Irrigation
E. Farrokhi; M. Nassiri Mahallati; A. Koocheki; alireza beheshti
Abstract
Introduction: The modeling approach for the simulation of the growth and development of tomatoes in Iran has been overlooked. Calibrated crop simulation models, therefore, are increasingly being used as an alternative means for the rapid assessment of water-limited crop yield over a wide range of environmental ...
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Introduction: The modeling approach for the simulation of the growth and development of tomatoes in Iran has been overlooked. Calibrated crop simulation models, therefore, are increasingly being used as an alternative means for the rapid assessment of water-limited crop yield over a wide range of environmental and management conditions. AquaCrop is a multi-crop model that simulates the water-limited yield of herbaceous crop types under different biophysical and management conditions. It requires a relatively small number of explicit and mostly intuitive parameters to be defined compared to other crop models and has been validated and applied successfully for multiple crop types across a wide range of environmental and agronomic settings. This study was conducted as a two-year field experiment with the aim of the simulation of soil water content, evapotranspiration, and green canopy cover of tomato using AquaCrop model under different irrigation regimes at two growth stages in Mashhad climate conditions. Materials and Methods: A field experiment was conducted over two consecutive seasons (2016-2017) in the experimental field of Ferdowsi University of Mashhad, located in Khorasan Razavi province, North East of Iran. The experiment was laid out in a split-plot design with different irrigation regimes at the vegetative and at the reproductive stage as the main and subplot factors, replicated thrice. In total, 27 plots of 4.5×3 m (13.5 m2) were used at a planting density of 2.7 plants per m2. Seedlings were planted in a zigzag pattern into twin rows, with a distance of 1.5 m between them, so there were four twin rows of three meters in each plot. The distance between tomato plants within each twin-row was 0.5 meters. A buffer zone spacing of 3 and 1.5 m was provided between the main plots and subplots, respectively. The following experimental factors were studied: three irrigation regimes (100= 100% of water requirement, 75= 75% of water requirement, 50= 50% of water requirement) and two crop growth stages (V= vegetative stage and R= Reproductive stage). The drip irrigation method was used for irrigation. The tomato water requirement was calculated using CROPWAT 8.0 software. The irrigation water was supplied based on total gross irrigation and obtained irrigation schedule of CROPWAT. Model accuracy was evaluated using statistical measures, e.g., R2, normalized root means square error (NRMSE), model efficiency (E.F.), and d-Willmott. The 2016 and 2017 measured soil and canopy data sets were used for calibration and validation of the AquaCrop model, respectively. Results and Discussion: For a water-driven model, such as AquaCrop, it is important to evaluate its effectiveness in simulating soil water content. During calibration (2016), the model simulated the soil water content with good accuracy. The simulated soil water content values were close to the observed values during calibration (2016) for all treatments with R2 ranging from 0.90 to 0.97, NRMSE in range of 8.47 to 17.96%, d varying from 0.76 to 0.99, and M.E. ranging from 0.87 to 0.96. Validation results indicated the good performance of the model in simulating soil water content for most of the treatments (0.79<R2<0.99, 10.04%<NRMSE<18.65%, 0.77<ME<0.92). Appropriate parameterization of canopy cover curve is critical for the model to provide accurate estimates of soil evaporation, crop transpiration, biomass, and yield. In general, the calibration results showed good agreement between simulated and observed data for canopy cover development in all treatments with high R2 values (>0.87), good E.F. (>0.61), low estimation errors (RMSE, ranging from only 4.5 to 9.2) and high d values (>0.92). Conclusion: The AquaCrop model (version 6.1) was calibrated and validated for modeling soil water content, evapotranspiration, and green canopy cover for tomatoes under drought stress conditions. In general, soil water content, evapotranspiration, and green canopy cover of tomato were simulated by AquaCrop model with acceptable accuracy in both calibration and validation stages. However, the model performance was more accurate in no and/or moderate stress conditions than in severe water stress environments. In conclusion, the AquaCrop model could be calibrated to simulate the growth and soil water content of tomatoes under temperate conditions reasonably well and become a very useful tool to support the decision on when and how much irrigate. For R2, values > 0.90 were considered very well, while values between 0.70 and 0.90 were considered good. Values between 0.50 and 0.70 were considered moderately well, while values less than 0.50 were considered poor. Root mean square error ranges from 0 to positive infinity and expresses in the units of the studied variable. An RMSE approaching 0 indicates good model performance.
