naser davatgar

Crop Growth Models have high simulation precision at a small level and field scale. However, their application at larger and regional levels causes a significant decrease in model precision. Few studies have investigated the reasons for this phenomenon. The aim of the present study is to investigate the effect of soil texture on the precision of the DSSAT model for predicting rice yield and biomass at a large scale. First, the DSSAT model was calibrated and validated using field data and then used to predict rice yield and biomass in 110 paddy fields in Soumeh-Sara County, Guilan Province. The required data was collected from the fields and entered into the model. Evaluation of the model output showed that the absolute error related to the model covers a relatively large range (up to 50%). However, the majority of this error occurs in the range of ±30%. Also, the model precision is acceptable for average regional yield values, but the model precision decreases for maximum or minimum yield ranges. The results showed that the precision of the model's simulation of yield and biomass was inversely related to the amount of sand in the soil. The lowest model error, or in other words, the highest precision, was observed in the 0-15 percent sand group, and the highest error and lowest simulation precision were observed in the sand percentage group above 30 percent.

Saturated hydraulic conductivity (Ks) is one of the most important soil physical properties that plays a major role in its hydrological behaviour. In this study, the hydraulic characteristics of 312 soil samples, taken from the top layer (0-30 cm), were measured. Additionally, soil texture and bulk density were analyzed in 2080 top-soil (0-30 cm) samples. The results showed that the soil texture in the region varied from sandy to clayey, with most soils classified as medium-textured. The average bulk density in the region was found to be 1.43 g.cm-3. The mean field capacity moisture content across the counties of Sistan Plain was less than 35%, placing them in the low field capacity class. The highest and lowest plant-available moisture content was observed in Hirmand and Zabul, respectively. The coefficient of variation for plant-available moisture in all surface agricultural soils of Sistan Plain was 33.83%, indicating a very high variability. Regarding the mean values of saturated hydraulic conductivity, the lowest and highest values of surface soil saturated hydraulic conductivity (Ks) were observed in Zabul (0.15 m per day) and Hirmand (0.42 m per day), respectively.

Nutrient limitations often reduce crop yield in farmers' fields. Identifying the status of rice plant nutrients in the soil and plant is necessary for plant nutrition management. In rice plant, it is common to use soil chemical properties test to understand the availability of soil nutrients. Although soil tests based on critical level may indicate the adequacy of nutrients, sometimes the rice plant in the field exhibit signs of its deficiency. Flooding conditions in rice cultivation leads to chemical and electrochemical changes in some nutrients, which result in inadequate nutrient uptake by the plant. Solely relying on soil testing in such conditions increase errors in results interpretation and fertilizer recommendations. Therefore, measuring the nutrients characteristics of both plant and soil can be effective in fertilizer recommendations. One method for interpreting leaf analysis results is the use of compositional nutrient diagnosis (CND) method. The aim of this study was to establish reference norms, the range of optimal concentration and nutrients limitation in rice plant using the CND method during 2018 growing season in 60 paddy fields of Guilan province, Iran.

Soil and leaf composite samples were collected from farmers' fields in a standard manner and analyzed using appropriate laboratory methods. At harvest time, the yield of each field was determined. Nutrient indices were assessed by the compositional nutrient diagnosis (CND) method. By employing the cumulative function model of the variance ratio of nutrients and solving third-degree cumulative function equations related to 10 nutrients along with their residual concentrations, yields corresponding to each of them were calculated in terms of tons per hectare. To categorize the yield community into favorable and unfavorable groups, initially, the yield-nutrient function was plotted and the yield groups were separated by identifying the inflection points of the curve. To validate the compositional nutrient diagnosis method, the relationship between the nutrition balance index (r2) and crop yield was evaluated through a scatter plot. Descriptive statistics were conducted using SPSS version 24 and CND calculations were performed using Excel software.

Based on the average of available phosphorus concentration and its critical level 47% of the fields exhibited phosphorus deficiency. According to the critical level of available potassium, except for one farm, the available potassium content exceeded the critical level in all fields. Due to the fact that the minimum amount of micronutrients (zinc, iron, copper, and manganese) was more than their critical level in paddy fields, indicating no deficiency in the studied soils. Available magnesium concentration ranged from 0.8 to 4.6 with the median of 2.4 cmol+/kg. Nearly 75% of the studied soils were deficient in magnesium, based on the critical level of available magnesium (3 cmol+/kg).The average phosphorus concentration in leaves was 0.23% and based on the critical level, there was phosphorus deficiency in two fields. The average potassium concentration in the sample of leaves collected from the fields was 1.57% and based on the critical level, potassium deficiency was observed in rice plant tissue in 55% of the fields. The average magnesium concentration in rice leaf samples was 0.17% and six farms showed deficiency based on the magnesium critical level. The average zinc concentration was 13.69 in rice leaf samples and based on zinc critical level, 58 farms (96%) showed zinc deficiency. Based on the calculated average yields, the target yield was determined as 4133 kg/hectare, and according to the target yield, 43.3% of selected fields were classified as high-yielding and 56.6% were classified as low-yielding group. The CND method correctly recognized the balance of nutrients in rice plant with 55% accuracy. The relationship between yield and nutrients balance index showed that 31% of fields had nutritional balance, 24% had nutritional unbalanced, 22.4% had yield reduction other than nutritional factors such as climate, root depth limitations, pests, and diseases.

