نشریه آب و خاک
سال سی و چهارم شماره 4 (پیاپی 72، مهر و آبان 1399)

Freezing-Thawing (FT) cycle is one of the processes that affects runoff generation. It is therefore necessary to control its negative effects due to specific topographic and climatic situation of Iran. However, there is no documented research about positive effects of vegetation cover on controlling detrimental effects of (FT) cycle yet. The present study aimed to explain the affectability of runoff generation from vegetation cover in small experimental plots under FT cycle.

In order to conduct this study, the soil was collected from Badranlou region located in 10 km west of Bojnourd in north Khorasan province. In this study, iron plots with Plexiglas walls with high ability to withstand lateral stresses and thermal insulation with dimensions of 0.5×0.5 m and a height of 0.3 m and a gradient of 20 percent in accordance with the general slope of the maternal area of the soil were used. The soil was passed from 4 mm sieve after air drying and then was placed in the prepared plots. Thirty plots were prepared for the entire selected plants species and transferred to the greenhouse and three species of A. trichophorum, M. sativa and L. prenne were planted. The species were then allowed until completing the main part of the phenological stages to maximally mimic the natural conditions governing the region. A FT cycle including three days of freezing and two consequent days of thawing and rainfall simulation with 72 mm h-1 in 30 min in three plots with vegetation cover was formulated similar to the study area situation. The entire experiments were conducted in three replicates. Similar control plots were also arranged for comparison purposes. Runoff components were measured in two minutes (three-time steps after runoff), three minutes (three second steps), five minutes until the end of the incident (three last steps) and five minutes after the end of the event. After measuring and recording the amount of runoff generation at the end of each rain event, the total amount of runoff generation in different treatments of rangeland species under FT cycle was recorded.

The result showed that the treated plots of M. sativa, A. trichophorum, and L. prenne significantly (P<0.05) reduced runoff generation by 0.97, 0.72 and 0.32 times compared with control treatments, respectively. The different effects of L. prenne and A. trichophorum species on runoff generation under the freeze-thaw cycles was confirmed. However, M. sativa did not have significant effect in reducing the amount of runoff generation compared with the control. The effect of FT cycle due to performance of ice lenses and formation of active melting layer in the soil surface was controlled owing to the presence of litter and adhesion of the surface layer of soil under treatments of M.sativa, A.trichophorum and L.Prenne. Besides, according to the measurement unlike the M. sativa, the main parts of root in two gramineae species of A. trichophorum and L. prenne were distributed superficially and caused more cohesion and improvement in soil aggregation. The runoff generation reduced in the presence of L. prenne more than the other two species. Based on the different studies, the percentage of fiber in gramineae species is more than broad-leaved species. Therefore, the presence of more fiber in A. trichophorum and L. prenne litters and subsequently their more resilience can be an effective factor in the relative reduction of runoff generation. In addition, the results of the study showed that the presence of vegetation on the soil surface increased the accumulation of fine grains on the soil surface and, if the soil remains intact, increases the stability of the soil structure. The accumulation of fine crops in the soil creates a large network of small roots in the soil and the soil particles become more adhesive. Due to the presence of the small roots in L. prenne species, there is the soil greater adhesion and further reduction of runoff in the presence of this plant.

The results of this study verified that plant cultivation can have significant effects on reducing runoff. In this regard, Lolium prenne had maximum benefit on reduction of runoff and soil loss induced by FT cycle due to better formation of superficial root system.

Reducing water resources in the country and increasing water loss in different methods of irrigation have increased oriented the attention to pressurized irrigation, especially drip irrigation. One of the most suitable solutions for proper water resources management in the country is applying drip irrigation system in gardens. The village of Mohammad Abad is located in the central part of Anbarabad Township and has 15 villages. The main economic activity is horticultural practices there. Water losses due to soil evaporation are minimized in pressurized irrigation due to the decrease in the level of soil wetting, as well as the loss of water distribution in the air or soaking the foliage by this method. The use of this method reduces the growth of weeds and, consequently, unwanted water consumption by weeds, which ultimately affects the various aspects of rural life in the area. The purpose of this study was to investigate the effects of new irrigation systems on villagers in Mohammad Abad village. Therefore, this research sought to answer the question of what are the consequences of new irrigation systems in the rural areas of Mohammad Abad.

The research method was based on the applied objective and descriptive-analytic based on the method used. To collect the information in the theoretical part of the documentary resources, in the practical section, a survey method based on the distribution of the questionnaire and direct observation was used. The statistical population of the research was Mohammad Abad village with 15 villages, 1113 households and 5358 people. The four villages including 300 households and 955 people which employed modern irrigation systems were sampled. Next sampling was based on the number of households. According to the research facilities, 50% of households was selected as 150 households. Then, the questionnaires were distributed randomly among the households' supervisors of the village to the number specified, which was allocated according to the population of each village. In the present study, SPSS software was used to analyze the data and Pearson correlation coefficient and regression analysis and one-sample T-test were used to measure the variables. The information gathering tool was a researcher-made questionnaire.

Based on the results, the highest employment in the agriculture and horticulture sector was at 45.3%, which is due to the climate of the surveyed community, and the land inheritance laws. The lowest employment rate was in the administrative and service sector with an average of 5.3%. Moreover, according to the table below, 94.7% of owners have new and drip irrigation systems. Additionally, 13 items were considered to investigate the effect of new irrigation systems on villagers' life. All items were achieved a weighted average and higher score. According to the items studied, the target issue was related to increasing the household welfare (3.78), quantitative and qualitative products (3.76), increasing household welfare (3.78), improving quality of life (3.65), reducing the motivation of immigration (3.49) , increase in product quality (3.93), reduction of irrigation problems (4.48), water saving (4.49), increase in the economic situation of people (3.65), increase in production efficiency (3.78), return of immigrants (3.61), reclamation of abandoned lands (4.46) which all were above-average. Overall, the economic status as a general indicator with average of 3.90 was also above-average. In addition, there was a positive and significant correlation between all variables with new irrigation systems. Thus, new irrigation systems have had a positive impact on the improvement of all variables. The income increase, return of migrants and increase in efficiency of production seem to be more useful variables for predicting the rural population's economic status.

Based on the results, applying traditional irrigation increased irrigation costs and reduced the production efficiency and the quantity and quality of production in our studied region. Modern irrigation has had a positive effect on the economic and social condition of the villagers leading to increased revenues. Consequently, this has resulted in the restoration of the abandoned lands and the return of migrants. The results also show that the use of new irrigation systems, in addition to reducing water losses, will increase household income, product quality and the level of welfare and quality of life, reduce migration, and restore the deserted lands.

In recent years, canola cultivation in Iran has been considered as oil production, and in 2014-2015, it has been allocated to 7.7% of the cultivation area of industrial products of the country. The yield of canola oil and seeds depends on the availability of sufficient water resources during the growth period. In the Mediterranean, with the cultivation of canola autumn, the high- temperature occurs in the stages of formation and growth of seeds in the spring can increase the water requirement of this plant and irrigation management at this time is important in increasing plant yield. Due to the weather conditions of each area, type of variety and soil conditions may vary the need for canola. In one study in Hamedan water use efficiency of canola in two ways drip and furrow irrigation were calculated as 1.09 and 0.63 kg m-3, respectively. The present study was conducted with the purpose of evaluating the net water requirement of canola plant in different cities of Isfahan province into different climatic zones and considering the phonological stages.

