Estimation of daily reference evapotranspiration by hybrid singular spectrum analysis-based stochastic gradient boosting

Başakın E. E., Ekmekcioğlu Ö., Stoy P. C., Özger M.

MethodsX, vol.10, 2023 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 10
  • Publication Date: 2023
  • Doi Number: 10.1016/j.mex.2023.102163
  • Journal Name: MethodsX
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, BIOSIS, EMBASE, Directory of Open Access Journals
  • Keywords: Estimation, Reference evapotranspiration, Singular spectrum analysis, Stochastic gradient boosting
  • Istanbul Technical University Affiliated: Yes


In this study, stochastic gradient boosting (SGB), a commonly-adopted soft computing method, was used to estimate reference evapotranspiration (ETo) for the Adiyaman region of southeastern Türkiye. The FAO-56-Penman-Monteith method was used to calculate ETo, which we then estimated using SGB with maximum temperature, minimum temperature, relative humidity, wind speed, and solar radiation obtained from a meteorological station. • The calculated ETo time series values were decomposed into sub-series using Singular Spectrum Analysis (SSA) to enhance prediction accuracy. • Each sub-series was trained with the first 70% of observations and tested with the remaining 30% via SGB. Final prediction values were obtained by collecting all series predictions. • Three lag times were taken into account during the predictions, and both short-term and long-term ETo values were estimated using the proposed framework. The results were tested with respect to root mean square error (RMSE) and Nash-Sutcliffe efficiency (NSE) indicators for ensuring whether the model produced statically acceptable outcomes.