Showing 14 results for Zarei
P. Ehsanzadeh, A. Zareian Baghdad-Abadi,
Volume 7, Issue 1 (spring 2003)
Abstract
Planting density, through its impact on the level of available environmental factors may have significant impacts on grain yield in safflower (Carthamus tinctorius L.). In order to investigate the impacts of plant density on grain yield, yield components and growth characteristics of safflower, a randomized complete block design field experiment with four replicates was conducted in spring-summer, 2000, at Lavark Research Farm (Lat. 320 32, N and Long. 510 23, E), College of Agriculture, Isfahan University of Technology, Isfahan, Iran. Arak-2811 and Kouseh safflower genotypes were seeded at 16.6, 22.2, 33.3 and 50 plants/m2. For establishing these plant densities, plants were seeded in 12, 9, 6 and 4 cm distances, respectively, on ten 8-m-long rows spaced 50 cm apart in each plot. Plant density had no impact on plant growth stages with the exception of button formation. Genotype had significant effects on days to seedling emergence, button formation, and 50% flowering. While both number of days and accumulated growing degree-days for all growth stages decreased with an increase in plant density, Arak-2811 was earlier than Kouseh for most growth stages. Number of branches and heads per plant, number of heads per branch, number of seeds per head and harvest index showed significant decreases with increasing plant density. The decrease in the mentioned grain yield attributes was mainly negated by greater number of plants per m2, leading to no significant variation in grain yield between plant densities of the two genotypes. Arak-2811 produced a significantly greater number of heads per branch and 1000-grain weight however, these differences did not lead to any greater grain yield compared to Kousehdue, mainly due to the greater number of branches in the latter. Neither of the leaf area index, leaf area duration, and crop growth rate varied significantly with plant density and between two genotypes, suggesting no difference in dry matter production capabilities of the two genotypes under environmental conditions of the present study.
S. S. Eslamian, A. Zarei, A. Abrishamchi,
Volume 8, Issue 1 (spring 2004)
Abstract
An approach for regional low flow frequency analysis is to use multiple regression techniques for obtaining relationships between low flows with specific return periods and catchments characteristics. In this paper, this method has been used. After single-site frequency analysis for 20 stream gauging stations, homogeneity test was performed. Regional relationships between low flows with return periods 2 , 5 , 10, and 20 years and catchments characteristics were derived.
For this purpose, catchment area, mean elevation, minimum elevation, shape factor, main channel length, length of main chanel from catchment centroid to outlet, forest area, mean annual rainfall, and mean catchment slope as model inputs were examined and cachment area, mean elevation, and mean catchment slope entered to the models. Finally, the mean relative error of models for different return period, 2, 5, 10, and 20 years, was computed 41.1, 41.3, 45.0, 47.2 percent, respectively that in comparison with other studies, it displays smaller errors.
M. Zarei, N. Saleh-Rastin, Gh. Savaghebi,
Volume 15, Issue 55 (spring 2011)
Abstract
A greenhouse experiment was conducted in factorial experiment arranged as a completely randomized design (CRD) to evaluate the role of tree indigenous arbuscular mycorrhizal fungi (AMF) species originated from a polluted soil in phytoremediation of zinc polluted soils using maize as a host plant. The experiment consisted of plants inoculated with AMF (G1(Glomus intraradices), G2(Glomus mosseae) and G3(Glomus versiforme)) and G0 as non-inoculated plants and 5 levels of zinc (0, 10, 50, 100 and 500 mg kg -1) in non-sterilized sandy loam soil with three replications. According to the results of greenhouse experiment, the zinc and phosphorus uptake and also the biological yield of maize plants were significantly increased by inoculation with AMF in comparison with non-inoculated plants and also no zinc toxicity symptoms were observed. Uptake, translocation, and phytoextraction efficiency of plants inoculated with G. intraradices was more than the other treatments up to the level of 100 mg kg -1, but at the level of 50 mg kg -1 these amounts were highest in plants inoculated with G. mosseae. The efficicncy of three AMF in zinc uptake was highest at the low level of zinc. In general, under the high soil pollution (500 mg kg-1), G. mosseae was the most effective fungal species in Zn extraction and translocation while G. intraradices had the highest effectiveness for accumulation of Zn in the roots. The overall situation of G. versiforme was mostly between the two other fungal species.
