COMET Hydromet 00-2 7 March 2000

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National Weather ServiceRiver Forecast
SystemModel Calibration

• COMETHydromet 00-27 March 2000
• 2290 East Prospect Road, Suite 1
• Fort Collins, Colorado 80525

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Calibration

• Calibration process
• Estimation of parameter values which will
  minimize differences between observed and
  simulated streamflows
• Calibration problems
• Parameter interaction
• Non-unique solutions
• Time-consuming
• Inaccuracies
• Non-linearities
• Lack of understanding

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Calibration System

• Parameter estimation/optimization and watershed
  simulation
• Input
• Point or areal estimates of historical
  precipitation, temperature, and potential
  evaporation
• Initial hydrologic conditions
• Output
• Basin areal averages for point value inputs
• Simulated hydrographs for historical analysis or
  use in ESP
• Parameter values for models in operational
  forecast and ESP systems

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Calibration System (continued)

• Characteristics
• Performs computations for few forecast points for
  many time steps
• Uses operations table
• Compatible with operational system and ESP
• Produces graphical output for manual calibration
• Includes algorithms for automatic optimization
• Applications
• Historical watershed simulation
• Model calibration

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Model Calibration

• Strategy
• Select river system
• Prepare data
• MAP - Mean Areal Precipitation
• MAT - Mean Areal Temperature
• PE - Potential Evaporation
• QME - Mean Daily Discharge
• QIN - Instantaneous Discharge

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Model Calibration (continued)

• Calibrate least complicated headwater basins
• Select calibration period
• Estimate initial parameter - observed Qs
• Trial and error using MCP
• Statistics, observed versus simulated plots
• Proper approach to parameter adjustment
• Automatic parameter optimization - OPT
• Fine tuning - MCP
• Calibrate other headwater areas
• Calibrate local areas

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Model Calibration (continued)

• Important considerations
• Model structure, simulation processes
• Effects of parameter changes
• Use of the forecast information

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Data Preparation

• MAP Algorithms - Mean Areal Precipitation
• Techniques for converting point precipitation
  measurements into areal measurements and
  distributing them properly in time
• Daily and hourly data
• Grid point algorithm
• Estimating precipitation at a point (1/D2)
• Estimate gtleast, ltgreatest
• 100-150 points within basin
• Normalize at each grid point, then renormalize
• Thiessen weights
• Grid point versus Thiessen
• Two-pass algorithm - distribute daily, then
  estimate missing
• Consistency plots
• MAT Algorithms - Mean Areal Temperature
• Max - min data
• Grid point algorithm (1/D)
• Elevation weighting factor
• Centroid (1/DP)
• Conversion to mean temperatures
• Consistency plots

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Historical Data Analysis

• General Information Needed
• Station data on Calibration files
• Station history infro - obs times, changes,
  location, moves

• Topog map of basin

MAP Specific Information Non- Mountainous
Mountains --basin boundary --isohyetal
map
--station weights
MAT Specific Information --mean max/min
temperatures Non-Mountainous Mountains
--basin boundary --areal-elev curve
MAPE Specific Information --Evaporation
maps --mean monthly evap --station weights

• PXPP
• check consistency
• compute normals

• MAT3
• check consistency

• MAPE
• check consistency
• generate daily time
• series of MAPE

• TAPLOT3
• get mean max/min for
• mean zone elevation

• MAP3
• (re)check consistency
• generate time series
• of MAP

• MAT3
• generate time
• series of MAT

Temperature
Evaporation
Precipitation
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Sacramento Soil Moisture Accounting Model
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Sacramento Model Structure
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Hydrograph Decomposition
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Sacramento Soil Moisture Components
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Initial Soil-moisture ParameterEstimates By
Hydrograph Analysis
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Initial Soil-moisture Parameter Estimates By
Hydrograph Analysis (continued)

• LZSK - Supplemental baseflow recession
  (always gt LZPK)
• Flow that typically persists anywhere from 15
  days to 3 or 4 months

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Initial Soil Moisture Parameters Estimates by
Hydrograph Analysis (continued)
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Initial Soil Moisture Estimates by Hydrograph
Analysis (continued)
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Multiyear Statistical Output
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Multiyear Statistical Output (continued)
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Automatic Optimization

• Program OPT3
• Uses operations table
• Compatible with MCP, OFS, ESP
• Objective functions
• Daily RMS error
• Monthly volume RMS error
• S - O Exp.
• log S - log O Exp.
• Correlation coefficient
• Maximum Likelihood Estimator

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Automatic Optimization (continued)

• Program OPT3 (continued)
• Optimization schemes
• Pattern search
• Adaptive random search
• Shuffled complex evolution
• Buffer
• Exclusion periods
• Low flows
• Convergence criteria
• Optimize SAC-SMA, SNOW-17, UG, API-SLC, XIN-SMA

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