Abstract
Interdependencies of ecologic, hydrologic, and social systems challenge traditional approaches to natural resource management in semi-arid regions. As a complex social-ecological system, water demands in the Sonoran Desert from agricultural and urban users often conflicts with water needs for its ecologically-significant riparian corridors. To explore this system, we developed an agent-based model to simulate complex feedbacks between human decisions and environmental conditions in the Rio Sonora Watershed. Cognitive mapping in conjunction with stakeholder participation produced a Bayesian model of conditional probabilities of local human decision-making processes resulting to changes in water demand. Probabilities created in the Bayesian model were incorporated into the agent-based model, so that each agent had a unique probability to make a positive decision based on its perceived environment at each point in time and space. By using a Bayesian approach, uncertainty in the human decision-making process could be incorporated. The spatially-explicit agent-based model simulated changes in depth-to-groundwater by well pumping based on an agent’s water demand. Changes in depth-to-groundwater feedback to influence agent behavior, as well as determine unique vegetation classes within the riparian corridor. Each vegetation class then provides varying stakeholder-defined quality values of ecosystem services. Using this modeling approach allowed us to examine effects on both the ecological and social system of semi-arid riparian corridors under various scenarios. The insight provided by the model contributes to understanding how specific interventions may alter the complex social-ecological system in the future.
Highlights
As complex social-ecological systems, water demands in semi-arid deserts from agricultural and urban users often conflicts with water needs for its ecologically significant riparian corridors
The purpose of this study was to assess the effects of rancher decision-making on groundwater pumping, depth-to-groundwater, riparian vegetation and ecosystem services along a 21 km stretch of the Rio San Miguel using a hybrid modeling approach
Ecological At the end of the simulation, the compositions of riparian vegetation classes were significantly different between rainfall scenarios (Table 2)
Summary
As complex social-ecological systems, water demands in semi-arid deserts from agricultural and urban users often conflicts with water needs for its ecologically significant riparian corridors. Agent-based modeling provides an excellent conduit in which to study coupled social-ecological systems since they are capable of addressing issues that make traditional approaches to studying social-ecological systems difficult, such as spatial and temporal complexity, non-linearity, and uncertainty (Schlüter et al, 2012). This is especially true for common pool resources, such as groundwater, since dynamic change is the result of interactions between social and physical systems
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