M. Ghorchiani, Gh. Akbari, H. A. Alikhani, M. Zarei, I. Allahdadi,
Volume 17, Issue 63 (Spring 2013)
Abstract
In order to evaluate the effect of arbuscular mycorrhizal (AM) fungi and Pseudomonas fluorescens bacteria on phosphorus fertilizer use efficiency, mycorrhizal dependence and grain yield and dry matter yield of maize under water deficit conditions, a field experiment was conducted as split-split plot arrangement based on randomized complete block design with three replications. The treatments in this experiment were included as follows: irrigation (normal irrigation and water deficit stress based on evaporation from class A pan evaporation) combined different seed inoculations with AM and Pseudomonas fluorescens and treatment of chemical phosphate fertilizer (non- consumption of phosphate fertilizer, consumption of 50 percent of triple superphosphate fertilizer needed, and consumption of rock phosphate, based on the quantity of consumed phosphorus of triple superphosphate source). The results showed that effects of irrigation, seed inoculation with AM and Pseudomonas fluorescens biological phosphate fertilizer and chemical phosphate fertilizer were significant on yield and yield components, dry matter yield, relative agronomic efficiency and root colonization. Mild stress significantly reduced grain yield, relative agronomic efficiency and fertilizer agronomic efficiency compared to optimum irrigation. Results showed that grain and dry matter yield are highly correlated with root colonization under mild stress condition. Maximum mycorrhizal dependence was obtained in mild stress condition. Maximum relative agronomic efficiency, fertilizer agronomic efficiency, yield and yield components was related to seed inoculation with AM and Pseudomonas fluorescens. The use of triple superphosphate fertilizer were increased grain yield in comparison with rock phosphate along with inoculation of phosphate solubilizing microorganisms. However, maximum root colonization and mycorrhizal dependence was achieved in non- consumption treatment of phosphate fertilizer.
M. B. Heyderianpour , A. M. Sameni, J. Sheikhi, N. Karimian, M. Zarei,
Volume 18, Issue 67 (Spring 2014)
Abstract
A study was conducted to evaluate the effect of vermicompost and nitrogen (N) on growth, nutrient concentration and uptake of N, phosphorus (P), potassium (K), iron (Fe), zinc (Zn), manganese (Mn), and copper (Cu) in sunflower shoots as a factorial experiment arranged in completely randomized design (CRD) with three replications under greenhouse conditions. Treatments included three levels of vermicompost (0, 2.5, and 5 % by w/w) and three N levels (0, 90, and 180 mg kg-1) as urea. Application of 2.5% vermicompost significantly increased the average fresh and dry weights, and uptake of K, Fe, Zn, Mn, and Cu of shoots as compared when no vermicompost was applied, but decreased Zn and Cu concentrations. Application of 90 mg N, increased fresh and dry weights, and concentration of N, Zn, and Mn, total uptake of N, P, K, Fe, Zn, Mn, and Cu in sunflower shoots, but decreased P concentration. Application of 180 mg N increased total N uptake than that of 90 mg N kg-1 treatment. Combination of 2.5% vermicompost with 90 mg N, significantly (p<0.05) increased dry matter yield of sunflower as compared to 2.5% vermicompost without N treatment
W. Zarei, M. Sheklabadi,
Volume 18, Issue 70 (winter 2015)
Abstract
The aim of the study was to investigate the effects of land use on soil quality parameters using multivariate statistical analysis. Soil samples (0-25 and 25-50 cm depths) were taken from three land uses in forest area of Marivan including forest, rangeland, and cultivated land. Soil characteristics of pH, EC, sand, silt, clay and CaCO3 content, water-stable aggregates and their organic carbon content were measured. Principal component, cluster and discriminant analyses were used to evaluate the soil quality. Principal component analysis classified soil properties into five factors. The most important factors were soil aggregates organic carbon content and aggregate stability indices. Schematic distribution of factors and also cluster analysis showed the same pattern. Soil aggregates organic carbon content, water-stable aggregates and aggregate stability indices were the most sensitive factors to land use changes. These soil properties and factors had the same pattern in forest and rangeland, but significantly reduced in the cultivated land use. Land use change from forest to cultivated land resulted in significant decrease of aggregates organic carbon content, water-stable aggregates and also an increase of pH. The results showed the usefulness of multivariate statistical methods for integration of the soil properties and determination of different soil quality indices.
