Publications and Presentations



Burchfield, E. K. & Gilligan, J. (2016). Agricultural adaptation to drought in the Sri Lankan dry zone. Applied Geography, 77, 92-100.

Burchfield, E. K. & Gilligan, J. M.  (2016). Dynamics of individual and collective adaptation to water scarcity.  In Proceedings of the 2016 Winter Simulation Conference (pp. 1678-1689). IEEE Press.

Burchfield E, Nay, J.J., & Gilligan, J. (2016). Application of Machine Learning to the Prediction of Vegetation HealthThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B2: 465-469, doi:10.5194/isprs-archives-XLI-B2-465-2016.

Davis, K., Gephart, J. & Gunda, T. (2015).Future environmental impacts of Sri Lanka’s policy on self-sufficiency in rice. AMBIO, DOI: 10.1007/s13280-015-0720-2.

Gunda, T., Bazuin, J., Nay, J. J. & Yeung, K. (2017). Impact of Seasonal Forecast Use on Agricultural Income in a System with Varying Crop Costs and Returns: An Empirically-Grounded Simulation. Environmental Research Letters. DOI: 10.1088/1748-9326/aa5ef7

Gunda, T., Benneyworth L., & Burchfield E. (2015). Exploring water indices and associated parameters: A case study approachWater Policy 17, 98-111. DOI:10.2166/wp.2014.022.

Gunda, T., Hornberger G.M., & Gilligan J.M. (2015) Spatiotemporal patterns of meteorological drought in Sri Lanka from 1880-2010International Journal of Climatology. In press.

Jacobi, J., Perrone, D., Lyons-Duncan, L., & Hornberger, G.M. (2013). A Tool for Calculating the Palmer Drought Indices. Water Resources Research 49, 1-4.

Lyons-Duncan, L., Perrone, D., Jacobi, J.H., & Hornberger, G.M. (2015).  Drought: Using High Resolution as Part of the Solution. Environ. Sci. Tech., In press.

Nay, J. J., & Gilligan, J. M. (2015, December). Data-driven dynamic decision models. In Proceedings of the 2015 Winter Simulation Conference (pp. 2752-2763). IEEE Press.

Perrone, D. & Hornberger, G.M. (2013). Water, Food, and Energy Security: Scrambling for Resources or Solutions?WIRES Water 1, 1-4.

Perrone, D. & Hornberger, G. (2016). Frontiers of the food–energy–water trilemma: Sri Lanka as a microcosm of tradeoffs. Environmental Research Letters, 11(1), 14005.

Stone, E. C., & Hornberger, G. M. (2016). Impacts of management alternatives on rice yield and nitrogen losses to the environment: A case study in rural Sri Lanka. Science of The Total Environment 542, 271-276.

Truelove, H. B., Carrico, A. R., & Thabrew, L. (2015). Agricultural Adaptation to Climate Change: A case study of Sri Lankan Farmers. Global Environmental Change 31, 85-97.

Williams, N.E. & Carrico A. (2017). Examining adaptations to water stress among farming households in Sri Lanka’s dry zone. AMBIO: A Journal of the Human Environment. DOI 10.1007/s13280-017-0904-z

Theses and Dissertations

Jacobi, John (2014). A Changing Climate in Sri Lanka: Shifts, Perceptions, and Potential Adaptive Actions. Vanderbilt University.

Abstract: Adaptation planners and water managers around the world are faced with the increasingly difficult challenge of allocating scarce water resources in a world of climate change and dynamic social pressures. Sri Lanka serves as a microcosm of these challenges and serves as the areas of study for this dissertation. To address the problem of how to distribute scare water resources, an interdisciplinary approach is needed. This dissertation examines the water landscape in Sri Lanka from both physical and social perspectives and integrates the two through the use of agent-based modeling. From the physical perspective, an easy-to-use drought monitoring tool is presented and shifts in spatial and temporal patterns of the Sri Lankan monsoons are examined. Analysis reveals that the timings of the monsoons have shifted over the past thirty years, with the spring monsoon starting later and the winter monsoon starting earlier. Next, Sri Lankan farmers’ perceptions of changes in the climate are compared against measured changes to reveal that perceptions of climate change do not always match the objective reality. Finally, agent-based modeling is used to evaluate the effect of a farmer’s decision model on the effectiveness of a seasonal forecasting program.

