JWSS - Journal of Water and Soil Science

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The estimation of crop water requirement is one the most important stages for designing different irrigation systems, programming and corrected management of water resources. Therefore, to determine the water requirement for Coriandrum sativum L. a study was conducted in College of Agriculture Research Farm at Razi University in the city of Kermanshah during two years, 2010 and 2011. For this purpose, three water balance drainable lysimeters with the diameter of 1.20m and height of 1.40 m were used. During the investigation, the irrigation was determined by using data logger equipment of (IDRG). The soil humidity was determined in the field capacity condition. The evapotranspiration was calculated using water balance equation. Finally, the Coriandrum sativum L. water requirement was determined to be 722.95 and 580.64mm for years 1388-1389 and 1389-1390, respectively. Meanwhile, the potential evapotranspiration using the Penman Monteith equation was calculated to be 643.58 and 530.17mm for the first and second year of investigation, respectively.

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Continuous decline of groundwater quality for agricultural purposes has become a major concern in extensive arid and semi-arid regions. Therefore, mapping the quality of groundwater on a broad scale is an essential step in land management. This study aimed to map spatial distribution of two important groundwater quality indices including EC and SAR in Isfahan province, Iran, using geostatistical techniques. Different techniques such as Kriging, IDW and RBF were applied to water quality data of 540 groundwater wells to map continuous variations of the EC and SAR indices in Arc GIS 9.3 environment. Among the interpolation methods, the Kriging by circular variogram model performed best and had the lowest RMSe error. Therefore, the produced maps from this technique were classified based on Wilcox method. Results showed that EC varies across the province from 392.2 in the west to about 17917.6 µmmhos/ cm in the northwest and eastern parts of the study area. The highest and lowest SAR values were estimated in the towns of Khour va Biabanak and Semirom, ranging from 38.9 to 0.13, respectively. According to the map of irrigation water quality based on Wilcox method, about 12.13 % of the region was classified as good, 16% as moderate, 17.5% as unsuitable and 54.35% as unusable category. In general, the quality of groundwater in Isfahan province decreases from west to east and also from south to north, especially in playas (non-agricultural lands) where the unusable class is dominant.

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Soft computing techniques have been extensively studied and applied in the last three decades for scientific research and engineering computing. The purpose of this study was to investigate the abilities of multilayer perceptron neural network (MLP) and neuro-fuzzy (NF) techniques to estimate the soil-water retention curve (SWRC) from Khozestan sugarcane Agro-Industries data. Sensitivity analysis was used for determining the model inputs and appropriate data subset. Also, in this paper, the van Genuchten and Fredlund and xing models were used to predict SWRC. Measured soil variables included particle size distribution, organic matter, bulk density, calcium carbonate, sodium adsorption ratio, electrical conductivity, acidity, mean weight diameter, plastic and liquid limit, resistance of soil penetration, water saturation percentage and water content for matric potentials -33, -100, -500 and -1500 kPa. The results of this study in terms of various statistical indices indicated that both MLP and NF provide good predictions but the neural network provides better predictions than neuro-fuzzy model. For example, using MLP and NF models values of NMSE at prediction θs, θr, α, n and m in Fredlund and Xing equation corresponded to (0.059, 0.065), (0.154, 0.162), (0.109, 0.117), (0.129, 0.135) and (0.129, 0.145), respectively. Furthermore, α and n parameters at the first depth, and θr and α parameters at the second depth in Fredlund and Xing equation were estimated with higher accuracy compared with equivalent parameters in van Genuchten equation

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The aim of this study was to evaluate soil properties changes in a soil toposequence series in Khuzestan province. Twelve soil profiles were dug in north to south direction in this province, according to the changes of the slope in Karoon’s alluvial deposits. The results showed that soil texture regularly changes to heavier form from north to south. It was slightly of redoxomorphic features in low land. Therefore, salic horizon was formed in this land. Despite high water table in this area, gray or mottle forms were few due to high soil salinity. The carbonates were eluviated from surface to subsurface horizon therefore, calsic horizon was formed due to illuviation. Secondary carbonate accumulation was maximum in the studied area. Both classic horizon and cambic horizon were formed in some pedons under long time cultivation in north regions. These developments were originated from organisms that grew under good drainage class. The smectite was seen in the south part of region. It may have been transported by river and deposited under high salinity and flocculated in contact to Persian Gulf’s saline water. The palygorskite was not seen in all patterns. This clay was removed in pedons under long time cultivation in the north area due to more leaching. High irrigation water can accelerate palygorskite transformation. Also, the XRD patterns showed that chlorite, illite, kaolinite and quartz were main clay minerals in the studied soils.

