F. Fahalian; R. Moazenzadeh; M.R. Nori Emamzadeie
Abstract
A precise estimation of water consumption throughout a crop's growth season and of the amount of water consumed in each growth stage may play an important role in water resources management, integrated water and soil management, and proper irrigation scheduling. In a greenhouse, this faces with the conditions ...
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A precise estimation of water consumption throughout a crop's growth season and of the amount of water consumed in each growth stage may play an important role in water resources management, integrated water and soil management, and proper irrigation scheduling. In a greenhouse, this faces with the conditions specific to this environment. This study was conducted to propose a model to make an appropriate and accurate prediction of evapotranspiration (ET) for greenhouse cucumber. Two same microlysimeters with 28 cm diameter and 30 cm height were deployed simultaneously in the greenhouse for the cucumber culture. Amount of ET was measured daily by the weighing method in both mycrolysimeters. The data from the first microlysimeter were used to derive, and those from the second to validate the proposed models. The developed models were evaluated by root mean square error (RMSE), drawing measured versus predicted ET values, and t-statistics. The proposed model was initially developed in the form of a single regression equation with independent variables such as vapor pressure curve slope and relative humidity for the whole growth season; further however, a separate equation was developed for each of the four growth stages, as the initial model did not perform well (RMSE= 46.61%). The results showed that the proposed models made appropriate predictions of greenhouse cucumber ET. Average amount of cucumber ET were obtained with proposed models 0.398, 1.79, 3.428 and 2.061 mm for four growth stages. RMSE values also were obtained 15.78, 11.48, 9.11 and 7.08 percentage for four growth stages. Correlation coefficient from measured and predicted values of cucumber ET varied from 0.4 (using single equation) to 0.95 (using variable equations for different growth stages). All of the proposed models were significant (p
R. Moazenzadeh; B. Ghahraman; F. Fathalian; A.A. Khoshnood Yazdi
Abstract
Abstract
Pedotransfer functions (PTFS) are useful means of prediction many properties of the soil, and especially the hydraulic characteristics of this porous media. The main advantages of this functions, as compare to conventional methods used to directly estimate soil hydraulic properties, is that ...
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Abstract
Pedotransfer functions (PTFS) are useful means of prediction many properties of the soil, and especially the hydraulic characteristics of this porous media. The main advantages of this functions, as compare to conventional methods used to directly estimate soil hydraulic properties, is that they are not time-cost consuming. Different approaches such as classic linear and non linear regressions, artificial neural networks and regressions tree are being employed to develop the PTFS. Rosetta is a software package to predict soil hydraulic properties making use of artificial neural networks- based PTFS. In the present study, the impacts of the type and count of input variables to this software, on the prediction of the moisture retention curve and saturated hydraulic conductivity were evaluated in some soils from northern region of Iran, classed as of Loam and Clay Loam textures (USDA). Our results indicated that addition of bulk density as input variable decreased the performance of moisture retention curve prediction in both textural classes. Addition of bulk density showed on RMSE, ME, GMER and GSDER a positive and negative effect in Loam and Clay Loam textures, respectively. Addition of one or two moisture retention point(s) (the moisture content at matric potential of -33 and -1500 kpa) significantly decreased the RMSE at the medium range of matric potential (i.e. -33 to -500 kpa) and especially at -33 kpa. All of the studied PTFS tended to underestimate both saturated hydraulic conductivity and moisture content at different matric potential.
Key words: Pedotransfer Functions, Hydraulic properties, Moisture retention curve, Saturated hydraulic conductivity, Rosetta, Iran
