The UWO dataset
Long-term data from a real-life field laboratory to better understand urban hydrology at small spatiotemporal scales
Keywords:Urban drainage systems, Hydrological processes, Spatio-temporal dynamics, Monitoring, Sensor data, Openly available datasets, Urban Water Observatory (UWO), Low-power wireless sensor network
Although urban drainage systems are essential infrastructure, monitoring their functioning is cumbersome, hazardous and can be very expensive. This makes it difficult to track spatio-temporal dynamics of the fast hydrological processes. Also, openly available datasets from urban drainage systems are lacking, which makes it challenging to develop methods for automated data quality control. In this study, we present a unique dataset from the Urban Water Observatory (UWO) field lab in and around the municipality Fehraltorf, Switzerland. The dataset comprises coherent information from 124 data sources that observe rainfall-runoff processes, wastewater and in-sewer atmosphere temperatures. Of those 124, 89 sources transmit their signals via a specifically set-up wireless network using low-range low-power transmission technologies. Sensor data has a temporal resolution of 1-5 minutes and covers a period of three years from 2019-2021. To make the data interpretable and re-useable we provide systematically collected meta-data, data on sewer infrastructure, associated geoinformation including a hydrodynamic rainfall-runoff model. Basic data quality checks were performed, and we motivate future research on the dataset with five selected research opportunities from detecting anomalies in the data to assessing groundwater infiltration and the capability of the low-power data transmission. To obtain interpretable and reusable urban drainage data, robust automated data quality checks, and standardized exchange formats are needed. In the future, using ontologies and knowledge graphs could be developed to expand the application of sewer observation data in solving scientific and practical problems.
Copyright (c) 2023 Frank Blumensaat, Simon Bloem, Christian Ebi, Andy Disch, Christian Förster, Mayra Rodriguez, Max Maurer, Jörg Rieckermann
This work is licensed under a Creative Commons Attribution 4.0 International License.