نشریه آب و خاک
سال سی و سوم شماره 5 (پیاپی 67، آذر و دی 1398)

In arid and semi-arid areas, water can be a limiting factor for plant growth and agricultural yields. Considering limited water resources in arid and semi-arid climate of Iran, deficit irrigation is one of the strategies for efficient use of water and increasing water use efficiency in agricultural lands. Deficit irrigation (DI) is a suitable solution to gain acceptable and economic performance by using minimum amount of water. The Partial Root- zone Drying (PRD) irrigation is a new improvement in deficit irrigation in which the half of the root zone is irrigated alternatively in scheduled irrigation events. The plants with PRD irrigation method can, therefore, have different root system in comparison with other irrigation methods. At this method the plant’s condition would be OK by withdrawing water from wet side, and the roots at the dry side can release abscisic acid hormone which decrease the stomatal conductance and consequently the water use efficiency would increase. Also, by using proper irrigation management in farm, we are able to utilize water, soil and fertilizer to produce high yield and quality products. Drip irrigation is considered one of the most efficient irrigation methods. One of the major advantages is its ability to apply water to the soil as often as desired and in smaller quantity than the other irrigation methods. Drip irrigation has been practiced for many years for its effectiveness in reducing soil surface evaporation and it has been widely used in horticultural crops in both greenhouse and open field.

In order to compare two deficit irrigation methods on plant growth characteristics of Rosmarinus officinalis L., a field experiment was carried out during 2016 growing season at an experimental farm in Kerman Municipality seedling production station. The experimental treatments were arranged as randomized complete block design with three replications. The irrigation regimes consisted of full irrigation (FI-100), regulated deficit (RDI75 and RDI55) and partial root zone drying irrigation (PRD75 and PRD55). In this study, drip lines were placed on the soil surface at a distance of 15 cm from the plant and plant rows were placed between drip lines. The irrigation interval was 4 days for all treatments. In the full irrigation and regulated deficit irrigation treatments, the plants were irrigated from two sides for every irrigation. In the PRD, one of two neighboring drip line was alternatively used for irrigation. The irrigation interval was 4 days for all treatments. Dry weight, leaf area index (LAI), number of shoots, plant height, water productivity, root fresh weight, root depth and root volume were measured. Since the highest essential oil of rosemary is at 50 percent of flowering time, the above-mentioned indices were measured at the middle of flowering (190 days after planting) by removing the side rows in each replicate and half a meter from the beginning and end of each row. As a marginal effect, 10 plants were randomly selected and sampled from two middle rows, each replicate of each treatment. The harvested bushes were dried at 25 °C for three weeks and then the dried weight of the vegetative organs was measured. Moreover, the number of 10 plants selected from each treatment was accurately counted to determine the number of shoots. Data were analyzed statistically using SAS Statistical software. Treatment means were compared using LSD test.

The results showed that highest herbage dry weight (145.3 g) and leaf area index in different stages of growth were under full irrigation treatment in which no significant difference between this treatment and 75 percent water replacement in partial root zone drying was observed. The highest number of shoots (128.7) and plant height (68.4 cm) were also obtained by full irrigation treatment and there was significant difference between this treatment and other treatments. However, the highest water productivity (2.06 kg/m3), root fresh weight (3.8 g), root depth (16.4 cm) and root volume (2.4 cm3) were found in 75 percent water replacement in partial root zone drying.

According to the results, 75 percent water replacement in partial root zone drying irrigation treatments, in addition to saving water consumption, provides better use of soil moisture and sunlight. Thus, this treatment can be considered as a suitable approach to cope with the water crisis and achieve a sustainable agriculture.
Keywords: Drip irrigation, Drought stress, Leaf area index, Medicinal plant, Rosmarinus officinalis, Water productivity

Understanding water budget components is crucial for making decisions regarding water resources planning and management. Surface water–groundwater interactions are commonly investigated at the river reach scale and generally classified as connected or disconnected type systems. Connected systems are either gaining surface water system, where groundwater discharges through the streambed to contribute to streamflow, or losing surface water system which loses (or recharges) water to the local groundwater system. Disconnected systems are defined by an unsaturated zone beneath the surface water system which loses water at a rate related to the hydrogeological properties of the streambed and the aquifer. These interactions have significant implications for both water quantity and quality. Seepage of fresh groundwater into a river can be important in maintaining flows during extended dry periods. This can be critical for supplying the needs of surface water users such as irrigators as well as for aquatic ecosystems. Pumping from an aquifer near a river can dramatically change the amount of this base-flow to the river. In contrast, if the groundwater is contaminated, increased groundwater discharge can have a negative effect on river water quality. The Bojnourd catchment is located in North Khorasan province. The catchment covers an area of about 1265.8 km2. The main river in this area, Firouze River, is approximately 10 km in length, and is hydraulically connected to the Bojnourd alluvial aquifer. The alluvial aquifer of Bojnourd plain with 65.2 km2 area is mostly covered by urban area. Hence, effective management of water quantity and quality issues in the Bojnourd catchment requires quantifying flow between surface water and groundwater. Furthermore, conveying water from the outside of basin caused water table to rise which made some problems for urban buildings and infrastructures. Therefore, the river and aquifer interaction needs to be studied more comprehensively.

