Urban wastewater management and the associated modelling has become indispensable today. Reliable calibration is essential for these models, and water level data is used as a standard. However, data collection can be limited due to high sensor costs and harsh conditions in the sewer. A novel solution is collecting data using low-cost temperature sensors, placing one in the stream, the other at the crest of the weir. In the case of dry weather, the sensor measures the air phase, whereas, in the case of Combined Sewer Overflow (CSO), the discharged storm and wastewater is measured. Autocalibration was performed using OSTRICH for a SWMM model in Berlin, with water level and fictional temperature data, and various number of measuring sites. Results showed that calibration using temperature data was as good as using water level data, with promising outcomes achieved by using one measuring site, offering a cost-effective alternative for water utilities.

The management of urban wastewater systems and the associated modelling of these systems has become indispensable in today's world. In order for these models to represent reality as accurately as possible, a reliable calibration is essential. Water level data is used as a standard, but due to expensive sensors and harsh conditions in the sewer, data can only be collected at a few key points of the system. One novel solution, that has experienced an upswing in recent years, is collecting data using low-cost temperature sensors. Two sensors are needed; one is placed in the stream; the other is placed at the crest of the weir. In the case of dry weather, the sensor measures the air phase, whereas, in the case of Combined Sewer Overflow (CSO), the discharged storm and wastewater is measured. The start and end of a CSO event can be determined via the merging of measured temperature values in both points of the overflow structure. Due to this method, the duration of CSO events in a sewer system can be detected.

In this work, the potential benefits of this novel method for model calibration are assessed. Therefore, autocalibration runs with water level data and fictional temperature data were carried out via OSTRICH for a SWMM model located in Berlin. Furthermore, calibration runs with a different number of measuring sites were performed, to evaluate the amount of necessary measuring sites for a reliable calibration. In order to be able to compare the different approaches, a calibration period of 19 events was first required for the respective datatype. Next, a validation period which consisted of 18 events was carried out and evaluated by the R² of three water level measuring sites for both approaches to ensure comparability. It was revealed that the calibration with duration data based on temperature sensors was able to achieve results as good as the conventional approach using water level data. Due to low spatial distribution of the measuring sites in the model, it could not be finally answered if more measuring sites would yield to even better results. However, already with one measuring site, promising calibration outcomes could be achieved and thus, offers an alternative for water utilities and practitioners.