Kenneth H. Reckhow
Affiliations: | Environment | Duke University, Durham, NC |
Area:
Water ResourcesWebsite:
https://nicholas.duke.edu/people/faculty/reckhowGoogle:
"Kenneth Howland Reckhow" OR "Kenneth H. Reckhow"Bio:
https://www.researchgate.net/profile/Kenneth-Reckhow
https://www.proquest.com/openview/cf57ae07cebc08680ba1bbb10bb67135/1
Parents
Sign in to add mentor| Harold Allen Thomas | grad student | 1977 | Harvard (PoliSci Tree) | |
| (Phosphorus Models for Lake Management) | ||||
Children
Sign in to add trainee| Laura J. Steinberg | grad student | 1993 | Duke (E-Tree) |
| Mark E. Borsuk | grad student | 2001 | Duke |
| Melissa A. Kenney | grad student | 2007 | Duke |
| Andrew D. Gronewold | grad student | 2008 | Duke |
| Roxolana O. Kashuba | grad student | 2010 | Duke |
| Ibrahim Alameddine | grad student | 2011 | Duke |
| Boknam Lee | grad student | 2012 | Duke |
BETA: Related publications
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Publications
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| Lee B, Kullman SW, Yost EE, et al. (2018) Corrigendum to "Predicting characteristics of rainfall driven estrogen runoff and transport from swine AFO spray fields" [Sci. Total Environ. 532 (2015) 571-580]. The Science of the Total Environment. 628: 1460 |
| Lee B, Kullman SW, Yost EE, et al. (2018) An object-oriented Bayesian network approach for establishing swine manure-borne natural estrogenic compounds budget. The Science of the Total Environment. 639: 815-825 |
| Mishra A, Ahmadisharaf E, Benham BL, et al. (2018) Generalized Likelihood Uncertainty Estimation and Markov Chain Monte Carlo Simulation to Prioritize TMDL Pollutant Allocations Journal of Hydrologic Engineering. 23: 05018025 |
| McLaughlin DB, Reckhow KH. (2017) A Bayesian network assessment of macroinvertebrate responses to nutrients and other factors in streams of the Eastern Corn Belt Plains, Ohio, USA Ecological Modelling. 345: 21-29 |
| Lee B, Kullman SW, Yost EE, et al. (2015) Predicting characteristics of rainfall driven estrogen runoff and transport from swine AFO spray fields. The Science of the Total Environment. 532: 571-580 |
| Nojavan A F, Qian SS, Paerl HW, et al. (2014) A study of anthropogenic and climatic disturbance of the New River Estuary using a Bayesian belief network. Marine Pollution Bulletin. 83: 107-15 |
| Lee B, Kullman SW, Yost E, et al. (2014) A Bayesian network model for assessing natural estrogen fate and transport in a swine waste lagoon. Integrated Environmental Assessment and Management. 10: 511-21 |
| Money ES, Barton LE, Dawson J, et al. (2014) Validation and sensitivity of the FINE Bayesian network for forecasting aquatic exposure to nano-silver. The Science of the Total Environment. 473: 685-91 |
| Van Houtven G, Mansfield C, Phaneuf DJ, et al. (2014) Combining expert elicitation and stated preference methods to value ecosystem services from improved lake water quality Ecological Economics. 99: 40-52 |
| Alameddine I, Karmakar S, Qian SS, et al. (2013) Optimizing an estuarine water quality monitoring program through an entropy-based hierarchical spatiotemporal Bayesian framework Water Resources Research. 49: 6933-6945 |