Urban drainage decision model for storm emergency management based on multi-objective optimization

This study proposes a solution to prevent urban waterlogging, challenging environmental issue, by integrating waterlogging prediction and drainage optimization schemes based on cellular automaton multi-objective theories. An model for uncertain flow was constructed considering surface fragmentation space complexity. For dynamic simulation, outputs of water depth flooded areas were projected with inputs rainfall, soil infiltration, plant interception, gully discharge, outflow its neighbors in each cell at any moment. Using approach, the decision optimal solutions calculated maximal amount pumping from zones candidate reservoirs minimal energy cost. integrated approach successfully applied DongHaoChong catchment, an 11 km2 watershed Guangzhou, southern China validated comparing simulated flood points two historical rainstorms (August 15, 2013 June 23, 2014). The RMSE maximum 26.89 78.48 mm, respectively. Therefore, proposed reliable capable simulating position moment data input parameters environment. Water-logged area could be predicted given rainfall assuming 1-, 10-, 50-, 100-year storm area, obtained verified. emergency models optimize decision-making improve plans reduce losses due waterlogging.