What Matters? The Peak, the Volume and the Duration of Floods

What Matters? The Peak, the
Volume and the Duration of Floods
and Their Coincidence Across the
Globe
Upmanu Lall Columbia University Floods as we know them
  We focus (largely) on a river basin •  flood frequency for infrastructure design and insurance (property & life) •  Peak discharge as the indicator (volume, dura7on) •  Es7mate Return Periods at Points of interest (not usually as a spa7al field or network) •  Star7ng to look at Nonsta7onary Risk condi7onal on changes in climate and landscape •  Regional damage assessment and coverage •  Property, life, business use, supply chains, economic Water Center
Global Flood
Some Open Challenges
  Globaliza7on •  Climate Teleconnec7ons and Predictability •  PorMolio Risk •  Supply Chain Risk   What MaOers for Flood Loss •  Event Dura7on (or persistent recurrence) and Spa7al Structure •  Coincidence across remote loca7ons (floods and related hazards) •  Pathways •  Cascading Failures •  Infrastructure Networks – Power, Water, Transporta7on, Emergency Response, Supplies, PH •  Social Networks •  Financial Coverage •  Structural Change – Economic Ac7vity, Recovery Dynamics (Event recurrence)
Water Center
Global Flood
All Floods from 1985 to 2014 in the Colorado Flood Observatory database Black circle > 15 day dura7on 850 events ~ 20% Red > 30 day dura7on 322 events ~ 7% Green > 60 day dura7on
95 events ~2% Blue > 90 day dura7on
32 events ~ 1% Mean Dura7on ~ 10 days, Median Dura7on ~6 days Total events = 4202 Water Center
Global Flood Ini7a7v
ED = January, February March LUE = April, May, June reen= July, August, September ack= October, November, December rcle Size =log(Dura7on) Water Center
Global Flood Ini7a7v
Mississipi River at Clinton, Iowa 2001 1965 1881 1888 1993 1892 and 2011 Red= Events larger than 1
year flood based on pea
flow Circle size=Peak flo
Note that highest peak
does not translate to highest volume and dura7on Indirect Costs of the 2011 Mississippi Floods 90+ day disrup7on –  Freight companies bankruptcies, Shigs to Great Lakes Shipping –  Increased costs of fuel, milk –  Es7mated $300 million/day impact in shipping revenue per day disrup7o
of New Orleans Port –  Es7mated damages $2 to 4 billion Extensive tornado outbreaks and damage related to storms Sequen7al storms and flooding in Ohio River basin, Missouri River
basin, Lower and Upper Mississippi over 90 day period star7ng in April – regional network perspec7ve? Flooding and rainfall structure – early May, late April 2011 Network structure – 7ming of inunda7on varies by loca7on –  Disrup7on of transporta7on, produc7on, labor, retail distribu7on over a region may depend on the space-­‐7me nature of flooding Ohio River Basin Moisture Transport into the region shows recurrent surges with the characterisDc Dme scales of synopDc waves – 90 days prior to the flood event – a precondiDoning mechanisms for antecedent condiDons Tropical Moisture Inflow
into the region Red = 2011 event Black and shaded area composites from 20 ev
> 10 year Peak flow da7
back to 1900 Clock: reverse from day
peak flow at loca7on N.E. Dam Inflows – Volume Dura7on Peaks from: Naresh Devineni Red= >10 year peak flow event Blue = Annual maximum flow Considerable varia7on across sites in Peak-­‐Volume-­‐Dura7on rela7on No. of 7mes each site has an annual maximum event when a
hi & Devineni, 2014 site has an annual maximum event over the 50 years data Note that this does not happen that ogen over the network,
for a few sites that are in sequence What about the global view?
A look at rainfall extremes for different durations
and their spatial manifestation
Naresh Devineni, Chen Xi, Upmanu Lall, Bianca Rahill-­‐Marier 2013 Are the number of exceedances of a 20 year event in any given year
random?
If not then
a)  Is there an apparent link to ENSO?
b)  Is there organization or scaling of contiguous flooded areas?
Water Center
Global Flood Ini7a7v
Devineni et al, 2013 Time series of the Total Number of Grids With Ann. Max > 95th Percen7le 1982-­‐ 1983; 1997-­‐1999; 2009 – 2010 ENSO events are marked All grids -­‐60 to 60 N Tropics -­‐20 to 20 N Subtropics 20 to 40 N /S Extratropics 40 to 60 N/S h Inter-­‐annual variability some associa7on with El o/La Nina All grids 1 day 10 day 30 day Tropics Subtropics Extratropics et al, 2010 1day rain >T=20yr Is th
Clus
acro
eart
sea
scal
of e es t n es 2010 30day rain >T=20 year Correlation between SOIDJF and
number of floods
flood duration
NSO correlates better with flood duration than with no. of floods
eaks to physics of organization of systems that bring moisture influx
ard et al. (2014)
Main Observations
•  Extreme rainfall and floods
–  Relate to sources of persistent & recurrent organization of
atmospheric moisture transport from the tropics
–  May have significant global teleconnections/clustering
–  May affect regional flow network differently in terms of peakvolume-duration à Multivariate, Network risk
Duration and clustering
–  significant socio-economic impacts that are associated with disaste
recovery à resilience to floods
–  Portfolio and Supply Chain Risk as targets – financial instruments
Water Center
Global Flood Initiativ
Models for space-­‐7me mul7variate weather condi7onal on climate sta
hydrologic model generates streamflow using a rainfall-­‐runoff model à
e mul7variate network risk via simula7on The Rio Doce Basin, Brazil Doce
Flood Peak Single Variable Flood Volume – Peak – Dura7on Mul7variate Risk Supply chain & portfolio risk
nancial network contagion models linked to spatio-temporal models of glob
gional flood and related climate hazard
–  Production losses
–  Transportation delays
–  Fuel supply/Energy/Labor disruptions
–  Inventory Models
ortfolio risk
–  Stochastic space-time global flood risk models of local and teleconnected
–  Dynamic Bayesian Networks for stress testing portfolio
Summary
Connect the 2 sides of floods: •  The climate dynamics that determine the space-­‐7me nature and predictability
of the stress and event character over regional and global networks •  The short and long term social, economic, environmental and physical dynamic of the flood in the real world Water Center
Global Flood