Predicting and understanding residential water use with interpretable machine learning
Environmental Research Letters.
TL;DR:
This work uses post-hoc interpretability methods to examine how drivers of water use interact, focusing on environmental, demographic, physical housing, and utility policy factors, finding all four categories of factors are important for estimating water use with environmental and utility policy factors playing the largest role.
(via
Semantic Scholar)
UN Sustainable Development Goal Categories
6. Clean Water and Sanitation
(OpenAlex)