Improving model hydrology accuracy using antecedent moisture modeling: Reparameterization update and case study

Developing simple and accurate hydrologic models for wet-weather sanitary sewer flow has long been enigmatic for the engineering community. Sanitary sewers respond to precipitation at various scales from hours to weeks to months. The flow response to precipitation is highly dependent upon antecedent moisture conditions and seasonality.

The Antecedent Moisture Model (AMM) was presented at ICWMM in 2021 by Robert Czachorski. This model is an empirically-calibrated method which models a capture coefficient which varies by antecedent moisture and by season. AMM has been particularly successful in modeling sanitary sewer infiltration, for which prior methods perform poorly.

A working group of AMM users has reparametrized the original model to improve interpretability and ease of use. The reparametrized model is designed to be more intuitive, scale independent, and timestep independent, while remaining essentially equivalent to the original model. These changes will be briefly presented and explained.

This presentation will also provide a case-study for the City of Joliet. The City’s model dating from 2015 was calibrated using the RTK method. The model was being used to size a sanitary storage tank for its Long-Term Control Plan (LTCP), which had been planned for over a decade. However, it was determined that the RTK method was unable to adequately calibrate to basins which had widely varying amounts of infiltration depending on antecedent moisture condition. After reviewing alternative hydrologic methods it was decided to recalibrate the model using the AMM method. The recalibrated model resulted in a much better calibration. With the newly calibrated model a Long-Term Continuous Simulation (LTCS) was run using historical data which showed that in fact no sanitary storage would be required. Using this evidence the City was able to obtain regulatory approval to remove this requirement from its Long-Term Control Plan, saving the City an estimated $8 million.

 Click here to watch recorded presentation on YouTube.