorasan Razavi province. For each weather variable (solar radiation, maximum temperature, minimum temperature, precipitation, and wind speed), the degree of correlation and agreement between OWD and AgMERRA data for the grid cell in which weather stations were located were evaluated. The intercept (b), slope (m), and coefficient of determination (r2) of the linear regression were calculated to determine the strength and bias of the relationship, while the root mean square error (RMSE) and normalized root mean square error (NRMSE) were computed to measure the degree of agreement between data sources. Crop water requirement or actual crop evapotranspiration (ETc) under standard condition was computed using CROPWAT 8.0. The CSM-CERES-Wheat (Cropping System Model-Crop Environment Resource Synthesis-Wheat) model, included in the Decision Support System for Agrotechnology Transfer (DSSAT v4.6) software package was used to calculate rainfed wheat yield. For each location in this study, rainfed wheat grain yield and water requirement were simulated using ground-observed and AgMERRA weather data and outputs were compared with each other.
The results of this study showed that AgMERRA daily maximum and minimum temperature and solar radiation showed strong correlation and good agreement with data from ground weather stations. AgMERRA daily precipitation had low correlation and good agreement (mean r2= 0.34, RMSE= 2.25 mm and NRMSE= 4.94% across the 9 locations) with OWD daily values, but correlation with 15-day precipitation totals were much better (mean r2 >0.7 across the 9 locations). There was reasonable agreement between a number of observed dry and wet days with AgMERRA compared to OWD. Results indicated that coefficient of variation of simulated water requirement and yield using AgMERRA weather data was remarkably similar to the degree of variation observed in simulated water requirement and yield using OWD at all locations (distribution of CVs in simulated water requirement and yield using AgMERRA weather data were within ±5% of the CV calculated for simulated water requirement and yield using observed weather data) except Torbat Jam, Torbat Heydarieh and Gonabad for water requirement and Mashhad, Kashmar and Ghoochan for yield. There was good agreement between long-term average yield simulated with AgMERRA weather data and long-term average yield simulated using observed weather data. For example, the distribution of simulated yields using AgMERRA data was within 10% of the simulated yields using observed data at all locations. Using AgMERRA weather data resulted in simulated crop water requirement that were not in close agreement with crop water requirement simulated with ground station data at two location including Gonabad and Torbat Heydarieh.
These results supported the use of uncorrected AgMERRA daily maximum and minimum temperature and solar radiation in areas that their weather stations only have a few years of daily weather records available or areas without weather station. Considering the advantage of continuous coverage and availability, use of AgMERRA dataset appears to be a promising option for simulation of long-term average yield and water requirement, as well as for assessing impact of climate change on crop production and also estimating the magnitude of existing gaps between yield potential and current average farm yield in Khorasan Razavi province. But they are not very reliable for accurate simulation of water requirement and yield in a specific year and estimate their inter-annual variation.

After the industrialization period, when humankind was able to multiply the speed and quantity of its production, the planet faced a new crisis, although this crisis was less known until the late 20th century. From the last years of the 20th century, the term of change has been added to the scientific literature of the world. The main reasons are the change in the phenomenon of blockage of greenhouse gases, especially carbon dioxide in the atmosphere of the planet. In this research, while introducing CMIP models under RCP scenarios, modeling of groundwater fluctuations using the MODFLOW numerical code is dominated by GMS software. The LarsWG software was used for statistical exponential measurements. Groundwater changes in the study area (Hashtgerd) are of great importance to the people of this region due to the proximity of the area to Tehran and the availability of horticultural products. The main objective of this research is to investigate the future fluctuations of groundwater in Hashtgerd plain over the next period from 2015 to 2040 using the HADGEM2 model under two scenarios RCP2.6 and RCP8.5. Innovations of this scheme include the use of the HadGEM2 climatic model to investigate the variation of underground water fluctuations.
In order to study and model the aquifer using the finite difference method and the Modflow model, the first step in the spatial division of the study area into a square or rectangular cell or network. Therefore, using topographic maps 1: 25000 of the Army Mapping Organization, the topographic layer was extracted and digitally extracted. Based on the 14 piezometers in the aquifer area, the potential lines were plotted and entered into the model as the initial staging level. In order to determine the thickness of the saturation layer, based on the geophysics in the aquifer, the bedrock was also introduced into the model network. In addition, to accurately evaluate the design of the network and its cells in the aquifer area, the hydrodynamic, feeding and evacuation characteristics of the aquifer within a cell are assumed the same. It is necessary to select smaller dimensions in areas where hydrological and hydrodynamic characteristics of the aquifer are significant at low distances, or that parts of the aquifer are studied for specific cases. Otherwise, it is not necessary to reduce the size of the cells. According to aquifer conditions, cells with 500 * 500 square meters area were selected. Calibration and verification were used in two steady state (one year data) and non-residual (full statistical period), each used for estimation of hydraulic conduction values and storage factor.
After calibration of the groundwater model in steady state, the hydraulic conductivity of the aquifer in different locations is in the range of 0.5 to 19 meters. In order to run the model in an unstable state, time intervals must be defined for the model. The time interval in modeling is defined in terms of both the stress period and the time step which must be defined before the definition of other parameters such as power and discharge conditions in unstable conditions. In the Hashtgerd plain, the length of the one-month stress period and the monthly measurements of the water level in piezometers, the time step were also selected for a month. Therefore, in order to simulate the groundwater flow, the study area for the unstable state was defined from October 2007 to late December 2013 for six years and three months for the model and the conceptual model was changed from unstable to unstable state. Therefore, data on surface water in rivers, the feeding of rainfall and return water from wells, pumping rates from wells, hydraulic load of boundary conditions, and groundwater surface data in piezometers were introduced monthly into a conceptual model. In addition, in an unstable state, the specific discharge parameter must be defined for the model. After implementation of the model in unstable conditions, special discharge rates were optimized. The amount of specially tailored discharge in the study area varies from 0.001 to 0.27. It should be noted that at this stage, the resource and expenditure statistics of 2008 were used. After constructing groundwater and surface water models for the base period, maintaining the existing coefficients and parameters, changing the rainfall and temperature values for the future period, first, the amount of surface water flow changes for the future period and then using the amount of nutrition The groundwater entered the model. Future modeling showed that surface runoff variations would be about 7 percent lower for RCP 2.5 and 19 percent for the RCP scenario of 8.5. Nutrition also includes nutrition from the rainfall. For the upcoming period, changes in land use and land use counts are considered constant. With rainfall changes under the two scenarios, the aquifer is projected to drop by about 12 m by 2040 for the RCP scenario of 2.6 and for the RCP scenario of 8.5 by 18 m.
After simulating the meteorological component by the HadGEM2 model introduced in AR5 using LarsWG software and applying future changes in rainfall and temperature on the IHACRES model and ModFlow model under GMS software for the two scenarios RCP2.6 and RCP 8.5, respectively. Due to the temperature rise of 1.8 ° C in the worst case and different rainfall variations in different months, it was found that runoff would be about 15% for the first scenario and 20% for the second scenario. The same factors are because the level of penetration into groundwater through snow melting as well as precipitation along with surface runoff is one of the important factors in feeding to the aquifer. Given the constant maintenance of groundwater withdrawals in the coming years, it was found that the aquifer will drop by about 12 m for the scenario RCP 2.6 by 2040, and for the RCP 8.5 scenario, it will drop by 18 m.