Showing 8 results for Zand-Parsa
S.h. Zand-Parsa, Gh.r. Soltani, A.r. Sepaskhah,
Volume 5, Issue 3 (fall 2001)
Abstract
In this study, the optimum irrigation depths for corn grain production under different conditions, i.e. maximum grain yield production and maximum benefit under limited land and water conditions, were determined under sprinkler irrigation in Bajgah (15 km. north of Shiraz).
The results showed that, the optimum depth of irrigation for maximum grain yield production was 77.0 cm. Because of low price of irrigation water and sensitivity of corn crop to water deficit, the optimum depths of water were 76.8 and 73.4 cm under land and water limitations, respectively. Therefore, under limited water conditions, only 4.7 percent of the full irrigation water (maximum corn grain production) can be saved for maximum profits.
A. Majnooni-Heris, Sh. Zand-Parsa, A. R. Sepaskhah, A. A. Kamgar-Haghighi,
Volume 10, Issue 3 (fall 2006)
Abstract
Agricultural investigations use computer models for simulation of crop growth and field water management. By using these models, the effects of plant growth parameters on crop yields are simulated, hence, the experimental costs are reduced. In this paper, the model of MSM (Maize Simulation Model) was calibrated and validated for the prediction of maize forage production at Agricultural College, Shiraz University in 1382 and 1383 by using maize forage yield under furrow irrigation with four irrigation and three nitrogen treatments. Irrigation treatments were I4, I3, I2, and I1, with the depth of water 20% greater than, equal to, 20% and 40% less than potential crop water requirements, respectively. Nitrogen treatments were N3, N2, and N1, with the application of N as urea equal to 300, 150, and 0 kg N ha-1, respectively. After calibration and validation of MSM, it was used to estimate suitable planting dates, forage yield and net requirement of water discharge for planting at different dates. The results indicated that the net requirement of water discharge was reduced by gradual planting at different planting dates. By considering different planting dates for maize, from Ordibehest 20th to Tir 10th, the planting area might be increased 17.9%, compared with single planting date on Ordibehesht 30th under a given farm water discharge and full irrigation.
A Majnoni-Heris, Sh Zand-Parsa, A Sepaskhah, M.j Nazemosadat,
Volume 12, Issue 46 (1-2009)
Abstract
Global solar radiation (Rs) has wide applications in several disciplines. The data of measured or predicted Rs are widely applied by solar engineers, architects, agriculturists and hydrologists. Due to the importance of Rs, several empirical models have been developed to predict its values all over the world. In this study, Angstrom model was calibrated based on the ratio of actual and possible sunshine hours n/N by using measured daily data of Rs at Bajghah meteorological station in Fars province during 2003-2004. The model was modified by using air temperature for considering the effect of cloudy conditions as well as n/N ratios. The results showed that using both the air temperatures and the ratios of n/N led to a higher accuracy. In regard to estimation of the Rs values, the results showed that mean air temperatures have a higher accuracy compared with differences between maximum and minimum air temperatures. Also, a new local model with higher accuracy was developed based on a number of daily meteorological parameters such as deficit vapor pressure, relative humidity, precipitation, mean air temperature, maximum and minimum air temperatures difference and n/N. This new local model that used different meteorological parameters had the highest accuracy in comparison with the other models. Also, a number of models developed by other investigators for estimation of Rs were calibrated for the study area. Finally, different selected models were validated by using the measured data of Rs in 2005. The results showed that the developed local multi-variable model provided higher accuracy results in comparison with the other radiation models.
