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"Application of Artificial Intelligence Approaches in the Flood Manageme" by Umair Iqbal

Floods are the most recurrent, widespread and damaging natural disasters, and are ex-pected to become further devastating because of global warming. Blockage of cross-drainage hydraulic structures (e.g., culverts, bridges) by flood-borne debris is an influen-tial factor which usually results in reducing hydraulic capacity, diverting the flows, dam-aging structures and downstream scouring. Australia is among the countries adversely impacted by blockage issues (e.g., 1998 floods in Wollongong, 2007 floods in Newcas-tle). In this context, Wollongong City Council (WCC), under the Australian Rainfall and Runoff (ARR), investigated the impact of blockage on floods and proposed guidelines to consider blockage in the design process for the first time. However, existing WCC guide-lines are based on various assumptions (i.e., visual inspections as representative of hy-draulic behaviour, post-flood blockage as representative of peak floods, blockage remains constant during the whole flo ....

Lab Dataset , Wollongong City Council , Neural Architecture Search Network Nasnet , Australian Rainfall , Hydraulics Lab Dataset , Visual Hydraulics Lab Dataset , Culvert Openings , Synthetic Images , Neural Architecture Search Network , Floor Management , Ross Drainage Hydraulic Structures , Ydraulic Blockage , Isual Blockage , Caled Physical Models , Artificial Intelligence ,