| Abstract |
Rapid urbanization has become and will continue to be an inevitable and inescapable phenomenon in the developing world. Unplanned expansion of cities and the impacts of climate change increase risks and pose challenges to sustainable development. Urban flooding is a hazard that is attributed to an increase in built-up area and extreme weather events. Despite this, little has been done to understand the impact of urbanization and climate change, particularly in the big cities of Africa. This research integrated GIS, remote sensing, and statistical analysis to study past and future urban development patterns, rainfall trends, and their impact on urban flooding risk in Addis Ababa, Ethiopia. Future urbanization scenarios were developed using an integrated artificial neural network-Markov model in the IDRISI Selva 17.0 software, while a soil conservation service-curve number model and a Mann-Kendell test were employed to study direct runoff and trends in precipitation. The methodology and workflow were designed to address limitations of conducting empirical study, especially for developing countries, caused by the lack of detailed data on past and present conditions like land-use maps, networks of meteorological stations, and soil-related datasets such as soil texture and moisture. The results indicate that rapid urbanization is the major cause of flooding in Addis Ababa, spiking from 80.1 km(2) in 1984 to 287.9 km(2) in 2020 and expected to increase to 367.1 km(2) in 2030 under a business-as-usual scenario. The fast urbanization has increased the number of flooding susceptible woredas (smallest administrative units) to a direct runoff depth of 25 mm from 40 in 1984 to 81 in 2020. On the other hand, no statistically significant increase has been found in the city's precipitation trend from 1976 to 2015. Furthermore, the flooding risk is likely to increase given the historical pattern of urban expansion and its current speed, as the number of flooding susceptible woredas increase to 90 in 2030 under the business-as-usual scenario. Thus, smart growth management on urban expansion and dense inner-city development are recommended to reduce the flooding risk. |