| Bayesian methods in hydrologic modeling: A study of recent advancements in Markov chain Monte Carlo techniques TJ Smith, LA Marshall Water Resources Research 44 (12), 2008 | 140 | 2008 |
| Modeling residual hydrologic errors with Bayesian inference T Smith, L Marshall, A Sharma Journal of Hydrology 528, 29-37, 2015 | 115 | 2015 |
| Development of a formal likelihood function for improved Bayesian inference of ephemeral catchments T Smith, A Sharma, L Marshall, R Mehrotra, S Sisson Water Resources Research 46 (12), 2010 | 112 | 2010 |
| Exploring uncertainty and model predictive performance concepts via a modular snowmelt-runoff modeling framework TJ Smith, LA Marshall Environmental Modelling & Software 25 (6), 691-701, 2010 | 42 | 2010 |
| Using field data to inform and evaluate a new model of catchment hydrologic connectivity T Smith, L Marshall, B McGlynn, K Jencso Water Resources Research 49 (10), 6834-6846, 2013 | 40 | 2013 |
| Tools for investigating the prior distribution in Bayesian hydrology Y Tang, L Marshall, A Sharma, T Smith Journal of Hydrology 538, 551-562, 2016 | 27 | 2016 |
| Predicting hydrologic response through a hierarchical catchment knowledgebase: A Bayes empirical Bayes approach T Smith, L Marshall, A Sharma Water Resources Research 50 (2), 1189-1204, 2014 | 27 | 2014 |
| Understanding the role of hydrologic model structures on evapotranspiration-driven sensitivity DI Jayathilake, T Smith Hydrological Sciences Journal 65 (9), 1474-1489, 2020 | 14 | 2020 |
| Assessing the impact of PET estimation methods on hydrologic model performance DI Jayathilake, T Smith Hydrology Research 52 (2), 373-388, 2021 | 13 | 2021 |
| Diagnostic calibration and cross‐catchment transferability of a simple process‐consistent hydrologic model T Smith, K Hayes, L Marshall, B McGlynn, K Jencso Hydrological Processes 30 (26), 5027-5038, 2016 | 13 | 2016 |
| Flood mapping uncertainty from a restoration perspective: A practical case study CG Rampinelli, I Knack, T Smith Water 12 (7), 1948, 2020 | 12 | 2020 |
| Typecasting catchments: Classification, directionality, and the pursuit of universality T Smith, L Marshall, B McGlynn Advances in water resources 112, 245-253, 2018 | 9 | 2018 |
| Calibrating hydrologic models in flow‐corrected time T Smith, L Marshall, B McGlynn Water Resources Research 50 (1), 748-753, 2014 | 7 | 2014 |
| Predicting the temporal transferability of model parameters through a hydrological signature analysis DI Jayathilake, T Smith Frontiers of earth science 14, 110-123, 2020 | 6 | 2020 |
| Identifying the influence of systematic errors in potential evapotranspiration on rainfall–runoff models DI Jayathilake, T Smith Journal of Hydrologic Engineering 27 (2), 04021047, 2022 | 2 | 2022 |
| Conceptual hydrologic modeling: insights into bayesian analysis, model development, and predictions in ungauged basins TJ Smith Montana State University, 2012 | 2 | 2012 |
| A conceptual precipitation-runoff modeling suite: Model selection, calibration and predictive uncertainty assessment TJ Smith Bozeman, MT: Montana State University. 177 p. Thesis., 2008 | 1 | 2008 |
| How to select an objective function using information theory TO Hodson, TM Over, TJ Smith, LM Marshall arXiv preprint arXiv:2212.06566, 2022 | | 2022 |
| Assessment of groundwater lowering for urban infrastructure works, a case study in Sumbe, Angola/Africa. CG Rampinelli, TJ Smith, AEM Lima, C Silva de AGUIAR, C Diniz, ... Journal of Water Resources/Recursos Hídricos 42 (2), 2021 | | 2021 |
| Model parameter sensitivity across time scales C Rampinelli, T Smith AGU Fall Meeting Abstracts 2021, H52C-02, 2021 | | 2021 |
Lucy MarshallMacquarie UniversityBestätigte E-Mail-Adresse bei mq.edu.au
