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PRECIPITATION-RUNOFF MODELING SYSTEM (PRMS). MODELING OVERVIEW & DAILY MODE COMPONENTS. BASIC HYDROLOGIC MODEL. Q = P - ET ± S. Components. Runoff Precip Met Vars Ground Water
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PRECIPITATION-RUNOFF MODELING SYSTEM(PRMS) MODELING OVERVIEW & DAILY MODE COMPONENTS
BASIC HYDROLOGIC MODEL Q = P - ET ± S Components Runoff Precip Met Vars Ground Water Soil Moisture Reservoirs Basin Chars Snow & Ice Water use Soil Moisture
SUGGESTED REGERENCE ON WATERSHED MODELING - Overview chapters on basic concepts - 25 Models, each a chapter with discussions of model components and assumptions
PRMSParameters MMS Version
PRMS Features • Modular Design • Deterministic • Distributed Parameter • Daily and Storm Mode • Variable Time Step • User Modifiable • Optimization and Sensitivity Analysis
SPATIAL CONSIDERATIONS LUMPED MODELS - No account of spatial variability of processes, input, boundary conditions, and system geometry DISTRIBUTED MODELS - Explicit account of spatial variability of processes, input, boundary conditions, and watershed characteristics QUASI-DISTRIBUTED MODELS - Attempt to account for spatial variability, but use some degree of lumping in one or more of the modeled characteristics.
GRID-BASED MODELS TOPMODEL Distributed Approaches - Explicit grid to grid - Statistical distribution ----(topgraphic index)
Distributed Parameter Approach Hydrologic Response Units - HRUs HRU Delineation Based on: - Slope - Aspect - Elevation - Vegetation - Soil - Precip Distribution
HRU DELINEATION AND CHARACTERIZATION Grid Cell Hydrologic Response Units (HRUs) Polygon Hydrologic Response Units (HRUs)
MODEL DRIVING VARIABLES - TEMPERATURE - max and min daily - lapse rate varied monthly or daily - PRECIPITATION - spatial and elevation adjustment - form estimation
MODEL DRIVING VARIABLES - SOLAR RADIATION - measured data extrapolated to slope-aspect of each HRU - when no measured data, then estimated using temperature, precip, and potential solar radiation - max daily temperature procedure - daily temperature range procedure
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.
Mean Daily Precipitation Schofield Pass (10,700 ft) vs Crested Butte (9031 ft) Mean daily precip, in. MONTH
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 For each HRU - DEPTH hru_precip(hru) = precip(hru_psta) * pcor(mo) pcor(mo) = Rain_correction or Snow_correction
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
[ ] tmax(hru) - tmax_allsnow prmx = * adjmix_rain(mo) (tmax(hru) - tmin(hru) PRECIPITATION For each HRU - FORM (rain, snow, mixture of both) MIXTURE OTHER Precipitation Form Variable Snowpack Adjustment
PCORComputation Precipitation Distribution Methods(module) • Manual (precip_prms.f) • Auto Elevation Lapse Rate (precip_laps_prms.f) • XYZ (xyz_dist.f)
PCORComputation • Manual
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)]
PCORComputation Auto Elevation Lapse Rate Parameters pmn_mo elv_plaps padj_sn or padj_rn
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)
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. San Juan Basin Observation Stations 37
XYZ Distribution Exhaustive Search Analysis - Select best station subset from all stations - Estimate gauge undercatch error for snow events - Select precipitation frequency station set
Precip and temp 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
P1 Mean Station Precipitation P2 P3 Elevation 2-D Example XYZ and Rain Day Frequency Slope from MLR Precipitation in the mean station set Precipitation in the frequency station set but not the mean station set Mean station set elevation
Application of XYZ Methodology Chesapeake Bay Subdivide the monthly MLRs by Sea Level Pressure (SLP) patterns using a map-pattern classification procedure Sea Level Pressure Patterns Low SLP High SLP
Application of XYZ Methodology Chesapeake Bay PRCP subdivided by SLP Mean Daily Precipitation 0 1 2 3 4 5 6 7 Sea Level Pressure Patterns Mean Daily PRCP (mm/day) Low SLP High SLP
SOLAR RADIATION For each HRU swrad(hru) = ( pot_rad(hru) / pot_horad ) * orad /cos_slp(hru) where orad is observerd sw radiation pot_rad and pot_horad are computed from hru slope, aspect, & latitude - Missing orad is computed byeither - obs_tmax - SolarRad relation - [obs_tmax - obs_tmin] --> sky cover --> SolarRad relation
Degree-Day Solar Radiation Estimation Procedure (non precip day) For days with precip, daily value is multiplied by a seasonal adjustment factor
ccov tmax - tmin Temperature-Range Radiation Estimation Procedure (non precip day) ccov = ccov_slope(mo) * (obs_tmax – obs_tmin) + ccov_intcp(mo) orad/pot_rad = crad_coef + (1. – crad_coef) * [(1. – ccov)** crad_exp] crad_coef and crad_exp from Thompson, 1976, WRR For days with precip, daily value is multiplied by a seasonal adjustment factor
DRIVING VARIABLE INPUT SOURCES • Point measurement data • Radar data • Satellite data • Atmospheric model data
RADAR DATA NEXRAD vs S-POL, Buffalo Creek, CO