Modeled changes in 100 year Flood Risk and Asset Damages within Mapped Floodplains of the Contiguous United States

Wobus, Cameron; Gutmann, E. D.; Jones, Russell; Rissing, Matthew; Mizukami, Naoki; Lorie, Mark; Mahoney, Hardee; Wood, A. W.; Mills, David; Martinich, Jeremy

doi:10.5194/nhess-2017-152

Cited by 9 publications

(17 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Because our approach relies on a delta method (i.e., we look at model to model changes in flow and superimpose those changes on observations), it is not critical that the modeled flows perfectly replicate observations. However, as shown in Wobus et al (2017), the multiscale parameter regionalization approach used to develop the simulated flows provides a reasonable representation of flows at this scale. Using these baseline flow magnitudes and the GEV parameters for each of the future temperature thresholds, we then calculated the AEP for each of the baseline events in the RiskMAP studies under each warming scenario.…”

Section: 1029/2018ef001119mentioning

confidence: 99%

“…Multiple extreme floods in the United States over recent years have refocused attention on the role of climate change in exacerbating damages from both inland and coastal flooding (e.g., Trenberth et al, 2018;van der Wiel et al, 2017). A number of recent studies have also estimated future changes in flood risk and damages both globally (e.g., Alfieri et al, 2017;Jongman et al, 2014;Knighton et al, 2017;Ward et al, 2017) and within the United States(e.g., AECOM, 2013;Wobus et al, 2017). Many of these studies indicate that inland flood damages are increasing and are projected to continue increasing, in a warmer world.…”

Section: Introductionmentioning

confidence: 99%

“…In the United States, most of the available data to inform inland flooding risk and damage are focused on the “100‐year” flood or the flood that has a 1% chance of occurring in any given year (e.g., AECOM, ; Wobus et al, ). This focus on the 1% annual exceedance probability (AEP) flood is largely a result of the National Flood Insurance Program (NFIP), which requires that homeowners with federally backed mortgages purchase flood insurance if their property lies within the 1% AEP floodplain.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Projecting Changes in Expected Annual Damages From Riverine Flooding in the United States

et al. 2019

Self Cite

View full text Add to dashboard Cite

Inland flood risk in the United States is most often conveyed through maps of 1% annual exceedance probability (AEP) or “100‐year” floodplains. However, monetary damages from flooding arise from a full distribution of events, including floods both larger and smaller than the 1% AEP event. Furthermore, floodplains are not static, since both the frequency and magnitude of flooding are likely to change in a warming climate. We explored the implications of a changing frequency and magnitude of flooding across a wide spectrum of flood events, using a sample of 376 watersheds in the United States where floodplains from multiple recurrence intervals have been mapped. Using an inventory of assets within these mapped floodplains, we first calculated expected annual damages (EADs) from flooding in each watershed under baseline climate conditions. We find that the EAD is typically a factor of 5–7 higher than the expected damages from 100‐year events alone and that much of these damages are attributable to floods smaller than the 1% AEP event. The EAD from flooding typically increases by 25–50% under a 1 °C warming scenario and in most regions more than double under a 3 °C warming scenario. Further increases in EAD are not as pronounced beyond 3 °C warming, suggesting that most of the projected increases in flood damages will have already occurred, for most regions of the country, by that time. Adaptations that protect against today's 100‐year flood will have increasing benefits in a warmer climate by also protecting against more frequent, smaller events.

show abstract

Section: 1029/2018ef001119mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Projecting Changes in Expected Annual Damages From Riverine Flooding in the United States

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…Despite this uncertainty, metrics can be used in a meaningful way for decision making. For example, changes in magnitude, or frequency of flooding can be connected to a geographic area and thus to infrastructure and economic impacts (Wobus et al, ).…”

