@article{82306a53b8244c619b8c0174ab73c544,
title = "Groundwater estimation from major physical hydrology components using artificial neural networks and deep learning",
author = "Hassan Afzaal and Farooque, {Aitazaz A.} and Farhat Abbas and Bishnu Acharya and Travis Esau",
note = "Funding Information: This research was supported by the Natural Science and Engineering Research Council of Canada, the Prince Edward Island Potato Board, the Canadian Horticultural Council, Potato Board New Brunswick, the New Brunswick Department of Agriculture, Aquaculture and Fisheries (CAP program), and Agriculture and Agri-Food Canada. The authors thank Ryan Barret (Research Coordinator; Prince Edward Island Potato Board), Joe Brennan and Khalil Al-Mughrabi (New Brunswick Potato Transformation Initiative), and the Precision Agriculture Team at the University of Prince Edward Island for their cooperation and assistance during the experiment. Funding Information: Funding: This research was supported by the Natural Science and Engineering Research Council of Canada, the Prince Edward Island Potato Board, the Canadian Horticultural Council, Potato Board New Brunswick, the New Brunswick Department of Agriculture, Aquaculture and Fisheries (CAP program), and Agriculture and Agri-Food Canada. Publisher Copyright: {\textcopyright} 2019 by the authors.",
year = "2020",
month = jan,
day = "1",
doi = "10.3390/w12010005",
language = "English",
volume = "12",
journal = "Water (Switzerland)",
issn = "2073-4441",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "1",
}