The findings showed that: 1- Using only the critical level of soil and plant nutrients for assessing the nutritional status of soil and plants was not efficient in the studied paddy fields. 2- The CND method, due to its consideration of the interactive effects of nutrients, had greater capability than the critical level method in diagnosing nutritional disorders, nutrient deficiencies, and fertilizer recommendations for the studied paddy fields. However, it was not the most accurate, sensitive and unique because factors other than soil fertility and rice plant nutrition, such as climatic conditions and irrigation, and field management, also influence the growth and development of rice plant and its yield. 3- The most important macronutrients and micronutrients needed in studied paddy soils based on the CND method were magnesium and phosphorus (macronutrients) and copper and zinc (micronutrients). 4- The CND method can be as an effective tool for interpreting soil and plant analysis in plant nutrition management at paddy farming systems.
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Spatial variability of soil hydraulic properties is important for soil-water balance and irrigation management in paddy fields. The objective of this study was to determine the spatial variability of saturated hydraulic conductivity (Ks) and the factors affecting it. Soil samples from 120 profiles were collected using random stratified sampling scheme. Soil samples were taken from top soil, compacted plow pan, and non-saturated subsoil. In these samples, soil texture, organic carbon, bulk density, saturated moisture, and saturated hydraulic conductivity were measured (by the falling head method). The most heterogeneity with a maximum coefficient of variation (CV), positive skewness, and lognormal frequency distribution for Ks indicated preferential flow caused by the presence of biological pores and cracks from previous drought stress. The results of the geostatistical analysis showed that hydraulic conductivity followed spherical and exponent semi-variogram model in puddled top soil and the non-saturated subsoil, respectively. This variable followed linear semi-variogram model with low slope in plow pan. The CV of Ks in plow pan (299%) was 121% and 284% higher than, respectively, the upper and the lower layers. The closeness of the behavior of Ks to random variables in this layer was mainly due to the existence of biological pores and root channels and the movement of animals, which lead to preferential flow. Despite the weak and moderate spatial structure of the variables, the kriging interpolation method was more accurate for Ks compared to inverse distance weighting. The spatial distribution pattern of Ks in puddled top layer was inversely related to clay content. Despite the high clay content in the west half of the study area, the Ks values in this region were high due to the presence of biopores. These results indicate that the compacted plow pan cannot play its key role for reducing hydraulic conductivity and retaining water in the soil. The magnitude and spatial variability of soil hydraulic conductivity and the factors affecting it depend on the site-specific irrigation management.

One of the consequences of the climate change in Khuzestan Province is thedrying up of a large part of the wetlands of this province, including Miangaran and Hoor al-Azim, which has caused dust storms in recent years. In this regard, this research aims to predictclimate changes in the area of Miangaran and Hoor al-Azim wetlands by using the SDSMstatistical microscale model based on HadCM3 B2 and A2 climate scenarios. Considering thespecific conditions of the region and the fact that few studies have been done regardingtemperature change in these areas, knowing the state of temperature change can help bettermanagement of resources, especially water resources management.

These parameters include the average sea level pressure, thegeopotential height of the surface of 850 hectopascals and the average temperature at a heightof two meters. For this purpose, by using the daily data of average temperature, minimum andmaximum temperature in the synoptic stations of Izeh and Bostan as the closest stations to Hooral-Azim and Miangaran wetlands in the periods of 2010-2039, 2040-2069 and 2070-2099,predictions were made and then a comparison was made with the base period (1961-1990). Theselected predictors in climate parameters were chosen using NCEP observational large-scaleparameters and SDSM software. These parameters included average sea level pressure, surfacegeopotential height of 850 hectopascals, and average temperature of two meters above thesurface. Also, with scenarios A2 and B2 until the year 2099, the prediction of the return periodof extreme climatic events in the HadCM3 model was done.

The results of the simulation of the HadCM3 model along withobservational data from the Izeh station, modeled annual average temperature data was 18.47°Cand for the Bostan station, modeled annual data average temperature was 19.10°C. Both stationshad a higher average temperature in the base period, and the maximum temperature in theMiangaran wetland was much higher than Hoor al-Azim wetland in the base period. The resultsshowed that in both stations in scenario A2, the average temperature had significant cycles withreturn periods of 1.2 years and the lowest significant cycles for the two stations were in returnperiods of 2.3 and 1.3 years, respectively. In scenario B2, the average temperature in twostations has significant cycles with return periods of 7.5 years and the lowest significant cyclewith a return period of 1.2 years. The results of examining the cycles in the studied areasindicate that in the A2 scenario, certain climatic conditions in the area have short-term returnperiods. One year was obtained in both scenarios, which indicates a wider range of the returnperiod and a higher probability of extreme temperature events in the B2 scenario. In thecomparison of the two stations, it can be seen that in scenario A2, the average temperature ofthe Miangaran wetland is 1.02 °C and the Hoor al-Azim wetland is 1.08 °C.

The results of the data analysis in the future observation and simulation periodswith scenarios B2 and A2 showed an increase in the mean, minimum, and maximum averagetemperature in the future simulation periods compared to the base period in Izeh and Bostanstations. In Bostan station, the average minimum and maximum annual temperature alsoincreased in the third period compared to the base period. In both scenarios, due to the increasein temperature, the drying process of both wetlands will continue.

Available water holding capacity (AWHC) is a key property for quantifying the amount of water available to plants. This c property determines the amount of water required for the crop and the irrigation time interval and is related to the inherent productivity of the soil. Determining the homogeneous zones of available water-holding capacity management is a possible way to evaluate the contribution of the soil in the optimal input of irrigation water in paddy fields. Because with its help, it is possible to manage the appropriate time of drying and wetting of paddy fields in intermittent irrigation. The rice fields of Guilan province, located in the north of Iran, with an area of about 238,000 hectares, are one of the most important rice cultivation areas because more than 30% of the country's rice is produced in this area. Irrigation in this area is done in the form of uniform flooding for easier transfer of rice seedlings, better water retention and weed control. In recent years, due to drought, population growth and increasing urban and industrial demand for water and inefficient management of flood irrigation, an attempt has been made to manage irrigation in the form of intermittent irrigation. Therefore, determining the homogeneous zones of water storage capacity management is a possible way to evaluate the contribution of soil in the optimal input of irrigation water in paddy fields. Because with its help, it is possible to manage the appropriate time of drying and wetting of paddy fields in intermittent irrigation. Water resource management is a priority to reduce productivity instability and negative socio-economic effects. For this purpose, homogeneous water storage capacity management zones were determined in Kouchesfahan region to investigate the physical-hydraulic conditions of paddy soils, dividing the entire region into zones with the same potential for water storage capacity and investigating its relationship with rice yield.

