Best practice of intelligent algorithms to optimise and prioritise capital investments and asset rehabilitation

Joel Wilson (WCS Engineering), Alvaro Cañizares (WCS Engineering), Stephen King (Hazen and Sawyer), Daniel White (Jefferson County)

Jefferson County, AL, implemented the application of intelligent algorithms to optimise and prioritise capital investments and asset rehabilitation. The County owns and operates wastewater collection systems across nine treatment plant basins serving approximately 600,000 people. The system-wide optimisation incorporated five treatment plant basins (Cahaba River, Five Mile Creek, Shades Creek, Valley Creek and Village Creek) that are all interconnected either by existing or potential future flow diversion structures. The project delivers simple to understand optimal solutions while delivering significant value added & return on investment through close collaboration with the utility staff.

The study involved the evaluation of conveyance infrastructure, storage facilities, and asset rehabilitation to determine the most cost-effective way to achieve 0.6m (2 ft) of freeboard system-wide in the 2-year design storms (6-hour and 24-hour), with emphasis on prioritising the elimination of reported SSOs. 

Recently completed pilot I/I rehabilitation projects provided updated data to consider different scenarios on the effectiveness of I/I reduction and the performance of other improvement infrastructure. Similarly, asset condition and sediment data were incorporated into analysis to determine whether it is more cost-effective to clean the sediment or replace and upsize based on a holistic consideration of conveyance, storage, and I/I reduction alternatives. The analysis identifies key basins that are cost-effective and ensures conservative conveyance capacity upgrades.

This project successfully demonstrated life-cycle cost savings on the order of $54M (30%) when compared to Valley Creek’s Baseline RMP (where an RMP had been developed). It also demonstrated that a prioritised capital improvement schedule could achieve 40% SSO volume reduction within the first 10% of capital expenditure and 98% reduction within 70% of the total capital expenditure required to eliminate all SSOs and achieve surcharge limit objectives system wide.

The Jefferson County study consistently demonstrated how timely implementation of optimised projects could eliminate the vast majority of SSOs at a fraction of the total program cost.