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Progress on the Modification of SAC-HT Evapotranspiration Component Project

Progress on the Modification of SAC-HT Evapotranspiration Component Project. Victor Koren. Problem Description.

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Progress on the Modification of SAC-HT Evapotranspiration Component Project

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  1. Progress on the Modification of SAC-HT Evapotranspiration Component Project Victor Koren

  2. Problem Description 1. Recently, SAC-SMA was enhanced by incorporating heat transfer component, SAC-HT version. It accounts for the frozen ground effects and allows much better evaluation of the model by comparing, e.g., soil moisture and temperature at different soil layers 2. Evaluation of SAC-HT over Oklahoma region showed significant runoff volume bias and soil moisture underestimation for dry basins. The main reason is deficiency in SAC-HT evapotranspiration component that leads to disproportional removal of soil moisture from upper and lower zones

  3. Problem Description – cont’d 3

  4. Problem Description – cont’d Comparing Daily Runoff and Soil Moisture Simulated Using a Priori (yellow) and Climate Adjusted Parameters (purple) , #07316500, Gavg =0. 30 4

  5. Three steps are considered for the improvement of the water exchange mechanism of SAC-HT: Formulation of SAC-HT water exchange mechanism based on the Noah evapotranspiration parameterization Implementation of Noah-type canopy resistance parameterization Investigation of the potential for the use of simpler approaches of potential evaporation estimation Ongoing Modification to SAC-HT

  6. Soil Moisture Redistribution Etsp=f(Ep,σ,Si,Fr,Ft,Fq) Elo=f(ΔEp,Slo) Eup=f(Ep,Sup) Ebare=f(Ep,σ,S1) Ecan=f(Ep,σ,Sc) Etsp1 Etsp2 Etsp3 • SAC-SMA free water redistribution • (percolation based) • Noah tension water redistribution • (diffusion equation with only layer evaporation source) Etsp4

  7. Four canopy stress components: Solar radiation Soil Moisture Air humidity Air temperature Total canopy resistance combines all stress factors Actual evapotranspiration is a potential evaporation reduced by a plant coefficient estimated following Monteith approach Ch is the surface exchange coefficient, Rr represents the upward long wave radiation, Δ is a humidity/temperature gradient ratio Canopy Resistance Parameterization

  8. Changes to Noah Canopy Resistance Estimation Solar radiation is estimated from air temperature (Bristow & Campbell, 1984) Empirical relationship (Popov, 1948) is used in estimation of air humidity Logistic dose-response curve (Schenk & Jackson, 2002) is used for root distribution calculation Minimal stomatal resistance parameter (Rsmin) depends on climate not just vegetation type Rsmin = f(veg_type, Gind)

  9. Estimated half-hour Solar Radiation (left ) and Plant Coefficient (right) for three Locations: Alptal (Switzerland), Berm (Canada), and Fraser (USA) Correlation (R2): Solar Radiation Plant Coefficient Alptal 0.81 0.95 Berm 0.78 0.89 Fraser 0.77 0.95

  10. Observed and Simulated 1-hr Solar Radiation at Alptal (Switzerland), March 2003

  11. Observed (red) and Simulated Soil Moisture at 5cm (4), 0-25 (5), 25-75 (6), and Upper (2) & Lower (3) SAC Storages: ARNE site (Climate Index = 0.306).Lines: white – SAC, purple – Mod_SAC, yellow - Noah

  12. Soil Moisture Climatology from SAC-HT and Modified SAC-HT vs Measurements

  13. Overall statistics for 10 Oklahoma basins

  14. Soil Moisture Simulations using Climate (purple) and Penman estimated (yellow) PET, WTTO2

  15. OHD Climatological and Penman-based PETBasin WTTO2, G=0.63 Statistics using uniformly adjusted Penman PET: Runoff: RMSE=15.4(21.2), Bias=7.5(14.9), NS=0.71(0.45) Upper: RMSE=0.12(0.12), Bias=0.02(0.05), NS=0.43(0.44) Lower: RMSE=0.08(0.07), Bias=0.004(0.03), NS=0.51(0.60)

  16. Soil Moisture Simulations using Climate (purple) and Penman estimated (yellow) PET, #7300500

  17. OHD Climatological and Penman-based PETBasin 7300500, G=0.27 Statistics using uniformly adjusted Penman PET: Runoff: RMSE=1.41(1.56), Bias=-0.93(-1.02), NS=-0.30(-0.59) Upper: RMSE=0.10(0.11), Bias=-0.03(-0.06), NS=0.03(-0.18) Lower: RMSE=0.12(0.14), Bias=-0.09(-0.12), NS=-0.76(-1.44)

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