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CBWM Phase 5 Status Report

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

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  1. CBWMPhase 5 Status Report Modeling Subcommittee Meeting October 2, 2002

  2. Overview • Model structure and responsibilities • Model segmentation • Precipitation modeling

  3. Model Responsibilities • Source data /p50X/pp/data/CBP • External transfer module (scripts) /p50X/pp/etm/CBP • Model parameters /p50X/pp/lib/catalogs/modules/USGS • Watershed-reach connection files /p50X/pp/lib/connect/USGS

  4. Segmentation • 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.

  5. Segmentation • 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.

  6. 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.

  7. 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.

  8. Precipitation Modeling: Scope • 487 daily-data stations • 192 hourly-data stations

  9. 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.

  10. 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:

  11. 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.

  12. Mean-hourly rainfall (Feb)

  13. Example Data • 10x10km daily data • January, 1990 • mm/day

  14. Future Plans • Complete trial Patuxent run • Complete F-tables • Begin PEST implementation • Continue investigating inclusion of estimates of ground-water residence times

  15. “on the graph paper”

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