English

A Dataset for Research on Water Sustainability

Machine Learning 2024-05-30 v1 Artificial Intelligence Computers and Society Performance

Abstract

Freshwater scarcity is a global problem that requires collective efforts across all industry sectors. Nevertheless, a lack of access to operational water footprint data bars many applications from exploring optimization opportunities hidden within the temporal and spatial variations. To break this barrier into research in water sustainability, we build a dataset for operation direct water usage in the cooling systems and indirect water embedded in electricity generation. Our dataset consists of the hourly water efficiency of major U.S. cities and states from 2019 to 2023. We also offer cooling system models that capture the impact of weather on water efficiency. We present a preliminary analysis of our dataset and discuss three potential applications that can benefit from it. Our dataset is publicly available at Open Science Framework (OSF)

Keywords

Cite

@article{arxiv.2405.17469,
  title  = {A Dataset for Research on Water Sustainability},
  author = {Pranjol Sen Gupta and Md Rajib Hossen and Pengfei Li and Shaolei Ren and Mohammad A. Islam},
  journal= {arXiv preprint arXiv:2405.17469},
  year   = {2024}
}

Comments

Accepted by ACM e-Energy 2024

R2 v1 2026-06-28T16:42:37.177Z