Evaluation of Multivariate Regression Models in Estimation of Evaporation and Transpiration Components of Maize, under Salinity Stress Conditions

Document Type : Research Paper


Department of Water Engineering, Faculty of Agriculture and Natural Resources, Imam Khomeini International University, Qazvin, Iran.


Estimation of evaporation and transpiration components of maize using by experimental models, is useful for management the water consumption in irrigation. In this research, the amounts of evaporation and transpiration components of maize were modeled for growth stages and salinity stress conditions. Salinity treatments were applied by water with EC of 0.5(S0), 2.1(S1), 3.5(S2), and 5.7(S3)dS.m-1, in the mini-lysimeter. Modeling of maize evapotranspiration components was performed by regression functions of linear, exponential, logarithmic, polynomial and power. Parameters of evapotranspiration (ETc), coefficients of evapotranspiration stress (Ks) and crop growth stage sensitivity (Kpi) were considered as the independent variables and transpiration (T) and evaporation (E) parameters (in separate models) were considered as the dependent variables. The equations coefficients were estimated by SPSS software and the multivariate regression models were generated. From S0 to S3 treatments, the values of evapotranspiration, transpiration and evaporation parameters (in the all of growth period) were measured in the range of 420-307.5, 289-150 and 131-157.5 mm, respectively. Under salinity stress conditions, the maize transpiration was decreased to a more value relative to evapotranspiration. But the evaporation was increased to the same extent. In modeling evaluation, exponential and polynomial models were selected as the optimal models for estimation the transpiration and evaporation rates, respectively. The sensitivity coefficient values (Kp) in four growth stages were equal to 0.556, 0.972, 1.315 and 0.432 (in exponential model) and 1.485, 1.238, 0.447 and 0.816 (in polynomial model). The result of this research was that regression models had an acceptable performance for simulation the evaporation and transpiration components of maize, under salinity stress conditions. Therefore, by estimation the transpiration amount, the crop net water requirement is estimated actually and the water use efficiency increases. Also, by estimation the amount of evaporation losses, the water application efficiency is calculated accurately.


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