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This study was done to compare K+ and NH4+ fixation in different agricultural systems in Khuzestan province. Soil samples were collected from Shushtar and Abadan. Samples were collected from depths of 0-30 and 30-60 cm in sugarcane, multi cropping, palm and uncultivated land. Then, 0-50-100-200-400-600-800-1000 mg kg-1 K+ or NH4+ concentrations were added to 0.5 gram of clay separated from these soil samples. These clay samples were kept for 24 h at room temperature. Then, they were extracted with 0.5 M magnesium acetate, and K+ and NH4+ were determined by flame photometer and micro diffusion methods, respectively. Fixed K+ or NH4+ was determined from added and extracted cations. Also, XRD studies were done in some samples. Kaolinite, palygoreskite, illite, chlorite, smectite and quartz were identified by XJRD. Statistical analysis showed that K+ or NH4+ fixation and rate were increased by increasing the concentration. Maximum K+ or NH4+ were fixed in surface layer’s clay in Shushtar multi cropping and Abadan Palm cultivation. The results showed that K+ and NH4+ fixation were increased by increasing the concentration. But, under increasing concentration for a cation, fixation decreased for others and vice versa. NH4+ fixation was more than K+. This may be due to smectite clay mineral in these samples. Smectite group tend to cause NH4+ fixation more than K+. These results can be applied for K+ or NH4+ fertilizers management.

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Dust deposition occurs extensively in arid and semiarid regions of the world. Since dust particles are fine-sized, they have a high adsorption capacity and also high contamination potential. The objective of this study was to evaluate the temporal and spatial distribution of the rate of atmospheric dust deposition in different locations in Kerman urban area. Dust samples were collected monthly using glass traps installed on the roof of 35 one-story buildings in Kerman for 7 months from April 20 to Nov. 20, 2012 (a total of 245 samples). After each monthly sampling, traps were washed and dust samples transferred to the laboratory and weighed. The mean dust deposition rate of 7 months was mapped using the inverse distance weighting (IDW) approach. The wind rose of Kerman was drawn by WRPLOT 7.0.0. The results showed that the average rate of dust deposition decreased during the 7 months studied from 17.4 to 5 g/m2. month, which could be attributed to the decrease in wind velocity. The spatial distribution of the samples also showed that the dust deposition rate varied from 4.84 in the southern parts to 14.84 g/m2.month, mostly in the northern locations of the city. The wind rose based on the average wind speed of the 7 months of sampling indicated the prevailing wind blows from north, northeast and northwest and the dust spatial distribution well follows the wind direction. In general, the rate of dust deposition in Kerman city is high and therefore, the source of dust has to be well detected and proper management practices are necessary.

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Evaluation of chemical and biological indicators of soil in different land uses could be helpful in sustainable range management, preventing degradation of soil quality trend. This study was conducted in Friedan in Isfahan province in 2010 to compare chemical and biological indicators in three land uses (rangeland, degraded dry land and dry land), during two growing seasons (May and September) in three slopes (0-10, 10-20, 20-30 %). Nitrogen, phosphorus, potassium, organic matter, cation exchange capacity and microbial soil respiration were measured. Results showed that all measured characteristics except potassium decreased over an increase in the slope. Maximum values of phosphorus, organic matters, cation exchange capacity and soil respiration were obtained in pasture (28.4 mg/kg, 0.62%, 20.38 cmol/kg, 33.2 mgC/day, respectively)but potassium maximum rate was seen in dry land form (406.8 mg/kg).The effect of season on all measured parameters was significant except for N, while the highest amounts of phosphorus, potassium, cation exchange capacity and soil respiration (28.7 mg/kg, 377.3 mg/kg, 19.6 cmol/kg and 25.9 mgC/day, respectively) were seen in May and the highest organic matter rate (0.68%)in September. The results of this study showed that an increase in the slope, poor range management, and the end of the growing season could be major factors degrading the soil quality indices and soil productivity.

