Implications of a changing climate for flood risk Dennis P. Lettenmaier Department of Geography University of California, Los Angeles Climate Roundtable,

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Presentation transcript:

Implications of a changing climate for flood risk Dennis P. Lettenmaier Department of Geography University of California, Los Angeles Climate Roundtable, “Precipitation in the U.S.” FM Global, Boston Jan 12, 2015

Motivating question: As the climate (and presumably precipitation and precipitation extremes) change, what will happen (is happening) to flood risk?

Outline of this talk 1)What causes a flood? 2)Evidence for changes in U.S. flood risk 3)Sensitivities and projections 4)How good are the models?

What causes a flood? Extreme precipitation Precipitation duration relative to catchment response time (“time of concentration”) Soils, topography, and (lesser extent) vegetation Catchment and storm geography; storm movement relative to catchment geography Antecedent conditions (soil moisture) Other factors (e.g., snow; frozen ground)

precipitationhydrological processes channel processes DOMINANT PROCESS CATCHMENT SIZE small mediumlarge flash flood large river flooding Dominant processes governing catchment storm response

Pecos River flood frequency distribution (from Kochel et al, 1988) Issues in the historical record

Evidence for changes in U.S. flood risk

A warmer climate, with its increased climate variability, will increase the risk of both floods and droughts IPCC WG2, 2007

Most climate scientists agree that global warming will result in an intensification, acceleration or enhancement of the global hydrologic cycle, and there is some observational evidence that this is already happening. UNESCO World Water Development Report Water in a Changing Climate, 2009

Total U.S. flood damages, from Pielke et al., 2000

First, (extreme) precipitation trends

Extreme precipitation should be increasing as the climate warms

replotted from Westra et al., J Clim, 2013 Relationship between annual daily maximum precipitation distribution and global mean temperature (red significantly positive, blue significantly negative, other no relationship)

Trends in annual precipitation maxima in 100 largest U.S. urban areas, from Mishra and Lettenmaier, GRL 2011

So what about flooding?

Number of statistically significant increasing and decreasing trends in U.S. streamflow (of 395 stations) by quantile (from Lins and Slack, 1999)

About 10% of the 400 sites show an increase in annual maximum flow from to Maximum flow Increase No change Decrease Visual courtesy Bob Hirsch, figure from McCabe & Wolock, GRL, 2002

Tufts University Decadal Magnification Factors of Floods – Sites w/ no regulation 1,642 of 14,893 USGS Gage Sites with M>1 and p>0.9 From Yaindl and Vogel, 2009 visual courtesy Rich Vogel

Tufts University Decadal Flood Magnification Factors - HCDN Sites 208 of 1,588 HCDN Gage Sites with M>1 and p>0.9 From Yaindl and Vogel, 2011 visual courtesy Rich Vogel

Tufts University Decadal Flood Magnification Factors Sites With No Regulation From Yaindl and Vogel, 2011 visual courtesy Rich Vogel

Tufts University Results Decadal Flood Magnification Factors From Yaindl and Vogel, Groups of USGS Gages visual courtesy Rich Vogel

Paradox: Given increases in precipitation and runoff, why are there so few significant trends in floods? Visual courtesy Tim Cohn, USGS

[Lins and Cohn, 2002 ] Possible explanation Visual courtesy Tim Cohn, USGS

Sensitivities and projections

Predicting urban flooding in a future climate – Thornton Creek example

Global Climate Models ECHAM5 Developed at Max Planck Institute for Meteorology (Hamburg, Germany) Used to simulate the A1B scenario in our study CCSM3 Developed at National Center for Atmospheric Research (NCAR; Boulder, Colorado)Used to simulate the A2 scenario in our study

Global Climate Models Mote et al 2005 ECHAM5 CCSM3

Dynamical Downscaling Courtesy Eric Salathé Global Model Regional Model

Results of Future Analysis SeaTacSpokanePortland 1-hour+16%+10%+11% 24-hour+19%+4%+5% 1-hour-5%-7%+2% 24-hour+15%+22%+2% * Statistically significant for difference in means and distributions, and non-zero temporal trends ECHAM5/ WRF CCSM3/ WRF * * * * Changes in average annual maximum precipitation between 1970–2000 and 2020–2050:

Results of Bias Correction -- SeaTac Raw ChangeCorrected Change 1-hour+16%+14% 24-hour+19%+28% 1-hour-5%-6% 24-hour+15%+14% ECHAM5 CCSM3 Comparison of changes in average annual maximum between 1970–2000 and 2020–2050: * * Statistically significant for difference in means and distributions, and non-zero temporal trends * **

Thornton Creek

Results of Hydrologic Modeling Changes in average annual maxima streamflow at outlet of watershed between and : Juanita CreekThornton Creek CCSM3+25%+55% ECHAM5+11%+28% * Statistically significant for difference in means **

Hydrological modeling (forced at the land surface with P, T, …)

Simulation Approach 10 GCMs from CMIP5: CCSM4, NorESM-1, bcc-csm1-1-m, CanESM2, HadGEM2-CC365, HadGEM2-ES365, MIROC5, IPSL-CM5A-MR, CSIRO-Mk3-6-0,CNRM-CM5 3 Scenarios: Historical ( ), RCP4.5 ( ) and RCP8.5 ( ) 10 GCMs from CMIP5: CCSM4, NorESM-1, bcc-csm1-1-m, CanESM2, HadGEM2-CC365, HadGEM2-ES365, MIROC5, IPSL-CM5A-MR, CSIRO-Mk3-6-0,CNRM-CM5 3 Scenarios: Historical ( ), RCP4.5 ( ) and RCP8.5 ( ) Variable Infiltration Capacity Model Multi-Model Ensemble Average P and T MACA Downscaling Method (to 1/16 deg spatial resolution) P and T Runoff, SWE

Assessment of potential flood changes in PNW based on (10) CMIP5 scenarios

Future Changes in the Mean Annual Maximum Flood

Timing of Annual Maximum Flood

Are these changes driven by SWE, Precipitation, or Temperature?

Future Changes in Mean Annual 24-hr Maximum Precipitation

Ratio of April 1 SWE to Cumulative NDJFM Precipitation 0-0.1: Rain Dominant : Transient 0.5-1: Snow-Dominant (see Elsner et al 2010)

Future Changes in April 1 SWE

Summary of Results Changes in timing primarily driven by warming summer warming stronger than winter warming, with significant differences between rcp4.5 and 8.5 on average, floods will come earlier by weeks Changes in flood frequency primarily driven increases in intense precipitation Next Steps: investigate duration of maximum flood event, expand analysis to regional level

How good are the models?

The appropriate test of downscaling’s relevance is not whether it alters paradigms of global climate science, but whether it improves understanding of climate change in the region where it is applied.

The November Surprise JANFEBMARAPR MAYJUNJULAUG SEPOCTNOVDEC Courtesy Eric Salathé NOV

60 Can RCMs reproduce the timing of precipitation maxima ? Winter Summer from Mishra et al., GRL 2012

Summary  “Preponderance of evidence” for (some) increase in precipitation extremes  Not showing up in flood records (why not?)  Flooding in western U.S. is sensitive to warming (in observations) aside from changes in precipitation extremes  Climate signal (in flooding) is most likely being obscured by lots of natural variability  Opportunities (for enterprising graduate students) to better understand the interaction of climate (change) and flood risk across the U.S.