Probabilistic mapping of flood hazards: Depicting uncertainty in streamflow, land use, and geomorphic adjustment. (March 2020)

• Record Type: Journal Article
• Authors: Stephens, Timothy A.; Bledsoe, Brian P.
• Is Part Of: Anthropocene. Volume 29(2020)
• Publication Date: 2020-03
• Subjects: Probabilistic floodplain map -- Uncertainty -- Hydraulic modeling -- Flood risk management; Nature -- Effect of human beings on -- Periodicals; Human ecology -- Periodicals; 304.2
• DOI: 10.1016/j.ancene.2019.100231
• Languages: English
• ISSNs: 2213-3054

Abstract

Highlights: Probabilistic floodplain maps were developed through Monte Carlo simulations of flood hydraulics. Probabilistic floodplain maps reflect uncertainty in discharge, land use, and geomorphic adjustment. Flood hazard uncertainty is spatially variable and zones of hidden risk are identified. Nonstationary flood peaks increase the magnitude of flood hazard estimates. A simplified approach simulates uncertainty from ensemble results with high skill. Abstract: Spatial and temporal variability in precipitation, land use, and river channels introduce uncertainty in flood estimates and pose challenges for floodplain management and mitigation. Yet, standard deterministic methods for quantifying flood hazards and evaluating risk assume stationarity in a nonstationary world and fail to account for uncertainties as they translate to flood hazards. A need exists for improved methods to portray flood hazards that incorporate uncertainty and enable integrated water management. This paper presents novel techniques for evaluating flood hazards through probabilistic flood inundation maps that reflect uncertainty quantified through Monte-Carlo analyses of model inputs and parameters. These techniques represent a first in simultaneously varying discharge, friction parameters, and channel change in probabilistic floodplain mapping while maintaining the high level of detail implemented in regulatory hydraulic models. This study evaluated four methods for quantifying the 1 % annual exceedance probability flood, including a nonstationary approach, at an urban watershed in Charlotte, North Carolina, USA. The range of variability in flood extents resulting from Monte-Carlo simulations was spatially variable, and the likelihood of inundation revealed areas of elevated or hidden risk that were not revealed by deterministic regulatory flood hazard boundaries. The nonstationary approach indicates a significant increase in flood hazards and suggests that the regulatory floodplain boundary underestimates and miscommunicates its intended risk status. A simplified approach for estimating uncertainty in flood hazards closely matched ensemble results, providing managers a practical method for conducting uncertainty analysis. These techniques can aid floodplain management by accounting for the inherent uncertainty in model estimates and the potential nonstationary behavior of flood hazards.