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

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

Snowpack Energy Balance Components Ground heat

Energy Balance Formulation Hm = Hsn + Hln + Hc + He + Hg + Hp + Hq Model Formulation (on each HRU) PRMS SNOW MODEL Hsn = swrad * (1. - albedo) * rad_trncf Hln = emis * sb_const * tavg 4 (   T 4) Hc + He = cecn_coef(mo) * tavg (ppt days) = 0 (dry days) Hp = tavg * net_precip Hg assumed 0 Hq is computed

Snow Surface Albedo vs Time

Solar Radiation Transmission Coefficient vs Cover Density

Net Longwave Radiation Hlw = (1. - covden_win) * [(emis * air) -snow)] + covden_win * (air -snow) emis = emis_noppt no precip = 1.0 precip air and snow = sb_const * tavg 4 [ (   T 4 )  where tavg is temp of air and temp of snow surface

Energy Balance Formulation Hm = Hsn + Hln + Hc + He + Hg + Hp + Hq Model Formulation PRMS SNOW MODEL Hsn = SWRin * (1. - ALBEDO) * TRNCF Hln =   T 4 Hc + He = Cce * Tavg (ppt days) = 0 (dry days) Hp = Tavg * PTN Hg assumed 0 Hq is computed

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

Areal Snow Depletion Curve

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

Max Temperature-Elevation Relations

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

Precipitation-Elevation Relations

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

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

Precipitation Gauge Intercomparison Rabbit Ears Pass, Colorado

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

Precipitation Distribution Methods (module) Manual (precip_prms.f) Auto Elevation Lapse Rate (precip_laps_prms.f) XYZ (xyz_dist.f) PCOR Computation

Manual PCOR Computation

Auto Elevation Lapse Rate PCOR Computation For each HRU 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 precip lapse rate by month [pmo_rate(mo)] hru_psta hru_plaps

PCOR Computation pmn_mo padj_sn or padj_rn elv_plaps Auto Elevation Lapse Rate Parameters

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

San Juan Basin Observation Stations 37 XYZ Spatial Redistribution of Precip and Temperature 1. Develop Multiple Linear Regression (MLR) equations (in XYZ) for PRCP, TMAX, and TMIN by month using all appropriate regional observation stations.

XYZ Spatial Redistribution 2. Daily mean PRCP, TMAX, and TMIN computed for a subset of stations (3) determined by the Exhaustive Search analysis to be best stations 3. Daily station means from (2) used with monthly MLR xyz relations to estimate daily PRCP, TMAX, and TMIN on each HRU according to the XYZ of each HRU Precip and temp stations

2-D Example XYZ and Rain Day Frequency Elevation Mean Station Precipitation P1 P2 P3 Precipitation in the frequency station set but not the mean station set Precipitation in the mean station set Mean station set elevation Slope from MLR

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

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

PARAMETER ESTIMATION

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

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 operational modeling Focus of research modeling

Upper San Joaquin River, CA El Nino Year

ANIMAS RIVER, CO SURFACE GW SUBSURFACE PREDICTED MEASURED

EAST FORK CARSON RIVER, CA SURFACE GW SUBSURFACE

CLE ELUM RIVER, WA SURFACE GW SUBSURFACE

REMOTELY SENSED SNOW- COVERED AREA AND SNOWPACK WATER EQUIVALENT

Satellite Image for Snow-Covered Area Computation

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

East Fork Carson River, CA

Observed and Simulated Basin Snow-Covered Area

SIMULATED vs SATELLITE-OBSERVED SNOW-COVERED AREA

GUNNISON RIVER BASIN LOCATION Upper Colorado River Basin Gunnison River Basin

SUBBASINS WITH CONCURRENT STREAMFLOW AND SATELLITE DATA East River Taylor River Lake Fork Cochetopa Creek Tomichi Creek

Cochetopa Creek East River Lake Fork

Taylor River Tomichi Creek

east Percent Basin in Snow Cover

east

Percent Basin in Snow Cover

coch Percent Basin in Snow Cover

lake Percent Basin in Snow Cover

STARKWEATHER COULEE, ND

DEPRESSION STORAGE ESTIMATION (BY HRU) USING THE GIS WEASEL (AREA & VOLUME)

WETLANDS HYDROLOGY DEPRESSION STORES (flowing and closed) HRU 1 HRU 2 STORAGE HRU FLOW  GW PET FLOW

Snow-covered Area 1997 April 17 March 20 April 22 May 6 SNOW NO SNOW

1997 April 12April 22 Snowpack Water Equivalent Snow-covered Area

Snow-covered Area 1999 March 25 April 1 April 8 April 13 SNOW NO SNOW

1999 April 7April 8 Snowpack Water Equivalent Snow-covered Area