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Hydrologic Modeling for Sustainable Watershed Management

The Pocono Creek watershed is a 46.5 square mile basin located in Monroe County, PA, and is a part of the Delaware River Basin (DRB). The DRB Commission designated the creek as a Special Protection Water, as it has high water quality and is of great ecological value. The creek's notable wild brown trout population supports a significant regional economic boon, recreational fishing and activities.

Monroe County's population is projected to grow by 60% by 2020. Potential impacts of population growth and land use change include degradation and loss of forested and agricultural lands, depletion of groundwater and stream flows, and despoiling of wild brown trout populations. Urbanization would increase impervious surfaces (e.g. sidewalks, roads) and projected population growth would increase the demand for groundwater, which threaten the sustainability of the watershed's current base flows. Furthermore, reduced infiltration and increased runoff rates would elevate peak flows during storms.

A distributed hydrologic model has been constructed, calibrated, and validated using the ArcView-based Surface Water Assessment Tool (AVSWAT), two rainfall gauge stations, Next Generation Radar Rainfall Data (NEXRAD), and continuous streamflow measurements from a USGS gauge station near the mouth of the watershed.

We apply the model to achieve six objectives:

  1. compare model performance calibrated with NEXRAD rainfall data against that based on surface raingauge data;
  2. compute spatial distribution of annual groundwater recharge rates pre- and post-urbanization for use by a USGS groundwater flow model (MODFLOW) to simulate an increase in groundwater withdrawals on base flow reductions;
  3. predict the effects of urbanization on median monthly stream flows for the Pennsylvania Instream Flow Model (PIFM) to establish a relationship between groundwater withdrawals, and of surface water reductions on brown trout habitat at the watershed-scale;
  4. compute the effect of urbanization on potential changes in the frequency of low (i.e., base flow) and high stream flows;
  5. adapt a stochastic, time series model to compute output errors and predictive uncertainty; and
  6. identify significant areas of the watershed (i.e., those that urbanization influences to alter streamflow statistics).

Contact: Mohamed Hantush (EIMS#117863)

Office of Research & Development | National Risk Management Research Laboratory

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