Perrone, Debra (2014). Characterizing Water, Food, and Energy Interrelationships. Vanderbilt University.

Abstract: Recent increases in competition for water, food, and energy are exposing the complex network threading these resources together. My dissertation explores how the interactions among these resources affect decisions about the delivery of adequate water, food, and energy to communities. I include technical elements that are ingredients in traditional engineering computations but also explore how societal norms and values enter into resource allocation decisions. My analyses show that for Tucson, AZ conveying water from long distances is 20 times more energy intensive than pumping groundwater and that coal-based electricity has eight times the water intensity of natural gas resources. Additional analyses illuminate tradeoffs made in using water for food (irrigation) versus using water for energy (electricity generation) and show that decisions are made partly on the basis of stakeholder preferences and perceptions and not just on the basis of a maximization of an overall benefit-cost ratio. I conclude with my views on approaches to mix, and properly balance, technological and non-technological water-food-energy considerations in sustainability planning.

Provenzano, Andrew (2015). Adapting to Water Scarcity: Effects of Irrigation Management and Psychological Factors on Crop Productivity. University of North Florida.

Abstract: In developing countries, farmers are dealing with climatic changes by adapting their agricultural practices. Little work has investigated the direct impact of structural variables (e.g., central vs. local management of irrigation water, location of village), psychological variables (e.g., risk perceptions, self-efficacy), and adaptation on crop yield.  We tested a psychology-based model that focused on risk perceptions and efficacy beliefs by longitudinally surveying 278 Sri Lankan rice farmers. We assessed risk perceptions and efficacy beliefs before the major paddy-growing season and measured whether farmers performed adaptations as well as their paddy yield/acre after the season. The model significantly predicted more than 25% of the variance in crop yield, with increased yields associated with centrally managed irrigation resources and with farmers low in perceived climate risk at the start of the growing season. Findings support the notion that while psychological factors are important, structural variables are the most important predictors of farm productivity in times of uncertain water supply.

Stone, E. C. (2015). Water and Nutrient Management in a Changing Climate: A Case Study from Rural Sri Lanka. Vanderbilt University.

Abstract: Efficient management of freshwater resources is critical as threats to water security increase due to changes in climate, population, and land use. The water and agricultural sectors of Asian countries have been identified as the most at risk for climate change impacts, and small-scale farmers are particularly vulnerable to changes in water availability and water quality. This research explored the tradeoffs between maximization of yield and minimization of environmental impact in rice production in Sri Lanka. The study used the DeNitrification-DeComposition (DNDC) model to examine how variations in climate, soil, and paddy management affect outputs of yield, greenhouse gas (GHG) emissions, and nitrogen (N) leaching in paddy systems in Sri Lanka from 1991 to 2010. Reducing fertilizer had little effect on yield, and N leaching and N2O emissions declined as a result. Reliable water inputs in irrigated systems increased yields over rain-fed schemes; alternate flooding techniques to mitigate water stress did not reduce yield. Alternate flooding increased N leaching as did rain-fed cultivation. A sensitivity analysis of soil parameters determined that high clay content reduced N leaching, low soil organic carbon increased yield, and the more basic the pH of the soil, the greater the reduction in GHG emissions. The results inform best practices for Sri Lankan farmers and decision makers on the supervision of water resources and agricultural inputs. This research demonstrates how cultivation in rice-growing regions in south Asia affects the environment and the nitrogen cycle on a global scale, in turn how informed management of these systems can adapt to a changing environment.

Nay, John J. (2017). A Machine Learning Approach to Modeling Dynamic Decision-Making in Strategic Interactions and Prediction Markets. Vanderbilt University.