In order to estimate the net water requirement of canola under two different climates (arid-cold winter with temperatures above freezing point - hot summer A-C-W) and (Semi-arid-cold winter with a temperature equal to or less than zero-hot summer SA-K-W) in Isfahan province, a research was conducted in 2014-2015 using a completely randomized, unbalanced design. The study was carried out in different cities of Isfahan province, which have canola cultivation. The required statistical information was obtained from 28 stations of synoptic and climatologic meteorology in Isfahan province and some neighboring provinces. Soil data was used to calculate the soil evaporation coefficient (Ke), which describes the evaporation component in the trait (ETc). In order to calculate the soil properties, in addition to the sampling of existing fields, a database of 1600 soil profiles in the Soil and Water Research Department of Isfahan province was also used. The plant growth stages were considered based on FAO’s 56 irrigation and drainage journal. For analyzing data in each climate, a completely randomized, unbalanced design (with inequality repeat) was used, and the meanings were compared with Duncan’s multiple range test (at 5% level).

There was a significant difference (α=1%) between the different cities in terms of total water consumption and the net water requirement of different phenological growth stages. In the SA-K-W climate, the net water requirement for each hectare of canola cultivated in the cities of Fereydoun Shahr, Friedan, Golpayegan, Khansari, Semirom, Tiran and Karvan, Shahreza, Chadegan, Dehaghan, and Boein va Mian Dasht was 3936, 4069, 4258, 4011, 3991, 4147, 3964, 3961, 4035 and 4055 m-3, respectively. In the SA-K-W climate (with ten cities), the net water requirement of canola was estimated at 4,000 m-3 ha-1. The difference between the highest and the least water requirement in this climate were 322 m-3 ha-1 and related to cities of Frieden and Fereydoun City, respectively. In the climate of A-C-W (12 cities), canola net water requirement was 892 m-3 ha-1 more than the net water requirement of this crop in the SA-K-W climate. On average, the initial, developmental, and (middle and final) net water requirements of the canola in the A-C-W climate were 540, 2150, and 2200 m-3 ha-1, respectively. The net irrigation requirement estimated for each ha-1 of canola cultivation in Isfahan, Ardestan, Khomeini Shahr, Falavarjan, Kashan, Lenjanat, Naein, Najaf Abad, Natanz, Shahin Shahr, Mobarakeh, and Borkhar cities was 4747. 4807. 4797, 5,105, 4885, 4908, 4750, 4785, 4974, 4971, 4879 and 5097 m-3, respectively.

Based on the results of the 10 cities in the SA-K-W climate, canola production per hectare requires an average of 4,000 cubic meters of net water per hectare. In the A-C-W climate of 12 cities, the average net water requirement per hectare was 4892 m-3. The difference in water requirement between this climate and the climate of SA-K-W was related to the middle and late stages of canola growth.

Sugarcane fields of the southwest of Iran have heavy soil texture, high temperatures, hot and dry wind flow at spring and summer seasons. The electrical conductivity of irrigation water was considered about 1.1 dS.m-1, in basic designs of this irrigation method. In addition to sugarcane production, sugar is a fundamental good in the economic section of Iran. It has multiple use in food, medical and chemical industry, production of by-products such as feedstuffs, yeast and alcohol, wood and paper. Sugarcane requires lots of water during the growing period and sensitive to water stress and is not compatible with long duration of flooding. If groundwater rises and covers the root zone, crop yield decreases due to root rot. Significant benefits are identified in terms of increased yield, improved crop quality, reduction in applied water, and reduced agronomic costs for weed control, fertilization, and tillage. Improved water management is crucial for a sustainable future, and SDI will be one tool that is available to improve water productivity. The main advantages of SDI are related to water savings because water is applied directly to the crop’s root zone, which prevents losses due to direct evaporation from the soil and deep drainage, and, if properly managed, SDI allows for the maintenance of appropriate levels of soil moisture. Due to the water crisis in Iran, this study aimed to reduce the volume of consumed water and water productivity for sugarcane and sugar yield by managing water consumption using drip irrigation for the first time in the cultivation of sugarcane.

According to recent droughts and severe water crises in Iran, subsurface drip irrigation was implemented in sugarcane for the first time. It seems that water consumed in subsurface drip irrigation is less than other methods. Therefore, its effect was investigated by 15, 20, and 30 cm depths and 75 cm space of subsurface emitters and comparison with control, on water productivity and sugarcane yield. An experiment based on randomized complete block design was carried out at the Sugarcane Research and Training Institute of Khuzestan in the South-West of Iran. After harvesting the plant field (start Ratoon), soil samples were collected at 0-30, 30-60, and 60-90 cm depths. In order to measure the bulk density of soil, samples were collected from the undistributed samples with sampler cylinders, and the texture was determined by the hydrometer method. To assess soil moisture percentage, pressure plate was used for determining content in field capacity (FC) and permanent wilting point (PWP) (the results were 25.1% and 12.9%, respectively). Emitters were pressure controlled emitter type, anti-siphon and the pressure at the pump station was 4.3 bar, and emitters with a flow 2.2 liter-1 and the depth of emitters pipes were 15, 20, and 30 cm from the surface soil. Depending on irrigation frequencies and irrigation water acidity, acid was injected into the irrigation water to prevent clogging of the emitters. After a specified time, it was discharged from the network. Regarding the presence of algae in irrigation water, chlorine gas was used in acid filtration before irrigation in field capacity. Finally, the average quantity and quality functions and Water Productivity in subsurface drip irrigation were compared with compression irrigation. For data fitting and curves, EXCEL software was used, and SAS statistical software was used for statistical analysis. Also, to investigate the salinity distribution in drip irrigation, the mean soil samples were used during the sampling period. The figures were drawn using 8 Surfer software in two dimensions. In drawing the shapes, Craig’s introspection was used.

High evaporation, air temperature, and relatively low quality of irrigation water are the most important limiting factors for sugarcane irrigation in Khuzestan. It seems that according to the research records, the irrigation of subsurface drops with proper management is successful. Therefore, for this purpose, the effect of planting depth of 15, 20, and 30 and a distance of 75 cm drops and to compare with the regular irrigation of sugarcane lands as control (control), on water productivity and sugarcane yield complete random blocks was applied. The results of the analysis of variance of quantitative traits showed significant effects of the planting depth of droplets, in terms of yield at the level of one percent and in terms of stem height traits, number of stems per hectare, and water efficiency per sugarcane and produced sugar, at the level of five percent. According to the results of qualitative traits, the effect of treatment of droplet implant depth in all traits was non-significant. At a depth of 20 cm, the highest efficiency of water production for sugarcane and sugar production were 1.6 and 0.73 kg / m3, respectively. The lowest water productivity for sugarcane and sugar produced in the control treatment was 4.2 and 0.51 kg / m3, respectively. As a result, water productivity in the treatment of selected index (planting depth of 20 cm) per sugarcane and produced sugar has resulted in an increase of more than 30% in water productivity compared to the usual irrigation of fields (control). The results of salinity distribution around the droplets also showed that under the conditions of irrigation of subsurface droplets with salt water, the lowest salinity values ​​were always seen as a range around the droplets. With increasing distance from the droplets, the salinity increased. More salts The drops are concentrated in the streams on both sides of the drops, The highest salinity occurred at the bottom of the furrow, and the lowest salinity was found on the ridge, where the drip pipe was planted and on either side of which there were two rows of reeds.

Subsurface drip irrigation is one of the most optimal irrigation methods that are almost unknown to sugarcane in the executive, research, and academic sectors, and has been implemented for the first time in sugarcane cultivation in Iran. Given the recent droughts and the crisis and water scarcity, and the importance of environmental issues, it will be invaluable to investigate further and apply them. In general, in this study, using a flow rate of 2.2 lit/hr and a space of 75 cm and an installation depth of 20 cm droplets, the highest quantitative and qualitative functions and the highest water productivity per sugar cane. And the sugar produced. Also, regardless of any deepening treatment, the drip irrigation system, compared to the conventional irrigation system, reduced water consumption by about 20% and water yield by 26% per sugarcane and sugar produced. According to the results and considering the uniformity of moisture distribution, soil surface salinity, lack of runoff, protection of the discharge pipe, removal of surface evaporation and sugarcane root development, depth of 20 cm, application of the discharge pipe with a distance of 75 cm drops on the hose with a flow rate of 2.2 lit/hr are recommended. Also, although the distribution of moisture onions is provided up to a distance of 80 cm, a shorter distance between the droplets, such as 60 cm with the above flow, needs further investigation.

