WMS:Overview of Floodplain Delineation

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In addition to stream network and drainage basin delineation, WMS can also be used to perform floodplain delineation. Water levels simulated by a river hydraulic model or collected from different sources are read from a text file as a scatter data set (see preparing stage data for more help). A smooth water surface is constructed by interpolating water levels at TIN vertices. User specified flood barriers such as embankments, roads, etc are also considered during this process. This surface is then intersected with the triangles in TIN representing the ground elevations, and the resulting set of edges defines the floodplain.

The basic steps to performing a flood plain delineation in WMS include:

  • Prepare a triangulated irregular network (TIN) surface of the area where the delineation is to be performed. This can be done by reading scattered elevation, converting from a DEM, or digitizing a contour map.

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  • Prepare your water surface elevation data. Water elevations data consists of a series of surface water elevations points defined as x, y, z (where z is the elevation of the water surface). Such points could be the results of a hydraulic model simulation, calculated in the WMS channel calculator, or retrieved from a known gaging station. They are stored as a scatter dataset.

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  • Select the appropriate options for delineating the flood plain, including the possibility of using a barrier coverage, and then delineate the flood.

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  • The result of the flood plain delineation will be a new dataset of water surface elevations and/or inundation depths. These datasets can be used to display contours on the TIN and converted to a series of output coverages (maps), including a flood depth map and impact maps derived from two separate delineations.

Stochastic Modeling

The flood plain delineation tools are connected with the HEC-1 hydrologic model and HEC-RAS hydraulic model to perform a series of floodplains based on the results of a series of model runs where rainfall, CN, and Manning's n are varied stochastically within a range of valid results.


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