Quantifying the importance of spatial resolution and other factors through global sensitivity analysis of a flood inundation model

James Thomas Steven Savage,Jim Freer,Paul Bates,Thorsten Wagener,Francesca Pianosi

doi:10.1002/2015wr018198

Abstract

AbstractWhere 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.

Highlights

Flood inundation models have been utilised widely to make flood hazard predictions
Each input factor takes a specific position in such rankings with a clearly highest frequency: for example in the bottom left panel, hydrograph (Hyd) is most often ranked first, flood friction (Flo) second, channel friction (Cha) third, spatial resolution (Res) fourth, and Digital Elevation Models (DEMs) fifth
This study has applied a GSA methodology, which allowed us to assess whether variability in spatial resolution, DEM, model parameters or model boundary conditions produce the most variance in the output of the hydraulic model LISFLOOD-FP

Summary

Introduction

Flood inundation models have been utilised widely to make flood hazard predictions. These models are typically run in either steady state, where the boundary conditions (for a river this would typically be the river discharge) are fixed in time, or in unsteady state, where the boundary conditions change through time. Cook and Merwade, 2009) and to compare different hydraulic models (Bradbrook et al, 2004), whilst models run in an unsteady state enable modellers to understand the dynamic variation of flood hazard throughout the passage of the flood wave (e.g. Bates and De Roo, 2000; Mignot et al, 2006; Skinner et al, 2015). The application of these models has allowed the mapping of regions at risk of inundation from coastal These uncertainties are typically represented probabilistically by computing multiple realisations of the model under different forcing conditions informed by the uncertainties under consideration, for example using the Generalised Likelihood

Methods

Results

Discussion

Conclusion