The most common cause of Sanitary Sewer Overflow stems from heavy rainfall events which cause massive infiltration of stormwater into sewerage lines. Blockage or rupture of sewerage lines also contribute to SSOs.
Municipal system owners look to civil engineers to determine the causes of SSOs and to design the most cost effective approach to eliminate them. The engineer's first step is often to perform a study to determine the causes and sources of the inflow and infiltration. An I/I study models the sanitary system, including determining how wet weather (especially those heavy rainfalls) will affect the system.
When it comes to wet weather responses, the antecendent moisture level can have a huge and vaying impact on the system's performance. From Wikipedia, antecedent moisture is a term that describes the relative wetness or dryness of a sewershed, which changes continuously and can have a very significant effect on the flow responses in these systems during wet weather. Antecedent moisture conditions are high when there has been a lot of recent rainfall and the ground is moist. Antecedent moisture conditions are low when there has been little rainfall and the ground becomes dry. So when you get down to it, a model that does not take antecedent moisture into account in determining a sewer system's capacity to respond to wet weather isn't really very accurate (or useful!) at all.
For more reading about hydrologic models that accurately account for antecedent moisture impacts, check out this overview of i3D, an antecedent moisture model:
Hydrologic model i3d white paper
View more documents from OHM Advancing Communities.
But wait, there's more! OHMers Tim Kuhns and Robert Czachorski recently presented a paper at the Water Environment Federation's national Collections Systems Conference. The case study outlined an inflow and infiltration modeling study in Scio Township, Michigan. The project demonstrated the value of a comprehensive approach that includes a highly accurate hydrologic model and radar reflectivity data to identify and correct a rainfall measurement error.
In the paper and presentation, Tim shares several interesting findings for a comprehensive approach to modeling:
-A continuous model that accurately predicts flows can be used to identify anomalies with rainfall and flow measurements. An event based model may not as easily identify these types of errors.
-A thorough evaluation of all error components (model prediction, rainfall, flow) should be completed for major calibration events to ensure model accuracy and confidence in the model results.
-Free and readily available radar reflectivity data can be used without pre-processing to assess the accuracy of rainfall measurements.
