170 The Future of Water in African Cities
Allocating a New Urban Area • The final stage calculated a potential new area needed to accommodate anticipated population growth at a defined density. • Input data sets: –– Urban density: Demographia measurements of urban densities in 2011 (Demographia, 2011) for all 31 cities. Lacking consistent data, these density levels were assumed to remain unchanged into 2025. –– Population growth: UN population estimates (UNDESA, 2011) for all cities but Blantyre were obtained for 2010 and 2025. Blantyre was too small, so Demographia data on Blantyre’s 2010 population was combined with Lilongwe’s annual growth rate to generate approximate population pressure into 2025. • Modeling steps: –– Calculate expected population change. –– Use density to calculate new urban area needed in number of cells. –– Starting with highest suitability, assign all cells as urban in each decreasing suitability level until reaching the suitability level where there are more cells available than required to meet demand. –– For this final suitability level, allocate remaining needed pixels randomly. Post-Modeling Adjustments to Displayed Urban Growth Potential • Cut out rivers. • Erase obvious places where effect of barrier was not captured. • In cases where area was allocated to large areas of low suitability, creating very dispersed random placements of pixels, this last stage of allocation was removed from the final display (see room for improvement). Post-Modeling Adjustments to Displayed Urban Growth Potential In general, the results of this modeling exercise should not be taken as assertions about where development will happen, but rather those areas most likely to be urbanized by 2025. The goal was to use some basic spatial characteristics of the context of each city to develop a more nuanced picture of where growth may happen than could be achieved just by assuming uniform expansion. Some specific limitations include: • Roads –– We did not model changes in transportation infrastructure.