1. Overview of Hydrologic Forecasting Research at the University of Washington
Alan F. Hamlet, Andy Wood,
Dennis P. Lettenmaier
JISAO/CSES Climate Impacts Group
Dept. of Civil and Environmental Engineering
University of Washington

2. Overview of the UW West-Wide Hydrologic Forecasting System

3. Fundamental Research Goals:
Implement a consistent set of fully distributed hydrologic simulation models and forecasting approaches over the entire West
Improve estimates of hydrologic initial conditions (SWE and soil moisture) via improved use of real time station records and data assimilation using remotely sensed (MODIS snow extent) and telemetered (SNOTEL SWE) snow observing systems.
Make use of improved climate information and forecasts (e.g. ENSO forecasts, climate model simulations) at number of time scales using a number of approaches

4. Experimental W. US Hydrologic Forecast System
NCDC met. station obs. up to 2-4 months from current
local scale (1/8 degree) weather inputs
soil moisture
snowpack
Hydrologic model spin up
SNOTEL Update
streamflow, soil moisture,
snow water equivalent, runoff
25th Day, Month 0
1-2 years back
LDAS/other real-time met. forcings for spin-up gap
Hydrologic forecast simulation
Month
INITIAL STATE
SNOTEL
/ MODIS*
Update
ensemble forecasts
ESP traces (40)
CPC-based outlook (30)
NCEP CFS ensemble (N)
NSIPP/GMAO ensemble (9)
This just describes the framework for simulations – how the forecasts are made.
Note that the update cycle is typically monthly, with forecasts initialized on day 1 of the month, although we occasionally do twice monthly forecasts if changing conditions warrant.
* experimental, not yet in real-time product

5. Experimental W. US Hydrologic Forecast System
Snowpack
Initial Condition
Here I typically say the system is implemented using VIC (wat/nrg balance model, etc.), and the spinup simulation produces an initial condition for snowpack and soil moisture over a domain of about 18,000 cells.
Soil Moisture
Initial Condition

6. Experimental W. US Hydrologic Forecast System
Multiple Seasonal Climate Forecast Data Sources
CCA
NOAA
CAS
OCN
CPC Official Outlooks
SMLR …
Coupled Forecast System
VIC Hydrology Model
NASA
NSIPP/GMAO dynamical model
Our framework has allowed the use of climate forecast information from a number of sources – ESP & derivatives, climate model (NCEP/NSIPP), and CPC probabilistic outlooks. Currently we are re-implementing the climate model forecasts, and the CPC forecast approach is also evolving as we try to improve the temporal disaggregation step.
ESP
ENSO UW
ENSO/PDO

7. A Walk Through the UW West Wide Hydrologic Forecasting Web Site:

8. Some Related UW Forecasting Research Projects:
Daily Surface Water Monitor:
Daily updated SWE and SM product for the U.S. [
Multi-Model Ensemble Forecasting Methods:
Sacramento Model
VIC
NOAH
Increased VIC Spatial Resolution Over a Smaller Domain
1/16th degree for WA, OR, ID, NV
Yakima basin
Klamath basin

9. Interaction with NRCS NWCC
Since last year, we have exchanged nowcast/forecast results with the NRCS National Water and Climate Center (head: Phil Pasteris)
Under a Memorandum of Understanding between NRCS & UW:
UW provides forecast results and data as NRCS requests
NRCS provides access to stream flow and climate data (primarily via NOAA ACIS)
NRCS has created a place for links to “experimental water supply forecasts” from its official website. Currently the UW is the only one, and they would like more!
We generally attempt to schedule a “pre-forecast” conference call just prior to NRCS coordination of forecasts with NWS RFCs, in which we summarize our forecast outlooks and compare notes.
In addition, there is a fair amount of informal exchange.
We also have an on-going interaction with the NWCC, and exchange results and comments on a routine basis during the forecast season. Credit Phil Pasteris, Tom Pagano, Tom Perkins, Jolyne Lea.
Note that NWCC is experimenting with a modeling capability based on the USGS PRMS model.

10. Overview of UW Climate Research

11. Pacific Decadal Oscillation El Niño Southern Oscillation
A history of the PDO
A history of ENSO
warm
warm
cool

12. Effects of the PDO and ENSO on Columbia River
Summer Streamflows
PDO
Cool
Cool
Warm
Warm
Red=warm ENSO Green=ENSO neutral Blue=cool ENSO

13. 1998 ✔
1999 ✔
2000 ✔
2001 X
2002 ✔
2003 ✔
2004 X
2005 ✔
In 6 out of 8 test years, accurate categorical ENSO forecasts (warm, neutral, cool) have been available in mid-summer preceding the water year. By October simple persistence gives an accurate forecast.