Numerous techniques and methods are available to describe and quantify the flow between surface water and ground water. This study combined two methods, numerical modeling using MODFLOW code and reach measurements, to quantitatively evaluate groundwater/surface water interactions under highly transient conditions. The groundwater flow system of the study area was conceptualized based on borehole logs, pumping tests, and available hydrogeological and geophysical information. Moreover, field work, including measuring streamflow in three seasons, was carried out to conceptualize and quantify the groundwater/surface water interactions. Following the conceptual model, the numerical model was developed to simulate flow through the system. The model grid had 1274 active cells with a uniform cell spacing of 250×250 m. The water exchanges between the main regional river, Firouze river, and Bojnourd aquifer was simulated using the River (RIV) package. Both hydraulic head target and flux target were used to calibrate the model. The head targets were compiled from the monitoring network which contains 11 observation wells. The flux targets were located in three measurement points along the Firouze river. The data obtained from the fieldwork were used as observed values for the groundwater/surface-water exchanges. The transient model was calibrated and validated for 15 hydrological years, i.e. from 1 October 2001 to 1 October 2016

Model performance was evaluated using root-mean-square error (RMSE). The model results were in agreement with corresponding observed data, including groundwater heads and measured groundwater/surface-water exchanges. The RMSE values during calibration and validation periods were 0.83 m and 1 m, respectively. Analyzing water balances resulted from transient simulation showed that Firouze river is gaining in some reaches and losing in other reaches. In losing reaches, the total flux into the aquifer is 6.4 MCM per year. In gaining reaches, the volume of groundwater discharges through the streambed is about 4 MCM per year. Furthermore, the effect of several management scenarios, including continuing the existing condition, turning the domestic wells off and implementing a sewage system by 2025, on groundwater heads and groundwater/surface-water exchanges was examined using the numerical model. Results showed that by implementing the sewage system, the volume of water discharged to the river would decrease, but it will prevent aquifer and river contamination caused by sewage water. 

In this study, groundwater budget components in Bojnourd aquifer including groundwater/surface-water exchanges were calculated. The results showed that understanding of these surface water-groundwater interactions, which has been ignored in previous studies, is important for effective management of water quantity and quality issues in Bojnourd plain. Moreover, the methodology used in this study including numerical modeling and measuring flow at multiple points along the stream is effective and easy to apply to estimate the direction and magnitude of seepage on a stream reach basis.

Despite being helpful to explore and analyze large multidimensional datasets, visualization Techniques have been rarely considered in hydrology. One of the techniques is Pixel-Based (Raster-Based) graphs. Pixel-based graph is a graphing technique that maximizes displayed information using a pixel or raster-based approach.

This study  two types of raster-based graphs, including Raster-Hydrograph and Raster Hyetograph were evaluated, for Gamasiyab Karstic Spring located in Nahavand. The graphs were drawn by applying discharge and rainfall daily information of gamasiyab spring in 1969-2018. The MATLAB was employed to draw the graphs. To calculate the spring discharge, recorded data from Sang Sorakh and Variane Canal station were used. The data gathered for Sang Sorakh and Variane were recorded from 1969 and 2005, respectively. Thus, the spring discharge was the summation of both stations. The maximum, minimum and average discharge was, respectively, 37.97, 0.3 and 4 m3/s. It is important to note that the basin area is about 60 Km2.  

