نوع مقاله : مقاله پژوهشی
1 گروه خاکشناسی دانشکده کشاورزی دانشگاه گیلان، رشت، ایران
2 دانشیار بخش آبیاری و فیزیک خاک، مؤسسه تحقیقات خاک و آب، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران
3 استادیار، بخش آبیاری و فیزیک خاک، موسسه تحقیقات خاک و آب، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران
4 محقق، بخش آبیاری و فیزیک خاک، موسسه تحقیقات خاک و آب، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران.
عنوان مقاله [English]
Introduction: Reference evapotranspiration (ET0), a complex hydrological variable that affects crop water requirements and irrigation scheduling, is defined by a number of climatic factors that have an impact on water and energy balances.
Objective: This study aims to answer the question: can reference evapotranspiration be estimated without reducing accuracy, regardless of the availability of all variables? In this research, the accuracy of data mining methods in estimating ET0 with respect to the plant water demand system (FAO Penman-Monteith standard method) was evaluated
Materials and methods: In order to purpose this, data from thirteen climatology stations in the Zanjan province over a ten-year period (2010-2021) were collected on meteorological parameters such as sunshine hour, air temperature, wind speed, and relative humidity. The ET0 extracted from the plant water requirement system was calculated using the Penman-Mantith method of FAO 56 and on a daily time scale, where the actual value (measured) and the estimated values obtained by data mining methods were evaluated. The data from each station was divided into two sets: training (two-thirds of the data) and testing (one-third of the data) in order to validate the results that were obtained.
Results and discussion: According to the results, ANNs performed better than SVM and RF methods. The mean values of, RMSE, EF and NRMSE criteria for the ANNs method in the training and testing steps were 0.49, 0.94 and 0.14, respectively. The mean values of these criteria for the RF method in the training step were 0.49, 0.94 and 0.14 and in the testing step it is equal to 0.52, 0.94 and 0.15, respectively. The mean values of these criteria for the SVM method in the training and testing steps were 0.52, 0.94 and 0.15, respectively.
. The average air temperature is the most significant and effective parameter to estimate ET0, according to more than 92 percent (12 stations) of the results from two ANNs and RF methods. The sunshine hours is the second-most crucial and useful input in estimating ET0, according to more than 84 percent (11 stations) of the results. As a result, using the four meteorological variables average air temperature, average relative humidity, wind speed, and sunshine hours as input, excellent performance can be achieved. The NRMSE values obtained from the estimation of ET0 did not exhibit regular variations with the average of any of the parameters .
Conclusion: It was discovered that the average air temperature was the most crucial and useful parameter as a result of the sensitivity analysis of the ANNs method and the Predictor Importance of the RF method. The results of the current study will help estimate ET0 for semi-arid climates where ET0 is critical for agricultural water resource management.