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Showing 7 results for Parvizi
Effect of Nitrogen and Manganese on the Growth and Chemical Composition of Spinach
A. Ronaghi, Y. Parvizi, N. Karimian,
Volume 5, Issue 4 (winter 2002)
Abstract
Nitrogen is usually the most limiting nutrient for crop production. Manganese deficiency in some calcareous soils of Iran has been reported. The objective of this study was to evaluate the effect of N and Mn on the growth and chemical composition of spinach (Spinacia oleracea L.) under greenhouse conditions. The experiment was conducted in a soil from Chitgar series (Fine-loamy, carbonatic, thermic, Calcixerollic Xerochrepts). Treatments consisted of factorial arrangement of five N rates (0, 50, 100, 200 and 400 mg kg-1 as NH4NO3) and three Mn rates (0, 15 and 30 mg kg-1 as MnSO4) in a completely randomized design with four replications. Plants were allowed to grow for 60 days and a hand-held SPAD-502 chlorophyll meter was used to evaluate leaf chlorophyll status at harvest.

 Results showed that N and Mn application increased shoot dry weight, N and Mn concentrations and total uptake, Mn:Fe ratios and chlorophyll readings, significantly. Nitrogen increased concentrations and total uptake of Zn, Cu and total uptake of Fe in plants, but decreased Fe concentration. Addition of Mn decreased Fe and Zn concentrations in spinach but increased total uptake of Fe and Cu. When maximum dry matter was obtained, the chlorophyll meter reading was about 40. A similar study should be carried out under field conditions before the N and Mn fertilizer recommendations for spinach can be made.


Effect of Nitrogen and Manganese on Availability of Some Soil Nutrients, Under Different Plants
Y. Parvizi, A. Rounaghi,
Volume 6, Issue 1 (spring 2002)
Abstract

Nitrogen is usually the most limiting nutrient for crop production. Thus, N fertilizer is widely used by farmers. Moreover, Mn deficiency in some calcareous soils of Iran with high pH has been reported. Therefore, the addition of nitrogen and manganese to achieve the optimum yield is necessary. The objective of this study was to evaluate the effect of N and Mn applications on the availability of some soil nutrients under wheat (Triticum aestivum L.), corn (Zea mays L.), and spinach (Spinacia oleracea L.) plants in greenhouse conditions. In a factorial test, five levels of N (0, 50, 100, 200 and 400 mg/kg soil as NH4NO3) and three levels of Mn (0, 15 and 30 mg/kg soil as MnSO4) in a completely randomized design with four replication were applied. Corn, wheat and spinach varieties were sc704 Falat and Spinacea spp., respectively. After eight weeks, total N content and DTPA-extractable Mn, Fe, Zn and Cu of soil were measured.

 The results indicated that N and Mn applications increased Mn-extractable of soil in three cultures but didn’t affect the soil total N. Nitrogen application in corn increased available Fe in soil. Mn application decreased extractable Zn and Cu of soil in wheat and soil extractable Cu in corn.


Evaluation of Simulated Soil Water Content, Dry Matter and Grain Yield of Winter wheat (cv. Shiraz) using WSM and AquaCrop Models
Sh. Zand-Parsa, S. Parvizi, A. R. Sepaskhah, M. Mahbod,
Volume 20, Issue 77 (Fall 2016)
Abstract

In agricultural development many factors such as weather conditions, soil, fertilizer, irrigation timing and amount are involved that are necessary to be considered by the plant growth simulation models. Therefore, in this study, the values of soil water content at different depths of soil profile, dry matter production and grain yield of winter wheat were simulated using AquaCrop and WSM models. The irrigation treatments were rain-fed, 0/5, 0/8, 1 and 1/2 times of full irrigation conducted in Agricultral College of Shiraz University during 2009-2010 and 2010-2011. The models were calibrated using measured data in the first year of experiment and validated by the second year data. The accuracy of soil water simulation was used to refer to the accuracy of simulated evapotranspiration. The accuracy of soil water content at different layers of root depth in the validation period was good for the WSM model (Normalized Root Mean Squer Error, NRMSE= 0/14). But the AquaCrop model showed less accuracy for soil water content (NRMSE=0/26). However, the values of predicted and measured crop evapotranspiration were close together at full irrigation treatment, the accuracy of AquaCop predictions was decreased with inceasing water stress. WSM model has had a good estimation of the dry matter and grain yield simulation with NRMSE of 0/15 and 0/18, respectively. However, they were simulated with less accuracy in the AquaCrop model with NRMSE of 0/19 and 0/39.


A New Method for Estimating Hydraulic Parameters by Measuring Soil Moisture in the Field
Sh. Zand-Parsa, S. Parvizi, A. R. Sepaskhah, A. A. Kamgar Haghighi,
Volume 22, Issue 1 (Spring 2018)
Abstract
In this study, the values of moisture and soil temperature were estimated at different depths and times under unsteady conditions by solving the Richards’ equation in an explicit finite difference method provided in Visual Studio C#. For the estimation of soil hydraulic parameters, including av and nv (coefficients of van Genuchten’s equation) and Ks (saturated hydraulic conductivity), soil moisture and temperature at different depths were measured by TDR probes and the stability apparatus, respectively. The objective function [equal to Root Mean Square Error (RMSE)] was minimized by the optimization of a parameter separately, using the Newton-Raphson method, while, the other parameters were considered as the constant values. Then, by replacing the optimized value of this parameter, the same was done for other parameters. The procedure of optimization was iterated until reaching minor changes to the objective function. The results showed that soil hydraulic parameters (coefficients of van Genuchten’s equation) could be optimized by using the SWCT (Soil Water Content and Temperature) model with measuring the soil water content at different depths and meteorological parameters including the  minimum and maximum temperature,, air vapor pressure, rainfall and solar radiation. Finally, the measured values of soil moisture and temperature were compared to the depth of 70cm in spring, summer, and autumn of 2015. The values of  the  normalized RMSE of soil water content were 0.090, 0.096 and 0.056 at the  soil depths of 5, 35 and 70 cm, respectively, while the values of the normalized RSME of soil temperatures were 2.000, 1.175 and 1.5 oC at these depths, respectively. In this research, the values of soil hydraulic parameters were compared with other previous models in a wider range of soil moisture varying from saturation to air dry condition, as more preferred in soil researches.