By applying the graphs, six different phenomena were investigated:Snowmelt: According to the raster hydrograph of the Gamasiyab spring, snowmelt occurs in the first 200 to 300 days of year (e.g. early April to late July). According to this graph, during the recent years, snowmelt period shortened. As of 2004, that the number of snowmelt days showed a considerable reduction as compared to the previous years. This issue has become more intense for the years after 2013 indicating a change in the spring discharge regime.Drought: According to the raster hydrograph of the Gamasiyab spring, droughts were observed in 1998 and 1999.Storm Flow: According to the raster hydrograph of the Gamasiyab spring, a storm flow was observed in the middle of April,1986. Storm flows were also observed in late February of 1986 and 2005, and the late March of 2016.Dry Year: Dry Year is a year that the discharge is less than the average. 2008 and 2009 were the examples of dry years. In addition, 2014 was one-year low water.Dry Month: Determine dry months are used for baseflow separation. In dry months, discharge is due to baseflow, and rainfall and snowmelt play a very small role in the discharge.Monthly changes: Monthly changes happen when rapid changes in discharge are observed from one month to another. For example, the discharge regime suddenly changes from a dry to wet condition. According to the raster hydrograph of the Gamasiyab spring, the monthly changes in April and May, 2014 were observed. It was observed that the rainfall was almost equal to 0 in June to September. In the other words, rainfall period is from early November to early June. Maximum rainfall is in April and May.Better results can be achieved by using both Raster Hydrograph and Raster Hyetograph. Discharge of Gamasiyab spring is affected by snowmelt and groundwater flow since late May to late September, and rainfall has no effect on spring discharge in this period. According to these graphs, it can be also concluded that springtime rainfall was impacted with one-month lag time. According to raster hydrograph, the minimum discharge occurs in October, however, the area receives rainfall during October based on raster Hyetograph. Therefore, the discharge increase in the November can be attributed to the precipitation falling during October.

Main benefits of this graphs are: 1. a way to view large datasets.  2. Quickly review and interpret. 3. Develop new types of products. 4. Cost and time efficiency. This method is able to show systematic error, missing data, outliers, comparison different places, potential new products. Results show that the snowmelt period in Gamasiyab spring decreased from 1969 to 2018. This period shortened from 100 to 30 days per year. The year of 2008 was the driest year during the statistical period of the spring, and a drought was also observed in 1998. According to raster hydrograph, the driest month was found to be October. Determining this month is very useful for base flow separation. One can conclude that these graphs including large amount of information, accelerate the processes of scanning and interpretation.

Population growth and water resource constraints make optimal operation of available resources important. Considering the utility of the stakeholders and the physical limitations of the problem, the optimal allocation of water resources is, therefore, necessary. Among the proposed strategies, the game theory is one of the methods used to improve water resources management. Also, in order to achieve the optimal and fair allocation, a model and method should be selected in accordance to the conditions. Our main purpose was to study the optimal water allocation from the dam reservoir by increasing the overall profitability of the system through forming a coalition as well as increasing the profits of each water users participated in the coalition. Increase in profits will be possible without the need for any additional costs and only with the change in the operation management. Integration of Genetic Algorithm optimization model with Shapley Crisp game theory can be considered as the innovation of this research work applied to optimally allocate water from Shahid Rajaee Dam reservoir to downstream needs.

In this study, a new methodology based on crisp Shapley games is developed for optimal water allocation from the dam reservoir. First, the standard operation policy was used to determine the volume of available water. Then, the optimization model of the Genetic Algorithm was employed for initial allocation considering an equity criterion. The Crisp Cooperative Game Theory was then applied for secondary optimization of water allocation among stakeholders. The possible coalitions for increasing the overall system profits were formed using the Shapley method and the profits of each coalition were then calculated. Finally, the Shapley's value relationship was used to reassign profits to players in order to encourage them to participate in the grand coalition. This study was carried out on Shahid Rajaee dam located in 45 kilometers southwest of Sari in Tajan basin. This dam mainly supplies agricultural and drinking water. Rice and citrus production were the largest and second largest water consumer, respectively.

In this study, the monthly amount of water released from Shahid Rajaee Dam reservoir was determined by using standard utilization policy and then the amount of initial allocation to downstream dam needs was calculated using genetic algorithm optimization model. Then, by using the players' profit coefficient and the amounts allocated from the implementation of the genetic algorithm model, the initial profit values were calculated for each stakeholder. Employing the Shapley Crisp method, the amounts of water allocated to each player and their corresponding economic benefits were obtained for the grand and two-player coalition. The results showed that the grand coalition had more benefits than the binary coalitions as well as the initial allocation. At this step, the Shapley value relationship was used to reallocate the profits among the players. After allocating water to three participants based on different coalitions, since the fair share of each was obtained in the first step, payments must be made between the players in order to be fair. The player who receives more water share determined at the first step must pay money to other players receiving water less than their fair share. The method proposed for the 18 years statistical period was used to allocate water among the stakeholder. According to the findings, the formation of a grand coalition increases overall system profit without the need for any additional costs and only with revising the operation management.

In this research, an integrated model of optimization was developed using Genetic Algorithm and Shapley Crisp Cooperative Game Approach. The amount of financial payments among the stakeholders in the coalition was also determined based on the Shapely value. Constituent coalitions show the management impacts on water policy and demand management in the studied area. The best results were obtained when players formed a grand coalition. In other words, by participating in the grand coalition and reallocation of water and profits among players, the overall system profits will increase by 10 % and the profits of players cultivating rice, citrus and other agricultural products will rise by 6, 16 and 15 %, respectively, as compared with the condition the players do not participate in the grand coalition and water allocation is only done using the Genetic Algorithm. Therefore, the water allocation should be based on a grand coalition requiring the cooperation and participation of all stakeholders. The results indicate that this method can be applied to allocate resources equitably. It can be also used to solve social conflicts among decision-makers.

