Artificial intelligence models to evaluate the impact of climate change on groundwater resources

Author:

Secci DanieleORCID,Giovanna Tanda Maria,D'Oria Marco,Todaro ValeriaORCID

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference67 articles.

1. Mathematical and Machine Learning Models for Groundwater Level Changes: A Systematic Review and Bibliographic Analysis;Afrifa;Futur. Internet,2022

2. Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. FAO Irrigation and Drainage Paper No. 56 - Crop Evapotranspiration.

3. ARPAE EMILIA ROMAGNA – Agenzia Regionale Prevenzione Ambiente Energia Emilia Romagna, 2021. URL https://www.arpae.it (accessed 9.01.22).

4. Asher, M. J., B.F.W.C., A. J. Jakeman, and L.J.M.P., 2015. A review of surrogate models and their application to groundwater modeling. Water Resour. Res. 51, 5957–5973. https://doi.org/10.1111/j.1752-1688.1969.tb04897.x.

5. Evaluating the effects of climate change on groundwater level in the Varamin plain;Azizi;Water Science and Technology: Water Supply,2021

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