Mark Bartlett

mark.bartlett@duke.edu
+1 (919) 660-5463
2421 CIEMAS

Research Interests

My research investigates the interconnections between rainfall-runoff processes and ecosystem productivity. For rainfall-runoff processes, my research studies how ecohydrological controls, soil moisture dynamics, and stochastic rainfall influence the rainfall-runoff response both in space and time. I'm interested in using the rainfall-runoff response to further the study of the productivity of ecosystems as determined by the response of the soil-plant-atmosphere-continuum to various environmental factors such as nutrient availability, climate change (e.g., temperature, precipitation), and water scarcity. Of particular interest is the optimal leveraging of cultivations with different photosynthetic systems (C3, C4, and CAM) so as to maximize productivity while reducing costs related to land degradation, water consumption, and fertilizer application. An improved theoretical understanding of the plant system and the rainfall-runoff process could lead to more informed planning decisions for the sustainability of managed ecosystems under changing climate and land use conditions. 

Education

Ph.D. in Civil & Environmental Engineering, September 2016, Duke University, Durham, NC

M.S. in Civil & Environmental Engineering, May 2009, University of Southern Cailfornia, Los Angeles, CA

B.S. in Civil Engineering, June 2005, Brown University, Providence, RI

Publications
  1. Bartlett, M. S., Parolari, A.J.,  McDonnell, J. J., and A. Porporato (2016) Framework for event-based semidistributed modeling that unifes the SCS-CN method, VIC, PDM, and TOPMODEL. Water Resources Research.
  2. Bartlett, M. S., Parolari, A.J.,  McDonnell, J. J., and A. Porporato (2016) Beyond the SCS-CN method: A theoretical framework for spatially lumped rainfall-runoff response. Water Resources Research. 52(6), 4608-4627.
  3. Bartlett, M. S., Daly, E.,  McDonnell, J. J., Parolari, A.J., and A. Porporato (2015) Stochastic rainfall-runoff model with explicit soil moisture dynamics. Proceedings of the Royal Society A, v. 471, no. 2183.
  4. Hartzell S., Bartlett, M. S., Virgin, L.,  and A. Porporato (2014) Nonlinear dynamics of the CAM circadian rhythm in response to environmental forcing. Journal of theoretical biology. 363, 83-94.
  5. Bartlett, M. S., G. Vico, and A. Porporato (2014) Coupled carbon and water fluxes in CAM photosynthesis: modeling quantification of water use efficiency and productivity. Plant and Soil 383(1-2), 111-138.
  6. Bartlett, M. S., G. Vico, and A. Porporato (2013) Elliptically Symmetric Distributions of Elevation Gradients and the Distribution of Topographic Aspect. Mathematical Geosciences 45(7), 819-835.
 
Conference Presentations
  1. Bartlett, M. S. and Porporato, A. (2016). Mean field approach to watershed hydrology. Abstract 17497-5, poster presentation at European Geophysical Union General Assembly. Vienna, Austria, April 18-22.
  2. Bartlett, M. S., Parolari, A.J.,  McDonnell, J. J., and Porporato, A. (2015). Beyond the SCS curve number: A new stochastic spatial runoff approach. Abstract H13C-1551, poster presentation at American Geophysical Union Fall Meeting. San Franciscon, CA, Dec. 14-18.
  3. Bartlett, M. S., Parolari, A.J.,  McDonnell, J. J., and Porporato, A. (2015). Theory of event based rainfall-runoff models: Spatially variable runoff generate by threshold or progressive partitioning over stochastic source areas, presentation at Gordon Research Conference for Catchment Science: Interactions of Hydrology, Biology & Geochemistry, Andover, NH, June 14-19.

  4. Bartlett, M. S., Parolari, A.J.,  McDonnell, J. J., Daly, E., and Porporato, A. (2015) Runoff production in stochastic soil moisture models: saturation-excess threshold and soil moisture-dependent progressive partitioning, presentation at Gordon Research Conference for Catchment Science: Interactions of Hydrology, Biology & Geochemistry, Andover, NH, June 14-19.
  5. Bartlett, M. S., Porporato, A. (2014) A statistically consistent determination of the antecedent soil moisture condition (retention parameter) of the SCS method, presentation at Soil & Water Assessment Tool (SWAT) Conference, Pernambuco, Brazil, July 28 - Aug. 1.
  6. Pelak, N.F., Bartlett, M.S., Albertson, J., Barbano, P., and Porporato, A. M. (2014) Theoretical considerations on stochastic soil moisture dynamics and the Optimal design of Soil Moisture sensor networks. poster presentation at CUAHSI 2014 Biennial Colloquium, Shepherdstown, WV, July 28-30.
  7. Bartlett, M.S., McDonnell, J. J., and Porporato, A. (2013). Deciphering and modeling interconnections in ecohydrology: The role of scale, thresholds and stochastic storage processes. Abstract H12D-01, oral presentation at American Geophysical Union Fall Meeting. San Francisco, CA, Dec. 9-13.
  8. Moura, A. E., Montenegro, S. M., Silva, B. B., Bartlett, M. S., Porporato, A. M., Antonino, A. C. (2013). Impact of rainfall interception on hydrologic partitioning and soil erosion in natural and managed seasonally dry ecosystems. Abstract H21F-1114, poster presentation at American Geophysical Union Fall Meeting. San Francisco, CA, Dec. 9-13.  
  9. Bartlett, M. S., Vico, G., and Porporato, A. (2012). Modeling analysis of the benefits of Crassulacean acid metabolism (CAM) for sustainable agriculture in arid regions, American Geophysical Union Fall Meeting. Abstract H53H-1663, poster presentation at American Geophysical Union 2012 Fall Meeting, San Francisco, CA. 3-7 Dec.
  10. Bartlett, M. S., Vico, G., and Porporato, A. (2011). Statistical Characteristics of topographic surfaces and dynamic smoothing of landscapes. American Geophysical Union Fall Meeting. Abstract EP43A-0661, poster presentation at American Geophysical Union 2011 Fall Meeting, San Francisco, CA. 13-17 Dec.
Certifications

Licensed Professional Engineer: States of New York (088651), California (C73536), and Massachusetts (48873)