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This study aimed to evaluate the performance of TM satellite data acquired in June 2009 to map soil salinity in southeast of Isfahan province. Ground salinity data (EC) was collected within 9 pixels, covering an area of approximately 8100 m2 using stratified random sampling technique at 53 sample sites. Spectral indices including TM bands, BI, SI1, SI2 and SI3, PC1, PC2, PC3 and also multiple linear regression modeling and maximum likelihood classification techniques were applied to the geometrically corrected image. Results of regression analysis showed that the TM band 4 had the strongest relationship with EC data (R2=0.48) and also the relationship of the modeling image using TM 3, TM 4, TM5 and PC3 was significant at the 99% confidence level. The accuracy assessment of the stratified TM4 and modeling image into five classes including 0-4, 4-20, 20-60, 60-100 and EC>100 ds/m indicated that there was more than 86% agreement with the field measurements of EC data. Therefore, it can be concluded that the discretely classified salinity maps have higher accuracy than regression methods for identifying broad areas of saline soils, and can be used as appropriate tools to manage and combat soil salinization.

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Since climate has a major impact on dust generation, it is essential to identify the climatic parameters affecting this phenomenon. In this study, climatic parameters including temperature, relative humidity, rainfall, maximum wind speed and direction were selected and their relationship with visibility data and also dust storm days (recorded at meteorological stations) was analyzed on monthly and yearly scales using multivariable linear regression. Results showed that the number of dust storm days has reached 366 days in the last five years. The minimum dust storm days occurred in autumn in all the stations of Khuzestan province including Abadan, Ahvaz, Omidiyeh, Dezful, and Masjed Soleiman and the maximum dust days for Abadan and Ahvaz stations and three remaining stations occurred in spring and summer, respectively. Results also showed that the highest frequency of dust storms in Abadan and Ahvaz stations did not coincide with summer season which has the lowest rainfall of the year. As a result, it seems that the main reason for this difference is the climatic characteristics of dust sources and deposition regions. The occurrence of dust events in the remaining stations in summer time indicated that the sources of dust storms might be local and within the study area. The regression analysis confirmed this issue as the number of climatic parameters which had significant correlations with visibility data increased from 8 to 16 from west to east in the region. Overall, the results showed that with the increasing distance from Arab countries such as Iraq and Saudi Arabia, dust sources were mostly local and provincial.

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Desertification is known as a major crisis in arid regions of Isfahan province. This study aimed to assess the performance of three main desertification models including MEDALUS, MICD and FAO-UNEP for mapping desertification severity in the hotspot of Jarghuyeh region, eastern Isfahan. Different desertification indicators and their related indices were chosen based on the characteristics of the region and fieldwork, and spatially mapped in 27 geomorphologic facies. The desertification severity maps were classified based on the classification scheme for each model in ArcGIS 10 environment, and then comparison of the models and selection of the best one were achieved using IDRISI Tiga 16.03 software. The results of all three models showed that more than 95% of the region can be classified as severe desertification but due to the differences in the number of desertification classes and also indicators and indices only 45% of desertification severity was observed to be similar across the models. Results indicated that the MEDALUS model due to its flexibility to accept new indicators and indices, GIS-based characteristics, and use of geometric mean of indicators in desertification mapping seems to be a suitable model for studying desertification severity in the region. According to this model, 85% and 15% of the area are classified as very severe and severe class of desertification, respectively, which indicates that the rate of desertification is very high and immediate management programs are needed to slow down the desertification process in the region.

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The present study was conducted to increase phytoextraction efficiency of Festuca ovina L. in lead contaminated soil in the EDTA-assisted (0, 1.5, 3, 1.5+1.5, 3+3, 6 mmol kg&minus;1), assess the best time of plant harvesting to increase Pb uptake and method of EDTA application to reduce Pb leaching risk. The results revealed that the greatest Pb uptake was observed in 3EDTA treatment. Therefore, 3mmolkg-1 was used in the second step for assessing harvest time for 15, 30 and 45 days. Results showed that the concentration of Pb in plant tissues was increased with the passage of time and the best harvest time to achieve maximum removal of Pb was 60 days of the first harvest. In the third step to reduce leaching of Pb-chelate, 3mmolkg-1 EDTA in five ways of single, double, triple, quadruplet, quintuplet were added to the soil. The results indicated that under quintuplet application, Pb content reached its minimum concentration in the soil and in the plant organs, the Pb concentration was maximum and metal concentration in the plant organs did not vary significantly when triple, quadruplet and quintuplet dosages were added (p<5%). Overall, optimum phytoextraction of F. ovina L. and Pb leaching reduction were achieved when 3mmol kg&minus;1 EDTA was added in quintuplet dosage and the plant was harvested at the end of growth stage.

