vahid Rezaverdinejad; M. Shabanialasl; S. Besharat
Abstract
Introduction: Greenhouse cultivation is a steadily developing agricultural sector throughout the world. In addition, it is known that water is a major issue almost all part of the world especially for countries which have insufficient water source. With this great expansion of greenhouse cultivation, ...
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Introduction: Greenhouse cultivation is a steadily developing agricultural sector throughout the world. In addition, it is known that water is a major issue almost all part of the world especially for countries which have insufficient water source. With this great expansion of greenhouse cultivation, the need of appropriate irrigation management has a great importance. Accurate determination of irrigation scheduling (irrigation timing and frequency) is one of the main factors in achieving high yields and avoiding loss of quality in greenhouse tomato and cucumber. To do this, it is fundamental to know the crop water requirements or real evapotranspiration. Accurate estimation on crop water requirement is needed to avoid the excess or deficit water application, with consequent impacts on nutrient availability for plants. This can be done by using appropriate method to determine the crop evapotranspiration (ETc). In greenhouse cultivation, crop transpiration is the most important energy dissipation mechanisms that influence ETc rate. There are a large number of literatures on methods to estimate ETc in greenhouses. ETc can be measured or estimated by direct or indirect methods. The most common direct method estimates ETc from measurements with weighing lysimeters. Thisalsoincludes the evaporation measuring equipment, class A pan, Piche atmometer and modified atmometer. Indirect method includes the measurement of net radiation, temperature, relative humidity, and air vapour pressure deficit. A large number of models have been developed from these measurements to estimate ETc. Due to the fast development of under greenhouse cultivation all around the world, the needs of information on how it affects ETc in greenhouses has to be known and summarized. The existing models for ETc calculation have to be studied to know whether it is reliable for greenhouse climate (hereafter, microclimate) or not. Regression and artificial neural network models are two important models to estimate ETc in greenhouse. The inputs of these models are net radiation, temperature, day after planting and air vapour pressure deficit (or relative humidity).
Materials and Methods: In this study, daily ETc of reference crop, greenhouse tomato and cucumber crops were measured using lysimeter method in Urmia region. Several linear, nonlinear regressions and artificial neural networks were considered for ETc modelling in greenhouse. For this purpose, the effective meteorological parameters on ETc process includes: air temperature (T), air humidity (RH), air pressure (P), air vapour pressure deficit (VPD), day after planting (N) and greenhouse net radiation (SR) were considered and measured. According to the goodness of fit, different models of artificial neural networks and regression were compared and evaluated. Furthermore, based on partial derivatives of regression models, sensitivity analysis was conducted. The accuracy and performance of the employed models was judged by ten statistical indices namely root mean square error (RMSE), normalized root mean square error (NRMSE) and coefficient of determination (R2).
Results and Discussion: Based on the results, the most accurate regression model to reference ETc prediction was obtained three variables exponential function of VPD, RH and SR with RMSE=0.378 mm day-1. The RMSE of optimal artificial neural network to reference ET prediction for train and test data sets were obtained 0.089 and 0.365 mm day-1, respectively. The performance of logarithmic and exponential functions to prediction of cucumber ETc were proper, with high dependent variables especially, and the most accurate regression model to cucumber ET prediction was obtained for exponential function of five variables: VPD, N, T, RH and SR with RMSE=0.353 mm day-1. In addition, for tomato ET prediction, the most accurate regression model was obtained for exponential function of four variables: VPD, N, RH and SR with RMSE= 0.329 mm day-1. The best performance of artificial neural network for ET prediction of cucumber and tomato were obtained with five inputs include: VPD, N, T, RH and SR. The RMSE values of test data sets for cucumber and tomato ET were obtained 0.24 and 0.26 mm day-1. Moreover, the sensitivity analysis results showed that VPD is the most sensitive parameter on ETc.
Conclusion: The greenhouse industry has expanded across many parts of the word and the need of information on a reliable ETc method especially by indirect method is crucial. In this research, the artificial neural network models indicated good performance compared with linear and nonlinear regressions. The evaluated method could be used for scheduling irrigation of greenhouse tomato and cucumber.
H. Rezaei; J. Behmanesh; S. Besharat
Abstract
With respect to necessity of the optimum use of water resources and existence of many various optimization methods, in this study 3 kinds of heuristic algorithms have been used including Particle Swarm Optimization, Genetic Algorithm and Simulated Annealing to optimize the operation of Shaharchai dam ...