In recent years much attention has been paid to the environment, especially river and lake pollution. Rivers and streams are usually receiving the outlet of sewage systems which may cause pollutant levels to rise. Pollutant dispersion is a key element in water quality modeling and the longitudinal dispersion coefficient is an important factor in stream pollution modeling due to its effect on pollutant mixing intensity. Various methods proposed to estimate longitudinal dispersion coefficient in natural streams based on different procedures and different set of data. The performance of the methods presented in previous research is mainly based on precision indices that alone cannot be used as a comprehensive index for comparing different methods.

In this study, in order to evaluate the performance of different methods, a combination of uncertainty criteria along with accuracy indexes were considered. First, the interval analysis approach was used to evaluate the uncertainty of different methods such as Deng et al. (2001), Kashefipour and Falconer (2002), Sahin (2014), Zeng and Huai (2014), M5 and Gene Expression methods. For ± 10% uncertainty in the independent parameters of estimating dispersion coefficient, for all 164 measured data, the probability bands of computational longitudinal dispersion coefficient was obtained for the 6 estimator methods. Then, by comparing the actual measured values with the position of the computational uncertainty bands, 10 uncertainty and accuracy indices were calculated for each estimator method. To determine the most appropriate method for estimating longitudinal dispersion coefficient with less relative uncertainty and greater relative accuracy, weighting was performed on 10 uncertainty-accuracy indices using the G1 weighting method, and then the performance of the methods was evaluated by three multi-criteria decision models including CUI, TOPSIS and VIKOR.

Based on the results, the M5 tree model has the lowest containing ratio among all methods and also has the lowest band, while the Kashefipour and Falconer (2002) model has the highest containing ratio and band values. In addition, for all methods except the method of Deng et al. (2001), the parameter of average deviation amplitude decreases with increasing containing ratio. Among the methods used, the M5 tree model has the lowest CR and the highest D. Based on the uncertainty and accuracy analysis, the method of Deng et al. (2001) was better than other methods and then the equation presented by Zeng and Huai (2014) with CUI = 0.717 had the best performance. The two data-driven methods of the M5 and GE are also ranked next. The results of TOPSIS method are completely in accordance with CUI method and there is no difference between the two methods. According to the VIKOR method, the two methods of Deng et al. (2001) and Zeng and Huai (2014) performed the best, followed by data-driven models. The only difference between the results of the VIKOR model and the two CUI and TOPSIS methods is the ranking of the two data-driven methods, so the GE model is more efficient than the M5 model in VIKOR method.

The results of the three multi-criteria decision-making methods were close to each other and in all the methods, the mathematical model of Deng et al. (2001) and the empirical model of Zeng and Huai (2014) were more efficient than the other methods. It is important to note that the uncertainties of decision-making models have not been examined in this study and the purpose of the present uncertainty study has been to quantify the inherent uncertainties of the methods and relationships for estimating the longitudinal dispersion coefficient.

Suspended load estimation is utilized to study and investigate many problems of water engineering sciences such as dam reservoir design, transportation of sediments and pollution in the rivers, creation of stable channels, estimation of erosion and sedimentation around bridge piers, and watershed management. The purpose of this study was to estimate the suspended load in the Dareh-Roud watershed in Ardabil province using the rivers discharge values and the physiographic characteristics of the sub-basins. Moreover, annual suspended load and sediment specific discharge were calculated for the whole of the watershed.

In this study, the Dareh-Roud watershed in Ardebil province was considered as the study area. The flow discharge and suspended load data were collected from 16 hydrometric stations with a statistical period of 15 years from 2001-2015. The physiographic characteristics of sub-basins, including area (A), slope (S), shape factor (Sf), and curve number (CN), were achieved using ArcGIS and WMS. Five different input combinations were defined based on the effect of flow discharge variables and physiographic properties on the suspended load. Also, considering the area and slope parameters, the sub-basins were divided into two groups (i.e., the first and second groups). The performance of data-intelligent models, including Artificial Neural Networks (ANN), Adaptive Neural-Fuzzy Interference System (ANFIS), and Gene Expression Programming (GEP) models were investigated in the predict of the suspended load in the study area. Several statistical indicators, including determination coefficient (R2), root mean square error (RMSE), and Nash- Sutcliffe efficiency (NS), were utilized to evaluate the model’s efficiency.

According to the results, estimation of suspended load without using the physiographic characteristics resulted in a high error, and in contrast, the suspended load estimation was most accurate by using a combined scenario involving all physiographic aspects and flow discharge. The scatterplots indicated that in the first group, the points were concentrated around the 1:1 axis for the values of less than 20 (ton/day). However, for the greater amounts, the scattering of issues around the one-to-one line was not appropriate, which means that the models were in the condition of underestimation. Similar conditions were observed for the second group, the excellent dispersion was seen for the values of less than 1000 (ton/day), and in general, the models had underestimation conditions. However, in both groups, the dispersion of the GEP model was somewhat better than the other models. Based on the values of R2 and NS, ANN and ANFIS models had the acceptable and satisfactory accuracy for the first group. The GEP model was more reliable and efficient in estimating the suspended load of the first group. On the other hand, the efficiency of ANN and ANFIS was not acceptable for the second group. Comparison of the results of different models using the best input combination indicated that the GEP model with the highest determination coefficient (R2 = 0.68), the lowest root mean square error (RMSE = 7.69 ton/day). The NS equal to 0.55 in the validation step has shown better performance than the other models in estimating the suspended load for the first group. Similarly, for the second group, the GEP model with the highest determination coefficient (R2 = 0.72), the lowest root means square error (RMSE = 975.26 ton/day). The NS equal to 0.43 in the validation step has shown better performance than other models in estimating the suspended load.

In the present study, the efficiency of different intelligent models was investigated in the suspended load estimation of Dareh-roud watershed. In this regard, an extended period (i.e., during 15 years) of measured data, including flow discharge and sediment at the hydrometric stations located on the mentioned watershed, were used. In order to simulate the suspended load, five different input combinations were considered. For all models, the accuracy of suspended load estimation was improved by combining the physiographic characteristics and discharge values. Due to the higher accuracy of the GEP model, regional sediment models were achieved for the first and second groups, separately. Also, annual suspended load and sediment specific discharge were calculated for all sub-basins. According to the results, most of the suspended load of the Dareh-Roud watershed is produced and transported in its old rivers (i.e., Dareh-Roud and Qarah-Su). Based on the results of this research, in the Dareh-Roud watershed, 6.33 million tons of suspended sediments were transported during 2001-2015.

Although jujube (Ziziphus jujuba Mill.) is known as a medicinal plant and is less important than other fruit trees, it has received more attention in recent years due to its significance in traditional Iranian medicine. There is no study on the actual water need for jujube trees and the impact of irrigation on yield and water use efficiency in the country. However, some studies emphasized on the need of regular watering and irrigation to improve the quality and quantity of jujube fruit. Given the importance of jujube in China, extensive researches have been conducted on water requirements, plant strategies to save water, impact of drought stress on plant morpho-physiological behaviors, impact of appropriate water distribution on soil quantity and quality of plant development, root distribution patterns and its impact on the amount of water consumed. In all cases, it has been emphasized that the mechanisms of water consumption in jujube differ by climate, genotype, irrigation method and management. In order to improve the quantity and quality of jujube fruit, it is necessary to balance the soil moisture condition and keep the plant away from stress. However, dehydration in jujube is a serious issue that should be addressed with the aim of saving water and improving fruit quality. In this study, the actual water requirement of the plant, the effect of different levels of deficit irrigation on evapotranspiration (ET) and crop coefficient (Kc) rate, yield and water use efficiency (WUE) in jujube trees were investigated. The moisture stress was applied through all stages of plant growth by deficit irrigation.