M. J. Zareian, S. S. Eslamian, H. R. Safavi,
Volume 20, Issue 75 (Spring 2016)
Abstract
This study investigated the effects of climate change on the evapotranspiration amount and water balance in the Zayandeh-Rud river basin. Two important weather stations; Isfahan and Chelgerd stations, located in the East and West of the basin respectively, were selected for investigation in this study. The combination of 15 GCM models were created based on the weighting method and three patterns of climate change including the ideal, medium and critical were defined. Using the proposed patterns, the effects of climate change on temperature and evapotranspiration in Isfahan station and precipitation in Chelgerd station were estimated under the A2 and B1 emissions scenarios. Two indices were considered to determine the sustainability of agricultural water consumption in the study area. Ratio of evapotranspiration in the East part of the basin to precipitation in the West part was defined as EPR index (Evapotranspiration-Precipitation Ratio), and the ratio of maximum agricultural water deficit to the amount of agriculture water need, was considered as maximum deficit index (MD). Results showed that the annual temperature would increase between 0.63-1.13°C in the eastern part of the basin. The west precipitation in the basin would reduce between 6.5-30% in the ideal to critical patterns. Summer season, showed the most amount of increase in the temperature, and winter season, showed the most amount of decrease in precipitation. The A2 emission scenario showed more temperature increase and more precipitation decrease in comparison with the B1 emission scenario and also indicated that the potential evapotranspiration would increase by 3.1 to 4.8% in the basin. The EPR index will increase between 13-52% and MD index will increase between 9-35% in Zayandeh-Rud river basin under different climate change patterns. The results revealed the imbalance between agricultural water use in eastern part and the precipitation in the western part of the basin. In other words, in these conditions, appropriate management strategies and planning should be implemented to ensure the sustainability of water resources in Zayandeh-Rud River Basin.
M. Mokarram, A. R. Zarei, Mohammad Javad Amiri,
Volume 22, Issue 3 (Fall 2018)
Abstract
The aim of this study was to evaluate the effect of increasing DEM spatial resolution on the assessment of the morphometric characteristics of waterways, as well as analysis and modeling of it by using RS and GIS techniques. In this study, which was carried out in the south of Darab city DEM 90 m (as one of the most usable data in waterway modeling), increase spatial resolution of DEM attraction algorithm in neighboring pixels with two models including: touching and quadrant neighboring models to estimate the value of sub-pixels. After manufacturing output images for sub pixels in 2, 3 and 4 scales with different neighborhoods, the best scale with the most appropriate type of neighborhood was determined using ground control points (270 points); then, the values of RMSE were calculated for them. The results showed that with using the Attraction model, the accuracy of the output of images was improved and the spatial resolution of them was increased. Among scales with different neighborhoods, 3 scales and quadrant neighboring model exhibited the most accuracy by the lowest value of RMSE for the DEM 90 meter. Evaluation of waterways morphometric features showed that DEM extracted from attraction algorithm had more ability and accuracy in waterways extraction, Extraction of morphometric complications, and information in the study area.
