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Streamflow Predictability. Sources of Predictability. Model solutions to the streamflow forecasting problem…. Historical Data. SNOW-17 / SAC. Historical Simulation. SWE. SM. Q. Past. Future. - PowerPoint PPT Presentation
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Streamflow Predictability
Historical Simulation
Q
SWESM
Historical Data
Past Future
SNOW-17 / SAC
Sources of Predictability
1. Run hydrologic model up to the start of the forecast period to estimate basin initial conditions;
Model solutions to the streamflow forecasting problem…
Historical Simulation
Q
SWESM
Historical Data Forecasts
Past Future
SNOW-17 / SAC SNOW-17 / SAC
1. Run hydrologic model up to the start of the forecast period to estimate basin initial conditions;
2. Run hydrologic model into the future, using an ensemble of local-scale weather and climate forecasts.
Sources of PredictabilityModel solutions to the streamflow forecasting problem…
• Physically based conceptual model• Two-layer model
– Upper layer: surface and interception storages– Lower layer: deeper soil and ground water
storages• Routing: linear reservoir model• Integrated with snow17 model
Sacramento Soil Moisture Accounting (SAC-SMA) model
Rainfall - Evapotranspiration - Changes in soil moisture storage = Runoff
• Model parameters: 16 calibrated parameters
• Input data: basin average precipitation (P) and Potential Evapotranspiration (PET)
• Output: Channel inflow (Q)
Soil Tension and Free Water
Sacramento Model StructureE T Demand
Impervious Area
E T
E T
E T
E T
Precipitation Input
Px
Pervious Area
E T
Impervious Area
Tension Water
UZTW Free Water
UZFW
PercolationZperc. Rexp
1-PFREE PFREE
Free WaterTension Water P S
LZTW LZFP LZFS
RSERV
Primary Baseflow
Direct Runoff
Surface Runoff
Interflow
Supplemental Base flow
Side Subsurface Discharge
LZSK
LZPK
Upper Zone
Lower Zone
EXCESS
UZK
RIVA
PCTIM
ADIMP
Total Channel Inflow
Distribution Function Streamflow
Total Baseflow
Model ParametersPXADJ Precipitation adjustment factorPEADJ ET-demand adjustment factorUZTWM Upper zone tension water capacity (mm)UZFWM Upper zone free water capacity (mm)UZK Fractional daily upper zone free water withdrawal ratePCTIM Minimum impervious area (decimal fraction)ADIMP Additional impervious area (decimal fraction)RIVA Riparian vegetation area (decimal fraction)ZPERC Maximum percolation rate coefficientREXP Percolation equation exponentLZTWM Lower zone tension water capacity (mm)LZFSM Lower zone supplemental free water capacity (mm)LZFPM Lower zone primary free water capacity (mm)LZSK Fractional daily supplemental withdrawal rateLZPK Fractional daily primary withdrawal ratePFREE Fraction of percolated water going directly to lower zone free water storageRSERV Fraction of lower zone free water not transferable to lower zone tension waterSIDE Ratio of deep recharge to channel baseflowET Demand Daily ET demand (mm/day)PE Adjust PE adjustment factor for 16th of each month
State VariablesADIMC Tension water contents of the ADIMP area
(mm)UZTWC Upper zone tension water contents (mm)UZFWC Upper zone free water contents (mm)LZTWC Lower zone tension water contents (mm)LZFSC Lower zone free supplemental contents
(mm)LZFPC Lower zone free primary contents (mm)
How the SAC-SMA Model Works
Study site: Root River basin in MN
• Drainage area: 1593 km2
• Largely agricultural (72%), USDA
• Receives 29 to 33 inches of annual precipitation
Root River basin
Greens Bayou river basin in eastern Texas
• Hourly discharge data • Hourly Mean Areal Precipitation • Model running time step is hourly
• Drainage area: 178 km2
• Most of the basin is highly developed • Humid subtropical climate (890-1300 mm annual rain)
Data for SAC-SMA
SMADA Basins
Error Growth models
• Lorenz, 1982
∂E∂t
= α E 1 −EE∞
⎛⎝⎜
⎞⎠⎟
Greens Bayou Precip forcing fields – Nov 17, 2003 tornado