How to predict and prevent CSOs and SSOs
Analytical systems that capitalise on existing wastewater collection infrastructure can help avoid the negative impacts of sewer overflows.
Combined sewer overflows (CSOs) and sanitary sewer overflows (SSOs) are natural hazards for wastewater collection systems. Without a comprehensive solution to monitor troublesome conditions, overflows can be triggered with little warning and lead to expensive and embarrassing situations. Fortunately, versatile analytical systems that capitalise on existing wastewater collection infrastructure hold promise for avoiding such negative impacts.
Collecting, formatting, and analysing data from a variety of sensor and data storage sources relieves management from much of the time and effort required to exercise insight and creativity. Here are several approaches to predicting and preventing CSOs and other drainage system issues.
Identifying the roots of the problem
Whether collection systems constitute sanitary sewer, stormwater sewer, or combined sewer flows using shared infrastructure, multiple issues contribute to overflow conditions. Smart solutions fed by multiple data inputs can keep both obvious and less-than-obvious problems from causing the following costly, destructive events.
Accumulation of debris over time can result in slowly diminishing flow rates or flow rates that lag behind diurnal water usage patterns, for a number of reasons:
- Routine blockages: Monitoring solutions that use data from flow meters, rain gauges, and lift-station level gauges can help to identify trending flow problems in any type of sewer or stormwater collection system.
- Storm-related blockages: Large debris deposits left by the most recent storm surge can affect drainage in upcoming storms, even though they have not yet caused a visible overflow event.
- Fatbergs: Certain areas of a sewer system — such as those around heavy industry or a downtown restaurant district — can naturally accumulate grease and oil that coagulates into sticky ‘fatbergs’. Unless detected early, these accumulating problems can eventually grow large enough to lead to SSOs and CSOs.
Concentrations of water resulting from wet weather events can exert a series of negative influences on storm-sewer and combined-sewer systems.
- Inflow: Combining normal sanitary sewer flow with inflow from storm drainage places increased demand on wastewater treatment capacity and cost.
- Infiltration: Depending on the age and condition of a sewer system, an unpredictable volume of underground stormwater can infiltrate a sanitary sewer collection system.
- System bypass: Whatever the source of increased flow, if the cumulative volume exceeds WWTP capacity and cannot be diverted to storage for subsequent treatment, raw sewage discharges that bypass treatment altogether can risk fines.
Sowing the seeds of a solution
A good analytics system makes it possible to stay ahead of unseen blockages and heavy rainfall events to prevent CSO occurrences. A solution that monitors precipitation forecasts, real-time rain gauges, IIoT devices or sensors, and flow rates in a GIS mapping system with corresponding elevation readings makes it possible to spotlight discrepancies between rain gauge readings and anticipated sewer flow rates. This means being aware of potential overflow conditions in time to do something about them.
Monitor flow rates
Collecting data from existing level detectors and flowmeters, then comparing it against historic performance under similar conditions, provides a good appreciation for stormwater situations as they evolve. The ability to incorporate future precipitation data, such as Bureau of Meteorology forecasts into the model can refine sewer flow forecasts even more to support better planning of how to minimise stormwater impacts on wastewater collection and treatment systems. For example, one utility created a series of evolutionary artificial neural networks to forecast CSO-chamber water levels six hours into the future — with 97% accuracy.
Reduce underground blockages before the storm
Comparing sewer system flow rates and level readings against historical trends can also highlight below-average or irregular flow rates indicative of potential hidden blockages. Helping maintenance crews locate those blockages in time to clear them before the next storm event can prevent costly CSOs or SSOs.
Plan for excess flows
Gaining better insight on stormwater flows from an analytics system makes it easier to plan for both short-term challenges and long-range infrastructure planning. Response options can include:
- Advance treatment: Knowing the timing and volume of precipitation expected can guide management choices on how to clear up as much WWTP capacity as possible in advance of the storm — through maintenance, emptying of basins, cleaning of storm screens, etc.
- Stormwater storage: Real time monitoring and timely precipitation forecasts can provide insights on how to allocate stormwater storage just before a storm arrives, then meter that stored water back into the system once the initial demand peak on treatment capacity recedes.
- Overflow forecasting: In a worst-case scenario, knowing where the heaviest drainage impacts will occur can provide time to issue CSO warnings and minimize negative impacts to the public and the environment (see Figure 1).
- Maintaining good will: In addition to averting fines, avoiding the negative embarrassing impacts of high-profile events can also help to maintain good consumer relationships.
- Upgrade savings: Charting historic performance provides more knowledge for planning better infrastructure expansion based on actual hydraulic performance in the targeted geography. This can save millions of dollars on capital expenses (CAPEX) and operating expenses (OPEX) for over-engineered stormwater systems.
Predictability beyond CSOs
The same analytics capabilities used to provide insights for CSOs have value throughout water treatment, distribution, and wastewater collection applications — and beyond. For example, Tasmania Water uses sewage pump station (SPS) data to spot and respond to blockages and spills in ecologically sensitive environments. By analysing just a single data point, whether a pump was running or not, Tasmanian Water & Sewerage Corp Pty Ltd discovered that the ‘time to fill’ or time between pump runs was the key determinant of a station’s operating profile. When the time between pump runs goes beyond what is normal, it suggests that the wet well (which collects the incoming water from the sewer system) is taking too long to fill and a blockage may be occurring upstream. TasWater created models of normal pump behaviour. Then they used Asset Framework, a part of the OSIsoft PI Server, to set up events and notifications for out-of-bounds conditions.
Using the templates feature of Asset Framework, TasWater quickly expanded the pilot project from the initial pump station to all of the SPS sites in the Midway Point region within a month, and since implementation, the PI System has rapidly expanded in both users and data. All 900-plus employees have view access to PI Vision and more than 240,000 data streams, supporting a range of business and stakeholder requirements.
“The success of the system is attributed to sound governance measures including the establishment of a dedicated Steering Committee, the development of data and system standards and a 5-year roadmap,” said Anthony O’Flaherty, Manager Asset Information Quality & Systems. “The Roadmap outlines business projects and general timelines all the while allowing for flexibility and maximising our innovative potential. This approach enables our ability to work effectively with our stakeholders such as shellfish growers for better outcomes.”
The rise of botnets targeting the Internet of Things (IoT) has emerged as a clear and present...
Partner with RS Components to consolidate your purchasing and save time.
For those involved in researching, developing and launching AI applications there is still much...