Conceptualisation of the consequences of land use decisions on water resources in the central region of South Africa: an agent based modelling perspective

14 January 2011

Over the past few decades, numerous researchers have improved measurements of land use change through representation of much more complex processes of land use and its impact on water resources. Understanding the causes of land use change has moved from a simplistic representation of a few driving forces to a much more detailed understanding that involves situation-specific interactions among a large number of factors at different spatial and temporal scales using agent-based models. The agentbased perspective is centred on the general nature and rules of land use decision making by individuals and represents the motivations behind decisions and the external factors that influence decisions about land use. In this paper, an attempt is made to conceptualise the social and biophysical interactions as the driving forces that lead to decisions of land use, and its potential impact on water resource, including factors such as interventions and technologies that influence the decision of land use change in rural agricultural areas. The development of the conceptual model was done through a series of meetings and workshops and by visualising the relationships between the different factors, such as biophysical and socio-economic factors, using a brain mapping technique. The resulting conceptual model illustrates the main domains of the environment, the socioeconomic factors, and captures all the factors and their interaction that lead to decision in land use change. The socio-economic factors and their interaction will be captured by the ABM module while the biophysical factors that have direct impact on runoff and stream flow could be handled by the hydrologic module which will then be integrated into the ABM model. This, however, is a primary effort in the development of an ABM within the Modder River Basin system and needs continues refinement for optimum functionality and simulation of the real world.