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With respect to necessity of the optimum use of water resources and existence of many various optimization methods, in this study 3 kinds of heuristic algorithms have been used including Particle Swarm Optimization, Genetic Algorithm and Simulated Annealing to optimize the operation of Shaharchai dam reservoir as an application. The optimization was carried out considering the probability of inflow for a period of 5 years. In order to obtain the best operation of reservoir, monthly release was defined as a second order polynomial according to storage volume and inflow, and different parameters of these algorithms have beenadjusted to minimize the objective function in which supplying the required demand of downstream was defined as the target. The best state of each algorithm is selected through 10 times running of programs (due to intrinsic random behavior of algorithms) and the results comparison leads to realization of which method can perform the best. According to the results, Particle Swarm Optimization method operates more effectively and produces the best results in solving reservoir operation problems. So as an application, control curves of release and storage volume have been extracted for Shaharchai dam reservoir using this method.
V.R. Verdinejad; S. Besharat; H. Abghari; H. Ahmadi
Abstract
Abstract
To optimal use of available water, irrigation scheduling is important to over scarcity of water resources in arid and semi-arid area. In this research to estimate of maximum allowable deficit (or: management allowed depletion) and irrigation scheduling of Fodder Mays based on canopy-air temperature ...
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Abstract
To optimal use of available water, irrigation scheduling is important to over scarcity of water resources in arid and semi-arid area. In this research to estimate of maximum allowable deficit (or: management allowed depletion) and irrigation scheduling of Fodder Mays based on canopy-air temperature difference, a field study was conducted in agricultural faculty of Karaj. The lower limit baseline (potential transpiration) and upper limit baseline (zero transpiration) were estimated by a wet treatment: (keeping soil water content at Field Capacity) and a dry treatment: (complete depletion of available water), respectively. To estimate the maximum allowable deficit, four soil moisture depletion to permanent wilting point treatments were applied in four different growth stages including settlement, vegetating, flowering and ripening of Fodder Mays with three replications. The measured data were wet and dry air temperature, canopy temperature, air relative humidity, root depth, soil water content in root depth and air vapor pressure and based the measured data, equations were extracted for lower and upper limit baselines of Fodder Mays. By comparison of canopy-air temperature difference of four treatments of soil moisture depletion with wet treatment, the maximum allowable deficit for four growth stages were estimated 42.8, 59.2, 58.9 and 67.5 percentages, respectively. The location of upper limit baseline (zero transpiration) was obtained +3.2 °C based on dry treatment. To irrigation scheduling in different growth stages by canopy-air temperature difference, crop water stress index was used and irrigation time was determined by direct method of canopy temperature.
Keywords: Canopy temperature, Evapotranspiration, Fodder Mays, Irrigation scheduling, Karaj
S. Besharat; A. H. Nazemi; A. Ashraf Sadraddini; S. Shahmorad
Abstract
چکیده
حرکت آب در خاک بر اساس جذب آب توسط ریشه کلید مراحل رشد گیاه و انتقال آب و املاح در سیستم خاک-گیاه میباشد. هدف از این تحقیق حل معادلات حاکم در انتقال آب در خاک و ارائه ...
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چکیده
حرکت آب در خاک بر اساس جذب آب توسط ریشه کلید مراحل رشد گیاه و انتقال آب و املاح در سیستم خاک-گیاه میباشد. هدف از این تحقیق حل معادلات حاکم در انتقال آب در خاک و ارائه مدل جذب آب توسط ریشه بر اساس مطالعات صحرایی میباشد. برای این منظور درصد حجمی رطوبت خاک با استفاده از دستگاه TDR اطراف درخت سیب که به صورت سطحی آبیاری شده بود در 12 نقطه تا عمق 2 متری در طول 20 روز بلافاصله بعد از آبیاری بدست آمد. مدل دو بعدی جذب آب توسط ریشه بر اساس تابع توزیع تراکم ریشه، تعرق پتانسیل و فاکتور تصحیح تنش آب برای شبیه سازی انتقال آب و تعیین تأثیر ریشه در حرکت آب بسط داده شد. مدل جذب ریشه حاصله با مدل انتقال آب در خاک مبتنی بر حل معادله ریچاردز تلفیق شد. بر اساس نتایج 60 درصد جذب آب در عمق 20 تا 40 سانتیمتری عمق خاک اتفاق افتاده است و در جهت شعاعی نیز در فاصله 30 تا 60 سانتیمتری حداکثر جذب بدست آمد که حدوداً 30 درصد از کل جذب را در بر میگیرد. نتایج درصد رطوبت خاک شبیه سازی شده با دادههای اندازهگیری شده میدانی مقایسه گردید که همبستگی قابل قبولی بین دادههای شبیه سازی شده و اندازهگیری شده مشاهده شد (97/0R2 =). مدل عددی انتقال و جذب آب می تواند وسیلهای مفید در شبیه سازی جریان آب همراه جذب آب توسط ریشه در محیط غیر اشباع باشد که در مهندسی آب از اهمیتی خاص برخوردار است.
واژههای کلیدی: حرکت آب، حل عددی، جذب ریشه، معادله ریچاردز، محیط غیر اشباع