Modeling Rain-Derived Inflow and Infiltration (RDII) Sources in the Absence of Condition Assessment Information

Typically, inflow and infiltration (I/I) sources are identified during condition assessments; however, knowing where to begin with your assessment efforts can be difficult to determine. Flow monitoring can prioritize flow meter basins for further study, but this approach presents a host of challenges with well over 1,000 flow meter basins. With an impending consent decree, the City of Houston needed an out-of-the-box solution to assessing their 1,500 flow meter basins. So the City and RJN set out to tackle the challenge of modeling I/I to create a prioritized assessment program, affectionally called the 'I/I Cafeteria Plan.' The City wanted a way to prioritize meter basins and estimate quantities of I/I while idenfitying potential I/I sources-manholes, gravity mains, service lines, etc. This tool would consider the unique challenges for a flat coastal city with no zoning regulations and would ultimately enable the City to efficiently and cost-effectively implement I/I reduction solutions. A phased approach was identified as the most pragmatic course of action, and four phases were established; Phases I and II created the framework of the model, Phase III calibrated the model, Phase IV will implement modeling automation solutions. Ideally, during the first two phases, characteristics such as age, material, size, elevation, grade, soil type, groundwater level, surface cover, and drainage area would be used to complete an evaluation. Unfortunately, the City's GIS lacked systemwide data for several of these characteristics, so it was decided that the model would be established with the following criteria:
- age, size, and material would be used for gravity mains;
- parcels would be used for service lines;
- and age alone would be used for manholes.
RJN's prior work throughout the City's sewer system provided a large dataset to fill gaps and establish the model framework through a desktop study.
The results of Phases I and II included the development of recommendations and their associated costs. This combination of characteristics divided the City of Houston's gravity mains into 120 different classifications. Estimated I/I rates per foot were developed for gravity mains based on actual observations from the City's and RJN's data sets. Available data for service lines was minimal, so it was decided to use parcel data to represent connection points to gravity mains. Equations were developed to estimate the number of defective parcels per study area and the number of defects found on defective parcels. An average I/I per defect was then applied to each defect in the area to determine the total estimated I/I coming from service lines. The City conducted a prior ponding analysis which provided the model with the ability to calculate inflow from pickholes for a manhole when the cover type was known. For manholes, breakpoints for age were established based on changes in City design practices, such as the transition from vented to concealed manhole covers. The size and quantity of pickholes per cover could then be determined using standard City construction details.
Phase III condition assessments filled in the data gaps identified during the initial phases. Data collected during this phase was used to calibrate the model. Phase IV is slated to begin in 2021 and will encompass the development of a customized software application to automate much of the model run while integrating into other City programs to share data and continue to refine the estimates the model generates.