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PRECIPITATION-RUNOFF MODELING SYSTEM (PRMS)

PRECIPITATION-RUNOFF MODELING SYSTEM (PRMS). SNOW MODELING OVERVIEW. PRMS. PRMS Parameters original version. PRMS Parameters. MMS Version. SNOW PROPERTIES. Porous media Undergoes metamorphosis Surface albedo changes with time Density increases with time Has a free-water holding capacity.

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PRECIPITATION-RUNOFF MODELING SYSTEM (PRMS)

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  1. PRECIPITATION-RUNOFF MODELING SYSTEM(PRMS) SNOW MODELING OVERVIEW

  2. PRMS

  3. PRMS Parametersoriginal version

  4. PRMSParameters MMS Version

  5. SNOW PROPERTIES • Porous media • Undergoes metamorphosis • Surface albedo changes with time • Density increases with time • Has a free-water holding capacity

  6. Energy Balance Formulation Hm = Hsn + Hln + Hc + He + Hg + Hp + Hq Temperature-Index Formulation M = Cm * ( Ta - Tb) Modifications Seasonal adjustment to Cm Vary Cm for forest and open Use equation only for non rain days Account for Hg and Hq

  7. Snowpack Energy Balance Components

  8. PRMS SNOW MODEL Energy Balance Formulation Hm = Hsn + Hln + Hc + He + Hg + Hp + Hq Model Formulation (on each HRU) Hsn = swrad * (1. - albedo) * rad_trncf Hln = emis * sb_const * tavg4 (es T4) Hc + He = cecn_coef(mo) * tavg (ppt days) = 0 (dry days) Hp = tavg * net_precip Hg assumed 0 Hq is computed

  9. Snow Surface Albedo vs Time

  10. Solar Radiation Transmission Coefficient vs Cover Density

  11. Net Longwave Radiation Hlw = (1. - covden_win) * [(emis * air) -snow)] + covden_win * (air -snow) air and snow = sb_const * tavg4 [ (es T4) e = 1.] where tavg is temp of air and temp of snow surface emis = emis_noppt no precip = 1.0 precip

  12. PRMS SNOW MODEL Energy Balance Formulation Hm = Hsn + Hln + Hc + He + Hg + Hp + Hq Model Formulation Hsn = SWRin * (1. - ALBEDO) * TRNCF Hln = es T4 Hc + He = Cce * Tavg (ppt days) = 0 (dry days) Hp = Tavg * PTN Hg assumed 0 Hq is computed

  13. SNOWPACK DYNAMICS • 2-layered system • energy balance: 2 12-hour periods • energy exchange between layers -- conduction and mass transfer • Tsurface = min(tavg or 0o C) • Tpack is computed • density = f(time, settlement constant) • albedo decay = f(time, melt) • melt volume: use depth-area depletion curve

  14. Areal Snow Depletion Curve

  15. MELT SEQUENCE cal_net > 0 snowmelt = cal_net / 203.2 pk_temp < 0o C refreeze to satisfy pk_def pk_temp = 0o C satisfy free water holding capacity(freeh2o_cap) remaining snowmelt reaches the soil surface

  16. Max Temperature-Elevation Relations

  17. TEMPERATURE For each HRU tmax(hru) = obs_tmax(hru_tsta) - tcrx(mo) tmin(hru) = obs_tmin(hru_tsta) - tcrx(mo) where tcrx(mo) = [ tmax_lapse(mo) * elfac(hru)] - -------------tmax_adj(hru) elfac(hru) = [hru_elev - tsta_elev(hru_tsta)] / 1000.

  18. Precipitation-Elevation Relations

  19. Mean Daily Precipitation Schofield Pass (10,700 ft) vs Crested Butte (9031 ft) Mean daily precip, in. MONTH

  20. Precipitation Gage Catch Error vs Wind Speed (Larsen and Peck, 1972) Rain (shield makes little difference) Snow (shielded) Snow (unshielded)

  21. Precipitation Gauge Intercomparison Rabbit Ears Pass, Colorado

  22. PRECIPITATION For each HRU - DEPTH hru_precip(hru) = precip(hru_psta) * pcor(mo) pcor(mo) = Rain_correction or Snow_correction

  23. PCORComputation Precipitation Distribution Methods(module) • Manual (precip_prms.f) • Auto Elevation Lapse Rate (precip_laps_prms.f) • XYZ (xyz_dist.f)

  24. PCORComputation hru_plaps • Auto Elevation Lapse Rate For each HRU hru_psta hru_psta = precip station used to compute hru_precip [ hru_precip = precip(hru_psta) * pcor] hru_plaps = precip station used with hru_psta to compute ------ -------preciplapse rate by month [pmo_rate(mo)]

  25. PCORComputation Auto Elevation Lapse Rate Parameters pmn_mo elv_plaps padj_sn or padj_rn

  26. PCORComputation pmn_mo(hru_plaps) - pmn_mo(hru_psta) pmo_rate(mo) = elv_plaps(hru_plaps)-elv_plaps(hru_psta) For each HRU • Auto Elevation Lapse Rate hru_elev - elv_plaps(hru_psta) adj_p = pmo_rate * pmn_mo(hru_psta) snow_adj(mo) = 1. + (padj_sn(mo) * adj_p) if padj_sn(mo) < 0. then snow_adj(mo) = - padj_sn(mo)

  27. PRECIPITATION For each HRU - FORM (rain, snow, mixture of both) RAIN tmin(hru) > tmax_allsnow tmax(hru) > tmax_allrain(mo) SNOW tmax(hru) <= tmax_allsnow

  28. PRECIPITATION For each HRU - FORM (rain, snow, mixture of both) MIXTURE prmx = [(tmax(hru) - tmax_allsnow) / -------------------------(tmax(hru) - tmin(hru)] * adjmix_rain(mo) OTHER Precipitation Form Variable Snowpack Adjustment

  29. PARAMETER ESTIMATION

  30. PRMS Parameters Estimated • 9 topographic (slope, aspect, area, x,y,z, …) • 3 soils (texture, water holding capacity) • 8 vegetation (type, density, seasonal interception, radiation transmission) • 2 evapotranspiration • 5 indices to spatial relations among HRUs, gw and subsurface reservoirs, channel reaches, and point measurement stations

  31. BASIN DELINEATION AND CHARACTERIZATION Polygon Hydrologic Response Units (HRUs) (based on slope, aspect, elevation, vegetation) Grid Cell Hydrologic Response Units (HRUs) (Equal to Image Grid Mesh) Focus of research modeling Focus of operational modeling

  32. Upper San Joaquin River, CAEl Nino Year

  33. SUBSURFACE SURFACE GW ANIMAS RIVER, CO PREDICTED MEASURED

  34. EAST FORK CARSON RIVER, CA SURFACE SUBSURFACE GW

  35. CLE ELUM RIVER, WA SUBSURFACE SURFACE GW

  36. REMOTELY SENSED SNOW-COVERED AREA AND SNOWPACK WATER EQUIVALENT

  37. Satellite Image for Snow-Covered Area Computation

  38. NASA Regional Earth Science Applications Center Objective - Integrate remotely sensed data into operational resource management applications SW Center - U of AZ, U of CO, USGS, --------------Lawrence Berkeley Labs ~ 1 km pixel resolution of NOAA snow-covered area product on 750 km2 basin

  39. East Fork Carson River, CA 1986 1988 1986

  40. Observed and Simulated Basin Snow-Covered Area

  41. SIMULATED vs SATELLITE-OBSERVED SNOW-COVERED AREA

  42. SIMULATED vs SATELLITE-OBSERVED SNOW-COVERED AREA

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