The integrated effects of climate and hydrologic uncertainty on future flood risk assessments

Abstract

This work examines future flood risk within the context of integrated climate and hydrologic modelling uncertainty. The research questions investigated are (1) whether hydrologic uncertainties are a significant source of uncertainty relative to other sources such as climate variability and change and (2) whether a statistical characterization of uncertainty from a lumped, conceptual hydrologic model is sufficient to account for hydrologic uncertainties in the modelling process. To investigate these questions, an ensemble of climate simulations are propagated through hydrologic models and then through a reservoir simulation model to delimit the range of flood protection under a wide array of climate conditions. Uncertainty in mean climate changes and internal climate variability are framed using a risk‐based methodology and are explored using a stochastic weather generator. To account for hydrologic uncertainty, two hydrologic models are considered, a conceptual, lumped parameter model and a distributed, physically based model. In the conceptual model, parameter and residual error uncertainties are quantified and propagated through the analysis using a Bayesian modelling framework. The approach is demonstrated in a case study for the Coralville Dam on the Iowa River, where recent, intense flooding has raised questions about potential impacts of climate change on flood protection adequacy. Results indicate that the uncertainty surrounding future flood risk from hydrologic modelling and internal climate variability can be of the same order of magnitude as climate change. Furthermore, statistical uncertainty in the conceptual hydrological model can capture the primary structural differences that emerge in flood damage estimates between the two hydrologic models. Copyright © 2014 John Wiley & Sons, Ltd.

Growth of the Decision Tree: Advances in Bottom‐Up Climate Change Risk Management

“…In studies taking this approach (e.g., Steinschneider et al. ; Poff et al. ), the coefficient of variation of precipitation has been found to be an important (relative to climate shifts) driving force in the system response.…”

Decision Analysis for Management of Natural Hazards

“…Flooding (Hine and Hall, 2010), Drought (Matrosov et al, 2013), Earthquake Resilient Design (Tang et al, 2015) Decision Scaling Uses stakeholder-defined thresholds, finds conditions under which these thresholds are exceeded Drought and Climate studies (Brown et al, 2012) and Flood Risk (Steinschneider et al, 2015) …”

“…Decision scaling was applied to improve management of the Great Lakes in the United States (Brown et al, 2012), to assess flood risk (Steinschneider et al, 2015) and to trade-off ecological and water engineering performance indicators (Poff et al, 2015, Singh et al, 2014.…”

The effects of climate model similarity on probabilistic climate projections and the implications for local, risk‐based adaptation planning

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