B. Ghahraman
Abstract
Introduction: Actual crop evapotranspiration (Eta) is important in hydrologic modeling and irrigation water management issues. Actual ET depends on an estimation of a water stress index and average soil water at crop root zone, and so depends on a chosen numerical method and adapted time step. During ...
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Introduction: Actual crop evapotranspiration (Eta) is important in hydrologic modeling and irrigation water management issues. Actual ET depends on an estimation of a water stress index and average soil water at crop root zone, and so depends on a chosen numerical method and adapted time step. During periods with no rainfall and/or irrigation, actual ET can be computed analytically or by using different numerical methods. Overal, there are many factors that influence actual evapotranspiration. These factors are crop potential evapotranspiration, available root zone water content, time step, crop sensitivity, and soil. In this paper different numerical methods are compared for different soil textures and different crops sensitivities.
Materials and Methods: During a specific time step with no rainfall or irrigation, change in soil water content would be equal to evapotranspiration, ET. In this approach, however, deep percolation is generally ignored due to deep water table and negligible unsaturated hydraulic conductivity below rooting depth. This differential equation may be solved analytically or numerically considering different algorithms. We adapted four different numerical methods, as explicit, implicit, and modified Euler, midpoint method, and 3-rd order Heun method to approximate the differential equation. Three general soil types of sand, silt, and clay, and three different crop types of sensitive, moderate, and resistant under Nishaboor plain were used. Standard soil fraction depletion (corresponding to ETc=5 mm.d-1), pstd, below which crop faces water stress is adopted for crop sensitivity. Three values for pstd were considered in this study to cover the common crops in the area, including winter wheat and barley, cotton, alfalfa, sugar beet, saffron, among the others. Based on this parameter, three classes for crop sensitivity was considered, sensitive crops with pstd=0.2, moderate crops with pstd=0.5, and resistive crops with pstd=0.7. Therefore, nine different classes were formed by combination of three crop types and three soil class types. Then, the results of numerical methods were compared to the analytical solution of the soil moisture differential equation as a datum. Three factors (time step, initial soil water content, and maximum evaporation, ETc) were considered as influencing variables.
Results and Discussion: It was clearly shown that as the crops becomes more sensitive, the dependency of Eta to ETc increases. The same is true as the soil becomes fine textured. The results showed that as water stress progress during the time step, relative errors of computed ET by different numerical methods did not depend on initial soil moisture. On overall and irrespective to soil tpe, crop type, and numerical method, relative error increased by increasing time step and/or increasing ETc. On overall, the absolute errors were negative for implicit Euler and third order Heun, while for other methods were positive. There was a systematic trend for relative error, as it increased by sandier soil and/or crop sensitivity. Absolute errors of ET computations decreased with consecutive time steps, which ensures the stability of water balance predictions. It was not possible to prescribe a unique numerical method for considering all variables. For comparing the numerical methods, however, we took the largest relative error corresponding to 10-day time step and ETc equal to 12 mm.d-1, while considered soil and crop types as variable. Explicit Euler was unstable and varied between 40% and 150%. Implicit Euler was robust and its relative error was around 20% for all combinations of soil and crop types. Unstable pattern was governed for modified Euler. The relative error was as low as 10% only for two cases while on overall it ranged between 20% and 100%. Although the relative errors of third order Heun were the smallest among the all methods, its robustness was not as good as implicit Euler method. Excluding one large error of 50%, the average relative errors in this method was less than 10%. However, the ETc is time-dependent and varies from one day to another. So, averaging ETc over a larger time step brings about more error in computations. Accumulated relative error in Eta (ETp=5 mm.d-1, W0=Wj, t=1 d) under medium soil and crop type was decreased as the number of time steps increased, irrespective of the numerical method.
Conclusions: Based on practical considerations, we propose implicit Euler for its robustness, and 3-rd order Heun for its low maximum relative error for all combinations of soil and crop types.
