Reference evapotranspiration estimation in hyper-arid regions via D-vine copula based-quantile regression and comparison with empirical approaches and machine learning models-Reference-Cited by-同舟云学术

Reference evapotranspiration estimation in hyper-arid regions via D-vine copula based-quantile regression and comparison with empirical approaches and machine learning models

Published:2022-12 Issue: Volume:44 Page:101259
ISSN:2214-5818
Container-title:Journal of Hydrology: Regional Studies
language:en
Short-container-title:Journal of Hydrology: Regional Studies

Author:

Abdallah Mohammed,Mohammadi Babak^ORCID,H. Zaroug Modathir A.,Omer Abubaker,Cheraghalizadeh Majid,Eldow Mohamed E.E.,Duan Zheng

Publisher

Elsevier BV

Subject

Earth and Planetary Sciences (miscellaneous),Water Science and Technology

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4. Application of an artificial intelligence technique enhanced with intelligent water drops for monthly reference evapotranspiration estimation;Ahmadi;Agric. Water Manag.,2021

5. Allen, R.G., Pereira, L.S., Raes, D., Smith, M.J.F., Rome, 1998. Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. 300(9): D05109.

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