A total of 131 undisturbed and undisturbed soil samples with uniform geographic distribution were prepared from the rice root growth area and some chemical, fertility and physical-hydraulic properties were measured. Rice yield was also measured in most of the soil sampling points. Then, among 14 characteristics, seven characteristics (clay, organic carbon, linear expansion coefficient, saturated hydraulic conductivity, average particle diameter, accessible water and integral energy) that can affect the water holding capacity in the soil were selected. The number of homogeneous zones of water storage capacity was determined using two statistics, fuzzy efficiency index and modified classification entropy index. Then, by using the concepts related to algebraic maps, the integration of information layers was done in the GIS environment and the relevant maps were prepared.

The results of the fuzzy efficiency index and the entropy index showed that the investigated area can be divided into four water storage capacity areas. The lowest and highest value of the average yield was seen in the first and fourth zones, respectively. A significant difference was seen between available water, organic carbon, COLE, integral energy and Saturated Hydraulic Conductivity (Ks)in four management zones, but no significant difference was seen in the amount of clay and the mean diameter of the pores. In the first zone, organic carbon, Coefficient of linear extensibility (COLE), Mean of Soil Pore Size Distribution (dmean) and Ks showed the lowest values, but in the fourth zone, all these properties have the opposite behavior. These results were showed that the available water-holding capacity ty increases from zone one to zone four. Therefore, zones one and two will be particularly sensitive during drought and lack of moisture during the growing season, and the management of these zones needs special attention. In these zones, the irrigation cycle (irrigation time interval) should be shorter than the other two areas, in order to avoid the occurrence of drought stress. The soils of the studied area were uneven in terms of water retention. These results showed that the uniform (fixed) management of water consumption, in addition to increasing costs, can also lead to the waste of a large amount of water. In this situation, location-specific irrigation management can be more efficient in sustainable economic production.The comparison of the estimation map of homogeneous zones shows the water storage capacity and yield, in some zones, although the soil conditions are suitable in terms of moisture conditions, the yield is not in optimal conditions. It seems that until the state of fertility is not favorable, physical conditions cannot show their effects in performance well. In other words, until the lack of fertility is not resolved, restrictions or suitable physical conditions will not have clear effects on performance.

The application of soil quality (SQ) in sustainable land management is evolving. However, despite their considerable importance, the inclusion of biological properties in soil quality assessments is limited due to the challenges and high costs associated with measuring these attributes. This study was carried out on the contribution of biological properties to soil quality. In this research, 22 physical, chemical, and biological properties of 90 surface soil samples (0-30 cm) were analyzed to determine the soil quality index (SQI) in the Honam region of Lorestan. Analyzed properties included pH, electrical conductivity (EC), organic carbon (OC), total neutralizing value, clay and silt content, microbial biomass carbon (MBC), basal microbial respiration (MR), the total fungal and bacterial populations, the populations of Azotobacter and Pseudomonas species, as well as the activities of urease, acid and alkaline phosphatase, the available potassium and phosphorus concentrations, the total nitrogen, and the content of manganese, iron, copper, and zinc. Principal component analysis (PCA) to select a minimum data set (MDS) revealed that eight principal components, each with eigenvalues greater than one, accounted for 89.83% of the total variance. Of the 22 soil properties 12 were selected for the MDS, with biological properties (5 properties) making a more significant contribution than the physical and chemical properties. The spatial distribution of the SQI underlines the significant influence of biological properties on soil quality. These results underline the importance of including biological properties in the assessment of soil quality.

This study expresses the steps of achievement to the indigenous-executive framework of integrated soil and water management at farm level through a mega project with 19 sub-projects. The projects were carried out during 2013-2020 with active participation of international, national and regional experts as well as local farmers in Honam Sub-basin, Lorestan Province, Iran. To understand the soil and water management problems for agriculture in the same homogeneous units (HSWMUs), farmlands were classified regarding physical, chemical and biological characteristics of soil, making it possible to convert soil maps into thematic maps. In this research, the fertility capability classification (FCC) method that integrates surface and sub-surface soil textures with modifieres was used. In addition, several modifieres were revised for soils of semi-arid regions and new modifieres were introduced for Irrigation Capability Classification (ICC). The required information was collected from 119 soil profiles and 101 surface soil samples in detailed scale of 1:25000 and the corresponding measurements were made. Accordingly, different data layers including detailed soil map were produced via geopedological method icluding land limitation, land suitability, and land production potential (LPP) of major crops, land degradation, location of water withdrawal, land use and agricultural cadastre of 2395 farms were prepared. To evaluate the current soil and water behavior of farmers within HSWMUs, the multidisciplinary team recorded the issues through field visits and open semi-structured questionnaire of 84 selected farmers in 24 villages who were interviewed during 2018-2019. The results showed that 23 and 30 HSWMUs that covered, respectively, 93% and 90% of the irrigated and rainfed areas were delineated on the map. Investigations showed that the sub-basin suffers from problems such as plow pan, phosphorus and zinc deficiencies, poor irrigation scheduling, and three types of farmers. Finally, recommended packages were prepared and validated for each HSWMU, which will be discussed in the part 2.

