Transcript Uncertainty Analysis of Climate Change Effects on Runoff for the

Uncertainty Analysis of Climate Change Effects on Runoff for the Pacific Northwest
Greg Karlovits and Jennifer Adam
Department of Civil and Environmental Engineering, Box 642910, Washington State University, Pullman, WA 99164
Introduction
Rainfall Statistics
The intensity of design storms in the Pacific Northwest is projected to increase
due to climate change. Assumptions of stationarity in estimating the intensity of
rainfall design events are no longer valid due to this change, and designs meant to
handle runoff events estimated by these storms need to be changed. Using the
Variable Infiltration Capacity (VIC) hydrology model, runoff over the Pacific
Northwest for the 1915-2006 and 2040s climate were simulated for design storms
of 2, 25, 50 and 100-year average return intervals. The results were weighted
using Monte Carlo simulation, with selections of uncertainty parameters made
randomly for 5000 realizations. Two parameters for climate uncertainty and two
for model uncertainty were modeled stochastically. The amount of uncertainty due
to emissions scenario, Global Climate Model (GCM), antecedent snow waterequivalent and soil moisture were isolated for their contributions to runoff.
Historical (1915-2006) and GCM-projected (2040s) annual maximum 24-hour
rainfall events were fit to the Generalized Extreme Value (GEV) distribution using
the method of L-moments at 1/2 degree resolution. Design storm intensities were
generated using the GEV quantile function. In general, design storms were found
to increase in intensity over the PNW.
Components of Uncertainty
The most uncertainty in projecting
future runoff is due to a choice in
emissions scenario. The uncertainty in
this choice is amplified by the different
GCM projections. Biases in the
historical runs of each GCM were
reflected in the future projections, with
the warmest and wettest models
forecasting the largest increases.
Overall Coefficient of Variation
The Pacific Northwest
Historical 50-Year Storm
CNRM CM3 (B1) 50-Year Storm
GEV Quantile Function
Difference in Emissions Scenario
Coefficient of Variation for GCMs
Difference in Snowpack
Difference in Soil Moisture
Monte Carlo Forecasts
Pictured above at 1/16-degree resolution are the average annual precipitation (L)
and elevation (R) for the Pacific Northwest (Elsner et al. 2010)
Monte Carlo Simulation
For weighting VIC runoff results, 5000 random selections of emissions scenario,
GCM, SWE and soil moisture were made based on a weighting scheme.
Emissions scenarios had equal selection probability (p=0.5)
GCMs were weighted by ability to re-create 1970-1999 climate over the PNW
SWE and soil moisture were simulated with VIC for 1960-1989 and quantiles
based on a discretized normal distribution were selected
GCM
T Bias
CCSM3
-1.7
CGCM3.1_t47
-2.3
CNRM_CM3
-0.8
ECHAM5
-1.8
ECHO_G
-2.2
HADCM
-1.9
HADGEM1
-1.8
IPSL_CM4
-1.6
MIROC_3.2
-1.5
PCM1
-2.8
P Bias
1.8
1.7
1.7
1.7
1.7
1.3
2.2
2.4
3.2
1.6
R
2.48
2.86
1.88
2.48
2.78
2.30
2.84
2.88
3.53
3.22
A1B P
0.107
0.093
0.141
0.107
0.095
0.115
0.093
0.092
0.075
0.082
Historical (50-Year Storm Runoff)
B1 P
0.118
0.102
0.155
0.118
0.105
0.127
-0.101
0.083
0.091
Using a weighting scheme, the VIC runs
were averaged to produce results reflecting
the likelihood or skill of a predictor, which
improves the forecasting results. For the
majority of the PNW, runoff is projected to
increase. Most locations with heavy
precipitation demonstrate increases in
runoff in the future. All locations in the
Puget Sound/Olympic Peninsula region
show an increase in runoff due to the
higher emissions scenario, which is closer
to actual emissions rates. Declining
snowpack west of the Cascades is linked to
increased runoff.
SWE or Soil Moisture
(mm)
800
700
600
500
400
300
200
100
0
0
0.2
0.4
0.6
Cumulative Probability
0.8
1
Monte Carlo (50-Year Storm Runoff)
Conclusions
While runoff is projected to increase due to climate change for much of the Pacific
Northwest, the magnitude of that change is uncertain due to a number of factors.
The built-in assumptions for the emissions scenario are already low in the 21st
century, so realistic scenarios are above the “worst case” in this study. A suite of
options created by emissions scenarios and GCMs helps find a central tendency in
projections, where reliance on a single scenario and GCM offers no guarantee of
reliability. Additional research on downscaling techniques and finer scale
simulation could offer insight into more complicated runoff interactions due to the
complicated topography and climate of the Pacific Northwest, and help advise
changes on a level more relevant to stormwater management.
Acknowledgements
Percent Change, Historical to Future
Thanks goes out to TransNOW for funding this research. This research is advised
by Jennifer Adam. The Master’s thesis committee consists of Michael Barber and
Liv Haselbach of WSU and Veronica Griffis of Michigan Tech.