مقایسه برآوردهای تبخیرتعرق مرجع روزانه با روش‌های داده کاوی و سامانه نیاز آبی گیاهان در استان‌البرز

نوع مقاله : مقاله پژوهشی

نویسندگان

1 محقق مؤسسه تحقیقات خاک و آب، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران

2 استادیار مؤسسه تحقیقات خاک و آب، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران

3 دانشیار مؤسسه تحقیقات خاک و آب، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران

چکیده

تبخیرتعرق مرجع (ET0) عامل مهمی در تعیین نیاز آبی و برنامه‌ریزی آبیاری گیاهان است و برای تخمین آن،، معمولا از روش نسبتا دقیق پنمن مانتیث فائو 56، استفاده می‌شود. هدف از این پژوهش ارزیابی عملکرد روش‌های شبکه عصبی مصنوعی (ANNs)، جنگل تصادفی (RF) و ماشین بردار پشتیبان (SVM) برای تخمین مقدار ET0 روزانه دراستان البرز است. در این پژوهش از داده‌های ده ساله (1389 تا 1399) پنج ایستگاه سینوپتیک استان شامل (مشکین‌دشت، هشتگرد، اشتهارد، طالقان و کرج) استفاده شد و نتایج حاصل با داده‌های سامانه نیازآبی گیاهان مورد مقایسه قرار گرفت. نتایج نشان داد که برآورد مقدار ET0 روزانه به روش ANN بر اساس برآوردهای سامانه پیشنهادی، دقت بالاتری نسبت به سایر روش‌ها دارد. در ایستگاه مشکین‌دشت، مقادیر آماره‌های EF و NRMSE در روش ANN برای هر دو مرحلۀ آموزش و آزمون به ترتیب برابر با 96/0 و 11/0، و در روش RF به ترتیب برای آموزش برابر با 96/0 و 11/0، و برای آزمون برابر با 95/0، و 12/0 به‌دست آمد. در ایستگاه کرج، مقادیر آماره‌های EF و NRMSE در‌روش ANNs به‌ترتیب برای آموزش برابر با 96/0 و 11/0، و برای آزمون برابر با 95/0، و 12/0، و در‌روش RF برای آموزش به ترتیب برابر با 96/0 و 12/0، و برای آزمون برابر با 95/0، و 13/0 به-دست آمد. با توجه به بالا بودن دقت تخمین مقدار ET0 روزانه به روش‌های ANNs و RF می‌توان ‌این دو روش را جهت تخمین ET0 روزانه برای استان البرز توصیه کرد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Comparison of the reference evapotranspiration estimations by data mining methods and Crop Water Requirement System project in Alborz province

نویسندگان [English]

  • Azadeh Sedaghat 1
  • Arash Tafteh 2
  • Niazali Ebrahimipak 3
  • Seyedeh Narges Hosseini 1
1 Researcher, Soil and Water Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran
2 Assistant Professor, Soil and Water Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran
3 Associate Professor, Soil and Water Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran
چکیده [English]

The reference evapotranspiration (ET0) is an important factor for determining the plant water requirements and irrigation scheduling, which is usually estimated by widely accepted equation of Penman Monteith FAO-56 method. The aim of this study was to evaluate the performance of artificial neural networks (ANNs), random forest (RF) and support vector machine (SVM) methods for estimating the daily ET0 in Alborz province. A ten- year-data (2010-2020) of five meteorological synoptic stations of namely MeshkinDasht, Hashtgerd, Eshtehard, Taleghan and Karaj were used for estimation of ETo. The obtained values were compared with the provided data of a national project entitled Crop Water Requirement System. According to the results, the best agreement was found in Meshkin Dasht and Karaj stations. Besides, among the applied approaches, the ANNs method had the highest accuracy comparing to other methods. The values of EF and NRMSE in the ANNs method were determined 0.96 and 0.11, respectively for both training and testing steps in Meshkin Dasht station. While, these values for the RF method were determined 0.96 and 0.11, for training stage and 0.95 and 0.12 for testing stage, respectively. The obtained results in the Karaj station showed that EF and NRMSE in the ANNs method were 0.96 and 0.11, respectively for the training and 0.95 and 0.12 for the testing stage. These values for the RF method were 0.96 and 0.12 for the training stage respectively and 0.95 and 0.13 for the testing. Considering the higher accuracy of the ANNs and RF methods, these approaches can be recommended for estimating the daily ET0 across Alborz province.

کلیدواژه‌ها [English]

  • Data Mining
  • Penman Monteith FAO-56 method
  • Reference Evapotranspiration
  • Water requirement system
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