| Hydrologic connectivity between landscapes and streams: Transferring reach‐and plot‐scale understanding to the catchment scale KG Jencso, BL McGlynn, MN Gooseff, SM Wondzell, KE Bencala, ... Water Resources Research 45 (4), 2009 | 558 | 2009 |
| A comparative study of Markov chain Monte Carlo methods for conceptual rainfall‐runoff modeling L Marshall, D Nott, A Sharma Water Resources Research 40 (2), 2004 | 279 | 2004 |
| Investigating controls on the thermal sensitivity of Pennsylvania streams C Kelleher, T Wagener, M Gooseff, B McGlynn, K McGuire, L Marshall Hydrological Processes 26 (5), 771-785, 2012 | 180 | 2012 |
| 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 | 130 | 2008 |
| Object-oriented crop classification using multitemporal ETM+ SLC-off imagery and random forest JA Long, RL Lawrence, MC Greenwood, L Marshall, PR Miller GIScience & Remote Sensing 50 (4), 418-436, 2013 | 118 | 2013 |
| 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 | 108 | 2010 |
| Towards dynamic catchment modelling: a Bayesian hierarchical mixtures of experts framework L Marshall, D Nott, A Sharma Hydrological Processes: An International Journal 21 (7), 847-861, 2007 | 107 | 2007 |
| Hydrological model selection: A Bayesian alternative L Marshall, D Nott, A Sharma Water resources research 41 (10), 2005 | 102 | 2005 |
| Modeling residual hydrologic errors with Bayesian inference T Smith, L Marshall, A Sharma Journal of Hydrology 528, 29-37, 2015 | 97 | 2015 |
| Landscape structure and climate influences on hydrologic response F Nippgen, BL McGlynn, LA Marshall, RE Emanuel Water Resources Research 47 (12), 2011 | 96 | 2011 |
| Hydrologic modeling in dynamic catchments: A data assimilation approach S Pathiraja, L Marshall, A Sharma, H Moradkhani Water Resources Research 52 (5), 3350-3372, 2016 | 86 | 2016 |
| Estimating thermal regimes of bull trout and assessing the potential effects of climate warming on critical habitats LA Jones, CC Muhlfeld, LA Marshall, BL McGlynn, JL Kershner River Research and Applications 30 (2), 204-216, 2014 | 82 | 2014 |
| Modeling the catchment via mixtures: Issues of model specification and validation L Marshall, A Sharma, D Nott Water resources research 42 (11), 2006 | 70 | 2006 |
| Bayesian calibration and uncertainty analysis of hydrological models: A comparison of adaptive Metropolis and sequential Monte Carlo samplers E Jeremiah, S Sisson, L Marshall, R Mehrotra, A Sharma Water Resources Research 47 (7), 2011 | 68 | 2011 |
| Generalized likelihood uncertainty estimation (GLUE) and approximate Bayesian computation: What's the connection? DJ Nott, L Marshall, J Brown Water Resources Research 48 (12), 2012 | 66 | 2012 |
| Detecting non-stationary hydrologic model parameters in a paired catchment system using data assimilation S Pathiraja, L Marshall, A Sharma, H Moradkhani Advances in water resources 94, 103-119, 2016 | 59 | 2016 |
| Calibrating and assessing uncertainty in coastal numerical models JA Simmons, MD Harley, LA Marshall, IL Turner, KD Splinter, RJ Cox Coastal Engineering 125, 28-41, 2017 | 55 | 2017 |
| Approximate Bayesian computation and Bayes’ linear analysis: toward high-dimensional ABC DJ Nott, Y Fan, L Marshall, SA Sisson Journal of Computational and Graphical Statistics 23 (1), 65-86, 2014 | 54 | 2014 |
| Data‐driven model uncertainty estimation in hydrologic data assimilation S Pathiraja, H Moradkhani, L Marshall, A Sharma, G Geenens Water resources research 54 (2), 1252-1280, 2018 | 50 | 2018 |
| It takes a community to raise a hydrologist: the Modular Curriculum for Hydrologic Advancement (MOCHA) T Wagener, C Kelleher, M Weiler, B McGlynn, M Gooseff, L Marshall, ... Hydrology and Earth System Sciences 16 (9), 3405-3418, 2012 | 50 | 2012 |
Brian McGlynnDuke UniversityBestätigte E-Mail-Adresse bei duke.edu
