APPLICATION OF DATABANK-BASED DATA ASSIMILATION TO URBAN INUNDATION MODEL FOR IMPROVED ACCURACY AND SENSITIVITY ANALYSIS OF PUMPING OPERATION

Abstract

 Water drained through sewer network installed in lower-lands shows complex behavior due to influence from pumping station and exhibits non-linearity in rainfall-runoff relation. Also validation of sewer network model is not sufficient due to lack of observed data. Present study validates urban inundation models by using water levels observed in storage pipes and applies databank-based data assimilation. Furthermore, effect of pumping operation is examined through sensitivity analysis. It was found that model prediction can be improved by the assimilation technique and also it was found that consideration of water levels in pumping stations are necessary.