Sugarcane cultivation has been revived in Khuzestan province of Iran since the 1960s and due to good results, it gradually began to grow from north to south of this region. Currently, sugarcane is cultivated in more than 100,000 hectares of the provinceand almost 25% of the country needs for sugar arebeing produced in this region. Sugarcane fields of Khuzestan province are mainly rich in lime percentage and poor in organic matter and phosphorus. Soil pH in this region of the country also is about 8-8.5 and phosphorus uptake by plants and phosphorus fertilizer efficiency in these soils (alkaline and calcareous soils) are expected to be low. The optimum use of phosphorus fertilizer and proper phosphorus uptake is essential for the quantitative and qualitative function of sugarcane plants. Due to the very low mobility of phosphorus in the soil, its uptake by plants such as sugar cane is affected by number of soil and plant factors (especially plant root characteristics). Changes in these factors can lead to a reduction or increase of P uptake by the crop.

Because of the role of organic compounds in the improvement of mobility and phosphorus uptake, the use of organic material has been considered in many types of research. Organic compounds can play a direct and indirect role in plant factors and in phosphorous uptake improvement. In this regard, a greenhouse pot experiment was conducted in 2016-2017 at Farabi Agro Industry Co, 35 km south of Ahvaz, Iran (48º 36' E, 30º 59' N). This research carried out by using three levels of humic acid (immersion of settes in three concentrations of 0, 0.3 and 0.5% of humic acid) as well as three levels of phosphorus fertilizer (triple super phosphate) 0, 50 % and 100% of the recommended amount in the region (250 kg/ha) in two different harvesting periods (45 and 90 days after planting). The experiment set up as a factorial, based on complete randomized design with three replicates. In this experiment, the effects of different levels of phosphorous fertilizers and humic acid on aerial part (shoot height, shoot dry weight), underground part (root length, root dry weight and root hair length), and also root CEC of sugar cane plant in two harvest times were studied. Finally, uptake and influx of phosphorus in different treatments were investigated.

As the results show, although the range of the changes was different, the use of humic acid could improve almost all of these factors. Shoot height, shoot dry weight in humic acid treatments showed a significant increase in both harvests compared to non-used humic acid treatments and also in phosphorus fertilizer treatments as the fertilizer levels rose. These results show that humic acid can increase the uptake of phosphorus from the soil reservoir (treatments without phosphorus fertilizer) and source of soil and phosphorus fertilizer (phosphorus fertilizer treatments). The underground plant parts have also shown similar results. Root length and root dry weights have also been shown positive results in humic acid treatments. Therefore, an increase in phosphorus uptake in non-use phosphorous fertilizer treatments or phosphorous fertilizer treatments, along with humic acid, relative to non-humic acid treatments could be explained. The humic acid application seems to increase the uptake capacity of phosphorus from soil and fertilizer sources by increasing root length and root dry weight. In addition, the use of humic acid in alkaline soil can increase the solubility of phosphorus in water and therefore the phosphorus uptake by the roots of the plant could be increased. Based on the results, using humic acid due to improved phosphorus fertilizer use efficiency, phosphorous uptake by plant is expected to be increased and hence the fertilizer use would be reduced. Phosphorus influx results had not the same direction with uptake and application of phosphorus fertilizer. P influx results showed an inverse relationship with root length. In other words, phosphorus uptake was more dependent on the root growth.

This study showed that it is possible to use humic acid in the practical form during the cultivating of sugarcane setts, but it seems that further research is needed to examine other important points such as the use of humic acid during plant growth season and other its application forms, such as spraying or application in irrigation water.

Wind erosion is one of the most important environmental challenges in arid and semiarid regions which cause soil loss and dust storm. In recent decades, the potential of soil erosion has been recognized as serious threat against soil sustainability. In addition, accelerated soil erosion has led to harmful environmental effects. Therefore, focus on soil erosion outcomes is necessary in order to mitigate its environmental impacts. Understanding interactions between land use management and topographical properties of landscape are important in order to effectively control soil erosion through implementing best management practices (BMPs). Application of mulch is one of the most prevailing scenarios to prevent the erosive soil against wind as an erosive factor in the hotspots. In this regard the type of much is really important because the environmental aspects and the mulch consistency are important factors for production and selection of mulch between several options. Nowadays, sustainable management is one of the most important scopes in order to achieve the aims of human healthy. In this regards the Bagasse of sugarcane and Conocarpus were selected as feedstocks to produce biochars. Biochar is the by-product of anaerobic process which called pyrolysis. The biogases, energy and so on are other outputs of pyrolysis. Another treatment which evaluated in this study was Zeoplant. Zeoplant is a super absorptive material which is able to hold the water in the soil therefore is capable to enhance the water holding capacity of the soil.      