M. A. Amini, G. Torkan, S. S. Eslamian, M. J. Zareian, A. A. Besalatpour,
Volume 23, Issue 1 (Spring 2019)
Abstract
In the present study, we used 27 precipitation average monthly data from synoptic, climatologic, rain-guage and evaporative stations located in Zayandeh-Rud river basin for the period of 1970-2014. Before interpolating, the missing data in the time series of each station was reconstructed by the normal ratio method. Also, for the data quality control, the Dickey-Fuller and Shapiro-Wilk tests were used to check the data stationarity and normality. Then, these data were interpolated by six interpolation methods including Inverse Distance Weighting,
Natural Neighbor, Tension Spline, Regularized Spline, Ordinary Kriging and Universal Kriging; then each method was evaluated using the cross-validation technique with MAE, MBE and RMSE indices. The results showed that among the spatial interpolation methods, Natural Neighbor method with MAE of 0.24 had the best performance for interpolating precipitation among all of the methods. Also, among Ordinary Kriging, Universal Kriging, Spline and
Inverse Distance Weighting methods, respectively, Exponential Kriging with MAE 0.54, Quadratic Drift Kriging with MAE of 0.5, Tension Spline with the MAE of 0.54 and Inverse Distance Weighting with the power of 4 with MAE of 0.57 had the least error compared to other IDW methods.
J. Jalili, F. Radmanesh, A. A. Naseri, M. A. Akhond Ali, H. A. Zarei,
Volume 24, Issue 3 (Fall 2020)
Abstract
Agricultural water management studies require accurate information on actual evapotranspiration. This information must have sufficient spatial detail to allow analysis on the farm or basin level. The methods used to estimate evapotranspiration are grouped into two main groups, which include direct methods and indirect or computational methods. Basics of the indirect methods are based on the relationship between meteorological parameters, which impedes the use of these data with a lack or impairment. On the other hand, this information is a point specific to meteorological stations, and their regional estimates are another problem of uncertainty of their own. To this end, the use of remote sensing technology can be a suitable approach to address these constraints. Real evapotranspiration can be estimated by satellite imagery that has short and long wavelengths and is estimated using surface energy equations. Examples of such algorithms include SEBAL, METRIC, SEBS. Among the above mentioned algorithms, SEBAL and SEBS have been used. Among the factors of superiority of the SEBAL and SEBS algorithms, in comparison with other remote sensing algorithms, is a satellite imagery analysis algorithm based on physical principles and uses satellite simulation and requires minimum meteorological information from ground measurements or air models.
S. Toghiani Khorasgani, S. Eslamian, M.j Zareian,
Volume 25, Issue 4 (Winiter 2022)
Abstract
In recent decades, water scarcity has become a global problem due to the growth of the world's population as well as the increase in per capita water consumption. Therefore, planning and managing water resources to prevent potential risks such as floods and drought in the future is one of the important measures of water resources management. One of the important measures to avoid potential risks and predict the future is rainfall-runoff modeling. The objective of this study was to investigate the efficiency of the WetSpa hydrological model in estimating surface runoff in the Eskandari watershed, which is one of the important sub-basins of the Zayandehrood watershed. In this study, Daran and Fereydunshahr synoptic stations have been used to collect meteorological information in the Eskandari watershed. Also, to study the flow of the Plasjan river, daily data of Eskandari hydrometric station, located at the outlet of the basin, have been used. Climatic data along with digital maps of altitude, soil texture, and land use were entered as input to the WetSpa model. Finally, the ability of the WetSpa model was evaluated in estimating river surface runoff. The observed flow at the basin outlet in the hydrometric station was used to evaluate and calibrate the model. The model was calibrated for the statistical period (1992-2000) and its validation was performed for the statistical period (2001-2004). In the calibration period, the trial and error method were used to calibrate the model parameters. The simulation results showed a good correlation between the simulated flow and the measured flow. In the present study, the Nash Sutcliffe coefficient in the calibration and validation stages was equal to 0.73 and 0.75, respectively which shows the good and acceptable ability of the model in estimating the surface runoff of the study basin.
