Participation
Assignment No. 1
Tracking Hotspots:
Putting Sewer Cleaning on the Map, WaterWorld Magazine.
This
article discusses the use of ArcGIS and ArcPy in particular to track distressed
areas of the sewer system that need frequent cleaning. A rise in sanitary overflows and sewer
stoppages at the Town of Mooresville, NC in 2010, due to an aging
infrastructure and the tripling of the population, resulted in the need for
distressed spots (hotspots) to be identified for maintenance.
Monthly
data, stored in Excel, containing the manhole location and last time the
corresponding sewer main was cleaned needed to be converted into a map to
identify anticipated hotspots. Python
scripting was used to process the batch of Excel data to generate a
comprehensive dataset. The resulting
dataset was joined with the features of the town’s sanitary sewer system which
had been recently created in ArcGIS.
Reports were created by using the ArcPy function in Python to present
the results.
Python
was used to automate the analysis process in ArcGIS resulting in color coded
maps representing cleaning frequency and identifying anticipated hotspots. With Python, the Analyst Frequency Tool was
used to calculate the number of sewer mains and length cleaned in a given month
and the process was automatically repeated by Python for each month and merged
into a single comprehensive layer.
The
resulting map facilitated the identification of areas that require more
frequent inspections and increased pumping/cleaning particularly for food
service establishments thus remedying problem grease interceptors in multiple
occasions. Productivity increased and
main-line stoppages decreased resulting in cost savings including less
overtime.
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