Targeted Source Detection for Environmental Data

Autor:	Zheng, Guanjie, Liu, Mengqi, Wen, Tao, Wang, Hongjian, Yao, Huaxiu, Brantley, Susan L., Li, Zhenhui
Rok vydání:	2019
Předmět:	Electrical Engineering and Systems Science - Signal Processing Computer Science - Machine Learning Statistics - Applications Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	In the face of growing needs for water and energy, a fundamental understanding of the environmental impacts of human activities becomes critical for managing water and energy resources, remedying water pollution, and making regulatory policy wisely. Among activities that impact the environment, oil and gas production, wastewater transport, and urbanization are included. In addition to the occurrence of anthropogenic contamination, the presence of some contaminants (e.g., methane, salt, and sulfate) of natural origin is not uncommon. Therefore, scientists sometimes find it difficult to identify the sources of contaminants in the coupled natural and human systems. In this paper, we propose a technique to simultaneously conduct source detection and prediction, which outperforms other approaches in the interdisciplinary case study of the identification of potential groundwater contamination within a region of high-density shale gas development. Comment: 8 pages, 4 figures, 1 table
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1908.11056 Zobrazit plný text záznamu View this record from Arxiv