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Using low-cost sensors, data can be collected on the occurrence and duration of overflows in each combined sewer overflow (CSO) structure in a combined sewer system (CSS). The collection and analysis of real data can be used to assess, improve, and maintain CSSs in order to reduce the number and impact of overflows. The objective of this study was to develop a methodology to evaluate the performance of CSSs using low-cost monitoring. This methodology includes (1) assessing the capacity of a CSS using overflow duration and rain volume data, (2) characterizing the performance of CSO structures with statistics, (3) evaluating the compliance of a CSS with government guidelines, and (4) generating decision tree models to provide support to managers for making decisions about system maintenance. The methodology is demonstrated with a case study of a CSS in La Garriga, Spain. The rain volume breaking point from which CSO structures started to overflow ranged from 0.6. mm to 2.8. mm. The structures with the best and worst performance in terms of overflow (overflow probability, order, duration and CSO ranking) were characterized. Most of the obtained decision trees to predict overflows from rain data had accuracies ranging from 70% to 83%. The results obtained from the proposed methodology can greatly support managers and engineers dealing with real-world problems, improvements, and maintenance of CSSsSupport for this project was provided by the ENDERUS Project (CTM-2009-13018) and the predoctoral grant FPI BES-2010-039247, founded by the Spanish Ministry of Science and Innovation. Lluís Corominas received the postdoctoral Juan de la Cierva grant (JCI-2009-05604) from the Government of Spain and the Career Integration Grant (PCIG9-GA-2011-293535) from the EU. The authors also acknowledge the support from the Economy and Knowledge Department of the Catalan Government through the Consolidated Research Group (2014 SGR 291)–Catalan Institute for Water Researc

Discharges of untreated wastewater from combined sewer overflows (CSOs) can affect hydraulic stress and have significant environmental impacts on receiving water bodies. Common flow rate and water level sensors for monitoring of CSO events are expensive in terms of investment costs, installation, operation and maintenance. This paper presents a novel surrogate method to detect CSO events by using two low-cost temperature sensors. The novelty is the experimental setup for installation of temperature sensors in CSO structures and an algorithm developed to automatically calculate the duration of CSO events considering the response time of the system. The occurrence and duration of CSO events is computed based on the convergence of the two temperature signals. The method was tested under field conditions in a CSO structure, and the results were compared to the information gathered from a parallel installed flow sensor. The application of two temperature sensors installed inside a CSO structure was proven to be robust and accurate for the automatic detection of the occurrence and duration of CSO events. Within the 7-month test phase, 100% of the 20 CSO events could be detected without false detections. The accuracy of detecting the start and end of the CSO events was 2 min in comparison to the flow sensor.Electronic supplementary materialThe online version of this article (10.1007/s10661-018-6589-3) contains supplementary material, which is available to authorized users.