In this study, the lysimeter experiment site of Yazd (Shahid Sadoghi Desertification Research Station) with 20 weighing drainage lysimeters (170 cm in height and 121 cm in diameter) was used. To measure evaporation from the soil surface, one lysimeter without plant was used. Note that the moisture content in this lysimeter was always maintained at the field capacity. For the measurement of reference ET (ET0), one lysimeter was used and it compared with ET0 calculated by Penman-Monteith-FAO. After preparing the lysimeters and providing the conditions for planting seedlings, we planted one tree per lysimeter. Trees collected from the villages of Alqoor, Flarg and Gyuk (South Khorasan Province). The suckers were two-years-old with the same size and shape. Trees were irrigated with 50 liters water on a weekly basis for six months. At the beginning of autumn of 2018, treatments including complete irrigation (field capacity), 30% and 60% of deficit irrigation were conducted in a completely randomized design with six replications. Soil moisture measurement during the experiment was performed by TDR. Soil moisture was recorded at 4 depths (0-30, 30-60, 60-90 and 90-120 cm) and their mean was considered as an index of soil moisture status to compensate the irrigation fraction. During the experiment and at the end, indices such as different stages of plant growth, ET, ET0, Kc, yield and WUE were determined. The data were analyzed by analysis of variance (ANOVA) using the statistical package SPSS ver. 16.0, and the mean values were also compared using LSD multiple range test (α = 0.05).

The results showed that the jujube trees began their vegetative growth from late March (leaves appear) until the end of November (leaves fall) over 2017-2018 agronomic year in Yazd. During this time, which lasted about 235 days, four major and important stages were evident. The steps cited were in FAO's recommendation for deciduous fruit trees (in Issue 122 of the Iranian Irrigation and Drainage National Committee). The results of these studies showed that the length of different growth periods of jujube trees (including early stage, plant development stage, mid stage and end stage) was different with another deciduous fruit trees. ET values in three irrigation regimes showed that the highest ET was observed in July and the lowest in March. Annual ET in control, 30% and 60% of deficit irrigation treatments were 828.06, 514.04 and 386.04 mm, respectively, with 0.45, 0.28 and 0.21, annual Kc, respectively. The results of ET and Kc computed at different growth stages showed that the reproductive growth development period (flowering, fruit set beginning of fruit growth) had the highest ET. In control treatment, the lowest ET (60.81 mm) and Kc (0.27) were observed in early growth period with less than 10% of crown cover. The highest ET (316.22 mm) and Kc (0.60) were found in growth development period with full crown cover. Analysis of variance showed that there was a significant difference (P <0.0001) between the different irrigation treatments in terms of dry matter yield. There was a significant difference for WUE (P <0.001) between different irrigation treatments. Each of different irrigation regimes had a significant difference in yield. The highest yield for each tree was found for the control treatment with 229.36 g and the lowest yield with 57.90 g was observed for 60% deficit irrigation regime. There was no significant difference between control and 30% deficit irrigation treatment in WUE. The value of WUE decreased with increasing the drought stress. In 60% deficit irrigation treatment, WUE was 0.366 g fruit dry weight per liter denoting the significant difference between this irrigation treatment and the others.

The results of this study showed that jujube trees were susceptible to drought stress in all four stages of growth, especially the period of growth coinciding with flowering, fruit set and early fruit growth. Hence, jujube trees yield and WUE seem to decrease under drought.

Supplying human and animal nutritional needs requires suitable use of water resources. Due to the decrease of fresh water resources for agriculture, saline water resources cannot be ignored. Increasing water salinity reduces the water absorption by plant, due to decreasing the water potential. On the other hand, soil infertility (such as nitrogen deficiency) decreases the evapotranspiration and crop yield. The present study was to increase the water and nitrogen fertilizer use efficiency of maize, under salinity stress condition. This was done by managing the consumption of saline water and nitrogen fertilizer. In this research, irrigation requirement was determined proportional to the plant evapotranspiration to avoid excessive saline water use.

In this research, two treatments of water salinity and nitrogen deficiency in four levels and three replications were implemented as a factorial experiment in a randomized complete block design. The studied plant was maize (S. C. 704 cultivar) sown in plots with dimensions of 3 × 3 meters and 1.5 meters distance. In this research, fertility stress was in the form of nitrogen fertilizer consumption and at four levels. Treatments of ، ، and consisted of consumption of 100, 75, 50 and 25% of nitrogen fertilizer, respectively. Salinity stress has been applied by irrigation of the plant with saline water. Water salinity treatments were selected based on the yield potential of maize, at four levels of 100, 90, 75 and 50%. According to the above four performance levels, treatments of ، ، and included irrigation water with electric conductivity of 0.5, 1.2, 3.5 and 7.5 (dS/m), respectively. The soil moisture content was measured at the depth of root development during the interval between two irrigations. Daily maize evapotranspiration was measured by the volumetric balance of water at the depth of root development. The stomata resistance of maize leaf was measured by the AP4 porometer device between two irrigations interval. Variance analysis and mean comparison of data were done by SPSS software and Duncan's multiple range test, respectively.

Water use efficiency In this research, the evapotranspiration and dry matter yield of maize decreased under salinity stress and nitrogen deficiency treatments. This seems to be caused by the water potential decrease (due to salinity stress) and the nitrogen deficit in the soil. Under these conditions, optimum use of water and fertilizer increased water use efficiency. At first without water and fertilizer management, water use efficiency in different treatments (to), ranged from 2.74 to 4.4 kg/ (in 2017) and from 2.57 to 4.35 kg/ (in 2018). With suitable management of irrigation, water use efficiency, however, increased in stress treatments and approached to optimum treatment. The range of water use efficiency was from 4.2 to 4.4 kg/ (in 2017) and from 4.15 to 4.32 kg/ (in 2018). The reason for this was the management of irrigation volume based on actual evapotranspiration in stress treatments. On the other hand, increasing soil nitrogen was an appropriate strategy to increase water use efficiency. But in high salinity stress, despite the optimum use of water and fertilizer, it was not possible to achieve optimal water use efficiency. This is explainable by the harmful effect of salinity on the reduction of nutrient uptake (especially nitrogen) by the plant. Nitrogen use efficiency Soil nitrogen deficiency and increasing water salinity reduced nitrogen use efficiency. In different stress treatments, nitrogen use efficiency ranged from 3.34 to 5.11 kg/kg (in 2017) and from 3.06 to 5 kg/kg (in 2018). The results showed the destructive effect of salinity on nitrogen uptake by the plant. Under these conditions, the ions in the soil (especially the sodium and calcium) caused the plant to be unable to absorb nitrogen from the soil. Therefore, the production of plant matter was reduced. The results showed that proper management of nitrogen can increase nitrogen use efficiency under salinity stress. At high salinity levels, the nitrogen fertilizer was not, however, absorbed by the plant and accumulated in the soil.

The results showed that water use management could increase the water use efficiency under stress treatments, by controlling evapotranspiration. On the other hand, soil fertility increased nitrogen fertilizer use efficiency under salinity stress. Among all treatments, had optimum water and nitrogen use efficiency. Overall, the volume of water used in the field should be adjusted to the actual requirement of the plant to prevent excessive consumption under salinity stress. In addition, increasing soil nitrogen, rather than more irrigation water, appears to be a suitable strategy to increase crop yield.

highly increases in population growth rate, in particular in developing countries, cause high pressure on agricultural resources. In north of Iran, the pressures are compounded by restricted rice paddy fields. Reliable and relevant land suitability evaluations are vital requirements for land use policy and decision making to support sustainable rural development. Therefore, it is necessary to employ and compare the classic model (FAO), new release technique (multi-criteria decision making strategy) and the capabilities of fuzzy systems to assess land suitability. In recent years, multi-criteria evaluations including Boolean overlay operators and weighted linear combination methods have been increasingly used. Also, using the Ordered Weighted Average (OWA) method can improve the above-mentioned techniques. The OWA method is able to calculate the degree of risk taking and risk aversion of individuals and apply them to the selection of the final option. Therefore, the purposes of the current study were to explore the most reliable method of land suitability evaluation for rice by using integrated fuzzy decision making and determine the optimum depth of soil for quantitative land suitability evaluation for rice production in Amol, Mazandaran province.

