Title: Forecasting Streamflow and Reservoir Storage Summer of 2003
1Forecasting Streamflow and Reservoir Storage
Summer of 2003
- Richard Palmer, Andre Ball, Ani Kameenui,
- Kasey Kudamik, Michael Miller,
- Nathan Van Rheenen, Matthew Wiley
- CEE
- University of Washington
- October 2003
2Talk Overview
- Background on Forecast Approach
- Evolving Summer Forecasts
- Accuracy of Forecast
- Conclusions
3Study Goals
- Create six-month forecasts for municipal water
supplies in the Puget Sound area using NCEP
forecasts - Water Supply
- Water Demand
- Storage in Reservoir
- Decision Support System
4Forecasting
- The herd instinct among forecasters makes sheep
look like independent thinkers. Edgar R.
Fiedler - If you have to forecast, forecast often. Edgar R.
Fiedler - An unsophisticated forecaster uses statistics as
a drunken man uses lamp-posts - for support
rather than for illumination. Andrew Lang
5Other Quotes
- The future will be better tomorrow.
- Dan Quayle (1947 - )
- Where a calculator on the ENIAC is equpped with
18,000 vacuum tubes and weighs 30 tons, computers
in the future may have only 1,000 vaccuum tubes
and perhaps weigh 1.5 tons. - Popular Mechanics, March 1949- More quotations
on Computers
6Other Quotes
- The best way to predict the future is to invent
it. - Alan Kay
- The future belongs to those who prepare for it
today. - Malcolm X (1925 - 1965)
-
- The future is here. It's just not widely
distributed yet. - William Gibson (1948 - )
7Other Quotes
- Enjoy present pleasures in such a way as not to
injure future ones. - Seneca (5 BC - 65 AD)
- The future ain't what it used to be.
- Yogi Berra (1925 - )
8Study Domain
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11Value of Forecasting
- Provide timely information for determining
- Timing of Spring Refill
- Instream Flow Requirements
- Necessity of water-use alerts
- Timing of Fall Drawdown
12Models Used to Generate Forecasts
13Water Demand ForecastingPuget Sound Region
- Models
- short (weekly-monthly) and long
(annual-decadal)-term - Regions Seattle, Tacoma, and Everett
- Tacoma and Everett Municipal demands
- Seattle System-wide demands
14Purpose
A common characteristic of water resources
planning is its failure to anticipate
change. -D. Sewell, 1978
- Increase the accuracy of demand models for
effective water resources planning and
management. - Provide information for monitoring and
controlling demands during droughts, planning
conservation programs, and supply and
infrastructure changes. - Create a framework for long-term forecasting
while considering urban planning.
15How well have we done?
- Increase the accuracy of demand models for
effective water resources planning and management.
16 Recent History
- Provide information for monitoring and
controlling demands during droughts, planning
conservation programs, and supply and
infrastructure changes.
17Data Resources
- WATER related
- Sources Seattle Public Utilities Tacoma Water
City of Everett - Daily water demands
- Rate History Number of users
- CLIMATE
- National Climate Data Center (NCDC) SeaTac
daily Tmax and precipitation - National Centers for Environmental Prediction
(NCEP) downscaled climate ensembles - HOUSEHOLD
- Puget Sound Regional Council (PSRC)
- Urban simulation group (UrbanSim)
18Short-term Model DesignSeattle Region
- Data must be on a weekly time-step
- Log-linear regression
- Water Demand InterceptAxBx2Cx3Dx4Ex5Fx6
Gx7 - Ln(Water Demand) Intercept xLn(A)
x2Ln(B) x3Ln(C) x4Ln(D) x5Ln(E)
x6Ln(F) x7Ln(G)
Dependent variable System (SPU)-wide weekly averages
Independent variables A. Temperature (average weekly max) (Tmax)
B. Precipitation (weekly average)
C. Winter water use
D. System user population
E. Water rate/price
F. Temperature (max) (one-week lag)
G. System-wide weekly average (one-week lag)
19Model CalibrationSeattle Region Summer
20Model ValidationSeattle Region Summer
21Model CalibrationTacoma Region Summer
22Model ValidationTacoma Region Summer
23Model ValidationEverett Region Summer
24Demand ForecastSeattle Region April forecast
25Forecast Skill and Error
- Forecast skill metric (Hamlet)
- Skill 1 - ?(forecast - observed)2/N /
?(historical - observed)2/M - Rewards precision, punishes spread
- Valuable metric during outlier years
- Summer 2003 was an climate outlier
- Model is calibrated during less dramatic
conditions - Validated during warming (hence the drop in
correlation)
26Long-Term Forecasting
- Create a framework for long-term forecasting
while considering urban planning. - Using PSRC and UrbanSim information from
household survey or Parcel Index Number databases - Highly disaggregated database for modeling
household or class specific water demands. - Incorporate household variables such as size,
income, house age, house value, yard size, etc. - Investigate benefits and drawbacks of
disaggregated model and consider water resources
during urban planning and land development
(UrbanSim component).
27Long-term Model DesignSeattle Region
28Long-term Model DesignCurrent workSeattle Region
29Overview of Meteorological Forecast Process
- National Centers for Environmental Prediction
30NCEP Forecast
- A set of 20 equally likely ensembles of paired
precipitation and temperatures generated by GSM
with slight variations in initial conditions - Downloaded from NCEP ftp site
- Forecasts bias-corrected and downscaled
31DHSVMDistributed Hydrology, Soil-Vegetation Model
- Characterizes basin hydrology with
- Elevation, aspect and slope data
- Soil type and vegetation data
- Stream network
- Meteorological data
- Energy balance for snow
- Mass balance for precipitation and run-off
32DHSVMDistributed Hydrology, Soil-Vegetation Model
33Streamflow Forecast
- System is initiated with one year of previous
conditions - Twenty assembles of paired precipitation and
temperatures are run. - Initial conditions are extremely important (same
future conditions are different with different
initiations) - Typically model underestimate summer flows
34Systems Simulation Model
- Model calculates movement of water throughout
system - Integrates water supply, demands, fish flows and
other operational considerations - Lacks subtleties of actual operation
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43Conclusions
- NCEP ensemble forecasts, combined with hydrologic
model, produced good summer forecasts for 2003. - Typically, NCEP ensemble forecasts, combined with
hydrologic model, provides does useful
information (exceptions noted). - Forecasts ranked by ENSO provides some insight
into forecast quality