In this study the effects of biochar of Bagasse from sugarcane, biochar of Conocarpus and Zeoplant in three levels (0, 2 and 4 percentage) and two moisture levels (25 and 50 percentage of FC) and 3 replications in randomized completely design with factorial on physical and mechanical properties of soil as indices of soil erodibility was studied. Soil sampling accomplished from Horalazim marshes and after application of treatment, incubated in tray with the size of 70×30×10 cm for 90 days. After incubations the trays located in wind tunnel in order to simulate wind erosion process under a wind with 15 m/sec speed and 2 m from soil surface. The main measured soil physical and mechanical parameters include mean weight diameter (MWD), penetration resistance (PR), tensile strength (TS), friability index (FI), shear strength, crusting index (CI), soil textural index and organic matter. The statistical analysis was performed using SAS 9.2 software and the mean comparison was accomplished with Duncan test (5 %). In order to draw the graphs Origin 2017 software was used.  

The soil texture was silty loam (SiL) including 62% silt, 26% clay and 12% sand, therefore the soil was sensitive to wind erosion. Soil organic matter before application of biochars and Zeoplant was around 1.93% and after application increased to 3.78%. Application of these treatments and the period of incubation, enhanced the soil porosity. Generally increasing soil organic matter and soil porosity and decreasing of bulk density are the main factors to increase the soil aggregation. Our results showed that all three treatments in two moisture levels significantly increased soil porosity, tensile strength and field capacity and decrease soil crusting index (P<0.01). Biochar of bagasse and Zeoplant (2%) also significantly increased shear strength whereas biochar of Conocarpus has no significant effect on shear strength. Overall the applied treatments with armoring effect (AE) and increase the soil aggregate stability, diminished the wind erosion.

Our study illustrated that application of biochar is able to improve soil physical and mechanical properties. The main aspect of this positive effect is the specific characteristics and the structure of biochar which showed with SEM (Scanning electronic microscope) images. Moreover, Zeoplant is organic-inorganic treatment and including high potential to absorb the water in the soil. Indeed, the mulching is an effective management strategy to maintain and preserve the soil against wind (as erosive agent) however afterwards a vegetation cover must be grow on the surface. Therefore some treatments such as Zeoplant are essential to hold the water in the soils of arid and semiarid regions because in those areas the water scarcity is one of the main challenges. Based on our results and evaluation of these treatments we found two main processes which are effective to mitigate wind erosion. The first is aggregation process because of organic carbon and organic matter in the soil and the binding between organic and inorganic components. The second one is an armoring effect which is originating from amendments especially biochar lumps on the surface. Finally our results confirmed the application of evaluated treatments to preserve the erosive soil against wind.

In cereal crops, nitrogen is the most important element for maintaining growth status and enhancing grain yield. Nitrogen is an important constituent of the chlorophyll molecule and the carbon-fixing enzyme ribulose-1, 5-bis-phosphate carboxylase/oxygenase. Therefore, providing enough nitrogen to achieve optimal yield is essential. Common chemical analyzes are used to determine the nutrient elements of plants using laboratory methods. Conventional laboratory techniques are expensive, laborious, and time-consuming. Determination of plant biochemical content by remote sensing could be used as an alternative method  which reduce the problems of laboratory analyses. Expensive and time-consuming direct determination of the nutritional status of the plant play an important role in the quantitative and qualitative yield of the product. However, exposure to rainfed wheat nutrient stresses (in particular, nitrogen) compared to irrigated wheat resulting in attempts to evaluate these features with acceptable accuracy without the direct measurement. In this regard, remote sensing data and satellite images are of the basic dryland management and optimal wheat production methods. As such, it collects massive information periodically from the surface of the planet, and it is easy to use this timely information to identify the stresses and apply appropriate agronomic methods in order to counteract them or reduce their negative impact on the production of this strategic product. Therefore, the goal of this study was to determine the nitrogen concentration of dryland wheat in the laboratory and its fitting with ETM+ images, evaluate the accuracy of remote sensing in determining the total nitrogen content of the plant and establish a regression relationship to estimate the amount of canopy nitrogen in the plant.

