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InfoSewer Load Allocator brings you unprecedented speed, accuracy, and flexibility for calculating, distributing, and managing wastewater loads (load factors) 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 sewer collection systems. It considers existing system conditions, future developments and various planning horizons - an indispensable aid in staging capital improvement programs.

Load Allocator Fully Supports ArcGIS Definition Queries

Working with huge data sets as part of your model build process is no longer an issue. InfoSewer 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 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 Sanitary Sewer flow 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.