In order to analyze the temporal and spatial changes in the amount of water required for puddling in rice fields of the Sapidroud Network, daily soil moisture data from the SMAP satellite was obtained and used in a seven-year period (2015 to 2021). The puddling stage (from April 20 to June 10) was analyzed after grouping based on different probability of occurrence (1%, 10%, 25%, 50%, 75%, 90% and 99%) and using raster calculations. In addition, in order to validate the calculations, the predicted values were compared with the saturated soil moisture values of 321 soil samples with specific geographic coordinates that had been measured by the Rice Research Institute of Iran. The comparison was conducted by using the mean absolute error (MAE), mean bias error (MBE), and normalized root mean square error (NRMSE). The results showed that in all moisture scenarios (from the wettest to driest), the foothills had less moisture than the plain and, especially, the low lands, and the soil moisture showed a decreasing trend during the growing period. The rate of this reduction increased gradually and in some areas it reached 2% per day at the end of the puddling period (May 22 to 31). The amount of gross water required for puddling increased from the wettest to the driest year and in the middle of the season (May 3 to 5) it was from 1693 to 2983 square meters per hectare and at the end of the season from 2496 to 3602 m3/ha, respectively. The validation results showed that the calculated MAE, MBE, and NRMSE values were 4.26%, 1.59%, and 15%, respectively, indicating that the accuracy is acceptable. The findings showed that the delay in the start of the puddling operation increases the water required for puddling operation (1.34 m3/ha for each day delay in a normal year). Therefore, in the lands of this network, in all circumstances, especially in dry years, to save water, it is better to release/supply water required for puddling from local reservoirs, wells, or from the Sepidroud Dam in early May.

Making management decisions for the quantitative and qualitative improvement of product production effectively begins with selecting the correct and appropriate set of physical and hydraulic characteristics in the form of a soil physical quality index. In order to investigate the physical quality of Shabaster Plain which were under wheat cultivation and to determine the role of the number and type of properties on the quality of the soils, 94 soils from these lands until the year 2022, were selected. To determine the soil physical quality index (SPQI), the minimum data set (MDS) was used by principal component analysis (PCA). 13 physical, chemical, and hydraulic properties (clay, silt, bulk density, aggregate size distribution, electrical conductivity, sodium adsorption ratio, pH, organic carbon, hydraulic conductivity (K_s), conventional plant available water (CPAW), integral energy (EI), dexter index (S_dex), Kirchhoff potential (M_h0)) were consciously entered into four stages in the principal component analysis so that the output is not only the minimum data set but also the best data set. EC appeared as one of the main components in all arrays. The first array was eliminated from the minimum data set. Comparing the mean soil physical quality index between the arrays with Duncan's test showed a significant difference at the 99% probability level (p<0.01) between the fourth array and the second and third arrays. The high sensitivity coefficient of the fourth array (9.78) with the second and third arrays (5.43) showed that the correct addition of the Kirchhoff potential to the data set, led to different results in terms of classifying soil physical quality. As a result, the quality of the soils decreased from 72% of very suitable and suitable soils and 28% of the soils with severe and very severe restrictions in the second and third arrays to 41% of very suitable and suitable soils and 59% of soils with restrictions in the fourth array. This data demonstrates using easily measured properties, to simplify the soil quality assessment system, does not always produce accurate results.

Considering the phenomenon of climate change and subsequent changes in plant water requirements, it is crucial to recognize and estimate climate change in the coming decades with the aim of proper environmental planning to adapt to future climate conditions and reduce its effects. The main factor in the consumption of water resources in arid and semi-arid areas is agriculture and, accordingly, evaporation-transpiration, therefore, awareness of the process of changes and its prediction plays an effective role in planning, development, and water resources management. Since evaporation-transpiration accounts for an important part of the water balance of arid and semi-arid regions, its correct estimation is very important in the optimal preservation of water resources. On the other hand, knowledge of evaporation-transpiration process is necessary to estimate plant water consumption and design irrigation systems. According to the conducted research, estimation of evapotranspiration in the present and future periods is one of the basic needs of development managers, therefore, this research aims to evaluate the evapotranspiration potential in the base period (1991-2005), and predict temperature changes, using 3 scenarios (RCP2.6, RCP4.5, and RCP8.5) and evapotranspiration based on CMIP5 models (1.1 BCC-CSM and CCSM4) in the 75 year period (2025-2100) was carried out in Tabriz city.

For this purpose, the Penman-Monteith method was used as a standard algorithm to estimate potential evaporation and transpiration in the basic period (1991-2005). Then, potential evaporation and transpiration in the period of 2025 to 2100 were estimated using 2.6 RCP, 4.5 RCP, and 8.5 RCP scenarios and the LARS-WG6 model. Finally, the predicted values of evaporation and transpiration in future periods were predicted using the statistical indicators and the calculated evaporation and transpiration values for the base period (1991-2005). The ROC skill score curve also was used in order to general assessment of the quality of the estimations.

The results showed an increase in the predicted potential evaporation and transpiration under the RCP scenarios. In all three scenarios, the highest amount of evaporation-transpiration was obtained in July and the lowest amount was obtained in December. Moreover, an increase in the predicted transpiration evaporation was observed in July, August, January and February, compared to the base period. In addition, a decrease in the predicted transpiration evaporation was obtained in November and December, compared to the base period. In the RCP 8.5 scenario, the difference was much higher than in the base period. The evaluation of the model performance showed that for the hot months of the year, the model had a better ability to estimate the amount of potential evaporation-transpiration compared to the cold months, and the lowest RMSE error was in the hot months, so that in January with a value of 0.15 mm, the lowest value Dara showed the error. A comparison between the months indicated the two months of February and August as the best estimation for the estimation of annual evapotranspiration values. Likewise, the results showed that in all future periods and under all scenarios, the average reference evaporation and transpiration in annual scales will increase significantly at the level of 0.01 compared to the base period. The verification results also showed an acceptable ability for the predictions of the potential transpiration evaporation model.

