Enhancing references evapotranspiration forecasting with teleconnection indices and advanced machine learning techniques

Author:

Helali Jalil,Mohammadi Ghaleni MehdiORCID,Mianabadi Ameneh,Asadi Oskouei Ebrahim,Momenzadeh Hossein,Haddadi Liza,Saboori Noghabi Masoud

Publisher

Springer Science and Business Media LLC

Reference101 articles.

1. Adnan M, Latif MA, Nazir M (2017) Estimating evapotranspiration using machine learning techniques. Int J Adv Comput Sci Appl 8(9):108–113

2. Aguilar E, Auer I, Brunet M, Peterson TC, Wieringa J (2003) Guidance on metadata and homogenization. Wmo Td 1186:1–53

3. Ahmadi M, Fathniya A, Abkharabat S (2015) Trend analysis of Iran’s precipitation and its relation to the teleconnection forces. J Clim Res 23:19–32 ((In Persian))

4. Ahmadi M, Salimi S, Hosseini SA, Poorantiyosh HA, Bayat A (2019) Iran’s precipitation analysis using synoptic modeling of major teleconnection forces (MTF). Dyn Atmos Oceans 85:41–56

5. Ali M, Jamei M, Prasad R, Karbasi M, Xiang Y, Cai B, Abdulla S, Farooque AA, Labban AH (2023) New achievements on daily reference evapotranspiration forecasting: potential assessment of multivariate signal decomposition schemes. Ecol Ind 155:111030

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