A hybrid machine learning model to predict and visualize nitrate concentration throughout the Central Valley aquifer, California, USA

M. Ransom, Katherine; T. Nolan, Bernard; A. Traum, Jonathan; C. Faunt, Claudia; M. Bell, Andrew; Ann M. Gronberg, Jo; C. Wheeler, David; Z. Rosecrans, Celia; C. Jurgens, Bryant; E. Schwarz, Gregory; Belitz, Kenneth; M. Eberts, Sandra; Kourakos, George; Harter, Thomas

doi:10.1016/j.scitotenv.2017.05.192

Public

A hybrid machine learning model to predict and visualize nitrate concentration throughout the Central Valley aquifer, California, USA

Published in The Science of The Total Environment • Jun 10, 2017

Authors:

Katherine M. Ransom

Bernard T. Nolan

Jonathan A. Traum

Abstract

Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater resource. To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical ...

Subject

Aquifer

Nitrate

Hydrology (agriculture)

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