Two-hundred soil samples from 50 observation points at four depths of 0 to 25, 25 to 50, 50 to 75 and 75 to 100 cm with a constant interval were selected. After crop harvesting and taking soil samples from four depths in 50 observation points, and from the genetic horizons of representative pedon excavated in the region, the parameters needed for land suitability evaluation of rice were measured. Then, land suitability classes were calculated using the parametric (square root), Fuzzy-AHP and Fuzzy-AHP-OWA methods and were compared in four depths from 0 to 25, 0 to 50, 0 to 75 and 0 to 100 cm. In Fuzzy-AHP method, Kandel membership functions were used to determine the membership degree and analytic hierarchy process (AHP) was used to determine the weight of each of the effective land properties in crop yield. In Fuzzy-AHP-OWA method, criteria weights were obtained from AHP method and ordered weights using linguistic fuzzy quantifiers.

The results showed significant difference between the potential yield (5.5 t/ha) and the average of actual yield (3.9 t/ha) in the study area. With respect to the same and acceptable agricultural management of all plots, this difference might be due to soil limitations and subsequently a decrease in the numerical value of the soil index. Except for 0 to 25 cm soil depth, actual yield for the other soil depths showed a positive significant correlation with all calculated land indices by parametric, Fuzzy AHP and Fuzzy-AHP-OWA methods. The compatibility percentage between the representative pedon and observation points was remarkable for 0-50 and 0-100 cm depths in three studied methods. Considering time and cost consuming for land evaluation, this finding shows that 0 to 50 cm soil depth information might be a relevant alternative for the optimal depth to evaluate land suitability for rice in studied paddy fields. The results of the Fuzzy-AHP method showed that soil texture and organic carbon content were the most important soil properties for rice production. The results of land evaluation using Fuzzy-AHP-OWA method showed that with increasing the levels of risk (decreasing the value of α from 1000 to 0.0001), areas with a higher suitability degree occupy greater area. This can be explained by the fact that the strategy associated with the fuzzy quantifier all (α=1000) represents the worst-case scenario (the lowest criterion value is assigned to each location) and under the strategy associated with the fuzzy quantifier, at least one (α=0.0001), the land suitability pattern is composed of the best possible outcomes. The highest correlation coefficients (R2= 0.37) were obtained for Fuzzy-AHP-OWA (α=1) based on correlation between actual yields and calculated land indices for different depths of each parametric method, Fuzzy-AHP and Fuzzy-AHP-OWA. This is due to the high trade-off among the evaluation criteria in the half fuzzy quantifier (α=1).

The proposed approach based on Fuzzy-AHP-OWA has great potential to model land use suitability evaluation problem. Half fuzzy quantifier is introduced as the best scenario using Fuzzy-AHP-OWA method for rice land suitability evaluation. This is due to the high trade-off among the evaluation criteria in this quantifier. Given the fact that the land suitability studies are often costly and time consuming, the land suitability evaluation by using 0-50 cm results might be a relevant alternative for the optimal soil depth required for land suitability evaluation in paddy fields.

Dryland farming is a major agricultural practice in northwest of Iran. Accurate understanding of soil fertility status is one of the basic needs of dryland agricultural system. Soil chemical properties play an important role in soil fertility. Assessing soil fertility is an essential need to identify environmental-friendly strategies leading to more sustainability in agricultural systems. Unfortunately, plant nutrients are insufficient in many dry farming areas of Iran, or soil conditions do not allow plant to uptake certain nutrients. Therefore, soil scientists focus on using commercial fertilizers and manures (rotation system and conservation tillage) to add nutrients and organic matter to soil. The fertility of soils can be further improved by cultivation of cover crops through adding organic matter to the soil which leads to a healthy soil with more macro-nutrients and micro-nutrients content and better structure. Therefore, evaluation of soil fertility is a basic tool for decision management in drylands and estimation of capacity of soil to maintain a continuous supply of plant nutrients for a crop production. Evaluation of soil fertility in drylands of the northwest Iran have two objectives 1) Assess nutrient status of soil-crop system 2) Diagnose suspected nutrient imbalances.

This study was carried out in northwest of Iran drylands including: west Azarbayjan, east Azarbayjan, Kurdistan and Kermanshah provinces. A total of 674 soil samples were collected from farmer’s fields in east Azarbayjan, west Azarbayjan, Kurdistan and Kermanshah 414, 97, 90 and 73 samples, respectively. The surface soil samples were taken from 0-25 cm depth in each field before the sowing of the rainfed plants in autumn by composite sampling method. After collection, soil samples were immediately dried, grounded, screened through 2 mm sieve, labelled and stored in plastic container. The samples were analyzed for 12 chemical and physical parameters include: soil texture (hydrometer method), pH (saturation paste) and EC (saturated extract), organic carbon, Total N (Kejeltak), calcium carbonate equivalence (acid-neutralizing value), phosphorus (Olsen), potassium (sodium bicarbonate extracted) and iron, zinc, Mn and copper (DTPA extracted). Soil samples were categorized as low, medium and high on the basis of their availability in soils by two Gomes (1985) (equation 1) and common (nutrient classification by critical level method for dryland wheat) methods. Low Medium Equation (1) High Where, , and SD are soil property, average of soil property in all area and standard deviation of soil property, respectively. In order to compare the levels of soil fertility of one province with those of another it is necessary to obtain a single value for each nutrient. Nutrient index value (NIV) was calculated by Parker et al., (1951) method (equation 2) for soil samples of each province or district from the proportion of soils under low, medium and high categories using following equation: Equation (2) Where, , and are number of samples testing low, medium and high category in each province, respectively. If the NIV is less than 1.67, the soil fertility status is low, the value of 1.67-2.33 reveals optimum fertility (sufficient nutrients). The values greater than 2.33 denote high fertility status.

The results showed that, the Gomes (1985) method could not classify the soil properties in all studied regions (population) correctly, due to the tends towards central limit theorem (optimal condition). Calculation of NIV showed that using conventional method (critical levels) for classification of soil properties was better than Gomes (1985) method because it was more compatible with the field conditions. The results revealed that soil salinity and calcium carbonate did not seriously make problems in dryland areas. However, increasing the amount of calcium carbonate decreased soil phosphorus, potassium, Fe, Mn, Zn and Cu, significantly. Soil phosphorus and Zn were more influenced by increasing calcium carbonate. Assessment of soil fertility status by NIV showed that, soil organic matter was low (deficient) in west and east Azerbaijan with 92 and 69 percent of those areas. But total nitrogen was optimum (sufficient) in all areas with 98 percent averagely (except east Azarbayjan). This is mainly due to the application of nitrogen fertilizers in wheat drylands and conservation tillage system in some areas. Soil phosphorus was evaluated low in two west Azerbaijan (81%) and Kermanshah (67%) provinces, but in east Azerbaijan (68 %) and Kurdistan (85%) were sufficiency or high for wheat production. Potassium was more than sufficiency (high) in 90 percent of all areas averagely. Micronutrients deficiency were observed in some provinces. The results showed the deficiency of Fe with 100 and 69 percent in west Azarbayjan and Kurdistan, respectively. Deficiency of Mn with 89 percent of west Azarbayjan, Zn with 84 percent in east Azarbayjan and Cu with 100 and 87 percent in west and east Azarbayjan were also the other obtained results of this study, respectively. The results of present study suggested that nitrogen and phosphorus fertilizer applications can also be important in micronutrient management in dryland areas.

