Thanks to Professor Murugesu Sivapalan, I delivered an invited talk at the Hydrosystems Laboratory, University of Illinois at Urbana-Champaign (UIUC) as part of Ven Te Chow Hydrosystems Lab Seminar Series.
Below is the abstract of my talk:
David J. Yu Assistant Professor,
Department of Civil Engineering & Political Science, Purdue University
A growing number of hydrologists are now incorporating individual human and group behavior as a key component in their studies to understand interdisciplinary questions such as how water resources and human society co-evolve in the long-run. Much of the recent effort in this field has focused on developing and analyzing conceptual models consisting of coupled nonlinear differential equations that link hydrology and social dynamics. There is, however, another approach that deserves more attention: laboratory behavioral experiments that incorporate simple hydrological dynamics and human-subject participation. In such behavioral experiments, human-subjects face a game-theoretic interface that captures the essence of a real-world situation. Experimental social scientists observe the choices individuals make when they play such game theoretic exercises and analyze the collected experimental data to test specific hypotheses about human behavior. As such, this method provides a way to observe and test hypotheses on how individuals and groups of individuals react or the decisions they make in response to certain simulated hydrological events. In this presentation, I will present one such example of an experimental study for socio-hydrology. In this experiment, which is designed to study how humans solve collective action problems under disturbances, participants are faced with a set of decision problems on collective management of shared irrigation infrastructure under hydrological variability. I compare the learning processes of human subject groups that participated in the experiment in order to search for empirical clues on what kind of social learning helps resilience and under what conditions.