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Monte Carlo Simulation to Characterize Stormwater Runoff Uncertainty in a Changing Climate
G.S. Karlovits, J.C. Adam, Washington State University2010 AGU Fall Meeting, San Francisco, CA
Outline
1. Climate change and uncertainty in the Pacific Northwest
2. Data, model and methods1. Climate data2. Design storms3. VIC4. Monte Carlo simulation
3. Results and uncertainty analysis
Climate Change in the PNW
95th percentile (10-year moving average)
5th percentile (10-year moving average)
LOWESS-smoothed21-model ensemble averages
Modeled historical (with bounds)
2045
From Mote and Salathé (2010)
Uncertainty
Projections for future climate based on many assumptions Greenhouse gas emissions scenario Global climate model (GCM) Downscaling of climate data
Effects of changing temperature and precipitation on hydrology uncertain as well Effects on moisture storage (moderation or
enhancement)▪ Snowpack▪ Soil moisture
Other sources of uncertainty in forecasting hydrology▪ Hydrologic model structure▪ Model calibration parameters
Objectives/Motivation
How much uncertainty is there in forecasting future runoff in the Pacific Northwest due to climate change?
What causes this uncertainty?
Can we improve our forecast for runoff in the future so planners and engineers have a tool to help prepare for climate change?
General Methodology
Find change in 2, 25, 50, 100-year 24-hour storm intensities for different emissions scenarios/GCMs
Use a hydrology model to compare future projected storm runoff to historical
Use a probabilistic method to isolate uncertainty and improve forecast
Design Storms
Storms with an average return interval of 2, 25, 50 and 100 years from extreme value distribution Annual probability of exceedance = 0.50, 0.96,
0.98, 0.99 Historical: 92 years of data (1915-2006) Future: 92 realizations of 2045 climate
Hybrid delta downscaling method▪ Delta method with bias correction
Historical and future data aggregated from data in Elsner et al. (2010)
VIC Hydrology Model
Need to take changes in precipitation and temperature and turn them into changes in runoff
Variable Infiltration Capacity Model
• Process-based, distributed model run at 1/2-degree resolution
• Sub-grid variability (soil, vegetation, elevation) handled with statistical distribution
• Gridded results for fluxes and states
• No interaction between grid cells
Gao et al. (2010), Liang et al. (1994)
Monte Carlo Simulation
Modeling random combination for met data and hydrologic model parameters Emissions scenario (equal probability) GCM (weighted by hindcasting ability)▪ GCMs with higher bias in recreating 1970-
1999 PNW climate given lower selection probability
Snowpack Soil moisture
Modeled in VIC, fit to discrete normal distribution
Monte Carlo Simulation For each return interval, 5000 combinations of emissions
scenario, GCM, soil moisture and snowpack quantile were made
(Pseudo-)random numbers generated using the Mersenne Twister algorithm (Matsumoto and Nishimura 1998)
Monte Carlo Results
Historical 50-year stormRandom selection of soil moisture
and SWE
Future 50-year stormRandom selection of emissions
scenario, GCM, soil moisture and SWE
Monte Carlo Results
Percent change, historical to future runoff due to 50-year storm
Coefficient of variation for runoff for 5000 simulations of 50-year storm
Emissions Scenario/GCM
Absolute difference in runoff due to emissions scenario (A1B – B1) (mm)
Coefficient of variation due to selection of GCM (50-year storm)
CDFs
-2 -1 0 1 2 3 4 5 6 7 80
0.2
0.4
0.6
0.8
1
Palouse (Cell 335)
Historical FutureDifference
Runoff (mm)
Cu
mu
lati
ve P
rob
ab
ilit
y0 25 50 75 10
012
515
017
520
00
0.2
0.4
0.6
0.8
1
Queets (Cell 291)
Historical FutureDifference
Runoff (mm)
Cu
mu
lati
ve P
rob
ab
ilit
y
Conclusions
Runoff is projected to increase for many places in the Pacific Northwest Largest increases related to most
uncertainty Uncertainty in emissions scenario is
a factor in all future projections Even A1FI scenario low for 21st century
Probabilistic methods can improve forecasts and isolate uncertainties
Questions?
Chehalis, WAPhoto: Bruce Ely (AP) via http://www.darkroastedblend.com/2008/06/floods.html
Contact me:
Gregory [email protected]
Jennifer [email protected]
