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CBWM Phase 5 Status Report. Modeling Subcommittee Meeting October 2, 2002. Overview. Model structure and responsibilities Model segmentation Precipitation modeling. Model Responsibilities. Source data /p50X/pp/data/ CBP External transfer module (scripts) /p50X/pp/etm/ CBP

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cbwm phase 5 status report

CBWMPhase 5 Status Report

Modeling Subcommittee Meeting

October 2, 2002

  • Model structure and responsibilities
  • Model segmentation
  • Precipitation modeling
model responsibilities
Model Responsibilities
  • Source data


  • External transfer module (scripts)


  • Model parameters


  • Watershed-reach connection files


  • Downstream ID has been added to all reaches in the Chesapeake Bay Watershed except for those draining directly to the estuary. (Their ID is zero.)
  • Working on attributing the southern Virginia watersheds with DSID.
  • Reaches and watersheds have been reconnected so that we know what streams are in what watersheds.
  • Working on transferring the mean annual discharge attributes to the watersheds so we have the flow attribute in the names.
precipitation modeling
Precipitation Modeling
  • Objectives:
    • Spatially distribute recorded point-precipitation data to provide high-resolution, low-bias areal precipitation time-series data at an hourly time step for use as input to hydrologic models.
    • Provide areal precipitation time-series data that can be used in a consistent manner over a range of spatial scales.
precipitation modeling scope
Precipitation Modeling: Scope
  • Data used to achieve these objectives are daily and hourly recorded precipitation totals from climate stations within the study area, including a 25-km buffer around the area boundary.
  • Precipitation data are from the period 1985 through 2000.
precipitation modeling scope1
Precipitation Modeling: Scope
  • 487 daily-data stations
  • 192 hourly-data stations
precipitation modeling scope2
Precipitation Modeling: Scope
  • Daily precipitation data are simulated for 10-km square grid cells throughout the study area.
  • Daily precipitation for each FIPS2 area within the study area is computed based on time-series data from grid cells within each FIPS2 area.
xyz methodology
xyz Methodology
  • Multiple linear regression (MLR) equations are developed for daily precipitation (p) in each of six sub-regions using independent variables x, y, and z from climate stations in each sub-region.
  • The general form of the MLR equation is:
hourly disaggregation
Hourly Disaggregation
  • Simulated daily precipitation data are disaggregated into hourly data using:
    • recorded hourly precipitation from the nearest climate station, or
    • Mean-hourly precipitation by month and weather type.
  • Simulated daily p totals are preserved during disaggregation.
example data
Example Data
  • 10x10km daily data
  • January, 1990
  • mm/day
future plans
Future Plans
  • Complete trial Patuxent run
  • Complete F-tables
  • Begin PEST implementation
  • Continue investigating inclusion of estimates of ground-water residence times