2022 CSDMS meeting-043

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"2) Image Segmentation using Deep Learning and Human-In-the-Loop Machine Learning - Part I" is not in the list (1) Modeling Water Movement and Reservoir Operations with mosartwmpy, 3) Introduction to Landlab, 4) Xarray for Scalable Scientific Data Analysis, 5) Will not attend a clinic) of allowed values for the "CSDMS meeting select clinics2 2022" property. "3) Image Segmentation using Deep Learning and Human-In-the-Loop Machine Learning - Part II" is not in the list (1) Component Creation with Landlab, 2) Rapid hypothesis testing and analysis with the open-source delta model pyDeltaRCM, 4) Publishing Reproducible Computational Research with the Whole Tale, 5) Will not attend a clinic) of allowed values for the "CSDMS meeting select clinics3 2022" property.

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Comparing multiple methods of decision-making in an agent-based model of environmental migration

Kelsea Best, (she, her),Vanderbilt University Nashville Tennessee, United States. kelsea.b.best@vanderbilt.edu



Environmental migration is an example of such a complex coupled human and natural system with dynamics that operate across multiple spatial and temporal scales. Agent-based modeling (ABM) has demonstrated potential for studying such complex systems, especially where individual decision-making is an important component. In this work, we use an original ABM of environmental shocks, livelihood opportunities, and migration decisions to study dynamics of environmental migration in rural Bangladesh. As ABMs are sensitive to the decision-making methods used, we present results utilizing multiple plausible decision-making methods for households deciding whether or not to send an internal migrant. We present results using both a simple economic method based on utility maximization as well as a more behaviorally complex method based on the Theory of Planned Behavior. We hypothesized that a more behaviorally complex decision method which incorporates social networks and community norms would more successfully reproduce the patterns of migration. However, using a pattern-oriented approach to reproduce two key patterns of migration from the empirical literature, we demonstrate that an economic model can reproduce our patterns of interest with high levels of success. For both decision methods, the level of community inequality in distribution of land ownership, which impacts the number of agricultural jobs available within the community, is critically important for patterns of migration outcomes. In this way, our model suggests that community-level inequality is has significant implications of migration dynamics in this study area.