This research amed at investigation of the amount of reference evapotranspiration changes based on RCP radiative forcing scenarios and climate models from 2025 to 2100 in Tabriz. The obtained results indicate the increase of reference evapotranspiration in all RCP scenarios for each of the future periods. In addition, the highest percentage of the reference evapotranspiration changes in the 8.5 RCP scenario is more than other scenarios because this scenario predicts the worst climate conditions and obvious changes in evapotranspiration will occur. The results of this research can be beneficial to solve the challenges of managers and relevant officials in the future periods. Considering this, the water, environment and health sector planners should adopt the necessary solutions for adaptation and reducing the consequences. Reasonable use of water resources is inevitable under the conditions of warming weather in Tabriz. Increasing evaporation and creating important changes in the quality and quantity of water resources, consequently changes in the quantity and quality of agricultural products. This situation determines the necessity of planning changes in the exploitation of water resources and agriculture. The future plans should be such that the upcoming changes have less harmful effects on the water and agriculture sector in this region. It is necessary to consider measures to improve the irrigation system, reduce evaporation, reuse wastewater and improve the cultivation pattern.

This study aimed to estimate the spatial distribution of soil properties including field capacity (FC), permanent wilting point (PWP) and  total available water (TAW) using ordinary kriging (OK) and random forest (RF) in agricultural lands of the southern Sistan Plain, covering an area of approximtely 147000 hectars. FC, PWP, and TAW and soil texture components were measured for a total of 200 surface soil samples (0-30 cm). Performance evaluation of the two methods based on the percentage of normalized root mean square error (nRMSE) revealed that the conventional OK with 5% less error in estimating FC, 3% less error in estimating PWP, and 5% less error in estimating TAW performed slightly better than RF. Comparing Bias values showed that OK underestimates both FC and PWP and overestimates TAW, while RF overestimates all three parameters. Spatial distribution maps of FC, PWP, and TAW produced by OK model showed that the highest amount of FC (23%) and TAW (14.4%) were in the west and northeast of the region, which had heavier texture and lower altitude from the sea level. In the southern and southeastern regions, which have lighter soil texture, the amount of available water was less compared to the western and northeastern regions. In the RF model, the most important variable extracted from satellite images was Digital Elevation Model  (DEM), and all three features had higher values in areas where DEM was lower. It seems that the flatness of the study area and the inadequacy of auxiliary variables caused the lower accuracy of the RF method.

Human activities in the range of natural resources affect the sustainability or instability of ecosystems. Therefore, data interpretation and analysis related to these activities can play a pivotal role in assessing environmental issues and problems. The aim of this study was to analyze human activities in the watershed to investigate the development of rainfed orchards on sloping lands and the stability or instability of related activities. For this purpose, field studies were conducted in two regions of arid (Birjand) and Mediterranean (Khalkhal) and the impact of the orchard estabilishment on the lands of these regions was analyzed. Contrary to expectations, in the arid region with about 170 mm of rainfall, the orchard estabilishment was successful and accompanied by sustainable development, and in the Mediterranean region with more than 350 mm of rainfall, this project was considered failed and unstable. One of the most important factors for the success of this project in the arid region was having indigenous knowledge in creating dams in suitable areas by collecting runoff and sediments, according to the parent materials and the resulting soil. In contrast, the lack of indigenous or formal knowledge in the Mediterranean region, followed by a lack of attention to soil constraints, some of which are affected by parent materials, is one of the main reasons for the failure of the project in this region. Based on the results, For sustainable management special attention should be paid to indigenous knowledge along with formal knowledge.

A national project was carried out in 10 provinces in order to compare the fertilization method of farmers with the integrated method of soil fertility recommendation for canola plants. The experiment included 54 farms in the provinces of Golestan, Mazandaran, Khuzestan (Dezful), Khuzestan (Ahvaz), Ardabil (Maghan), East Azerbaijan, Isfahan, Bushehr, Khorasan Razavi, Kermanshah, Fars and Varamin regions. These areas consisted of a wide range of canola cultivation regions, climatic conditions and a different range of soil characteristics. In a part of selected fields, fertilization was recommended based on the soil test (optimal use of fertilizers) and in the other half of the fields, application was according to the traditional method of the farmer in the region. At the end of the growth stage, the seed yield of treatments was compared in each province and in each region. According to the results, phosphorus had the highest percentage of deficiency in the soil of the fields, and among the micro nutrients, the highest deficiency was related to the zinc element. On average, the increase in grain yield of first year was 600 kg ha-1 or 24%, compared to the conventional treatment. In the second year, the increase in grain yield was 784 kg ha-1 or 27.4%. For the average of two years, the amount of 692 kg ha-1 or 25.7% increase in grain yield was obtained. The benefit to cost ratio of different regions depended on the characteristics of the soil and the amount of used fertilizers. The highest value of this ratio was obtained from the region of Neishabur (26.52) and Darab (22.31. The lowest was obtained from Bushehr (0.28). The results showed that the consumption of fertilizers with considering the time, quantity, source and method of application will improve the yield of canola in all regions.

