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DWF
Allocator
InfoSWMM DWF Allocator brings you unprecedented
speed, accuracy, and flexibility for calculating,
distributing, and managing Dry Weather Flows (wastewater
loads) in your sewer network model. The program
automatically and reliably computes and assigns
wastewater loads generated by your various customer
categories (e.g., land use and population characteristics,
sanitary service areas, ownership parcel data),
using state-of-the-art geospatial polygon processing
and advanced flow estimating GIS technology. This
will ensure the development and simulation of
credible hydraulic models of your sanitary and
combined sewer collection systems. It considers
existing system conditions, future developments
and various planning horizons - an indispensable
aid in staging capital improvement programs.
DWF Load Allocator Fully
Supports ArcGIS Definition Queries
Working with huge data sets as part of your model
build process is no longer an issue. InfoSWMM
and all associated Suite Modules now fully support
ArcGIS Definition Queries. This allows master
planners and model builders to quickly use any
subset of GIS data with blazing speed in relation
to loading and using entire GIS data sets. This
is especially important in regards to use of the
DWF (Dry Weather Flow) Load Allocator. In a typical
large system, there may be many thousands and
10's of thousands of meter records (in the largest
cases multiple 100's of thousands). When water
meter records are not available for a sewer system,
it is typical to have ERUs (or Equivalent Residential
Units) to identify DWF Sewer loads.
Allocating loads for these huge numbers of meters
or ERUs can be extremely time consuming. Using
a simple Definition Query to identify only meters
that meet your needs i.e. either commercial, residential,
industrial, and others; or only ones that match
a geographical areas such as each pressure zone,
City A out of a County's worth of meter data,
or other geographical data; are a couple instances
of where this new capability will save hours,
days, or weeks of manipulation of model background
data.
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