S. A. Banimahd, D. Khalili, A. A. Kamgar-Haghighi, Sh. Zand-Parsa,
Volume 18, Issue 70 (winter 2015)
Abstract
In the present research, the performances of six empirical models, i.e., simple threshold exceedance, fixed proportion exceedance, quadratic function of storage, power function of storage, cubic function of storage, and exponential function of storage were investigated for estimation of groundwater potential recharge in a semi-arid region. First, the FAO Dual Crop procedure was used to calibrate evaporation from bare soil during the occurrence of potential recharge period. Then, the empirical models were calibrated utilizing soil moisture and potential recharge data. For validation of empirical models, soil moisture and potential recharge were simultaneously estimated for an independent event. Results indicated that 5 of the six models (except for the simple threshold exceedance model) were able to estimate potential recharge with a reasonable accuracy, showing the maximum computed value of NRMSE (Normalized Root Mean Square Errors) of 24.4 percent. According to validation results, exponential, cubic, and power function models provided better estimation of potential recharge in comparison with the linear models. Also, all of the applied empirical models were able to simulate soil moisture during the recharge period with an acceptable accuracy. Finally, the exponential model with minimum NRMSE value for soil water simulation and also acceptable performance of potential recharge estimation was recommended for estimation of potential recharge in the study area.
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.
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.
Sh. Zand-Parsa, F. Ghasemi Saadat Abadi, M. Mahbod, A. R. Sepaskhah,
Volume 24, Issue 2 (Summer 2020)
Abstract
Due to the limited water resources and growing population, food security and environmental protection have become a global problem. Increasing water productivity of agricultural products is one of the main solutions to cope with the difficulties. By optimizing applied water and nitrogen fertilizer, the pollution of groundwater could be deceased and the water productivity could be increased. The aim of this research was to determine the relationships between water productivity (IRWP) and water use efficiency (WUE) and different amounts of applied water (irrigation + rain fed) and nitrogen (applied and residual). This study was conducted on wheat (Triticum aestivum L., cv. Shiraz) in Shiraz University School of Agriculture, based on a split-plot design with three replications, in 2009-2010 and 2010-2011 periods. Irrigation treatments varied from zero to 120% of full irrigation depth, and nitrogen fertilizer treatments varied from zero to 138 kg ha-1 under basin irrigation system. The experimental data of the first and second years were used for the calibration and validation of the proposed relationships, respectively. The calibrated equations using the dimensionless ratios of irrigation depth plus rainfall, actual evapotranspiration and nitrogen fertilizer plus soil residual nitrogen to their amounts in full irrigation and maximum fertilizer amounts were appropriate for the estimation of water productivity and water use efficiency. The values of the determination coefficient (R2) for water productivity and water use efficiency (0.88 and 0.93, respectively), and the values of their normalized root mean square error (NRMSE) (0.2 and 0.13, respectively) showed a good accuracy for the estimation of IRWP and WUE.
F. Ghasemi-Saadat Abadi, S. Zand-Parsa, M. Mahbod,
Volume 25, Issue 4 (Winiter 2022)
Abstract
In arid and semi-arid regions, water resource management and optimization of applying irrigation water are particularly important. For optimization of applying irrigation water, the estimated values of actual evapotranspiration are necessary for avoiding excessive or inadequate applying water. The estimation of actual crop evapotranspiration is not possible in large areas using the traditional methods. Hence, it is recommended to use remote sensing algorithms for these areas. In this research, actual evapotranspiration of wheat fields was estimated using METRIC algorithm (Mapping EvapoTranspiration at high Resolution with Internalized Calibration), using ground-based meteorological data and satellite images of Landsat8 at the Faculty of Agriculture, Shiraz University, in 2016-2018. In the process of METRIC execution, cold pixels are located in well-irrigated wheat fields where there is no water stress and maximum crop evapotranspiration occurred. The estimated maximum values of evapotranspiration using the METRIC algorithm were validated favorably using the obtained values by the AquaCrop model with NRMSE (Normalized Root Mean Square Errors) equal to 0.12. Finally, the values of water productivity (grain yield per unit volume of evapotranspiration) and irrigation efficiency were estimated using the values of predicted actual evapotranspiration using remote sensing technique. The values of measured irrigation water and produced wheat grain yield in 179 ha were estimated at 0.86 kg m-3 and 75%, respectively.
