Water scarcity, land use conversion and cultural and ecosystem changes threaten the way of life for traditional irrigation communities of the semi-arid southwestern United States. Traditions are strong, yet potential upheaval is great in these communities that rely on acequia irrigation systems. Acequias are ancient ditch systems brought from the Iberian Peninsula to the New World over 400 years ago; they are simultaneously gravity flow water delivery systems and shared water governance institutions. Acequias have survived periods of drought and external shocks from changing economics, demographics, and resource uses. Now, climate change and urbanization threaten water availability, ecosystem functions, and the acequia communities themselves. Do past adaptive practices hold the key to future sustainability, or are new strategies required? To explore this issue we translated disciplinary understanding into a uniform format of causal loop diagrams to conceptualize the subsystems of the entire acequia-based human-natural system. Four subsystems are identified in this study: hydrology, ecosystem, land use/economics, and sociocultural. Important linkages between subsystems were revealed as well as variables indicating community cohesion (e.g., total irrigated land, intensity of upland grazing, mutualism). Ongoing work will test the conceptualizations with field data and modeling exercises to capture tipping points for non-sustainability and thresholds for sustainable water use and community longevity.

We tested the Moment Distance Index (MDI) in combination with texture features for the summer vegetation mapping in the eastern Pamir Mountains, Tajikistan using the 2014 Landsat OLI (Operational Land Imager) image. The five major classes identified were sparse vegetation, medium-dense vegetation, dense vegetation, barren land, and water bodies. By utilizing object features in a random forest (RF) classifier, the overall classification accuracy of the land cover maps were 92% using a set of variables including texture features and MDI, and 84% using a set of variables including texture but without MDI. A decrease of the Kappa statistics, from 0.89 to 0.79, was observed when MDI was removed from the set of predictor variables. McNemar’s test showed that the increase in the classification accuracy due to the addition of MDI was statistically significant (p < 0.05). The proposed method provides an effective way of discriminating sparse vegetation from barren land in an arid environment, such as the Pamir Mountains.

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.