7
Reza Mohammadikia; ali ashraf sadraddini; amir hossein nazemi; Reza delearhasannia; ajdar onnabi milani
Abstract
This study aimed to determine the crop coefficient of sugar beet using canopy cover extracted from digital images under different irrigation managements. The crop coefficient and canopy cover were directly measured by water balance and image processing methods, respectively, in 10 days intervals during ...
Read More
This study aimed to determine the crop coefficient of sugar beet using canopy cover extracted from digital images under different irrigation managements. The crop coefficient and canopy cover were directly measured by water balance and image processing methods, respectively, in 10 days intervals during the growing season. The crop coefficient of sugar beet in three irrigation managements with maximum allowable depletion (MAD) of 40%, 60%, and 80%, was estimated using its regression equation with canopy cover. This was modeled for potential conditions and then validated by using the average measurements in two years. The findings showed that the estimated crop coefficients were in good agreement with the observations in irrigation managements that had MAD of 40% and 60%. The coefficient of determination (R2), normalized Root Mean Square Error (nRMSE), and model efficiency (EF) were 0.95, 0.11 and 0.95, for 40% MAD, 0.9, 0.13 and 0.85 for 60% MAD, respectively. The results illustrate that the crop coefficient of sugar beet, within the moisture range between field capacity to a MAD of 60%, can be reliably estimated by this approach. The values of determination coefficient (R2), normalized Root Mean Square Error (nRMSE) and model efficiency (EF) decreased to 0.49, 0.37 and 0.63, respectively, for 80% MAD, indicating poor performance of the model under severe drought stress conditions. The proposed method has some advantages including easy and fast data collection, greater accuracy and lower cost, the ability to provide the desired number of images, and no need for meteorological data. Therefore, this can be applied to study the plant growth and crop coefficient variations during the growth period.
7
Ali Morshedi; Hossein Jafari; azhdar Onabi Milani
Abstract
The aim of this study was to estimate the actual evapotranspiration of wheat using Surface Energy Balance Algorithm for Land (SEBAL) and compare with data measured by lysimeters in two study sites in Tabriz and Karaj during three growing seasons (1396-1399). Values of actual evapotranspiration of wheat ...
Read More
The aim of this study was to estimate the actual evapotranspiration of wheat using Surface Energy Balance Algorithm for Land (SEBAL) and compare with data measured by lysimeters in two study sites in Tabriz and Karaj during three growing seasons (1396-1399). Values of actual evapotranspiration of wheat during the growing seasons were calculated by two methods: a) using Landsat 8 satellite data through SEBAL, and b) using drained lysimeter data. Considering that evapotranspiration in SEBAL is in actual conditions and lysimeters provide evapotranspiration in potential conditions (standard situation without any limitation), to reduce errors, remote sensing data were used for pixels that had moisture conditions similar to standard lysimeters conditions. Comparison of actual evapotranspiration obtained from SEBAL and lysimeter in both sites showed relatively good correlation. The coefficients of determination (R2) were 0.73 and 0.65 in, respectively, Karaj and Tabriz sites. In addition, using statistical parameters such as NRMSE, RMSE, MAE, and MBE showed that SEBAL actual evapotranspiration data and lysimeteric data were, relatively, in agreement in the two study sites. However, in most cases, evapotranspiration values by SEBAL were greater than values measured by the lysimeter. In general, considering the advantages of the SEBAL, it is suggested this technology be used to estimate the actual evapotranspiration of wheat in large-scale areas.
ali ataee; Mohammadreza Neyshaboori; Mehdi Akbari; Davood Zare haghi; Ajdar Onnabi Milani
Abstract
Multidimensional nature of water flow, plant uptake, and high frequency of water application increase the complexity in modeling soil moisture dynamics from trickle irrigation. By determining soil hydraulic properties, parameters of root distribution model for pistachio trees in the field, evapotranspiration ...
Read More
Multidimensional nature of water flow, plant uptake, and high frequency of water application increase the complexity in modeling soil moisture dynamics from trickle irrigation. By determining soil hydraulic properties, parameters of root distribution model for pistachio trees in the field, evapotranspiration and inflow flux, soil moisture distribution was modeled using HYDRUS-2D model for surface (DI) and sub-surface drip irrigation (SDI) systems. Also, soil moisture content in the following days after irrigation was measured at different lateral and vertical distances from the tree by using Moisture Meter Profile Probe. Leaf stomatal conductance was used to test the model and parameterize water-stress response function. The h50 for pistachio tree, which represents the pressure head at which the water extraction rate is reduced by 50%, was calculated 4935 cm. HYDRUS outputs were compared with measured data in corresponding locations, and values ofME, RMSE, E and R2 statistics were obtained -0.002, 0.02, 0.7, 0.741 for DI and 0.006, 0.021, 0.761, and 0.794 for SDI respectively. The calculated transpiration by HYDRUS showed high correlation with stomatal conductance, especially in SDI. Based on plant measurements and HYDRUS results, root water uptake in SDI was significantly more than DI. Therefore, using SDI systems, by decreasing evaporation, saves more water and increases irrigation efficiency. The calculated root water uptake and measured stomatal conductance for the pistachio trees revealed that soil moisture perfectly supports plants until four days after irrigation. Thus, by decreasing irrigation interval in the field, maximum potential of drip irrigation systems can be achieved.