| Modeling urban coastal flood severity from crowd-sourced flood reports using Poisson regression and Random Forest JM Sadler, JL Goodall, MM Morsy, K Spencer Journal of hydrology 559, 43-55, 2018 | 153 | 2018 |
| Forecasting groundwater table in a flood prone coastal city with long short-term memory and recurrent neural networks BD Bowes, JM Sadler, MM Morsy, M Behl, JL Goodall Water 11 (5), 1098, 2019 | 145 | 2019 |
| Training machine learning surrogate models from a high‐fidelity physics‐based model: Application for real‐time street‐scale flood prediction in an urban coastal community FT Zahura, JL Goodall, JM Sadler, Y Shen, MM Morsy, M Behl Water Resources Research 56 (10), e2019WR027038, 2020 | 118 | 2020 |
| Physics-guided recurrent graph model for predicting flow and temperature in river networks X Jia, J Zwart, J Sadler, A Appling, S Oliver, S Markstrom, J Willard, S Xu, ... Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021 | 92 | 2021 |
| Leveraging open source software and parallel computing for model predictive control of urban drainage systems using EPA-SWMM5 JM Sadler, JL Goodall, M Behl, MM Morsy, TB Culver, BD Bowes Environmental Modelling & Software 120, 104484, 2019 | 80 | 2019 |
| Exploring real-time control of stormwater systems for mitigating flood risk due to sea level rise JM Sadler, JL Goodall, M Behl, BD Bowes, MM Morsy Journal of Hydrology 583, 124571, 2020 | 69 | 2020 |
| Design of a metadata framework for environmental models with an example hydrologic application in HydroShare MM Morsy, JL Goodall, AM Castronova, P Dash, V Merwade, JM Sadler, ... Environmental Modelling & Software 93, 13-28, 2017 | 63 | 2017 |
| A cloud-based flood warning system for forecasting impacts to transportation infrastructure systems MM Morsy, JL Goodall, GL O'Neil, JM Sadler, D Voce, G Hassan, ... Environmental modelling & software 107, 231-244, 2018 | 59 | 2018 |
| Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality? C Varadharajan, AP Appling, B Arora, DS Christianson, VC Hendrix, ... Hydrological Processes 36 (4), e14565, 2022 | 49 | 2022 |
| Impact of sea-level rise on roadway flooding in the Hampton Roads region, Virginia JM Sadler, N Haselden, K Mellon, A Hackel, V Son, J Mayfield, A Blase, ... Journal of Infrastructure Systems 23 (4), 05017006, 2017 | 45 | 2017 |
| Multi‐task deep learning of daily streamflow and water temperature JM Sadler, AP Appling, JS Read, SK Oliver, X Jia, JA Zwart, V Kumar Water Resources Research 58 (4), e2021WR030138, 2022 | 40 | 2022 |
| Toward open and reproducible environmental modeling by integrating online data repositories, computational environments, and model Application Programming Interfaces YD Choi, JL Goodall, JM Sadler, AM Castronova, A Bennett, Z Li, ... Environmental Modelling & Software 135, 104888, 2021 | 39 | 2021 |
| A taxonomy for reproducible and replicable research in environmental modelling BT Essawy, JL Goodall, D Voce, MM Morsy, JM Sadler, YD Choi, ... Environmental Modelling & Software 134, 104753, 2020 | 39 | 2020 |
| Integrating scientific cyberinfrastructures to improve reproducibility in computational hydrology: Example for HydroShare and GeoTrust BT Essawy, JL Goodall, W Zell, D Voce, MM Morsy, J Sadler, Z Yuan, ... Environmental Modelling & Software 105, 217-229, 2018 | 38 | 2018 |
| Physics-guided machine learning from simulation data: An application in modeling lake and river systems X Jia, Y Xie, S Li, S Chen, J Zwart, J Sadler, A Appling, S Oliver, J Read 2021 IEEE International Conference on Data Mining (ICDM), 270-279, 2021 | 28 | 2021 |
| A recipe for standards-based data sharing using open source software and low-cost electronics JM Sadler, DP Ames, R Khattar Journal of Hydroinformatics 18 (2), 185-197, 2016 | 22 | 2016 |
| Physics-guided recurrent graph networks for predicting flow and temperature in river networks X Jia, J Zwart, J Sadler, A Appling, S Oliver, S Markstrom, J Willard, S Xu, ... arXiv preprint arXiv:2009.12575, 2020 | 20 | 2020 |
| Partial differential equation driven dynamic graph networks for predicting stream water temperature T Bao, X Jia, J Zwart, J Sadler, A Appling, S Oliver, TT Johnson 2021 IEEE International Conference on Data Mining (ICDM), 11-20, 2021 | 19 | 2021 |
| Heterogeneous stream-reservoir graph networks with data assimilation S Chen, A Appling, S Oliver, H Corson-Dosch, J Read, J Sadler, J Zwart, ... 2021 IEEE International Conference on Data Mining (ICDM), 1024-1029, 2021 | 19 | 2021 |
| Stream temperature prediction in a shifting environment: Explaining the influence of deep learning architecture SN Topp, J Barclay, J Diaz, AY Sun, X Jia, D Lu, JM Sadler, AP Appling Water Resources Research 59 (4), e2022WR033880, 2023 | 18 | 2023 |
Jonathan L. GoodallUniversity of VirginiaVerifisert e-postadresse på virginia.edu