14. Evaluation of Real Time Nino3.4 Forecast for WY 2005
Observed Nino3.4 anomally

15. Natural Streamflow (cfs)
Bias Corrected Long Range Streamflow Forecast for the Columbia River at The Dalles
January Nino3.4 index between 0.2 and 1.2
Red = Unconditional mean
Blue = Ensemble mean
Black = 2005 Observed
Natural Streamflow (cfs)

16. Comparison of Skill For Warm ENSO Years

17. Comparison of Skill For Cool ENSO Years

18. Comparison of Skill For ENSO Neutral Years

19. X100 wENSO / X100 2003 X100 nENSO / X100 2003 X100 cENSO / X100 2003
Fig 8 Warm, neutral, cool ENSO 100-year flood
DJF Avg Temp (C)
DJF Avg Temp (C)
DJF Avg Temp (C)
X100 wENSO / X
X100 nENSO / X
X100 cENSO / X

20. Some Current Users of Long-Range Climate Forecasts for Hydrologic Forecasting
Seattle Public Utilities
Portland General Electric
3-Tier Environmental Forecast Group
Seattle City Light
Tacoma Power
Columbia Basin
USACE
Libby and Dworshak forecasts (SOI)

21. At almost every USHCN station, winters warmed
+ signs: warming but not statistically significant

22. TMAX Regionally Averaged Cool Season Temperature Anomalies 0.74 0.63
0.76
0.62
(Regional to Global
Correlation R2 )
TMAX

23. TMIN Regionally Averaged Cool Season Temperature Anomalies 0.84 0.87
0.94
0.73
(Regional to Global
Correlation R2 )
TMIN

24. Simulated Changes in Snowpack Timing in the Western U.S.
a) 10 % Accum.
b) Max Accum.
c) 90 % Melt
Effects of
Temperature
and
Precipitation
DJF Temp (C)
DJF Temp (C)
DJF Temp (C)
Change in Date
Change in Date
Change in Date
Effects of
Temperature
only
DJF Temp (C)
DJF Temp (C)
DJF Temp (C)
Change in Date
Change in Date
Change in Date
Effects of
Precipitation
only
DJF Temp (C)
DJF Temp (C)
DJF Temp (C)
Change in Date
Change in Date
Change in Date

25. Flood Control vs. Refill
Streamflow timing shifts can reduce the reliability of reservoir refill
Full
Model experiments (see Payne et al. 2004) have shown that moving spring flood evacuation two weeks to one month earlier in the year helps mitigate reductions in refill reliability associated with streamflow timing shifts.
Payne, J.T., A.W. Wood, A.F. Hamlet, R.N. Palmer, and D.P. Lettenmaier, 2004, Mitigating the effects of climate change on the water resources of the Columbia River basin, Climatic Change, Vol. 62, Issue 1-3,

26. Simulated Changes in the 20-year Flood Associated with 20th Century Warming
DJF Avg Temp (C)
X / X
Fig year flood A spatial scale
DJF Avg Temp (C)
X / X
X / X

27. Regionally Averaged Cool Season Precipitation Anomalies

28. 20-year Flood for “ ” Compared to “ ” for a Constant Late 20th Century Temperature Regime
DJF Avg Temp (C)
X20 ’73-’03 / X20 ’16-’03
X20 ’73-’03 / X20 ’16-’03

29. Summary:
1) Overview of UW West-Wide Hydrologic Forecasting System:
Some overall research goals of the project are to implement a set of consistent hydrologic simulation models and forecasting procedures over the West, improve spatially explicit estimates of initial hydrologic conditions by accessing real time station and assimilating measured SWE data, and to explore the use of climate information and forecasts using a number of approaches.
Some related current research projects include implementation of multi-model ensembles to improve forecasting accuracy, daily updating of SM and SWE fields for the continental US for the US Drought Monitor, and a four-state higher spatial resolution forecasting system with pilot applications in the Yakima and Klamath basins.

30. Summary:
2) Use of Climate Information and Forecasts:
Long range ENSO and PDO forecasts have been shown in retrospective tests to improve ESP forecast skill and to extend the practical lead time of long-range streamflow forecasts at The Dalles. Some operational statistical forecasting procedures currently include ENSO information (via SOI). ENSO also appears to affect flood risks in the PNW, particularly in coastal areas.
Temperature and precipitation variability have been changing over the 20th century. The late 20th century is warmer and has different cool season precipitation variability than the pre-1975 period. Rising temperatures have resulted in reduced and earlier snowmelt (e.g. affecting refill timing). Both effects have been shown in simulations to result in altered flood risks over the West. Are current flood control practices robust to these changes?