Showing 4 results for Sarai Tabrizi
M Sarai Tabrizi, H Babazadeh, M Parsinejad, S.a.m Modares Sanavi,
Volume 14, Issue 52 (sumer 2010)
Abstract
Deficit irrigation is one of the irrigation management methods that is used to increase Water Use Efficiency. Considering the internal plant adaptability characteristic to water shortage, Partial Root Drying method has been introduced in recent years. In this field research improvement of Water Use Efficiency for Soybean was determined. This experiment which was conducted at four furrow irrigation treatments at the Research Field of Tehran University in Karaj in 2008, consists of full irrigation (100% soil moisture deficit compensation), conventional deficit irrigation at 50 and 75 percent soil moisture deficit compensation and Partial Root Drying at 50 percent soil moisture deficit compensation with three replications. The amounts of irrigation used were exactly compensation level (negligible loss). Results indicated that Water Use Efficiency according to Duncan's Multiple Range Test at the five percent level of probability there was a significant difference between partial root drying treatment (PRD50%) and conventional deficit irrigation treatment at fifty percent soil moisture deficit compensation (DI50%),. Water Use Efficiency in PRD50% compared with DI50%, DI75% and full irrigation increased by 48.3%, 61.9% and 70.1% respectively.
M. Sarai Tabrizi, M. Homaee, H. Babazadeh, F. Kaveh , M. Parsinejad,
Volume 19, Issue 73 (fall 2015)
Abstract
Salinity and nutrient deficiency particularly nitrogen are two important limiting factors for yield production in arid and semi-arid regions. The objective of this study was to model basil response to combined salinity and nitrogen deficiency. To that end, modified Leibig-Sprengel (LS) and modified Mitcherlich-Baule (MB) and also some newly derived models based on combination of MB with salinity models of Maas and Hoffman (31), van Genuchten and Hoffman (36), Dirksen and Augustijn (17) and Homaee et al., (23) were evaluated. The experiment was conducted under four salinities including 1.175, 3, 5, and 8 dSm-1 and four nitrogen levels including 100, 75, 50, and 0 percent of fertilizer requirements each with three replicates. Results indicated that from among the evaluated models, the derived models of MB and Maas and Hoffman (MB-MH) (nRMSE=4.9), MB and van Genuchten and Hoffman (MB-VG) (nRMSE=5.4), and also MB and Homaee et al., (MB-H) (nRMSE=7.0) provide best fits to the measured data. Also, the comparison of two modified LS and MB models indicated that the estimated relative yield for irrigation water salinity levels by modified LS model (nRMSE=4.6) provides better results (nRMSE=5.9). However, for soil nitrogen levels and interactive effects of salinity and nitrogen, the modified MB model (nRMSE=10.3) provided better outputs (nRMSE=14.4). Consequently, instead of the modified LS and MB models the proposed models in this research can be recommended for use.
S. Khalilian, M. Sarai Tabrizi, H. Babazadeh, A. Saremi,
Volume 24, Issue 4 (Winter 2021)
Abstract
In the present study, the SWAT hydrological model was developed for the upstream of the Zayandehrood dam to evaluate the inflow to this dam. Accordingly, after entering the meteorological and hydrometric information of the region, the runoff simulation was performed. Due to the high volume of entrances to the Zayandehrood Dam, Shahrokh Castle hydrometric stations were selected as the base station for calibration and validation during the statistical period of 1990-2015. After hydrological simulation and accuracy of results, climate prediction was performed using the fifth model of the climate change for the RCP scenarios. According to the forecast, by using climate change models, the temperature could be assumed to increase in all models and the highest rate of increase would occur under the RCP 8.5 climate scenario. After evaluating climate change in different diffusion scenarios, the runoff of the basin was simulated in the SWAT model. The simulation results of runoff in the catchment area showed that although the amount of rainfall was increased in the region, increasing the temperature had a greater effect, reducing the amount of runoff in the basin. Based on the results of climate change, hydrological simulation was performed using the SWAT model. The results showed that the effect of diffusion scenarios in the region was different, causing an increase in temperature and precipitation. The highest increase was observed in the RCP8.5 scenario, which was consistent with the nature of this emission scenario, with the highest emission of greenhouse gases and carbon dioxide. Then, the evaluation of the hydrological model was done; the results showed that although the amount of rainfall in the region had been increased, the increase in temperature of this basin had a greater effect and efficiency in reducing the amount of runoff.
M. Ghodspour, M. Sarai Tabrizi, A. Saremi, H. Kardan Moghadam, M. Akbari,
Volume 25, Issue 3 (Fall 2021)
Abstract
The application of simulation-optimization models is a valuable tool for selecting the appropriate cropping pattern. The main objective of this research is to develop a two-objective simulation-optimization model to determine the pattern of cultivation and water allocation. The model performs the optimization with the multi-objective metamorphic algorithm (MOALO) after simulating different states of the cultivation pattern. The decision variables including land and water allocated to ten-day periods of plant growth were designed in a way that the minimum utilization of water resources and economic maximization were identified as target functions. The developed model was used to simulate and optimize the cultivation pattern with an area of 5500 hectares and water allocation of Semnan plain with renewable water at the rate of 60.8 million cubic meters. Harvesting scenarios of 80 (GW80) and 100 (GW100) percent of renewable groundwater and scenarios of change in existing cropping pattern of 30 (AC30) and 60 (AC60) percent were considered and each scenario was simulated with the MOALO algorithm. Optimization using the proposed model in four scenarios improved the water and economic objective functions compared to the initial simulation performance. The results showed that the four proposed scenarios were obtained by minimizing the water objective function and maximizing the economic objective function relative to the current situation (simulation). In general, the proposed model had a good performance despite its simplicity, which is a specialized tool to optimize the crop pattern with water allocation.
