| Title | Developing novel robust models to improve the accuracy of daily streamflow modeling. |
| Publication Type | Journal Article |
| Year of Publication | 2020 |
| Authors | Mohammadi, Babak, Farshad Ahmadi, Saeid Mehdizadeh, Yiqing Guan, Quoc Bao Pham, Nguyen Thi Thuy Linh, and Doan Quang Tri |
| Secondary Title | Water Resources Management |
| Volume | 34 |
| Pagination | p.3387-3409 |
| Call Number | OSU Libraries: Electronic Subscription |
| Keywords | Elkton (Or.), hydrology, mathematical modeling, neural networks, precipitation, streamflow, Umpqua River |
| Notes | In this article, the authors discuss different methods for enhancing models of daily streamflow, using two sites in Canada and two sites in the United States, including the hydrologic station at Elkton. Proposed boosted models showed improvement over classic multi-layer perception and time series models. |
| DOI | 10.1007/s11269-020-02619-z |
| Series Title | Water Resources Management |