The development of olive cultivation needs detailed studies to achieve the maximum yield and product quality by applying management plans including nutrition. In this research, the interactions of gas exchange and photosynthetic parameters were investigated with leaf nutrients contents of olive trees (cv. ‘Arbequina’) in super high density (SHD) cultivation under saline and calcareous soils condition in Tarom Sofla, Zanjan, Iran. The nutritional disorders and their effects on photosynthetic indices were revealed using the compositional nutrient diagnosis (CND) index micronutrients and macronutrients status. Finally, principal component analysis (PCA) was used to determine, the effects of all parameters on yield. The results showed that photosynthetic parameters had a significant positive correlation with nutrients such as zinc, phosphorus, and copper. Photosynthesis, transpiration, and stomatal conductance had highly correlated with yield of olive trees, which are important factors in increasing yields. The final CNDr2 index showed nutritional disorders in most orchards in the low yielding group. The average order of nutrient requirement is Ca> Mg> N> P> K in macronutrients and Zn> B> Mn> Cu in micronutrients in the group of low yielding orchards. The principal component analysis showed that highest yield of olive trees had a higher positive correlation than other orchards with P and K in macronutrients and Zn, and Cu in micronutrients; this increased the rate of photosynthesis and yield. PCA also showed the hidden effects of Ca and Mn deficiency on the reduction of photosynthetic parameters and yield.

Soil water repellency reduces soil infiltrability, water availability for plants, and can increase surface runoff, soil erosion and preferential flows, and reduces environmental fertility. Land use is one of the factors affecting soil water repellency. Soil water repellency can increase runoff in areas where land use change occurs. Thus, knowledge about the soil water repellency properties is necessary for effective environmental management. Changing the soil properties upon reduction of soil wettability can affect crop growth and yield, and water use efficiency. However, relations between soil water repellency and physical and chemical properties among different land uses in the large scale have not been studied yet. Therefore, the objectives of this study were: i) to investigate the persistence and severity of soil water repellency in different land uses, and ii) to develope regression relations between the water repellency indices and soil physical and chemical properties in the central part of Mazandaran province.

In this study, the persistence and severity of soil water repellency were investigated in the paddy fields located in the plains to mountainous areas consisting of four land uses of pasture, citrus garden, paddy field, and forest located in Amol city in the central part of Mazandaran province. Ninety-two soil samples were collected to determine soil water repellency and physical and chemical properties in the dry season of the year. The persistence of soil water repellency was determined using the water droplet penetration time (WDPT) test, and water repellency index (RI) and soil-water contact angle (β) were measured using the intrinsic sorptivity test in the laboratory. Correlation between water repellency indices and soil properties was studied. Relations between the water repellency indices and soil properties were derived by multiple regression.

Soil water repellency in all the land uses was sub-critical and all of the soil-water contact angle values were less than 90°. The highest mean values of soil water repellency indices in all methods were found in the forest land use, so that Log WDPT value was significantly different from paddy field land use. Log WDPT showed positive and significant correlations (r = 0.33**) with RI, indicating that the water repellency persistence (i.e., Log WDPT) and water repellency severity (RI) are directly related in the studied soils. The correlation between soil organic matter content and calculated β in the citrus garden land use was positive and significant (r = 0.42*). There was also a positive and significant correlation between Log WDPT and soil organic matter content (r = 0.36***). Negative and significant correlations were found between calcium carbonate equivalent (CCE( and Log WDPT in the whole study area (r = -0.28**) and in the paddy field land use (r = -0.29*)

The results showed that the land use through the effect on the soil organic matter content can induce and intensify water repellency in the studied soils. Moreover, the derived regression relations indicated that soil organic matter content, total nitrogen and CCE are important properties affecting water repellency in the studied soils.

One of the practices to improve the agricultural management of paddy fields for sustainable rice production is land equipment, renovation, and integration operations. However, due to some shortcomings, this does not seem to achieve all its goals. Therefore, the purpose of this study was to evaluate the effect of land leveling operations on non-uniformity and severity of changes in soil fertility using fuzzy logic and integrated fertility quality index, in paddy fields of Khosroabad village which is located in fouman city in Guilan province where the land equipment, renovation, and integration operation has been done. In two stages, before and after land leveling operations, 95 and 126 soil samples were prepared from surface horizons, respectively, and then some soil properties related to rice fertility (electrical conductivity, clay, organic carbon, total nitrogen, available phosphorus and available potassium) were measured. In the next step, using fuzzy functions, soil quantitative characteristics were converted into qualitative variables and by using the effect of weight on qualitative variables, the integrated fertility quality index was calculated. The results of measured properties, calculated indices, and the produced maps from them, showed that due to the land leveling operation, the average amount of clay increased (76/9%), and organic carbon, nitrogen, available phosphorus, and available potassium decreased (37, 32%, 41/7 %, and 20/3%, respectively) significantly. One of the main reasons for this is excavation operations and the placement of subsurface soil with more clay and lower concentrations of nutrients in the lower horizon. The integrated fertility quality index also decreased (from an average of 0.31 to 0.18) in most of the studied areas. As a result, it seems that improper implementation of agricultural land equipment, renovation, and integration operations, by reducing the fertility of topsoil, will have long-term negative effects on agricultural land, that elimination of which, will increase the cost of production.

Nutrient management, as recommended by fertilizers, is essential for achieving an economically sustainable rice crop. Nutrient management programs for each farm condition should have the least adverse environmental effects while optimizing farmer's production and profits. This study was conducted to determine the most appropriate rice plant nutrition management in paddy fields in terms of yield and economic benefit from 1397 for two years. In this study, ten farms were selected in Kuchesfahan section, that were different in terms of soil characteristics and nutritional management. Then, in each field, six plots were prepared and fertilizer treatments including N0 (without nitrogen), P0 (without phosphorus), K0 (without potassium) and N1P1K1 (general fertilizer recommendation of Rice Research Institute), N2P2K2 (fertilizer recommendation of rice research institute based on soil testing) and N3P3K3 (fertilizer recommendation based on soil test plus full fertilizer and growth stimulant fertilizer) were applied in them and compared with the customary fertilizer management of the farmer. In this study, characteristics related to soil fertility and crop yield were measured and soil nitrogen, phosphorus and potassium supply were calculated. The results showed that indigenous supply of nitrogen and phosphorus in the soil was low in the range of 20 to 37 and 3 to 9 kg.ha-1, respectively. Combined analysis of data variance showed that the effect of fertilizer treatments on paddy yield was significant at 5% probability level and the highest average yield related to N3P3K3 treatment was 3968 kg.ha-1. But this recommendation did not differ significantly from the treatment (N2P2K2) with an average yield of 3914 kg.ha-1. These two recommendations significantly increased the average rice yield by 259 and 313 kg ha-1, respectively, compared to the usual crop management yield. The economic benefits of N2P2K2 nutrition management practices were not significantly different from N3P3K3, however they were significantly different from the management of farmer custom. These findings showed that for economically sustainable production of rice, it is necessary to pay attention to the interest-cost balance along with the type, amount and time of fertilizer inputs.

