Follow-up: Understanding of Extraneous Water in Ekeby

Follow-up: Understanding of Extraneous Water in Ekeby

Since the initial implementation of Dryp’s wireless monitoring system in Ekeby, we have now collected over 18 months of water data under varying seasonal conditions — from autumn rainfall and winter saturation to early spring. The objective has been to gain a deeper understanding of where and when extraneous water enters the sewer network, and how it impacts system performance.

Summary of Phase One

This follow-up presents key findings from the extended monitoring period. It highlights how data-driven insights have sharpened NSVA’s ability to identify critical problem areas, prioritize investments, and support long-term planning. In the initial phase, 28 wireless sensors were installed in strategically selected manholes in the Ekeby catchment. These sensors were supplemented by Dryp’s rain gauge and NSVA’s X-band radar data, allowing for a high-resolution picture of how the system responds to different types of precipitation. Within five months, eight overflows were recorded, and 84% of sensors showed high water levels, indicating widespread system pressure. Early results led to a 15% reduction in catchment area and identified two subcatchments with clear signs of infiltration — but no inflow from misconnections. Read the original case: Detection of Extraneous Water in Ekeby

The data

The data collection has now spanned 1.5 years, covering nearly 50 manholes across   Using Dryp’s I&I module in Lens, the time series have been analyzed to separate infiltration from inflow — both influenced by rainfall, soil moisture, and seasonal variations.

Key Findings: 

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66% of the total volume treated at the Ekeby Wastewater Treatment Plant is extraneous water. 
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Of this, 63% is due to infiltration, and 3% is inflow from drain misconnections. 
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Infiltration is the primary cause of overflows — all recorded overflow events occurred during periods of high infiltration. 
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9 simultaneous overflows were measured across three structures, with some lasting more than 24 hours. 
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The results highlight a stark seasonal contrast — the system behaves almost like two different sewer networks in winter versus summer. In winter, infiltration drastically reduces capacity, leading to backpressure and overflow risk even during relatively minor rainfall events. 

Prioritizing Action: Subcatchment Analysis 

To localize and quantify sources of extraneous water, the Ekeby catchment was divided into 14 subcatchments, strategically defined based on sensor placement and drainage structure. This spatial breakdown allowed for a more granular analysis of how different areas contribute to infiltration and inflow. 

Using Dryp’s analysis tools in Lens, infiltration and inflow volumes were calculated for each subcatchment over time. This included normalization for area size, helping distinguish not just the largest contributors in absolute terms, but also the most intense sources relative to their footprint. 

As a result, two overview maps were created

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Nr. 1

showing how much extraneous water came from each subcatchment in total

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Nr. 2

showing how much came from each subcatchment relative to its size

This made it easy for NSVA to see which areas contributed the most infiltration and inflow, and to focus their efforts where it would have the biggest impact. 

With this level of insight, NSVA can now prioritize actions based on data — not assumptions — and use their resources more strategically. This means not only fixing existing problems, but also preventing future ones through long-term, cost-effective solutions. 

Overall, NSVA has gained a much clearer and more actionable understanding of how the Ekeby sewer network behaves. The results confirm that infiltration — especially during the wet season — is the main challenge, and that real-time data is essential for managing both day-to-day operations and long-term planning. 

This data-driven approach empowers NSVA to make smarter decisions, target investments effectively, and reduce both environmental and operational risks. 

Overview