ASSESSING THE IMPLICATIONS FOR URBAN DRAINAGE INFRASTRUCTURE OF FUTURE SCENARIOS OF URBAN GROWTH WITH CELLULAR AUTOMATA

Urbanization, climate change and population growth represent an enormous challenge for urban water managers. In this respect, computer models coupled with spatial mapping techniques have proved to be invaluable. The present paper demonstrates the use of a cellular automata model (Dinamica Ego) for modeling land use change processes on a case study of Birmingham (UK). The analysis was carried out using the Corine dataset for the years 1990 and 2000 and the fuzzy similarity test was used to assess the spatial correlation and as the objective function in the calibration process. In order to minimize computational demands the optimization loop was simulated with the NSGA II algorithm using the parallel computing approach. Two approaches were evaluated for the calibration of the land use change model. The results obtained show that the model based on optimization of parameters that deal with the process of expansion/contraction is capable of producing promising results. The highest gain in correlation is achieved initially by adjusting the weight of evidence matrix that is at the heart of the land use transitions. The overall results demonstrate the possibility of using an integrated modeling approach as a planning tool to evaluate future scenarios of urban development. Different scenarios were assessed for the year 2040 and the implications in terms of urban drainage infrastructure expansion are analyzed.