Developing a Representative Year of Precipitation in Support of a Wet Weather Plan

In support of a regional wet weather plan, computer models have been developed to simulate baseline conditions to establish frequency and duration of combined sewer overflow and sanitary sewer overflow (CSO/SSO) discharges, their potential water quality impacts, and to develop and assess alternative control strategies. Much of the uncertainty in a carefully constructed hydrologic and hydraulic model derives from uncertainty in the precipitation record. Therefore, increasing the detail of the rainfall input, both spatially and temporally, increases the accuracy and precision of the model results. Careful attention to rainfall collection and analysis is critical to the modeling effort. The refinement of precipitation data becomes an important issue because precipitation is a driving force that increases wastewater flow along sewers and transports pollutants via CSO and SSO to receiving waters.

The U.S. Environmental Protection Agency CSO Control Policy (1994) requires characterization of the combined sewer system area and evaluation of control measure performance in terms of a “typical year” or system-wide average annual hydrologic conditions. A selected representative year, based on quality-assured long-term local precipitation data, should be able to produce annual CSO statistics such as volume, duration and event frequency that closely match the long-term average.

CSO occurrence is a complex function of storm-event characteristics such as precipitation volume, duration, peak intensity, and length of antecedent dry period. Continuous 12-month periods selected from recent quality assured radar rainfall data were evaluated against the long-term record based on storm-event characteristics such as annual event frequency, total annual precipitation volume and event peak hourly rainfall intensity. Statistical analyses were conducted to determine adjustments to the actual 12-month precipitation that were needed to eliminate bias against historical record average values.

This work presents a rigorous statistical analysis approach including double-mass regression and cumulative distribution frequency analysis of long-term regional rain gage data and high resolution short-term radar rainfall data to establish a representative one-year precipitation record.