Rapid growth of population, followed by increasing food demand, necessitates knowledge of the relationship between yield and soil conditions. The soil quality index (SQI) is one of the indicators showing the soil conditions and the related properties very well.This study was performed to determine the effect of soil quality on rice yield in north of Iran (Gilan province). 64 soil samples from rice fields were prepared to measure the physical and chemical properties affecting soil quality and also the yield of rice in the mentioned fields were determined using plot. Then the total yields were divided into three classes with yields of less than 4000 kg/ha (first class), 4000-4500 kg/ha (second class) and more than 4500 kg/ha (third class). Among the studied properties, 16 properties as selected indicators of total data method (TDS) and five properties using principal component analysis as selected indicators of minimum data set method (MDS) were selected to determine the soil quality index. Fuzzy logic was used for scoring and the concept of communality index was used to weight the indicators and finally they were combined using weighted additive method. The results of quality index showed a positive and high correlation between TDS and MDS methods (R2 = 0.87). The results of correlation coefficient between yield and SQI by TDS method (R2 = 0.52) were higher than the SQI by MDS method (R2 = 0.28).  In the MDS method, simmilar to TDS method, there was an increasing trend in the SQI value of higher yield classes, but there is no significant difference between the second and third classes. The difference between soil quality and lower yields with MDS method is significant, but this difference is not significant at higher yield levels, because as the number of indicators decreases, the accuracy and sensitivity of soil quality assessment decreases.

Irrigation water scarcity is one of the major limiting factors in agricultural production. This study was conducted to investigate the effect of different intensities of water deficit stress on yield and water use efficiency of Chamran 2 wheat cultivar in a moderate-textured soil in Khuzestan province. In this research, 10 treatments including full irrigation and water deficit stress at three intensity levels (low, moderate, and severe) were applied under two conditions: during whole growing season or at a given stage of plant growth. This research was done as a completely randomized design with three replications. The salinity of studied soil was 2.95 dS m-1, and soil texture was silty clay loam. The mean water use in different stress treatments was less than full irrigation by 17% (moderate-intensity stress in the third growth stage of wheat) to 43% (high-intensity stress throughout the plant growth period). Applying different intensities of water stress caused reduction in wheat grain yield by 13% (low-intensity stress throughout the growth period) to 76% (high-intensity stress throughout the growth period). The results showed that water stress at stem elongation and grain filling stages of wheat reduced the grain yield more than stress at flowering and milk stages. The lowest value of mean thousand kernel weight (28 g) was observed in the treatments applied in the final growth stage of wheat, confirming the importance of irrigation effects during grain filling stage on the quality of grain. The overall water use efficiency in low-intensity water stress (0.78 g L-1) was higher than the full irrigation treatment (0.62 g L-1), probably due to the reduction of irrigation water losses by drainage and evaporation.

Suitable water management in irrigation and drainage networks without mapping water requirement of different plants in macro levels is not possible. Iran was located in arid climate and has Drought problems and management of Drought, need to macro management of its water resources. In this study using meteorological data in Khuzestan, reference evapotranspiration and Wheat water requirement was determined in pilots. Finally different methods of mapping for example regression method, Inverse Distance Weighted and Co- Kridging were evaluated. In calibration stage power and logarithmic regression presented suitable results and have 8 and 16percent error respectively. Result show that ET0 and water requirement have significant relation with height. So these parameters have spatial continuity. In evaluating stage,  The result show that Co- Kridging method with  0.82 R2 (regression coefficient) , 0.66 d(Agreement index)  , 22.9 Root Mean Square Error  and 0.05 Normal Root Mean Square Error  and  5 percent Normal error  has lowest error in estimation of water requirement  of wheat and using this method can mapping water requirement with well accuracy. So Co- Kridging method is the best method between other methods. Use map obtained can has suitable conclusion from wheat water requirement changes in Khuzestan and manage crop pattern base of maps.

Soil physical quality plays a major role in soil quality studies and it is considered necessary for sustainable economic production, conservation of the environment and prevention of soil degradation. To determine the soil physical quality indicators and their optimal range, the specific conditions of land use and type of cultivated plant should also be considered. Unlike other land uses in rice paddies, many soil physical, chemical and biological behavior and properties are altered by adding water to the soil and puddling. Hence, it is expected that its limitations will vary with other soils. Therefore, this study was conducted with the aim of reviewing the definition of soil available water index in assessing soil physical quality based on specific conditions of rice plant and land preparation operations.

40 soil samples were selected from rice paddies of Guilan province, and soil physical and chemical properties were measured. In addition to Dexter's S index, the soil available water index for plant (PAW) was calculated in three different ways including 1) by assumption of filed capacity at soil suction of 100 cm as upper limit of soil water availability (PAW100), 2) by assumption of filed capacity at soil suction of 330 cm (PAW330), and 3) Redefining of PAW using soil saturation moisture and soil moisture at a suction of 2000 cm as the upper and lower limits of soil available water indicator for rice, respectively (PAWrice).