Section: Overview Of Hydroclimate Metricsmentioning

confidence: 99%

Robustness of hydroclimate metrics for climate change impact research

Ekström

Gutmann

Wilby³

et al. 2018

WIREs Water

View full text Add to dashboard Cite

Metrics based on streamflow and/or climate variables are used in water management for monitoring and evaluating available resources. To reflect future change in the hydrological regime, metrics are estimated using climate change information from Global Climate Models or from stochastic time series representing future climates. Whilst often simple to calculate, many metrics implicitly represent complex physical process. We evaluate the scientific validity of metrics used in a climate change context, demonstrating their use to reflect aspects of timing, magnitude, extreme values, variability, duration, state, system services, and performance. We raise awareness about the following generic issues (a) formulation: metrics often assume stationarity of the input data, which is invalid under climate change; and do not always consider potential changes to seasonality and the relevance of the temporal window used for analysis; (b) climate change input data: how well are the physical processes relevant to the metric represented in the climate change input data; what is the impact of bias correction on relevant spatial and temporal scale dependencies and relevant intervariable dependencies; how realistic are the data in representing sequencing of events and natural variability in large‐scale ocean–atmosphere systems; and (c) decision‐making context: are rules and values that frame the decision‐making process likely to remain constant or change in a future world. If critical climate or hydrological processes are not well represented by the metric constituents, these indices can be misleading about plausible future change. However, knowledge of how to construct a robust metric can safeguard against misleading interpretations about future change. This article is categorized under: Science of Water > Methods Science of Water > Water and Environmental Change Science of Water > Water Extremes

show abstract

“…Our focus on high flow estimation is motivated by: (a) their importance to a wide range of hydrologic applications related to high flow characteristics (e.g., flood forecasting, flood frequency analysis), their relevance to historical change and future projections (Wobus et al, 2017); and (b) lack of community-wide awareness of the pitfalls associated with use of squared error type metrics for high flow estimation.…”

mentioning

confidence: 99%

On the choice of calibration metrics for high flow estimation using hydrologic models

Mizukami¹,

Rakovec²,

Newman³

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. Calibration is an essential step for improving the accuracy of simulations generated using hydrologic models, and a key modeler decision is the selection of the performance metric to be optimized. It has been common to used squared error performance metrics, or normalized variants such as Nash-Sutcliffe Efficiency (NSE), based on the idea that their squarederror nature will emphasize the estimation of high flows. However, we find that NSE-based model calibrations actually result in poor reproduction of high flow events, such as the annual peak flows that are used for flood frequency estimation. Using 5 three different types of performance metrics, we calibrate two hydrological models, the "Variable Infiltration Capacity" model (VIC) and the "mesoscale Hydrologic Model" (mHM) and evaluate their ability to simulate high flow events for 492 basins throughout the contiguous United States. The metrics investigated are (1) NSE, (2) Kling-Gupta Efficiency (KGE) and variants, and (3) Annual Peak Flow Bias (APFB), where the latter is an application-specific "hydrologic signature" metric that focuses on annual peak flows. As expected, the application specific APFB metric produces the best annual peak flow estimates; however, 10 performance on other high flow related metrics is poor. In contrast, the use of NSE results in annual peak flow estimates that are more than 20% worse, primarily due to the tendency of NSE to result in underestimation of observed flow variability.Meanwhile, the use of KGE results in annual peak flow estimates that are better than from NSE, with only a slight degradation in performance with respect to other related metrics, particularly when a non-standard weighting of the components of KGE is used. Overall this work highlights the need for a fuller understanding of performance metric behavior and design in relation to 15 the desired goals of model calibration.

show abstract

Modeled changes in 100 year Flood Risk and Asset Damages within Mapped Floodplains of the Contiguous United States

Cited by 9 publications

References 26 publications

Projecting Changes in Expected Annual Damages From Riverine Flooding in the United States

Projecting Changes in Expected Annual Damages From Riverine Flooding in the United States

Robustness of hydroclimate metrics for climate change impact research

On the choice of calibration metrics for high flow estimation using hydrologic models

Contact Info

Product

Resources

About