Three-dimensional modeling of sediment resuspension in a large shallow lake S Lin, L Boegman, R Valipour, D Bouffard, JD Ackerman, Y Zhao Journal of Great Lakes Research 47 (4), 970-984, 2021 | 22 | 2021 |
Characterizing spatial and temporal distributions of turbulent mixing and dissipation in Lake Erie S Lin, L Boegman, YR Rao Journal of Great Lakes Research 47 (1), 168-179, 2021 | 14 | 2021 |
An automatic lake-model application using near-real-time data forcing: development of an operational forecast workflow (COASTLINES) for Lake Erie S Lin, L Boegman, S Shan, R Mulligan Geoscientific Model Development 15 (3), 1331-1353, 2022 | 10 | 2022 |
Prediction of algal blooms via data-driven machine learning models: an evaluation using data from a well-monitored mesotrophic lake S Lin, DC Pierson, JP Mesman Geoscientific Model Development 16 (1), 35-46, 2023 | 8 | 2023 |
Observation and parameterization of bottom shear stress and sediment resuspension in a large shallow lake S Lin, L Boegman, A Jabbari, R Valipour, Y Zhao Earth and Space Science 10 (6), e2022EA002786, 2023 | 4 | 2023 |
Multi-model machine learning approach accurately predicts lake dissolved oxygen with meteorological and hydrological input S Lin, DC Pierson, R Ladwig, BM Kraemer, FRS Hu Available at SSRN 4454256, 2023 | 2 | 2023 |
An automatic lake-model application using near real-time data forcing: Development of an operational forecast model for Lake Erie S Lin, L Boegman, S Shan, R Mulligan Geoscientific Model Development Discussions 2021, 1-37, 2021 | 2 | 2021 |
An automatic lake-model application using near real-time data forcing: Development of an operational forecast model for Lake Erie, V1, Scholars Portal Dataverse [data set] S Lin, L Boegman, S Shan, R Mulligan | 2 | 2021 |
Sediment resuspension modeling in Lake Erie SQ Lin, R Valipour, YM Zhao, L Boegman 59th Annual Conference on Great Lakes Research, Guelph, Ont., June, 6-10, 2016 | 1 | 2016 |
Multi‐model machine learning approach accurately predicts lake dissolved oxygen with multiple environmental inputs S Lin, DC Pierson, R Ladwig, BM Kraemer, FRS Hu Earth and Space Science 11 (7), e2023EA003473, 2024 | | 2024 |
Observation and parameterization of bottom shear stress and sediment resuspension in a large shallow lake S Lin, L Boegman, A Jabbari, R Valipour, Y Zhao Authorea Preprints, 2022 | | 2022 |
Prediction of algal blooms via data-driven machine learning models: An evaluation using data from a well monitored mesotrophic lake S Lin, D Pierson, J Mesman Geoscientific Model Development Discussions 2022, 1-18, 2022 | | 2022 |
Turbulence and Sediment Resuspension Modelling in Lake Erie S Lin | | 2019 |
Prediction of algal blooms via data-driven machine learning models S Lin, DC Pierson, JP Mesman | | |