The results showed that assuming the moisture content of the field capacity at the soil suctions of 100 and 330 cm, 65 and 55 percent of the soil samples had a good physical quality, respectively. While redefining of the PAW indicator of rice paddies (PAWrice) confirmed a good to great soil physical quality in 57.5% of the studied samples. In the studied samples, the use of PAW100 overestimated the amount of soil available water in all soil texture classes. While the use of the PAW330 concept has led to an overestimation of the soil available water value in medium soil textural classes (i.e. silty loam and silty clay loam). However, as the soil texture becomes clayey, the estimated soil available water using PAW330 was less than actual value. The variation of the average values of Dexter S and PAWrice indicators in different soil texture classes was observed by the same trend and as silty loam > silty clay > silty clay loam > clay loam > clay. It should be noted that despite the redefining of the soil available water indicator in rice paddies, the value of Dexter's S index in its optimal range for studied soils was more than 0.035.

Difference in the range of soil water availability in rice paddy fields and its effect on rice yields confirmed the need to redefine soil available water indicator paddy fields. In addition, despite the redefining the soil available water indicator, the results indicated that the Threshold value of 0.035 for S index is probably suitable to evaluate soil good physical quality based on the soil water availability for plant in rice paddies.

To evaluate water, soil and plant relationships, soil water availability for plants is very important for irrigation management and scheduling. Integral energy shows the readily available water for plant in the range of soil available water. The purpose of this study was to investigate the concept of integral energy in 40 samples of paddy soils in Guilan province and to study the relationship between this index and various soil properties. The results showed that all soil samples had moderate to heavy texture. The mean Dexter S index in two soil textures including clay and clay loam was less than 0.35 (27% of the soil samples). The mean values of integral energy in the all studied soil samples, assuming the upper limit of soil water available at saturation, field capacity (at soil suctions of 100 and 330 cm) were 226.65, 270.21 and 336.91 J kg-1, respectively. The results showed that the soil texture classes with the highest value of integral energy were associated with the lowest values of S index. Moreover, the results confirm the better correlation between the calculated integral energy, assuming the upper limit at field capacity in soil suction of 330 cm, with the other soil properties. In addition, the integral energy values can be accurately estimated using soil saturation moisture and organic carbon to clay content ratio for silty clay loam (R2= 0.70) and clay loam (R2=0.95) textured soils, respectively.

Multi-variate statistical methods such as principal component analysis (PCA) and regressions could be used to facilitate the interpretation of complex relationships. The objective of this study was to determine the most important soil fertility properties affecting rice yield in the paddy fields. For this purpose, soil samples were taken from the plow layers of 119 points with suitable distribution in the paddy fileds located in Shaft and Fouman cities of Guilan province. Then after, physical and chemical properties of the soil fertility were measured and analysed using descriptive statistics, principal component analysis and regression methods. Results showed that three PCs with eigen values greater than one named as “k and it’s preservation factors”, ”Total N and it’s provider factors” and ”P and Thickness of plow layer” are respectively explained more than 67.4% of the variability in the soil physical and chemical properties and 55% of the yield variability. In addition, the corresponded properties to the PCs explained 80% of the yield variability. Consequently, in order to increase the yield, management practices such as proper fertilizer applications of nitrogen, potassium and phosphorous and proper tillage for creating suitable plow layer are recommended.

Understanding soil biology and ecology is increasingly important for renewing and sustainability of ecosystems. In all ecosystems, soil microbes play an important role in organic matter turnover, nutrient cycling and availability of nutrients for plants. Different scenarios of land use may affect soil biological properties. Advanced information technologies in modern software tools such as spatial geostatistics and geographical information system (GIS) enable the integration of large and complex databases, models, tools and techniques, and are proposed to improve the process of soil quality and sustainability. Spatial distribution of chemical and biological properties under three scenarios of land use was assessed.
This study was carried out in Mirabad area located in the western part of Souldoz plain surrounded by Urmieh, Miandoab, Piranshahr and Naghadeh cities in the west Azerbaijan province with latitude and longitude of 36°59′N and 45°18′E, respectively. The altitude varies from 1310 to 1345 with average of 1325 m above sea level. The monthly average temperature ranges from -1.4 °C in January to 24.6 °C in July and monthly precipitation ranges from 0.9 mm in July to 106.6 mm in March. Apple orchard, crop production field and rich pasture are three selected scenarios in this research work. Soil samples were systematically collected at 65 sampling points (0-30 cm) on mid July 2010. Soil chemical and biological properties i.e. microbial community, organic carbon and calcium carbonate equivalent were determined. The ArcGIS Geostatistical Analyst tool was applied for assessing and mapping the spatial variability of measured properties. The experimental design was randomized complete blocks design (RCBD) with five replications. Two widely applied methods i.e. Kriging and Inverse Distance Weighed (IDW) were employed for interpolation. According to the ratio of nugget variance to sill of the best variogram model three following spatial dependence conditions for the soil properties can be considered: (I) if this ratio is less than 25%, then the variable has strong spatial dependence; (II) if the ratio is between 25% and 75%, the variable has moderate spatial dependence; and (III) otherwise, the variable has weak spatial dependence. Data were also integrated with GIS for creating digital soil biological maps after testing analysis and interpolating the mentioned properties.
Spherical model was the best isotropic model fitted to variograms of all examined properties. The value of statistics (R2 and reduced sum of squares (RSS)) revealed that IDW method estimated calcium carbonate equivalent more reliably while organic carbon and microbial community was estimated more accurately by Kriging method. The minimum effective range (6110 m) was found for microbial community which had the strong spatial dependence [(Co/Co)