Département Gestion des eaux urbaines

Urban drainage systems are integral infrastructural components. However, their monitoring poses considerable challenges owing to the intricate, hazardous nature of the process, necessitating substantial resources and expertise. These inherent uncertainties act as barriers, discouraging active involvement of researchers and sewer operators in the rigorous monitoring and utilization of data for a comprehensive understanding and efficient management of drainage-related processes. Consequently, a notable absence of openly available urban drainage datasets hampers exploring their potential for engineering applications, scientific analysis, and societal benefits. In this study, we present a distinctive dataset from the Urban Water Observatory (UWO) in Fehraltorf, Switzerland. This dataset is unique in terms of its completeness, consistency, extensive observation period, high spatio-temporal resolution and its availability in the public domain. The dataset comprises coherent information from 124 sensors that observe rainfall-runoff processes, wastewater and in-sewer atmosphere temperatures. Of these 124 sensors, 89 transmit their signals via a specifically set-up wireless network using long-range, low-power transmission technologies. Sensor data have a temporal resolution of 1–5 min and cover 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 geo-information including a validated hydrodynamic rainfall-runoff model. Basic data quality checks were performed, and we motivate future research on the dataset with five selected applications from detecting anomalies in the data to assessing groundwater infiltration and the capability of the low-power data transmission. The datasets are available at https://doi.org/10.25678/000C5K (Blumensaat et al., 2024a). We also suggest directions for future research using the UWO dataset from uncertainty analysis of rainfall runoff models to smart databases. In the future, ontologies and knowledge graphs should be developed to expand the application of sewer observation data in solving scientific and practical problems.

Granule detachment in aerobic granular sludge (AGS) systems is considered an important aspect for both granulation and nitrification performance, yet it has received little attention. This study aimed to identify the dominant detachment mechanisms (erosion, abrasion, sloughing, breakage) and quantify their respective kinetics under operational shear conditions. Ultimately, the impact of detachment on nitrifier migration and growth conditions in flocs was also investigated. Granules from two full-scale AGS wastewater treatment plants (WWTP) were exposed to operational shear (157 s^-1) for up to one week in a Couette-Taylor reactor. The distribution of size-classes in terms of total suspended solids (TSS) and nitrifiers was measured, and detachment kinetics and solids retention time (SRT) in flocs, accounting for detachment, were estimated. Under the tested shear rate, shear-induced erosion from the granule surface was the main detachment mechanism with a median detachment rate of 0.017 gTSS_detach gTSS_granule^-1 d^-1 (25th–75th percentile: 0.014–0.027 gTSS_detach gTSS_granule^-1 d^-1). In contrast, granule breakage was not observed within 15 detachment tests and therefore does not appear to be a continuous process, indicating that re-growth on breakage debris is not a main driver of granulation as previously proposed in literature. Nitrifiers were found to migrate almost exclusively to biomass <0.2 mm, i.e., flocs. While the migration rates of ammonia- and nitrite-oxidizing bacteria (AOB and NOB) were similar in autumn, distinct values were quantified in winter, with two to six-fold lower NOB migration rates, likely reflecting a temperature-dependent stratification of nitrifiers within granules. Consequently, the influence of nitrifier migration on the growth conditions in flocs varies across nitrifying groups and seasons. The floc SRT of AOB was estimated to be above their minimum SRT throughout the year, indicating migration is not critical for AOB to persist in flocs. In contrast, the minimum SRT of NOB increases significantly at low temperature, such that migration becomes crucial to prevent NOB washout. Migration of NOB from granules to flocs may sufficiently increase the SRT of NOB in flocs, if they are predominantly enriched in granules rather than in flocs. Overall, flocs provide favourable growth conditions for AOB throughout the year, whereas this is only intermittently the case for NOB, which ultimately rely on migration from granules, particularly during cold winter months.

Cities can harbor greater plant diversity than other ecosystems, yet how city sociocultural factors may determine differences in plant composition across equivalent urban green space types remains understudied. Here, we compare plant communities in five main urban greenspace types across three Swiss cities representing the country's French (Geneva), Italian (Lugano), and German (Zurich) cultural regions. We found that over half of the species recorded occurred in only one of the three cities, whereas less than a quarter were shared across all three. Our study supports the idea that cities' sociocultural contexts can leave a strong imprint on their urban plant life, underscoring the need to consider sociocultural diversity alongside ecological and planning factors when managing and promoting urban biodiversity.

Cities are increasingly adopting blue-green infrastructure (BGI) to address the dual challenges of extreme rainfall and rising temperatures driven by climate change. While the potential of BGI for urban stormwater management is well-studied, the cooling effect of stormwater-focused BGI remains underexplored. This study investigates the heat mitigation potential of three stormwater BGI elements, bioretention cells, porous pavements, and detention ponds, within three urban street canyons in a Swiss town near Zurich. The Urban Tethys-Chloris (UT&C) microclimate model was modified to explicitly represent stormwater BGI and assess their influence on the Universal Thermal Climate Index (UTCI) at 2 meters above the ground. Simulations were conducted under both historical climate and a future climate projection, including a sensitivity analysis of soil types. BGI can cool up to 2.7 °C, but their effectiveness depends on the type of BGI, the surface it replaces, the time of the day, and the availability of water. Soil properties were found to significantly influence the cooling effect of bioretention cells, with finer-textured soils achieving higher soil moisture levels and greater reductions in UTCI. A trade-off between cooling and stormwater infiltration also emerged. Sandy soils favor infiltration but dry out quickly, limiting cooling, while clay-rich soils limit infiltration but retain moisture and sustain evaporative cooling, even under future climate conditions with longer dry spells. These findings highlight the importance of integrating hydrological and thermal considerations into BGI design. Integrated approaches that balance both objectives are needed.

The Air-temperature Response to Green/blue-infrastructure Evaluation Tool (TARGET) is a compact urban climate model designed to predict intra-urban temperatures and assess city cooling strategies. Until now, the lack of a user interface has limited its broader adoption. This study presents an open-source interface for TARGET, integrated within the Urban Multi-scale Environmental Predictor (UMEP) tool in QGIS. The interface supports a complete workflow, including input data preparation, simulation, and output visualisation. Its applicability is demonstrated through a case study in Zurich, Switzerland, where it identified thermal hotspots and quantified the cooling benefits of targeted interventions. By lowering technical barriers, UMEP-TARGET enhances the accessibility of physically based urban temperature modelling for both the scientific community and practitioners, supporting evidence-based planning for climate adaptation.