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The rainfall-runoff process and flooding are hydrological phenomena that are difficult to study due to the influence of different parameters. So far, different methods and models have been provided to analyze these phenomena. The purpose of this study is evaluation of adaptive neuro-fuzzy inference system (ANFIS) for storm runoff coefficient forecasting. To that end, Barariyeh watershed was chosen in Neishabour and the data of 33 events were collected from 1952 to 2006. Factor analysis (FA) was used for determination of independent variables in storm runoff coefficient forecasting. Four variables were selected as independent variables, including average rainfall, third, first and fourth quartiles of rainfall intensity and also five other variables included &phi index and first to fourth quartiles of rainfall intensity. Other variables combined based on their hydrological role were considered as ANFIS inputs. The results revealed that the ANFIS inputs including first to fourth quartiles of rainfall intensity, &phi  index, and total rainfall of five days before can predict storm runoff coefficient with R²=0.91, RMSE=0.02506, MAE=0.0666 and CE=0.87.

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Spatial estimation of evapotranspiration (ET) rates is essential for agriculture and water resources management. This study aimed to estimate ET v an ET estimation algorithm called Surface Energy Balance Algorithms for Land (SEBAL) and also by using TM June 2009 satellite data in Damaneh region of Isfahan province. To calculate the ET, all the energy balance components and related parameters including net radiation, surface albedo, incoming and emitting shortwave and longwave radiation, surface emissivity, soil heat flux, sensible heat flux, NDVI vegetation index, Leaf Area Index(LAI),  and surface temperature were extracted from the geometrically and radiometrically corrected TM images. Results showed that ET rate was about 7.2 mm day^-1 in agricultural areas, which was almost equal to 6.99 mm day^-1 extracted from the FAO Penman-Monteith method in the synoptic weather station of Daran. Results here indicate that the extraction of ET rate which is almost equal to plant water requirements from remote sensing data can be used in selecting appropriate plants for agriculture and rehabilitation purposes in extensive arid and semi-arid regions of Isfahan province where severe droughts and water shortage are major problems.

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A laboratory research program was arranged to study the effect of different factors influencing the stability of fine soils against wind action. For this purpose, a laboratory wind tunnel was stabilized and several soil samples were examined by putting the sample trays inside the wind tunnel for different rates of wind velocities. The tray for soil samples was 20´30 cm² with the depth of 5 cm, and the fine soil samples were chosen with different sizes of particle and porosity. Because the main aim of this research was to investigate the effect of some polymer additives to the soil, many samples were made of the soils improved by different additives in different percentages. Furthermore, the effect of infiltration of the liquid additives was also examined, which could show different infiltration heights as functions of soil type, additive type and the height of pouring. Some of the results were examined by using software. The lab results in this research were compared with some proposed theoretical ones. It was found that as the average diameter of particles increases, erodibility under the same wind velocity decreases, and the applied polymer emulsions decrease the erodibility up to 90% compared to the initial condition. Impacts of dust emission due to the suspended dispersion of fine particles and creeping movements of coarse particles are mitigated as a result of treatment with these emulsions. Variations in erosion of soils at various wind velocities depend on the value of threshold friction velocity with the result that the soil erosion values in case of coarser soils after the increase in velocity would be higher than those of threshold friction velocity. Finally, a relationship is proposed for estimation of soil erosion in terms of wind velocity. The results are consistent with the transport rate relationships proposed by different scholars.

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In this study the effect of temperature, evaporation or evapotranspiration, precipitation, hillside direction and altitudinal classes, texture and acidity of soil on organic carbon content in the depths of 15 and 45 cm were evaluated. Paired t-test results showed that there is a significant difference between measured parameters in two soil depths. After preparing required data and processing them, outlier's data were removed. Then, base maps for each of the information layers were prepared by Arc GIS9.3 software and all relatd information fit together by overlapping them. Pearson correlation between environmental factors and soil organic carbon values were calculated and it was found that in the depth of 15 cm, the correlation between soil organic carbon values and two environmental factors including temperature and altitude were significant at the level 0.01. As well the results of statistical analysis by using principal component analysis (PCA) method showed that the factors temperature, evaporation (1%), and silt and clay (5%) have had a significant effect on the amount of soil organic carbon. The first, second, and third axes with eigenvalues of 98/4, 78/3 and 92/1, respectively, explained the values 0.33, 0.25, and 0.13 % of correlation between organic carbon and environmental data.