It can be concluded that the capability of critical level method is better than Gomes (1985) method in classification of soil properties. Nutrient index value (NIV) method can efficiently evaluate soil fertility status in Iran drylands. According to this research, Fe, Zn and Cu nutrient deficiencies are just as important as P and N deficiencies in Iran dryland areas.

This research aimed to evaluate the qualitative land suitability for irrigated cultivation of Date Palm (Phoenix dactylifera L. cv Kabkab) using FAO (parametric -the second root formula) and Multi-criteria approaches. The FAO approach has been used by many scholars in different parts of the world and Iran for land suitability assessment. In this approach, the most commonly used method is the parametric method. The FAO approach uses Boolean logic to assess land suitability. This logic has been criticized by a number of land evaluation researchers. Because it does not take into account the continuous nature of the soil variations along the earth's surface and the uncertainty in the measurements. To overcome these shortcomings, the fuzzy analytical hierarchy process (FAHP) was presented to determine the land suitability classes. Land suitability should be determined based on a fuzzy analytical hierarchy process, in which, unlike the Boolean logic, unequal importance of different land characteristics and continuity of soil variations are considered.

The studied area is located in Kheshet and Komaroj plain, Kazerun County, Fars province, southwestern- Iran; between latitudes 29º 32΄ and 29º 36΄ N and longitudes 51º 20΄ and 51º 22΄ E. Its surface area is 5000 ha. The mean annual rainfall and temperature are 377mm and 23 °C, respectively. The soil temperature and moisture regimes are hyperthermic and xeric, respectively. The physiographic unit is river alluvial plain with a very gently sloping. The entire Kabkab date palm plantation of Fars Province is located in this plain. To fulfill the objectives 10 date palm groves, each with an area of at least 0.5 ha and palm date (Kabkab cultivar) cultivation, aged between 20 and 25 years, identical in soil management and vary soil characteristics were selected. A soil profile was dug randomly in each date palm grove, with dimensions of 1.5 (length), 1(width) and 1.5 (depth) meters and described, using soil profile description (Soil Survey Staff). Soil samples were collected from each horizon. After pre-treatments soil samples were analyzed and some physical and chemical characteristics were measured using standard laboratory methods. The profile site was chosen to have a date palm tree in each of the four corners of the profile. The yield of the four trees in four corners of each profile was measured and their average yield was considered as the yield of the corresponding profile. Meteorological data was collected for a period of 10 years from the nearest synoptic station (Kazerun). Land indices were calculated, using soil and climatic data and FAO (parametric-second root formula) and fuzzy AHP and AHP methods. Weighted average of the climatic and the soil data were used and a land index was calculated for each soil profile. In the fuzzy AHP and AHP methods, relative weight of each of the studied criteria was determined by analytical hierarchy analysis using a pair wise comparison matrix. In the fuzzy AHP method the membership degree for each soil and climatic criteria was determined through an appropriate membership function and finally, land suitability class for each soil profile was determined. Landscape characteristics such as slope, drainage and soil depth were not considered in the land evaluation, because these characteristics did not show any limitation for the date production in the studied area. Finally the accuracy of the methods was compared.

The results of qualitative land suitability evaluation based on FAO (parametric-second root formula) method showed that about 10 and 90 percent of the studied area were classified as S2 and S3, respectively. Based upon fuzzy AHP method, 100 percent of the studied area was classified as S2 and according to AHP method about 90 and 10 percent of the studied area were in S1 and S2, respectively. According to the results, the suitability classes resulted from AHP method was higher than of the fuzzy AHP and FAO methods. Correlation coefficients between the measured yields and the calculated land indexes showed that the fuzzy AHP method results were more correlated to the measured yield than of the other two methods which indicated that the fuzzy AHP was the most appropriate method for land suitability assessment for Kabkab Date palm plantation compared to the FAO (parametric-second root formula) and AHP methods.

According to the results of this research, the fuzzy AHP was the most appropriate method for qualitative land suitability evaluation for Kabkab Date compared to the other two methods in Fars province, Iran

SALTMED model is one of the most practical tools for simulating soil salinity and crop production yield. Growth models are important and efficient tools for studying and evaluating the impact of different management conditions and scenarios on water, soil and plant relationships and can be used to make or predict appropriate management scenarios according to the region's conditions and to predict plant performance in the field. Since the performance of irrigation scenarios in field conditions are costly and time consuming, and due to the limited water resources in the country and the necessity of optimal water use in agriculture, using the efficient and generic models can be useful tool for simulating crop production and soil salinity variations. This research has been conducted in order to simulate soil salinity and yield production using SALTMED model in Azadegan Plain of Khuzestan province.

This study was carried out in wheat fields of Azadegan plain in Khuzestan province during 2014-2015 in three regions including Ramseh (as saline soil), Atabieh (as very saline soil) and Hamidieh (as control, non-saline soil). Three 10-hectare plots were selected in each area and a pilot with area of 2000 m2 was used for evaluation and measurement in each plot. First year data were used to calibrate the SALTMED model and second year field data were used to validate the model and to achieve the results in three conditions. The dominant soil texture in the area was clay loam. The quality of used irrigation water with average salinity of 2 dSm-1 was classified as C3-S1(high salinity with low sodium absorption ratio) and had no effect on wheat yield loss. In this study, version 3-04-25(2018) of SALTMED model was used and after calibrating in the first year, the results of simulated wheat grain yield and soil salinity variation values were used for model validation in different regions and in soils with different degrees of salinity, in the second year.

The average measured and simulated biomass yield in the first year were 6.6 and 6.1 t/ha, respectively. Furthermore, the average of measured and simulated of wheat grain yield was 2.9 and 2.6 t/ha, respectively. Some statistical indices including mean bias error, normalized root mean square error, and root mean square error for grain yield were 0.11, 0.04, and 0.12 t/ha, respectively. The values of the same statistical parameters for biomass were -0.49, 0.1, and 0.61t/ha, respectively. These results showed that the measured values of grain yield and wheat biomass were in good agreement with the simulated values using SALTMED model. The simulated and measured variations of soil salinity at three soil depths of 0-30, 30-60, and 60-90 cm, showed close agreement with each other in three layers. Root mean square error, normalized root mean square error, and mean bias error for soil salinity values were 1.3, 0.20, and -0.06, respectively. After calibrating the model in the first year, to validate this model in the second year, the results of three pilots locations in three regions of Ramseh (saline), Atabieh(very saline) and Hamidieh(non-saline) were used. Comparison of simulated and measured wheat grain yield and biomass values showed that there was no significant difference between simulated and measured values. The simulated values of grain yield and wheat biomass in the three non-saline, saline and very saline soils had high correlation with the measured values, indicating high accuracy and efficiency of this model in simulating grain and biomass yield in different degrees of soil salinity. Moreover, the trend of soil salinity changes simulated by the SALTMED model in three highly saline, saline and non-saline soils (for three soil layers) was close to the measured values. The SALTMED model with normalized root mean square error and mean bias error of 0.18 and -0.13, respectively, showed good accuracy in different salinity conditions. There was no significant difference (5% level) between the measured and simulated salinity values of the different soil layers. The mean standard error at the 0-30, 30-60, and 60-90 cm layers was 1.1, 1.05, and 0.81 dSm-1, respectively. Therefore, based on the results and statistical indices, it was found that SALTMED model had good accuracy and efficiency in simulating yield, biomass and soil salinity under different salinity conditions.

According to the results and statistical indices, SALTMED model had good performance and accuracy in simulating grain yield, biomass and soil salinity variations in different soil salinity conditions and so it can be used to predict wheat yield, yield components and soil salinity in different soil condition with different degrees of soil salinity to sustain soil and water and improve water productivity in similar areas.

