Integrating socio-economic and biophysical data to support water allocations within river basins: an example from the Inkomati Water Management Area in South Africa

Abstract

Sustainable natural resource management requires inputs from both the natural and the social sciences. Since social and natural systems are inter-related and inter-dependent, it is essential that these data can be integrated within a given analysis, which requires that they are temporally and spatially compatible. However, existing environmental and socio-economic monitoring networks tend to observe, collect and report socio-economic and biophysical data separately; with the result that much of these data are spatially and temporally incompatible and therefore add to the complexity of objective and consistent trade-off analyses. This paper presents an approach for overcoming spatial incompatibilities between socio-economic and biophysical data; based on a meta-modelling approach using Geographical Information Systems, the geo-spatial analysis platform, and an application of a water-use simulation model. The method is developed and applied to the irrigation agriculture sector in the Inkomati River Basin, South Africa. Agricultural census data, which is measured on a magisterial district level, is integrated with geo-referenced land-cover data, which is independent of political boundaries. Initial results indicate that the method could enable natural-resource managers and policy makers to develop an understanding of the spatial relationships between socio-economic and biophysical variables over time, and assist them in the allocation of land and water resources across heterogeneous landscapes.