Abstract: My overarching modeling goal for my dissertation is to maximize generalization – some function of data and knowledge – from one sample, with its observations drawn independently from the distribution D, to another sample drawn from D, while also obtaining interpretable insights from the models. The processes of collecting relevant data and generating features from the raw data impart substantive knowledge into predictive models (and the model representation and optimization algorithms applied to those features contain methodological knowledge). I combine this knowledge with the data to train predictive models to deliver generalizability, and then investigate the implications of those models with simulations systematically exploring parameter spaces. The exploration of parameter space provides insights about the relationships between key variables.

Burchfield, Emily (2017) Agricultural adaptation to drought. Vanderbilt University.

Abstract: This research integrates geospatial and social datasets to understand the adaptive strategies employed by individuals, communities, and institutions during periods of drought. I apply dimension reduction techniques to remotely sensed data to identify agricultural communities in which cultivation occurred during an extreme drought. Two dominant adaptive strategies emerged from this research: crop diversification and a complex land reallocation process known locally as bethma. I supplemented this qualitative research with Bayesian analysis of project survey data to identify the multi-scalar factors driving participation in these adaptive behaviors. Results suggest that farmers with more assets (agrowell, land, higher socio-economic status) are more likely to engage in adaptive behaviors. To better understand the role of farmers’ risk perception in influencing adaptive behaviors, I constructed an agent-based model to assess the extent to which farmer decision heuristics affect participation in crop diversification and bethma. Simulation results suggest that though environmental changes may produce sudden disruptions in agricultural outcomes, the variations in these outcomes are strongly influenced by the mental models farmers use to make agricultural decisions. I also collaborated with a data scientist to apply machine learning techniques to large remotely sensed datasets to create an open-source prediction software to forecast vegetation health. This is particularly important in tropical countries where cloud cover significantly reduces data availability. The latest version of the software is global in coverage and performs extremely well across agroecological contexts, time, and levels of data availability. The results of my research in Sri Lanka will increase the capacity of decision makers to monitor agricultural systems, identify and promote successful adaptive strategies, and increase agricultural adaptation to changing climate.

Conference Presentations

Bazuin, J.T. (2013). “Climate change and the political economy and political ecology of land in post-conflict areas.” Annual Meeting of the Peace and Justice Studies Association. Waterloo, Canada.

Bazuin, J.T. & Fraser, J.C. (2014). “Not food but debt: Drought vulnerability in Sri Lanka’s Dry Zone.” Annual Meeting of the Association of American Geographers. Tampa, FL.

Berry, S., Greene, A., and Truelove, H.B. (February 2014). “Lost in translation: The meaning of climate change to rural farmers in Sri Lanka.” Society for Personality and Social Psychology. Austin, TX.

Burchfield, E.K. (February 2013) “Resettlement and coloniality in the Mahaweli Ganga Watershed.” Annual Dimensions of Political Ecology Conference on Nature/Society, Lexington, KY.

Burchfield, E.K. (March 2013) “Water security and rural livelihood: Water management regimes and livelihood outcomes in the Dry Zone of Sri Lanka.” Community Research and Action Departmental Conference, Nashville, TN.

Burchfield, E. (June 2014) “Patterns of agricultural drought in Sri Lankan paddy fields.” Poster presented at Borlaug Summer Institute on Global Food Security, Purdue University.

Carrico, A.R. (January 2013). “Climate, Drought & Agricultural Adaptations: Vulnerabilities and Responses to Water Stress Among Paddy Farmers in Sri Lanka.” 2013 NSF Water Sustainability and Climate Annual Meeting, Washington DC.

Greene, A., Berry, S. and Truelove, H.B. (February 2014). “Benevolence trust as a predictor of perceptions of socially dependent agricultural systems.” Society for Personality and Social Psychology. Austin, TX.

Gunda, T. and G.M. Hornberger (November 2014). “Effects of Climate Change on Irrigation Demand from Rice Fields in the Dry Zone of Sri Lanka.” Talk presented at American Water Resources Association Annual Meeting, Tysons Corner, VA.

