Quantifying the importance of spatial resolution and other factors through global sensitivity analysis of a flood inundation model. Issue 11 (30th November 2016)

• Record Type: Journal Article
• Authors: Thomas Steven Savage, James; Pianosi, Francesca; Bates, Paul; Freer, Jim; Wagener, Thorsten
• Is Part Of: Water resources research. Volume 52:Issue 11(2016:Nov.)
• Page Start: 9146
• Page End: 9163
• Publication Date: 2016-11-30
• Subjects: sensitivity analysis -- Sobol's method -- flood inundation modeling -- spatial resolution -- uncertainty -- hydraulic model; Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2015WR018198
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: Where high‐resolution topographic data are available, modelers are faced with the decision of whether it is better to spend computational resource on resolving topography at finer resolutions or on running more simulations to account for various uncertain input factors (e.g., model parameters). In this paper we apply global sensitivity analysis to explore how influential the choice of spatial resolution is when compared to uncertainties in the Manning's friction coefficient parameters, the inflow hydrograph, and those stemming from the coarsening of topographic data used to produce Digital Elevation Models (DEMs). We apply the hydraulic model LISFLOOD‐FP to produce several temporally and spatially variable model outputs that represent different aspects of flood inundation processes, including flood extent, water depth, and time of inundation. We find that the most influential input factor for flood extent predictions changes during the flood event, starting with the inflow hydrograph during the rising limb before switching to the channel friction parameter during peak flood inundation, and finally to the floodplain friction parameter during the drying phase of the flood event. Spatial resolution and uncertainty introduced by resampling topographic data to coarser resolutions are much more important for water depth predictions, which are also sensitive to different input factors spatially and temporally. Our findings indicate that the sensitivity of LISFLOOD‐FP predictions is more complex than previously thought. Consequently, the input factors that modelers should prioritize will differ depending on the model output assessed, and the location and time of when and where this output is most relevant. Key Points: Sensitivity of flood inundation predictions to different input factors shown to be more complex than previously thought The most influential model input factor for predicting flood extent changes during the flood event Spatial resolution is much more influential for localized predictions of water depth than for flood extent