The Impact of Shah Qasem Dam in Yasouj from the Viewpoint of Beneficiary Villagers
A. Khatoon Abadi, E. Parvizi, M. Ataie,
Volume 22, Issue 4 (Winter 2019)
Abstract
In the recent decades, dams have paradoxically been considered as a constraint and or a driving force of surface water conservation. On the other hand, dams have had a number of socio-economic and environmental impacts, the main reason for conducting the current case study on Shah-Qasem Dam in Yasouj, Iran, was to employ the survey field research through a questionnaire to assess the rural peoples’ viewpoint; this was done in four villages of the Southern Sar’roud County. Based on the (Cochran) formula, 192 individuals were relatively selected from each village. According to the findings, the most important impact of the dam was mainly economical (the average impact was between 2.37 and 3.7), whereas the least one was environmental (the average impact was between 1.81 and 3.54). Also, the results of the hypotheses’ analyses by means of 2 and Wilcoxon showed the following results: rise of the villages’ income, increase of the cultivated farms, increase in the employed individuals, enhancement of the cultivated crops, the regions production rising, improved tourism, lack of people’s participation in the decision making process, and reaming of the same plant varieties in the area, as compared with the pre-dam era. It is worth considering, however, that based on the statistical population used, this study was concerned mainly with the short benefits of the dam, rather than its long-term destructive ones.

Prioritization of Sub-Watersheds from Flooding Viewpoint Using the SWAT Model (Arazkoose Watershed, Golestan Province)
A. Talebi, E. Abyari, S. Parvizi,
Volume 23, Issue 4 (Special Issue of Flood and Soil Erosion, Winter 2019)
Abstract
Flood is a natural disaster making the heavy humanistic and economic damages each year in most parts of Iran. In this research, the SWAT model performance in flood prediction and sub-basin priority was investigated in terms of flooding in Araz-Kose watershed in Golestan province. To calibrate the model, SUFI2 was applied. The calibration and validation were done for the 1991-1998 period based on the data of 2001-2009. After validation, the indices (R2, bR2, and NS) were estimated. They were equal to 0.81, 0.81 and 0.73 for calibration and 081, 0.78 and 0.64 for validation, respectively. The sensitivity analysis results showed 13 effective parameters. The curve number (CN2) was determined as the most effective parameter. For studying the flooding in a watershed, the Araz-Kose watershed was divided into six parts. Based on the obtained results from the SWAT model with different CN and F indexes (with/without considering the sub-watershed), the sixth sub-basin with 22.4% decrease in discharge was chosen as the most effective region in flooding. Meanwhile, the other sub-basins including 4, 1, 3, 5 and 2 had more flood potential, respectively.

Regional Frequency Analysis of Drought Severity of SEI-SRI and SEI-SSI Indices in Common Duration Using Multivariate L-Moments and Copula Functions (Case Study: Karkheh River Basin)
S. Parvizi, S. Eslamian, M. Gheysari, A.r. Gohari, S. Soltani Kopai, P. Mohit Esfahani,
Volume 26, Issue 3 (Fall 2022)
Abstract
Investigation of homogeneity regions using univariate characteristics is an important step in the regional frequency analysis method. However, some hydrological phenomena have multivariate characteristics that cannot be studied by univariate methods. Droughts are one of these phenomena their definition as univariate will not be effective for risk assessment, decision-making, and management. Therefore, in this study, the regional frequency analysis of drought was studied in multivariate methods using SEI (Standardized Evapotranspiration Index), SSI (Standardized Soil Moisture Index), and SRI (Standardized Runoff Index) indices in the Karkheh River basin from 1996 to 2019. The indices calculated probabilistic distribution between the variables of evapotranspiration, runoff, and soil moisture using multivariate L-moments method and Copula functions and considered meteorological, agricultural, and hydrological droughts simultaneously. The results of multivariate regional frequency analysis considering the Copula Gumbel as the regional Copula showed that the basin is homogeneous in terms of severity of SEI-SSI combined drought indices and is heterogeneous in terms of severity of SEI-SSI combined drought indices. However, after clustering the basin into four homogeneous areas in terms of characteristics of SPI (Standardized Precipitation Index), the basin is homogeneous in all areas in terms of univariate SEI, SSI, and SRI indices and is heterogeneous in the third and fourth clusters of SRI and SSI drought indices. Pearson Type (III), Pareto, normal, and general logistics distribution functions were found suitable to investigate the characteristics of SEI, SSI, and SRI drought indices in this case. Finally, large estimates of the types of combined droughts and their probability of occurrence showed that the northern and southern parts of the Karkheh River basin will experience short and consecutive droughts in the next years. Droughts in areas without meteorological data can be predicted in terms of joint probability using the multivariate regional frequency analysis method proposed in this study.

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