This research was undertaken in parts of the south of the West Azerbaijan Province in Iran. The sampling was done from 45 dryland wheat fields using a stratified random method in May 2016. The wheat canopy nitrogen was determined using the Kjeldahl method. Satellite images of the ETM+ were downloaded on the USGS website. Then the required pre-processing was performed on images to reduce systematic and non-systematic errors. Statistical analyses were performed by excel and SPSS. Descriptive statistics and correlations were obtained between reflectance data obtained from various satellite bands and nitrogen measured in the laboratory. Correlated variables among the reflectance data of different bands were analyzed by principal component to reduce repeat calculations. The regression relationship between the plant canopy nitrogen and the first principal component has been evaluated using the stepwise regression method. To draw the plant canopy nitrogen, map, the equation was obtained and the ETM+ image has been used for land uses. Finally, the map of canopy N distribution at the studied area was drawn.

The results showed that nitrogen content varied from 1.6% to 0.79%, with an average of 1.11%. The normality data was verified by the Shapiro Wilk test. The results of the Pearson correlation showed that the wheat canopy nitrogen has a high correlation with digital number values of all bands of satellite images except band 4, so that it has the highest and the least correlation with band 2 and band 4, respectively. The correlation between remote sensing data in different bands was also evaluated using bi-plot statistics, which results showed a high correlation between all bands except band 4 with the first one of the principal component (PC1). Therefore, only PC1 data has been used to study the regression relationships between wheat canopy nitrogen and remote sensing data. A regression equation  between wheat canopy nitrogen and ZPC1 (R2= 0.71) was developed. ZPC1 is obtained according to the following formula:  where ZPC1 is the standardized Z parameter, is the average of PC1 and the ????pc1 is the standard deviation of PC1. Finally, the map of canopy N distribution was drawn to the studied area. According to the results of this study, the application of remote sensing data such as Landsat ETM+ data is a very important variable for improving and managing the prediction of wheat canopy nitrogen.

Overall, the results indicated that the remote sensing data provide more accurate and timely information from the drylands of Iran to manage farm fertilization and prevent the decline in yields at critical points. However, proper management to avoid the fertilizer loss by precise and timely application of N-fertilizer is needed.

Leafy vegetables such as spinach (Spinaciaoleracea L.) contain high levels of nitrate. Using nitrification inhibitors (NIs) such as 3,4-dimethylpyrazole phosphate (DMPP) is one of the strategies for reducing nitrate accumulation. Nitrification inhibitors are compounds that delay the biological oxidation of ammonium to nitrite by depressing the activity of Nitrosomonas bacteria in soil. Soil properties such as texture, pH, organic matter, moisture, temperature and mineral nitrogen have important effects on the efficiency of NIs to delay nitrification. A pot experiment was conducted to investigate the effects of NI 3,4-dimethylpyrazole phosphate (DMPP) on soil mineral nitrogen (ammonium and nitrate) content, yield and nitrate concentration of spinach.

A completely randomized factorial design was carried out employing three factors consisted of nitrogen fertilizer type, soil type and spinach variety with three replications at Shahrekord University. Nitrogen fertilizers included urea, ammonium sulfate nitrate (ASN) and ASN plus DMPP (0.8 %). A no N fertilizer application was considered as control treatment. The soil factor contained 3 different soils with different physical and chemical characteristics. Two spinach varieties were smooth-leaf (Giant Santos) and wrinkled-leaf (Viking). The dose of applied nitrogen in all experimental treatments was 150 mg kg-1 soil that was applied in two split doses before sowing and after one month. The textures of three selected soils were loamy sand, loam and silty clay for the soils number 1, 2 and 3, respectively. Three selected soils were non-saline (EC1:2=0.14-0.31 dS m-1) and alkaline (pH1:2=7.9-8.0). Organic carbon and calcium carbonate equivalent (CCE) ranged from 0.26% to 0.35% and 28.5% to 36.2%, respectively. At 30 and 60 days after sowing, soil subsamples were taken to determine ammonium and nitrate content. The ammonium and nitrate concentrations (extracted with 0.5 M K2SO4) were determined calorimetrically using a spectrophotometer at a wavelength of 667 and 410 nm, respectively. At the end of the experiment, shoot fresh weight was determined and plants was mixed and dried to measure nitrate accumulation.

