Modeling Acequia Irrigation Systems Using System Dynamics: Model Development, Evaluation, and Sensitivity Analyses to Investigate Effects of Socio-Economic and Biophysical Feedbacks

摘要

Agriculture-based irrigation communities of northern New Mexico have survived for centuries despite the arid environment in which they reside. These irrigation communities are threatened by regional population growth, urbanization, a changing demographic profile, economic development, climate change, and other factors. Within this context, we investigated the extent to which community resource management practices centering on shared resources (e.g., water for agricultural in the floodplains and grazing resources in the uplands) and mutualism (i.e., shared responsibility of local residents to maintaining traditional irrigation policies and upholding cultural and spiritual observances) embedded within the community structure influence acequia function. We used a system dynamics modeling approach as an interdisciplinary platform to integrate these systems, specifically the relationship between community structure and resource management. In this paper we describe the background and context of acequia communities in northern New Mexico and the challenges they face. We formulate a Dynamic Hypothesis capturing the endogenous feedbacks driving acequia community vitality. Development of the model centered on major stock-and-flow components, including linkages for hydrology, ecology, community, and economics. Calibration metrics were used for model evaluation, including statistical correlation of observed and predicted values and Theil inequality statistics. Results indicated that the model reproduced trends exhibited by the observed system. Sensitivity analyses of socio-cultural processes identified absentee decisions, cumulative income effect on time in agriculture, and land use preference due to time allocation, community demographic effect, effect of employment on participation, and farm size effect as key determinants of system behavior and response. Sensitivity analyses of biophysical parameters revealed that several key parameters (e.g., acres per animal unit or percentage of normal acequia ditch seepage) which created less variable system responses but which utilized similar pathways to that of the socio-cultural processes (e.g., socio-cultural or physical parameter change → agricultural profit → time in spent in agriculture → effect on socio-cultural or physical processes). These processes also linked through acequia mutualism to create the greatest variability in system outputs compared to the remainder of tests. Results also point to the important role of community mutualism in sustaining linkages between natural and human systems that increase resilience to stressors. Future work will explore scenario development and testing, integration with upland and downstream models, and comparative analyses between acequia communities with distinct social and landscape characteristics.