Towards a large-scale locally relevant flood inundation modeling framework using SWAT and LISFLOOD-FP

摘要: Abstract Lack of geospecificity or local relevance is a major limitation in contemporary large-scale flood modeling frameworks. There little practical value for configuring model if the produces streamflow and/or inundation maps only along large rivers while numerous lower order streams remain overlooked. This study fills gap through new prediction framework based on loose coupling hydrologic Soil and Water Assessment Tool (SWAT) 1D/2D hydrodynamic LISFLOOD-FP (hence, SWAT-LISFP). The prototype SWAT-LISFP was configured with ~26,000 stream reaches across ~500,000 km2 Ohio River Basin, United States. After being calibrated against 50 gauge stations basin, SWAT simulated outputs were fed as upstream boundary conditions LISFLOOD-FP. resultant extents consistently captured 70–80% remotely sensed inundation, irrespective events locations within basin. also confirmed via cross-validation an existing AutoRAPID ( Follum et al., 2017 ). Additional experiments conducted to facilitate two critical discussions – how extent affected by uncertainty density conditions. Taking into account uncertainties streamflow, showed remarkable improvement more than 95% extent. While this approach variable-area map (i.e., range areas likely be inundated at particular point time), can still undetected. A solution problem demonstrated setting up further streams, which subsequently justified need high-resolution network, hence, essence locally relevant modeling. contributions his study, particularly introducing functional alternative supplement such series draw insights addressing lack accuracy relevance, will enhance global initiatives.