| Title: | Developing a deep learning model for the simulation of micro-pollutants in a watershed |
| Authors: | Yun, D., A. Abbas, J. Jeon, M. Ligaray, S.-S. Baek and K.H. Cho |
| Year: | 2021 |
| Journal: | Journal of Cleaner Production |
| Volume (Issue): | 300 |
| Pages: | |
| Article ID: | 126858 |
| DOI: | 10.1016/j.jclepro.2021.126858 |
| URL (non-DOI journals): | |
| Model: | SWAT |
| Broad Application Category: | pollutant only |
| Primary Application Category: | model and/or data comparison |
| Secondary Application Category: | pesticide, antibiotic and/or PFAS fate and transport |
| Watershed Description: | 3,370 km^2 Yeongsan River, located in southwest South Korea. |
| Calibration Summary: | |
| Validation Summary: | |
| General Comments: | |
| Language: | English |
| Keywords: | Micro-pollutant; Deep learning; SWAT; Long short-term memory |