برآورد تبخیر از تشت در سه اقلیم متفاوت با استفاده از روش‌های داده محور

تبخیر یکی از پیچیده ترین و مهم ترین فرآیندها در بررسی عوامل هیدرولوژیکی و هواشناسی بوده و نقش عمده ای در تعیین معادلات توازن انرژی در سطح زمین دارد. در این راستا و در پژوهش حاضر، توانایی سه روش داده محور درخت گرادیان تقویت شده، مدل خطی تعمیم یافته و پرسپترون چندلایه در برآورد مقدار تبخیر از تشت در سه اقلیم خشک (ایستگاه یزد و بافق)، نیمه خشک (ایستگاه بیرجند و سیاه بیشه) و مرطوب (ایستگاه ساری و فردوس) با استفاده از داده های هواشناسی به عنوان ورودی مدل مورد بررسی قرار گرفت. از بین متغیرهای موثر، چهار پارامتر دمای میانگین، رطوبت نسبی، سرعت باد و ساعات آفتابی در دوره زمانی بیست ساله (2020-2001) جمع‌آوری گردید. با توجه به متغیرهای ورودی و میزان همبستگی آن‌ها با پارامتر تبخیر، شش سناریو مختلف از متغیرهای هواشناسی انتخاب شده، تعریف گردید. همچنین برای ارزیابی دقت مدل های مذکور از چهار معیار ارزیابی جذر میانگین مربعات خطا، میانگین خطای مطلق، ضریب همبستگی و شاخص پراکندگی استفاده گردید. نتایج حاصل نشان داد که در ایستگاه‌های بیرجند، یزد،  مدل ششم روش پرسپترون چندلایه به ترتیب با جذر میانگین مربعات خطای 1.97، 1.95، 1.97، در ایستگاه ساری مدل چهارم روش پرسپترون چندلایه با جذر میانگین مربعات خطای 1.41، در ایستگاه سیاه‌بیشه مدل دوم روش پرسپترون چندلایه با مقدار خطای 2.91 و در ایستگاه بافق مدل پنجم روش پرسپترون چندلایه با جذر میانگین مربعات خطای 1.92 بهترین عملکرد را در برآورد میزان تبخیر از تشت داشتند. در نهایت می‌توان چنین نتیجه‌گیری نمود که در تمامی ایستگاه‌های مورد مطالعه، روش پرسپترون چندلایه دقیق‌ترین برآوردها را ارائه نمود و به عنوان روشی با دقت بالا پیشنهاد گردید.

estimating pan evaporation in three different climates using data-driven methodsm

background and objectivesevaporation is one of the most complex and important processes in studying hydrological and meteorological factors and plays a major role in determining the energy balance equations on the earth's surface. so, knowing the exact amount of evaporation volume is important for monitoring and correct management of water resources, irrigation planning, determining the irrigation needs, estimating evaporation from the reservoir of dams and modeling hydrological projects, especially in arid and semi-arid regions. on the other hand, modeling such a complex process in which many parameters interact with each other is so difficult that it is not possible to simplify this issue without multiple assumptions. therefore, accurate estimation of evaporation has always been of great importance. many experimental methods have been presented for estimating evaporation, but since these methods require a lot of input data or it is not possible to measure the variables in all areas, many of these methods have lost their effectiveness. therefore, it is necessary to use methods which need fewer number of meteorological variables and estimate the evaporation with high accuracy. therefore, the aim of the current research is to evaluate and present the most accurate model of evaporation estimation using three data-driven models in six synoptic stations in arid, semi-arid and humid climates of iran, so that the proposed model, in addition to having sufficient accuracy, requires fewer input parameters to estimate evaporation even when there is no sufficient data.methodologyin this regard, the ability of three machine-learning methods of gradient boosted tree (gbt), generalized linear model (glm) and artificial neural network-multi layer perceptron (mlp) in estimating the amount of pan evaporation in dry (yazd and bafq stations), semi-arid (birjand and siah-bisheh stations) and humid climates (sari and ferdous stations) were investigated. daily parameters of some meteorological variables on evaporation during the time period of 2001-2020 were collected. in order to investigate the possibility of using different combinations of meteorological parameters to estimate the evaporation as accurately as possible, six different combinations of the meteorological parameters (average temperature, relative humidity, and wind speed and sunshine hours) were considered. also, to evaluate the accuracy of the mentioned models, four assessment criteria including root mean square error (rmse), mean absolute error (mae), correlation coefficient (r) and scatter index (si) were used. furthermore, diagrams of time series ofthe best models and the scatter plots diagram of observed and predicted pan evaporation by the models were presented and the most suitable combination of the meteorological parameters that had suitable accuracy for estimating pan evaporation was suggested.findingsthe results showed that in birjand, yazd, ferdos, and siah-bisheh stations, mlp-vi with rmse of 1.97, 1.95, 1.97, 2.91, respectively, performed more accurate than other studied models. moreover, in sari station, mlp-iv and in bafq station, mlp-v with rmse of 1.41 and 1.92, respectively, provided the most precise estimates of evaporation values. finally, it can be comprehended that in all six studied stations, mlp provided the most accurate estimations of the amount of pan evaporation and it is suggested as a method with high degree of accuracy. furthermore, gbt presented the weakest performance in comparison with other studied models. the mentioned trend about the high accuracy of the mentioned models for all studied stations can also be concluded from presented figures. it can be inferred that the accurate models mentioned in each station had the least distribution around the bisector line and had the most accuracy and the least error. in other words, it is possible to estimate the evaporation values in all stations with the meteorological data of temperature, relative humidity, sunshine hours and wind speed with acceptable accuracy.conclusionevaporation is one of the main components of water balance in agriculture and is one of the effective and influential factors for suitable irrigation planning. therefore, accurate estimation of this parameter has a significant role on reducing excessive water consumption. in this study, three data-driven models of mlp, gbt and glm were implemented in six stations including yazd, birjand, sari, bafq, siah-bisheh and ferdous. the obtained results indicated that the sixth scenario using all utilized meteorological parameters in yazd, birjand, siah-bisheh, and ferdous stations, forth scenario in sari and fifth scenario in bafq station with the lowest error provided the most accurate estimates of the evaporation and may be recommended for proper estimation of pan evaporation values.