Der anthropogene Klimawandel hat auf den sensiblen Hochgebirgsraum der Seenplatte Macun, die seit dem Jahr 2000 als Teil des Schweizerischen Nationalparks genauer erforscht wird, starke Auswirkungen. Die langjährigen Klimadaten der Station Buffalora beim Schweizerischen Nationalpark zeigen eine deutliche Erwärmung seit 1917 mit einem linearen Anstieg der Temperaturen um 2,1°C. Eine starke Erwärmung zeigt sich ab 1987 und ab 2010. Gleichzeitig gehen die Niederschlagsmengen seit 2010 deutlich zurück. Während auf Macun die mittlere Schneehöhe stabil blieb, tritt die Schneeschmelze mittlerweile rund 15 Tage früher ein. Das folgende Kapitel beleuchtet, welche klimatologischen Veränderungen auf Macun aufgetreten sind.

Underground infrastructure networks form the backbone of vital supply and disposal systems. However, they are under-monitored in comparison to their value. This is due, in large part, to the lack of energy supply for monitoring and data transmission. In this paper, we investigate a novel, energy harvesting system used to power underground sewer infrastructure monitoring networks. The system collects the required energy from ambient sources, such as temperature differences or residual light in sewer networks. A prototype was developed that could use either a thermoelectric generator (TEG) or a solar cell to capture the energy needed to acquire and transmit ultrasonic water level data via LoRaWAN. Real-world field trials were satisfactory and showed the potential power output, as well as, possibilities to improve the system. Using an extrapolation model, we proved that the developed solution could work reliably throughout the year.

The Macun lakes form a high-alpine (> 2,600 m asl) cirque landscape (3.6 km2) in the Swiss National Park, comprising 26 small lakes together with a number of temporary ponds. Streams interconnect the four largest lakes, forming the drainage network that flows into the Inn River at the town of Lavin. The drainage network of Macun consists of a north and a south basin that overlie an ortho-gneiss, meta-granitoid bedrock. The south basin is influenced by various rock glaciers. The physico-chemistry of surface waters at 10 sites has been monitored annually in midsummer since 2001. Further, an YSI EXO2 Multiparameter Sonde (Exosonde) with various water quality sensors has been employed since 2016 at the last lake in the network to examine seasonal and diel patterns in physico-chemistry. Results showed clear physico-chemical differences between the two basins, which mostly reflect rockglacier inputs in the south basin. Nitrogen values were two-fold higher and particulate phosphorus values two-fold lower in the south basin than in the north basin. Over time, the physico-chemistry in the two basins became more homogeneous, with a reduction in rock-glacial inputs in the south basin and an overall decrease in nitrogen in the catchment. Data from 30 springs and tributaries sampled in 2002 and 2017 reflected the basin differences and temporal changes observed at the primary study sites. Continuous temperature records showed north basin streams to be ca. 3°C warmer than south-basin streams, but with high inter-annual variation that reflected annual differences in weather and no evidence of a general change over time (increase or decrease). Exosonde data revealed strong seasonality in measured parameters as well as seasonality in diel patterns (e. g., dissolved oxygen, temperature, chlorophyll-a); diel fluctuations were most pronounced in summer and least in winter. The results highlight the importance of long-term monitoring for understanding ecosystem state changes in alpine freshwaters, especially during periods of rapid environmental change.

This chapter first provides information on general health and safety rules to be applied by operators in monitoring urban drainage and stormwater management (UDSM) systems, especially in the harsh confined environment of underground sewer systems. Second, it presents experience-based key recommendations for best practice and quality in operation, management and maintenance of sensors and installations for rainfall and discharge measurements. In the last part, three numerical methods (ordinary least squares, Williamson least squares, non-linear regression) are presented, with detailed examples of application, to establish calibration functions which are necessary for all sensors used in UDSM monitoring.

Untreated sewer overflows can contaminate receiving waters with micropollutants. Although concentrations of discharged micropollutants can be ecotoxicologically relevant, only limited data is available to assess occurrence and spatial differences among sewer overflow catchments. Therefore, we present an innovative type of data obtained with passive samplers at 20 combined sewer overflow sites (2-7 events per site; 95 events in total). The data sheds light on concentration ranges for 13 representative polar organic micropollutants and shows that micropollutants in both municipal wastewater and stormwater can be relevant sources of contaminants. We identify indicator micropollutants for further studies: benzotriazole (80% interquantile of time-weighted average concentration: 250–4800 ng/L), carbamazepine (33-910 ng/L), diclofenac (78-1000 ng/L), carbendazim (21-900 ng/L), diazinon (2.1-53 ng/L), diuron (22-1100 ng/L), mecoprop (98–5300 ng/L), metolachlor (6-230 ng/L), and terbutryn (29-810 ng/L). These concentration estimates are assumed to be on the safe side for comparison with environmental quality standards (EQS). A majority of sewer overflow sites (13 of 20) show discharge concentrations above acute EQS for at least one micropollutant and thus would have to rely on dilution by receiving waters to not exceed any EQS. The intersite variability among sewer overflows exceed the within-site variability. Hence, future monitoring studies should cover more sewer overflow sites. No correlation could be found with event durations, specific storage volume or land use data, thus showing the complexity of micropollutant occurrence and indicating that other factors led to the observed high spatial variability. In conclusion, our results clearly show the potential relevance of micropollutants in sewer overflows and the need to assess site-specific measures.