M. Zareian,
Volume 26, Issue 2 (ُSummer 2022)
Abstract
This study was conducted to investigate the effects of climate change on temperature and precipitation changes in important synoptic weather stations in Yazd province (including Yazd, Bafgh, Marvast, and Robat-e-Poshtebadam). Accordingly, a combination of the outputs of the latest AOGCM models presented in the IPCC sixth assessment report (CMIP6) were used to increase the accuracy of temperature and precipitation forecasts. A weighting method was used based on the Kling-Gupta combined index (KGE) to combine these models. After weighting the models, the monthly temperature and precipitation changes were calculated based on SSP126, SSP245, and SSP585 emission scenarios. Then, daily temperature and precipitation time series were extracted for different weather stations using the LARS-WG downscaling model. The results showed that in all the weather stations, CanESM5 and BCC-CSM2-MR models have the best ability to simulate the temperature and precipitation of the historical period, respectively. Results also showed that in all emission scenarios, the annual temperature will increase and the annual precipitation will decrease. The annual temperature of this region will increase between 0.2 to 0.6 °C, and the annual precipitation will decrease between 2.9 and 13.7% in different weather stations. Also, the maximum temperature increase and precipitation decrease in this region, will occur in spring and autumn, respectively.
F. Zarei, M.r. Nouri Emamzadehei, A.r. Ghasemi Dastgerdi, A. Shahnazari,
Volume 26, Issue 4 (Winiter 2023)
Abstract
The pattern of root distribution in layered soils is one of the significant issues in the calculations of soil water and irrigation management and planning. The objective of this study was to determine the pattern of root distribution of soybean in layered soils and its effect on water uptake. The research was conducted in a completely randomized design with 15 treatments consisting of three different textures of soil (light, heavy, and medium) in four replications. The pattern of root distribution was monitored by the sampling of columns at the end of the growth period of the soybean. It was observed that the presence of the layer with medium texture has led to better plant development and growth after comparing the treatments in terms of plant growth. In general, root length density decreased with increasing soil depth, except in cases where there were different layers of soil, and root length density takes place in the following order: root length density in layers with medium texture≥ heavy texture≥ light texture. The rate of root water uptake rate was highest in the sandy layers, intermediate in clay, and lowest in loamy texture. Also, the rate of root water uptake rate increased significantly with increasing depth regardless of treatments. It can be concluded that the pattern of root distribution and plant growth is significantly affected by soil texture and its stratification.
M.j. Zareian, R. Seraj Ebrahimi, H. Dehban,
Volume 28, Issue 3 (Fall 2024)
Abstract
In the present study, the impact of climate change on maximum temperature and daily precipitation in 16 weather stations was investigated in the Sefidrood Basin from 2023 to 2052. 10 AOGCM models related to the sixth IPCC Assessment Report (CMIP6) were ranked based on their ability to simulate temperature and precipitation in the historical period (1980 to 2014). Then, the maximum temperature and daily precipitation outputs of the best model at each weather station were extracted using the LARS-WG downscaling model under three emission scenarios SSP126, SSP245, and SSP585 from 2023 to 2052. The Mann-Kendall test (95% confidence level) was also used to investigate the trend of changes in the average maximum temperature and maximum daily precipitation. The results showed that different AOGCMs have different accuracies in simulating temperature and precipitation in different regions of the basin, and their accuracies in simulating temperature were better than simulating precipitation. In general, the IPSL-CM6A-LR and HadGEM3-GC31-LL models had the best performance in simulating maximum temperature and precipitation, respectively. Results also indicated that the mean maximum temperature will increase between 0.9 and 2.8 °C in different emission scenarios. Also, the mean maximum daily precipitation will change between -8.6 and 7.17 mm in different emission scenarios.
