The seminar present a study that integrates different scientific information into an agent-based model to serve for anticipatory policy making in the city of Huancayo, located in central Andes of Peru. Assuming current demographical, hydrological and political trends, the potential for undesired levels of emigration and social unrest are explored. To carry out this work, every available information on water supply and demand has been collected and organized using official data sources, producing a baseline dated in 2011; and the basic demographics of the population has been implemented using the last official censuses (2007, 1993, 1981). Based on these data, many computations have been made to find, calibrate and represent the trends in population growth and water balance. For the basic mechanisms at the individual level, a fieldwork guided both by theoretical considerations and ethnographic findings has been done. A key assumption on the processing of information, not identified from the fieldwork, has been introduced via Bayesian belief updating mechanism.
To sustain the emergence of migration, the information collected from the empirical work has allowed the identification of hypothetical mechanisms that the individuals will use when facing extreme water scarcity, and how this situation will force them to migrate. In the same way, the emergence of conflict is sustained by the identified reactive mechanism that will lead people to become frustrated or relatively deprived. For the rural case, peri urbanization and immigration are assumed to play a critical role for the potential of conflict; for the urban case, it is population growth and negative water balance the key elements assumed to condition migration and conflict. The model has been calibrated to represent the urban and rural areas of Huancayo, the most important province of the Central Andes in Peru, which strongly depends on the Shullcas river for water supply, a source that will soon be negatively affected by the total retreat of the local glacier Huaytapallana.