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Dust deposition phenomenon is an important climatic and environmental issue in arid and semi-arid regions. The objective of this study was to examine important characteristics of atmospheric dust in Kerman as one of the major cities in arid areas of our country with high potential of dust production. Dust samples were collected monthly using glass traps installed on the roof of 35 one-story buildings in Kerman for 7 months from April 20 to Nov. 20, 2012. To compare the results of atmospheric dust with those of soil, 60 surface soil samples (0-10 cm) from outside Kerman and 35 soil samples from urban areas were also collected. Some physical and chemical characteristics such as pH, electrical conductivity, organic matter, calcium carbonate equivalent, and  particle size distribution were determined in dust and soil samples. The results of chemical analyses indicated that the amount of these properties is much higher than that in soils. Atmosphere dust particles appear to mainly originate from alkaline and saline soils surrounding the city of Kerman. Dust particle size distribution analysis further confirmed that dust particles have been transferred to Kerman city from medium to long distance areas.  Temporal variability in dust chemical properties indicates that the contribution of anthropogenic and natural sources to urban dust in Kerman has seasonal changes. Based on the results obtained, it is necessary to control dust production outside and inside the city and its distribution in populated areas employing proper management practices.

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Mapping the spatial distribution of soil taxonomic classes is important for useful and effective use of soil and management decisions. Digital soil mapping (DSM) may have advantages over conventional soil mapping approaches as it may better capture observed spatial variability and reduce the need to aggregate soil types. A key component of any DSM activity is the method used to define the relationship between soil observations and environmental covariates. This study aims to compare multiple logistic regression models and covariate sets for predicting soil taxonomic classes in Bam district, Kerman province. The environmental covariates derived from digital elevation models, Landsat imagery, geomorphology map and soil unit map that were divided into two different sets: (1) variables derived from digital elevation models, remote sensing and geomorphology map, (2) variables derived from digital elevation model, remote sensing, geomorphology map and the soil map. Stratified sampling schemes were defined in 100000 hectares, and 126 soil profiles were excavated and described. The results of accuracy model showed that data set 2 increased accuracy of model including overall accuracy, kappa index, user accuracy and reliability of the producer. The results showed that the multiple logistic regression model can promote traditional soil mapping and it can be used to large group of other scientific fields.
 

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Appropriate criteria and methods are required to assess desertification potential in various ecosystems. This paper aimed to assess desertification levels in Segzi plain located in east part of Isfahan, with a focus on soil quality criteria used in MEDALUS model. Bayesian Belief Networks (BBNs) were also used to convert MEDALUS model into a predictive, cause and effects model. Soil samples were collected from 17 soil profiles in all land units and some of their characteristics such as texture, soluble sodium and chlorine, organic material, Sodium Absorption Ratio (SAR), Electrical Conductivity (EC) and CaSo4 of all soil samples were determined in soil laboratory. The effects of measured soil quality indicators on desertification intensity levels were assessed using sensitivity and scenario analysis in BBNs. Results showed that the used integrated method can appropriately accommodate uncertainty in the desertification assessments approaches created as a result of the influence of different soil characteristics on desertification. According to the results of MEDALUS model, 28.28 % and 71.72 % of the study area were classified as poor and moderate areas in terms of soil quality respectively. Sensitivity analysis by both models showed that soil organic matter, SAR and EC were identified as the most important edaphic variables responsible for desertification in the study area. Evaluating the effects of various management practices on these variables can assist managers to achieve sound management strategies for controlling desertification.
 

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This paper aimed to assess the severity of desertification in Segzi plain located in the eastern part of Isfahan city, focusing on groundwater quality criteria used in MEDALUS model. Bayesian Belief networks (BBNs) were also used to convert MEDALUS model into a predictive, cause and effects model. Different techniques such as Kriging and IDW were applied to water quality data of 12 groundwater wells to map continuous variations of the CL, SAR, EC, TDS, pH and decline in water table indices in GIS environment. The effects of measured water quality indicators on desertification severity levels were assessed using sensitivity and scenario analysis in BBNs model. According to the results of the MEDALUS, the desertification of the study area was classified as severe class due to its low quality of groundwater. Sensitivity analysis by the both models showed that decline in waater table, water chloride content and electrical conductivity were the most important parameters responsible for desertification in the region from ground water condition standpoint. The determination coefficient between the outputs of the MEDALUS and BBNs models (R2>0.63) indicated that the results of both models were significantly correlated (α=5 %). These results indicate that the application of BBNs model in desertification assessment can appropriately accommodate the uncertainty of desertification methods and can help managers to make better decision for upcoming land management projects.