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Importance of Snow Measurements on the River Flood Modeling/Prediction

Importance of Snow Measurements on the River Flood Modeling/Prediction. Victor Koren, NOAA/NWS/OHD/HL Victor.Koren@noaa.gov. Outline. Importance of cold season processes How well do we model snow cover Some modeling results Data requirements.

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Importance of Snow Measurements on the River Flood Modeling/Prediction

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  1. Importance of Snow Measurements on the River Flood Modeling/Prediction Victor Koren, NOAA/NWS/OHD/HL Victor.Koren@noaa.gov

  2. Outline Importance of cold season processes How well do we model snow cover Some modeling results Data requirements

  3. Importance of Cold Season Processes on the Heat and Water Fluxes The figure displays differences in runoff for cold- and warm-season flood events on the Root river basin, MN, where frozen depth can be as much as 2m. The soil moisture content only can not explain significant differences in the amount of runoff generated by precipitation events of similar size. The figure displays differences in soil and air temperature relationship during warm and cold periods. After strong correlation during warm season there was no correlation at all when soil freezing and snow cover was occurred.

  4. Diurnal cycles of (a) skin temperature, (b) ice content change, (positive when freezing, and negative when thawing), and (c) the first layer soil temperature during snow free surface.

  5. Energy Based Snow-Frozen Ground parameterization (NOAH LSM) • - One-layer snow pack with explicit snow compaction and variable snow properties • - Multi-layer soil profile with explicit calculation of frozen/unfrozen soil moisture • Degree-day Based Model (SNOW-17) • - Simplified Heat Balance during rainfall events • - Degree-day Melt Factor during non-rain periods • - Some parameters should be adjusted to get better results

  6. 1970-1971 1973-1974 1976-1977 1975-1976 Observed and simulated snow water equivalent and depth from SNOW-17, Danville, Vermont. (Blue lines without use of precipitation phase, Red lines with use of precipitation phase)

  7. Effect of (a) fractional snow cover on (b) skin temperature and (c) sensible heat flux (negative to the atmosphere; positive to the soil) during snowmelt. Results from the new parameterization (solid lines) are plotted against the original Eta model (thick solid lines).

  8. Observed (thick solid line) and simulated soil temperature for the first layer using different snow Densities after heavy rain are plotted in the bottom panel.

  9. Simulated snow water equivalent (plot 3) and depth (plot 4) from NOAH-LSM (red lines) and SNOW-17 (white lines), Weissfluhjoch, Switzerland, 1992-1993.

  10. Simulated snow water equivalent and depth from NOAH-LSM and SNOW-17, Col de Porte, France, 1997-1998.

  11. Simulated snowmelt variables from NOAH-LSM & SNOW-17 Col de Porte, France February 10-22, 1998. Weather: Very low wind; High diurnal amplitude of air temperature Effect: (a) Much faster snowmelt from SNOW-17; (b) Significant effect of net radiation and liquid water refreezing

  12. Figure 2. Observed (white) and simulated (red) soil temperature at 20cm, 40cm, and 80cm depths. Valdai, Russia, 1971-1972.

  13. Figure 3. Observed (white) and simulated (red) soil temperature at 20cm, 40cm, and 80cm depths. Valdai, Russia, 1972-1973.

  14. Observed and simulated frost depth and frost index. Root river basin, MN.

  15. Observed hydrograph and simulated hydrograph, frost index, and water balance components. Hydrograph simulated with (red line) & without (yellow line) use of a frost index. Root river basin, MN.

  16. Summary • The model complexity does not guaranty a high accuracy • Simple models can provide a practically reasonable results under ‘usual’ weather • conditions if most important processes are accounted properly • Degree-day based models are sensitive to weather conditions, specifically wind • speed and solar radiation conditions • In regions with a deep snow cover, it is very important to account for a snow • liquid water state including its refreezing • Energy-based models are sensitive to input data errors specifically solar radiation • and albedo treatment • Some calibration/tunning is needed to get better results from both simple or • complex models that requires measurements of snow cover dynamics, solar • radiation in addition to solid precipitation

  17. Heat Transfer Parameterization (NOAH LSM) • N-layers soil column • The layer-integrated form of diffusion equation • Soil moisture and heat fluxes are simulated separately at each time step • Surface temperature is determined from the energy balance • Lower boundary is set at the climate annual air temperature • Unfrozen water content is calculated assuming that water potential and vapor pressure is in an equilibrium at the middle of each layer

  18. SNOW-17Surface Energy Exchange • Ta > 0oC – Snowmelt • If Rainfall > 0.25 mm/hr - Simplified Heat Balance Equation: - no Solar Radiation, - Atmosphere & Snow is a Black Body, - Relative Humidity = 90%, - Rainwater at an Air Temperature • Else • - Degree-day Melt Factor (Seasonal Variable) • Ta < 0oC – No Snowmelt • - Estimate Change in Snow Heat Deficit

  19. Transformation of SAC-SMA Storages into Soil Layers and Vice Versa

  20. Reduction in Percolation and Interflow Rates • Parameterization uses a threshold-type dependency of the reduction rate, • R, on the frost index and soil saturation • R = Rs + (1 – Rs)* DLZ • Rs = (1 – Cr)FIcr – FI • It mimics an empirical relationship between losses and soil saturation • and freezing depth

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