The results indicated that the application of ASN with DMPP led to significant increase of ammonium compared with ASN and urea fertilizers in three soils. At 30 days after sowing, the amount of this increase for ASN plus DMPP in comparison of ASN and urea were 182% and 78% for the soil number 1 (loamy sand), 105% and 65% for the soil number 2 (loam) and 89% and 74% for the soil number 3 (silty clay), respectively. By contrast, the application of ASN with DMPP led to significant decrease of soil nitrate in comparison of ASN and urea fertilizers in three soils. At 60 days after sowing, the amount of this decrease for ASN plus DMPP in comparison of ASN was 52%, 40% and 27% for the soils number of 1, 2 and 3, respectively. It means that the application of DMPP has slowed down the process of ammonium oxidation to nitrite. In fact, the addition of DMPP retained soil nitrogen as ammonium form for longer time. The application of NI DMPP also had positive effect on decrease of nitrate concentration in the soil. Unlike nitrate, ammonium is less susceptible to leaching and thus the application of DMPP can reduces nitrogen loss from the soil. However, the application of ASN with nitrification inhibitor DMPP in soils No. 2 (loamy sand) and No. 3 (loamy) significantly reduced shoot fresh weight of both spinach varieties compared with the similar treatment but without NI. This decrease was due to the toxic effects of high level of soil ammonium on the plant growth. While, in the soil No. 3 (silty clay) in Viking variety, the use of ASN plus DMPP resulted in significant increase of spinach shoot fresh weight to 29% in comparison with the same treatment but without NI. The highest and lowest values of shoot fresh weight (229 and 16.2 g pot-1, respectively) were obtained by Giant Santos variety in soil No. 3 (silty clay) with ASN plus DMPP and soil No. 1 (sandy loam) with no added N fertilizer. The application of ASN with nitrification inhibitor DMPP induced significant decrease of shoot nitrate concentration in spinach in comparison of ASN and urea. The amounts of this decrease for ASN plus DMPP in comparison with ASN and urea were 25.7% and 31.5% for the soil number 1 (loamy sand), 29.1% and 37.1% for the soil number 2 (loam) and 33.9% and 34.0% for the soil number 3 (silty clay), respectively. This decrease was due to ammonium nutrition of spinach plants.

In all studied soils, application of ASN with nitrification inhibitor DMPP is recommended for diminishing nitrate content in both spinach varieties (Giant Santos and Viking).

Soil organic carbon (SOC) is released from decomposition of plant residues, while root secretion products in rhizosphere are also a substantial source of SOC input to soil. Binding SOC to clay minerals leads to increase aggregate stability and protect organic carbon against microorganisms. Organo-mineral complexes have important role in decreasing organic carbon decomposition. Assessment of organic carbon particle size and biochemical fractionation is an appropriate approach to investigate organic carbon dynamics and durability against microorganisms in rhizosphere as a hot spot of activity.  

The study area was a semi-arid rangeland with the main plants species including five perennial rangeland species: crested wheat grass (Agropyron cristatum), astragalus (Astragalus verus), sheep fescue (Festuca ovina), phlomis (Phlomis oliveri), feverfew (Tanacetum parthenium). Whole soil surrounding plant roots with all roots was taken for each plant. Three sample with different distances from root surface were taken by applying this procedure: sample A: The soil which is adhered to the root surface and separates quickly from roots after drying, sample B: The soil in root zone, which is not stuck and almost is so close to roots, sample C: The soil which is wholly far from root area and apparently not affected by roots. Intact samples removed from ground and transferred quickly to laboratory to separate roots and soils with different distances from root surface by drying the root system before shaking. Particle size fractionation was done by wet sieving of aggregates and SOC in different aggregate sizes was measured by wet combustion method. Biochemical fractionation of SOC was done by acid hydrolysis method to study organic carbon stability at different distances from root surface.

ANOVA results showed a significant effects of plants and distance from root surface on aggregate size classes. The results showed the increasing amounts of microaggregates at root vicinities compare to macroaggregates. By increasing distance from root surface, the >2 mm aggregates increased, but, the amount of <0.15 mm aggregates decreased significantly. Toward root surface from C to A locations, the mean weight diameter (MWD) of soil aggregates decreased due to decreasing macro-aggregates at root vicinity. Maenwhile, SOC increased approaching to root surface due to root exudates and rhizodeposits. The highest and lowest of SOC content were found in the A location of Feverfew and the C location of Astragalus (4.16 and 0.82%), respectively. The OC contents in root vicinity were higher than other locations due to high root exudates and rhizodeposits which had C-containing molecules. Soil OC contents had significant correlation with measured soil parameters. The highest SOC content was found in micro-aggregate and in vicinity of roots. Low-decomposed OC, which has crucial role in linking microaggregates to make macroaggregates, led to high OC contents in macroaggregates. Soil OC biochemical fractionation demonstrated higher OC contents in recalcitrant pool at further distances from root surface, while by going toward root vicinity the amounts of OC in water soluble and labile pool increased. In average for A locations, 66% of total OC was measured as water soluble fraction, while for C location, the average fraction of labile and recalcitrant pools from total OC were found 62.5% and 50%, respectively. As the root exudates had fresh OC such as carbohydrates and sugars, the concentration of OC in water soluble and labile pools were so high at root vicinity. Moreover, OC in labile and water soluble pools had high correlation coefficient and, contributed to high fractions of total OC in root vicinity. Whilst C in recalcitrant pool were found higher in further distances from root surface, because activities of microorganisms and the fresh OC were decreased toward bulk soil.