Increasing freshwater consumption caused to reduce renewable freshwater resources in recent years, and one of the basic strategies would be use of non-conventional water resources. Arsenic is one of the natural elements widely distributed in the Earth’s crust. It is commonly found in compounds with oxygen, chlorine, or sulfur, which generally contain inorganic arsenic compounds. Arsenic organic compounds also contain hydrogen and arsenic carbon. There are several methods that can limit the amount of arsenic in water and wastewater; one of these methods is surface adsorption. In this process, any solid that tends to absorb the fluid environment on its surface is considered as an adsorbent. Absorption capacity, selectivity, reproducibility, kinetics, compatibility, and cost are the most essential characteristics of the adsorbent.

In this study, activated carbon derived from agricultural waste was used as tertiary treatment. The heated coal powder used in this study was obtained from the almond and walnut peel waste (from Tuyserkan city of Hamedan province). Activated carbon powder was used in laboratory-scale experiments and was performed for arsenic removal from synthetics samples. Physically activated carbon was obtained and then chemically activated by acidification. Characterization tests (i.e., XRD, FT-IR, BETand SEM tests) were carried out on both types of the adsorbent. Arsenic removal was carried out in batch experiments. The effect of laboratory parameters (i.e., contact time, pH, adsorbent dose, and initial concentration) on the removal process was studied. Experiments are carried out step by step, and after optimizing each parameter and keeping the other parameters constant, all the parameters are optimized accordingly.

The contact time for the adsorption process was considerably decreased in comparison with previous studies. Kinetic and equilibrium studies showed that the adsorption process followed by Langmuir isotherm and second-degree kinetic models. Chemical activation, improved performance, and characteristics of the adsorbent. Acidified charcoal and raw charcoal were compared, and it was found that acidic charcoal had the finest cavities and had a uniform distribution. Although the volume of the cavities has not changed significantly, the structure of the cavities has changed substantially, with the most enormous volume of cavities (0.5 cm3 / g) being less than 5 nm in diameter and the average diameter of the cavities Decreased by 2 nm. According to the results of the Coal Structure Morphological Survey (SEM), in crude coal, the cavities have large openings. Their number is small, but in acidified coal, the number of cavities is increased, and the surface area of the coal is high. The high internal surface area and the presence of microstructural cavities lead to high adsorption of arsenic at the acid-adsorbed sites. With increasing contact time from 0 to 3 minutes, the removal rate of arsenic increases, and after 3 minutes to 10 minutes, it grows with a low gradient and then the removal percentage slightly. In other words, after 10 minutes, there is a balance between the solid and liquid phases. The arsenic removal rate reaches 90% at the third minute and 100% in approximately 13 minutes. As the retention time increases, the contact time of the arsenic with the adsorbent increases, and the adsorption rate increases as the opportunity for contact with the adsorption sites increases. Due to the high specific surface area of the adsorbent and its morphological characteristics, the removal rate reaches 100% with time.

The XRD experiment shows that improved coal is closer to the stable structure than the raw coal. According to the FT-IR experiment, the acidified charcoal decreased the oxygen and aliphatic functional groups and increased the hydrophobicity of the charcoal. The BET experiment revealed that the cavity surface size increased, and the cavity diameter decreased. The cavity distribution was such that the largest volume of cavities was in the range of nanomolecular size. The SEM image also shows an increase in the fine cavities. As a result, the adsorbent has a good morphology and reduces the adsorption time. Also, its special surface is high and has uniform cavities distribution, which can be one of the main causes of high removal percentage. The results showed that at concentrations of less than 120 µg / L and 10 min retention time, the removal rate was 100%. At higher concentrations, drinking water standards can be reached by increasing the retention time or adsorbent dose. The rate of uptake depends on both the concentration of arsenic and the amount of the adsorbent

Land evaluation plays a decisive role in determination of land suitability for the intended uses. For this purpose, various approaches have been proposed, among which the parametric approach is an important one. In this approach, the land index (LI) is calculated using the Khidir (the square root) and/or the Storrie methods, and then the land suitability classes were determined based on the LI. Unfortunately, in many land suitability studies, the LI has been used without any correction, called uncorrected land index (ULI) that led to different results in evaluation of land suitability approaches. The current study shows the importance of the corrected land index (CLI) and its effect on land suitability classes.

In this study land suitability classes were determined by four methods including 1-simple limitation, 2- number and intensity of limitations, 3- Kiddir (square root) and 4- Storrie, using two cases i.e. the CLI and ULI. Properties and criteria for determining land suitability classes are shown in Table1. Simple limitation method is based on the Liebig’s law or the law of the minimum. Land classes are defined according to the lowest class level of the land characteristics. Number and intensity of limitation method has been described in Table 1. In parametric approach, the ULI is calculated using Kiddir and Storrie methods as shown in equations 1 and 2, respectively. The relationships between ULI and CLI are presented in Table 2. (1) (2) Then, a simulation process was done for the eight characteristics involved in calculating the land suitability index. For this purpose, one million random values were considered for each of the S1 to N2 classes; so that the minimum rating (Rmin) was a random number for each class in own defined range (Rating in Table 1) and the other seven characteristics were random numbers between Rmin and 100. For example, in the S2 class, a minimum random number is in the range of 60 to 85 and seven other characteristics were between this Rmin and 100. Finally, a total of five million random simulations were considered.

Table 3 shows the results of five million simulations for S1 to N2 classes. Based on the minimum, maximum and mean values obtained, it can be seen that the simulation process is acceptable. These numbers show that the simulations have simulated almost all the cases that may occur in reality, from the best to the worst. Based on the results, it is clear that the mean values of the ULIs or the Storrie method are much lower than the Khiddir ones (Table 3), but there was no significant difference between mean values both in Storrie and Khiddir methods using CLIs. These results are sufficient to conclude the importance of using CLIs and to show the difference between the results obtained from the CLIs and ULIs. Tables 4 to 8 show the results of one million simulations for each suitability class. The present study revealed that the results of the four employed methods using the CLIs are much closer, especially for the Storrie and Khiddir methods. All together, the simple limitation method was more consistent with the Khiddir method. On the other hand, the employed methods differed greatly when the ULIs were used. The analysis of five million simulations has shown that the contradictory results of land evaluation methods in various studies can be quite mathematically logical, but with a different probability.

According to the findings of the current study, it can be illustrated that it is very important and necessary to use the CLIs to determine the land suitability class. The study showed that using the CLIs leads to the closeness of the results of different methods, so that there was no significant difference between Storrie and Khiddir methods. In general, the results of the Khidir method are closer to the simple constraint method compared to Storrie. There was a significant difference between the Khiddir and Storrie methods using the ULIs, but the difference was too small and insignificant using the CLIs. Totally, the results of the ULIs may be largely inaccurate, misleading and unrealistic. Therefore, it is strongly suggested that the CLIs be used in determining the suitability classes, and then the results be compared with the observations in the reality.

High-accuracy of soil maps is a powerful tool for achieving land sustainability in agricultural and natural resources. This study was conducted to determine the effect of different feature selection methods with machine-learning algorithms to prepare digital mapping of soil classes at two taxonomic levels from subgroup down to family in the interest region, i.e. Vargar lands of Abdanan city, related to the Ilam province.

