- Nelson, K., Burchfield, E. (2017). Effects of the Structure of Water Rights on Agricultural Production During Drought: A Spatio-temporal Analysis of California’s Central Valley. Water Resources Research, 53.
- Nay, J., Burchfield, E., Gilligan, J. (2016). A machine learning approach to forecasting remotely sensed vegetation health. In press. International Journal of Remote Sensing. Check out the project website here.
- Burchfield, E., Gilligan, J. (2016). Agricultural adaptation to drought in the Sri Lankan dry zone. Applied Geography, 77, 92-100.
- Burchfield, E., Gilligan, J. (2016). Dynamics of individual and collective agricultural adaptation to water scarcity. Winter Simulation Conference 2016 Proceedings.
- Burchfield, E., Nay, J., Gilligan, J. (2016). Application of machine learning to prediction of vegetation health. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. XLI-B2, 465-469, doi:10.5194/isprs-archives-XLI-B2-465-2016.
- Gunda, T., Benneyworth, L., Burchfield, E. (2015). Exploring water indices and associated parameters: A case study approach, Water Policy, 17(1), 98 – 111.
Papers Under Review
- Burchfield, E., Williams, N., Carrico, A. (2017). Assessing the expansion of a traditional drought adaptation strategy among rice farmers in Sri Lanka’s dry zone. Under review.
- Tozier de la Poterie, A., Burchfield, E., Carrico, A.R. The implications of group norms for adaptation in collectively-managed agricultural systems: evidence from Sri Lankan Paddy farmers. Under second review at Ecology and Society.
- Burchfield, E., Tozier de la Poterie, A. (2017). Determinants of crop diversification in rice-dominated agricultural systems. Under review.
Works in Progress
- Data-driven drought effect estimation, SESYNC Graduate Pursuit co-PI (more information here).
- Land-use variable drought response (with Katherine Nelson).
- Agent-based modeling of multiscalar determinants of agricultural adaptation (with Jonathan Gilligan).