Gunda, T. and E.K. Burchfield (August 2014). “Patterns of meteorological and agricultural drought in Sri Lankan agricultural areas.” Poster presented at Gordon Research Seminar and Conference on Science & Technology Policy: Systems Approaches to Research and Practice, Waterville Valley Resort, NH.

Gunda, T. and G.M. Hornberger (December 2013). “Comparative Assessment of Irrigation Water Quality in Sri Lanka’s Tank-Cascade and Mahaweli Irrigation Schemes.” Poster presented at American Geophysical Union Fall Meeting, San Francisco, CA.

Hornberger, G.M. and Carrico, A.R. (December 2012). “Determining paths by which farmers can adapt effectively to scarce freshwater resources.” Invited talk at American Geophysical Union Annual Meeting, San Francisco, CA.

Hornberger G.M. and A. R. Carrico (June 2014). “Interdisciplinary Challenges in Studying Social-Ecological Systems: Partnerships across the Natural and Social Sciences.” Gordon Research Conference – Water, Holderness New Hampshire.

Jacobi, J., Carrico, A.R., Gilligan, J., and Hornberger, G. (December 2012). “Diffusion of a sustainable farming technique in Sri Lanka: An agent-based modeling approach.” Poster presented at American Geophysical Union Annual Meeting, San Francisco, CA.

Jacobi, J., J. Nay, and J. Gilligan (December 2013). “The Effect of Seasonal Forecasts on Farmer Behavior.” American Geophysical Union Fall Meeting. San Francisco, CA.

Perrone, D., J. Jacobi, and G. Hornberger (December 2013). Adaptation Planning in Sri Lanka under Shifting Rainfall Patterns. Poster presented at American Geophysical Union Fall Meeting. San Francisco, CA.

Provenzano, A.C. (April 2014) “I Love to Take Risks…Will that Make Me an Effective Farmer?” Annual Meeting of the Georgia Psychological Society, Brunswick, GA.

Provenzano, A.C. and Truelove, H.B. (April 2014) “Risk aversion and farming success: An investigation of climate change adaptation among Sri Lankan farmers.” Showcase of Osprey Advancements in Research and Scholarship Jacksonville, FL.

Truelove, H. B. (February 2014). “The social psychology of climate change adaptation: A study of Sri Lankan farmers”. Invited presentation at Society for Personality and Social Psychology Sustainability Psychology Pre-Conference. Austin, TX.

Truelove, H. B. (April 2014). “Crossing national and disciplinary borders: A multi-disciplinary investigation of climate change adaptation among Sri Lankan farmers.” Scholars Transforming Academic Research Conference. Jacksonville, FL.

Truelove, H.B., Carrico, A., Thabrew, L., Jacobi, J. and Hornberger, G. (August 2012). “Agricultural adaptation in Sri Lanka: Psychological and Environmental Influences.”  American Psychological Association Annual Meeting, Orlando, FL.


Nay, J., Gilligan, J. & Burchfield, E. (2016). Forecasting Vegetation Health [computer software].

Nay, J., Gilligan, J. (2016). Data-driven Dynamic Decision Modeling [computer software].

Other Presentations

Bazuin, J.T. (2014). “Agricultural Decision Making and Adaptation to Precipitation Trends in Sri Lanka: Project Update.” Seminar on Agricultural Adaptation to Water Scarcity hosted by the Ministry of Disaster Management, Colombo, Sri Lanka.

Bazuin, J.T. (2014). “Agricultural Decision Making and Adaptation to Precipitation Trends in Sri Lanka: Project Overview.” Presentations made to the University of Moratuwa, University of Peradeniya, and Rajarata University.

Carrico, A.R. (2014). “Correlates of the adoption of agricultural adaptations among smallholding farmers in Sri Lanka.” Keynote Address, Seminar on Agricultural Adaptation to Water Scarcity hosted by the Ministry of Disaster Management, Colombo, Sri Lanka.