Study area is 1027 hectares with 628.6 mm and 22.6 ºC mean annual precipitation and temperature, respectively. Three major physiographic units including Hilland, Piedmont plain and Alluvial plain were considered. Soil moisture and temperature regimes are calculated based on the Newhall model in JNSM 6.1 version software. A total of 44 soil profile observation with random sampling pattern was determined based on standardized soil surveys then digging, description and after sampling from all genetic horizons then soil samples were transferred to the laboratory. Finally, all of the soil profiles were classified based on the soil taxonomy system (2014) down to the family level. Geomorphometric covariates as a representative of soil-forming factors were prepared from the digital elevation model (ALOS PALSAR Satellite,2011) with 12.5 m resolution in SAGA GIS 7.4 version software. Three feature selection approaches included Boruta, Variance inflation factors (VIF) and Mean decrease accuracy (MDA) with two Random forest (RF) and Fuzzy logic data mining algorithms were applied for relating soil-landscape relationship by using “random-forest”, “caret” packages in R 3.5.1 and SoLIM solution version 2015 software’s. Sample-based project used for predicting soil classes in Fuzzy logic modeling process. In total observation profile split into two data set included 80 percent (n=36) for calibrating and 20 percent for validating (n=8) based on bootstraps sampling algorithm random forest. Internal validation of the random forest algorithm was done based on out of bag error percentage (OOB%). The best model performance was determined based on overall accuracy (OA) and kappa index, also for each individual class user accuracy (UA) and producer accuracy (PA) were applied.

The results have shown that from a number of 40 geomorphometry covariates, six covariates included Terrain classification index for lowlands, Annual insolation, Topographic position Index, Upslope curvature, Real surface area, and Terrain surface convexity were selected by MDA as the best environmental covariates. Also, the RF-MDA method with overall accuracy of 84% and Kappa index of 0.56 had the best performance compared to other methods (RF_VIF, RF-BO, Fuzzy-MDA) in the subgroup level with 58, 55, 50 and 0.3, 0.67 and 0.18 respectively. Out of bag error results (%OOB) for RF-MDA, RF-VIF and RF-Boruta were obtained that 72.42%, 67.86%, and 82.76% for subgroup level and 93.10%, 93.10% and 86.21% for the family level respectively. while there was little difference between the accuracy of the method at the family taxonomic level and performed similar results in the modeling of soil classes process. The results of the fuzzy approach showed that the kappa index values ​​and overall accuracy of this method were similar to the other three scenarios and there was a slight difference between the accuracy of the results at the soil family level. In the fuzzy method, it was observed that the kappa and overall accuracy values ​​at the subgroup level were lower than the other scenarios. Fuzzy approaches in contrasted to RF modeling prevented continuous spatial variability by generating fuzzy maps for each of the soil classes in the landscape. These results indicate that the random forest method is superior to the fuzzy method in family class mapping and soil subgroups. Based on the MDA sensitivity analysis index, similarly, three geomorphometry covariates included Terrain surface convexity (convexity), Terrain classification index for lowlands (TCI_Low) and Real surface area (Surface_Ar) had the highest importance for predicting soil classes at two taxonomic levels. With regarded to final soil predicted maps area, two classes (Fine-silty, carbonatic, hyperthermic Typic Haplustepts) and Typic Calciustolls with 32.70% and 48.90% and (Fine-silty, carbonatic, hyperthermic Typic Calciustolls) and Typic Haplustepts with 0.18% and 1.85% had the highest and lowest content at family and subgroup maps respectively.

In general, using different variable selection approaches in situations where soil classes have a relatively imbalanced abundance can increase the accuracy of digital mapping in soil studies. Increasing the number of field observations and the use of other environmental variables affecting soil formation can also be used for graduating in prediction low-accuracy soil classes.

The date bunch fading disorder causes huge loss on farmers' incomes and damages to economy of date producing regions. Thus it is important to find a way for controlling the disorder or reducing its economic damages. It seems that the water losses of the tree under critical environmental conditions, such as high temperature and very low air relative humidity, cause date bunch fading disorder especially when is accompanied by regional warm wind. According to the scientific literatures, the use of different covers on bunches, high-frequency irrigation, foliar application of mineral nutrients and anti-transpiring substances, and soil mineral fertilization can affect date palm bunch fading disorder. Superabsorbent polymers have great capability for storage water and can be used in soil to improve its water retention and increase soil available water under drought conditions. On the other hand, potassium has important roles in metabolism of carbohydrates, plant water relations as the major element in action mechanism of stomata, and plant water osmotic potential. Organic matter can also improve soil physical properties, i.e., soil structure and soil available water as well as soil fertility and bioavailability of mineral nutrients. Because of mentioned roles of these three factors, the effects of them on date palm bunch fading disorder were investigated in this research.

The effects of superabsorbent, potassium fertilizer, and manure on yield and date bunch fading disorder of "Mazafati" date palm cultivar were investigated in Jiroft, Kerman province, south of Iran. An experiment was conducted in factorial randomized complete block design. The factors were included superabsorbent polymer A200 in 0 (S1), 200 (S2), and 300 (S3) g.tree-1 levels, potassium sulfate fertilizer in 0 (K1), 2 (K2), and 3 (K3) kg.tree-1 levels, and cow manure in 0 (O1), 65 (O2), and 130 (O3) kg.tree-1 levels. Treatments were applied in February in three blocks and harvest was done at the first half of August. The yield of intact fruits, the yield of dried and dropped fruits (collected in an elastic silicone wire cloth cover), and total yield were determined at the harvest time and date bunch fading disorder was calculated as weight percentage (the dried fruits weight was divided by the total fruits weight and multiplied by 100, in each plot). Weight, diameter, and length of fruits were measured and determined from a random sample containing 30 intact fruits per each plot (a tree). Statistical analysis was done by IBM SPSS Statistics version 25.

According to the results, the block had no significant effect on any of studied parameters, on the other hand, the results showed significant effects of all three factors on all of the measured parameters including percentage of date bunch fading disorder, total fruits yield, intact fruits yield, fruit weight, fruit diameter, and fruit length, except fruit length by the manure factor, by ANOVA at the 0.01 level. Three factors interaction significantly affected only the fruit characteristics including weight, diameter, and length of fruit. About the intact and total fruits yield and date bunch fading disorder, interactions between superabsorbent and two other factors were statistically significant. The highest means of intact fruits yield were observed in S3K3 and S3O3 treatments (28.9 and 28.7 kg.tree-1) increased by 98% and 93% compared to S1K1 and S1O1 treatments, respectively; and they were also significantly higher than those of all other treatments. The maximum means of total yield were found in S3K3 and S3O3 treatments (35.0 and 26.8 kg.tree-1) increased by 33% and 28% compared to S1K1 and S1O1 treatments, respectively. The mean percentage of date bunch fading disorder was significantly decreased by increasing the levels of superabsorbent, potassium fertilizer, and manure factors in interactions between superabsorbent and two other factors (SK and SO interactions), thus the lowest mean of date bunch fading disorder percentage in both interactions was found in third levels of each factor (S3K3 and S3O3 treatments), decreased by 60% and 63% compared to S1K1 and S1O1 treatments, respectively. The lowest and the highest mean of fruit weight, fruit diameter, and fruit length parameters were observed in S2K1O3 and S3K3O3 treatments, respectively. Negative significant correlations were found between percentage of date bunch fading disorder and total fruits yield, intact fruits yield, fruit moisture, fruit weight, fruit diameter, and fruit length, while the last six parameters had positive significant correlations with each other. In addition to common positive effects of three factors on water supply improvement, they can influence plant progress in different ways, such as carbohydrate metabolism and activation of some enzymes by potassium, and increasing of mineral nutrients availability and soil microbial activities by organic matter and manure. Therefore, these three factors could have some positive interactions on their effects on control of the disorder, increasing the yield, and improvement of weight and size of fruit. An observed decrease in weight and size of fruit by using 2nd level of superabsorbent and 3rd level of manure can be resulted from significant decrease in percentage of disorder and finally competition between safe fruits for potassium in carbohydrate metabolism and so on.

According to the results of this research, applying of superabsorbent polymer (300 g.tree-1), potassium fertilizer (3 kg.tree-1), and manure (130 kg.tree-1) together can be recommended to improve qualitative parameters of date palm fruits (weight, length, and diameter). Applying the 3rd levels of these factors together can also control date bunch fading disorder cv. Mazafati, and increase the economic income because of qualitative improvement of fruits.