This study investigated the effect of root activities of five perennial rangeland plants on the particle size and biochemical fractionation of soil OC at different distances from root surface. In root vicinity due to addition of fresh OC from roots to soil and higher microorganisms’ activities, mineral particles were aggregated to micro-aggregates which contained a large fraction of soluble and labile Soil OC. But, recalcitrant OC were dominated in macro-aggregates far from root surface. Rangeland plants with various root systems and characteristics had strong impact on particle size and biochemical fractionation of soil OC which needs more investigation. Durability of biochemical C pools has important role in carbon dynamic and stability in soil.

Drought is a very complex natural phenomenon which changes with time and space. Spatial and temporal variations of drought are analyzed separately. Geostatistical methods can be used for spatiotemporal analyses to find related spatial and temporal pattern changes. These methods, which use the spatio-temporal data, considering the spatial position of the data relative to each other, also take into account their temporal dependence. If needed, they can estimate values of their variable at any location and any time. Moreover, the drought spatial variations in the studied region can be drawn at every desired period. On the other hand, it is expected that intervening of the time dimension in the equations of these methods, as compared to the purely spatial methods, provide more precision in estimating the values of drought indices, which is studied in this research.

Monthly rainfall data of 48 stations in the northeast of Iran for the period of 1981-2012 were used in this study. The SPI drought index is calculated for the 12-month time scale. Data were divided into two groups of training data from 1981-2011 and experimental data of 2012. After analyzing the data regarding their stationarity and isotropic assumptions, the spatiotemporal data were formed and their spatiotemporal empirical variogram was drawn. Furthermore, the purely spatial and temporal variograms for the zero space and time steps were also drawn. Then, four models of the spatiotemporal variogram functions were applied on the training data. The performance of these models was tested and compared by estimating the parameters of the model based on the Square Error (MSE). Moreover, three-dimensional fitted variograms were drawn for different models. Mean The best spatiotemporal variogram model was selected by comparing the models prediction with experimental data using the Mean Square Prediction Error (MSPE). Using spatiotemporal kriging method, the predicted values of experimental data were interpolated ​​and that of the observed values ​​were interpolated by kriging method. Cross validation on experimental data was also performed using RMSE, MAE, ME and COR. Then spatiotemporal and purely spatial variogram models were investigated and compared.

The results showed that the 12-month SPI index had no spatial trend but had a decreasing trend against the time. Hence, a simple regression equation was used for fitting the trend of the data. After detrending the data, the SPI index values were considered as the dependent variable, while the time was taken as the independent variable. On the other hand, drawing the variogram in different directions (0°, 45°, 90°, and 135°) had no significant effect relative to each other, and the hypothesis of isotropic state was accepted. The plots of purely spatial and temporal variograms showed that the spherical variogram for space and the linear variogram for the time would have the best fitting. The empirical 3-D and 2-D spatiotemporal variograms of the training data were plotted. The empirical 3-D variogram showed that the data had reached to its temporal sill in a 1-year time lag, and had reached to its spatial sill, in about 25-kilometers, which are in conformity with the purely spatial and temporal variograms. The comparison of different variogram functions showed that the MSE values of the separable, metric, product-sum and sum-metric models were 0.00139, 0.00295, 0.00111, and 0.00112, respectively, the last two of which had fewer errors. Drawing the spatiotemporal variogram of these functions showed that the spatiotemporal variogram of product-sum and sum-metric models have more similarity to the sample one. Regarding the selection of the best model, the MSPE statistics of the product-sum and sum-metric models were 0.281 and 0.389, respectively. Therefore, the product-sum model could be selected as the best model. The least rate of errors was found in the exponential variogram model for space, and in the linear variogram for the time. The parameters of the nugget effect, partial sill and range for the spatial variogram would be 0.00, 0.063, and 5.78, and for the temporal variogram would be 0.00, 0.635, and 1.044, respectively. After predicting values of 12-month SPI in 2012 by the product-sum variogram model and adding the values of the trend, they were interpolated by using the spatiotemporal kriging, and the observed values were interpolated by the use of kriging. The obtained plot from the predicted values had great similarity with that of the observed values, which indicates the appropriate capability of the model in predicting the unobserved values. The cross-validation of different spatiotemporal and the spatial models with 25 and 47 neighborhoods showed that the performance of the models had no significant differences relative to each other, and they also had no better performance relative to the purely spatial model.

The results of this study showed that the product-sum model had a better performance among different spatiotemporal variogram models in predicting the 12-month SPI values of 2012. However, the performances of different spatiotemporal models were quite close to each other. There is no significant difference that could be observed between spatiotemporal and purely spatial models. Also, it is proposed to use the dynamic spatiotemporal models and the results to be compared with the classical models.