Hat Niedrigenergiefunk das Potenzial, die Prozessüberwachung in Entwässerungsnetzen und anderen Infrastrukturen im Untergrund zu revolutionieren? Ein Langzeitexperiment im Vollmassstab in der Gemeinde Fehraltorf zeigt die Möglichkeiten, Grenzen und Entwicklungspotenziale der neuartigen Übertragungstechnologie auf. Grundsätzlich unterstreicht das Experiment die Eignung des Niedrigenergiefunks für eine komplementäre Systemüberwachung. Sinnvoll eingesetzt kann diese Neuerung wesentlich zu einer evidenzbasierten Bewirtschaftung von Ver- und Entsorgungssystemen beitragen.

Hat Niedrigenergiefunk das Potenzial, die Prozessüberwachung in Entwässerungssystemen und anderen Infrastrukturen im Untergrund zu revolutionieren? Inwieweit verbessern technologische Neuerungen unser Verständnis für Daten und deren Nutzung für Betriebsoptimierung, Investitionsplanung und Erfolgskontrolle?

Niederschlags- und Mischabwasserentlastungen aus Siedlungen tragen zu Mikroverunreinigungen in Gewässern bei. Mit Passivsammlern wurden erstmals Konzentrationsbereiche an 20 Standorten für insgesamt 95 Ereignisse bestimmt, was die Analyse von Unterschieden zwischen Standorten sowie die Identifikation relevanter Eintragspfade unterstützt. An 13 Standorten waren bei mindestens einer Substanz die Konzentrationen im Mischabwasser höher als akute Qualitätskriterien.

Mit kurzen Videosequenzen von Überwachungskameras und Smartphones können Oberflächengeschwindigkeiten in Abwasserkanälen gemessen werden. Eingesetzt wird dabei die bildbasierte Methode namens Surface Structure Image Velocimetry, kurz SSIV. Die resultierenden Ergebnisse stimmen gut mit Ultraschall-Referenzmessungen überein und unterstreichen das Potenzial der innovativen Methode.

Blossoming visions foresee an ubiquitous availability of data enabled through emerging sensors, novel transmission technologies and revisited data analysis techniques. It is often expected that this likewise applies to urban water management (Kerkez et al., 2016; Eggimann et al., 2017). Contrary to the envisioned easiness to collect data, an in-creasing number of studies report about a declining effort to conduct experimental field re-search in catchment and urban hydrology, implying the risk of scientific advancement to be misdirected (Blume et al., 2017; van Emmerik et al., 2018). In this paper, we present re-sults from a unique sensor network that collects, transmits, and organizes very high resolu-tion status information from an urban drainage catchment. Our findings are based on a two-year operation at full-scale with more than 50 sensor nodes connected to a low-power wireless sensor network (LPWSN). In essence we i) illustrate the scalability of LPWSNs, ii) reveal telemetry limitations of the LoRaWAN standard (LoRa®Alliance 2015), iii) suggest a novel technique (LoRaMesh) to master this constraint, and iv) discuss challenges associ-ated with managing the amount of data collected from diverse sources. We find: 1. the proposed transmission technique considerably improves telemetry performance of the en-tire network without introducing additional gateway stations (total packet loss 2.2 %). 2. Dynamic and flexible data management solutions come at a price. 3. It is not the pure amount of data that is most challenging but the diversity of different signals. 4. Full metada-ta integration in the data warehouse is laborious but clearly consolidates data interpretation in the long-term run.

Urban drainage systems traditionally lack adequate monitoring and evaluation technologies. Although weather radar and high-resolution remote sensing technologies promise vast advances for rainfall and land-use data collection, it is still challenging to deploy dense hydrological monitoring networks for sewers. Low-power data transmission technology, which is the communication backbone in the Internet-Of-Things (IoT), has the potential to contribute to a game change towards an evidence-based management of urban drainage systems. In this paper, we share our experiences with establishing and operating a wireless sensor network (WSN) at full-scale with approximately a 1 sensor per hectare connected catchment area and a monitoring frequency of 5 minutes or less. Specifically, we discuss i) the monitoring and deployment approach and ii) the adequacy of sensorand LoRaWANTM wireless data transmission technology for monitoring applications in sewer networks. A thorough evaluation of the telemetry performance provides evidence that the proposed technique allows a highly distributed monitoring of drainage capacity, sewer infiltration, performance of retention basins and overflows, with a far less effort compared to conventional methods. Remaining challenges concern the radio network architecture to allow better access to deep underground structures and efficient methods for automated data quality control to handle this type of data in the future.

Obgleich gegenwärtig mittels Regenradar und hochauflösender Fernerkundung immer effizienter Daten zu Niederschlag, Topographie und Landnutzung erhoben werden, ist es nach wie vor schwierig, eine hydrologische Überwachung für Entwässerungssysteme mit hinreichender Informationsdichte und -konsistenz zu realisieren. Ob und inwieweit die Technologie des Niedrigenergiefunks (LPWAN) – als Kommunikations-Backbone des Internet der Dinge (IoT) bekannt – das Potenzial hat, diese Lücke zu schließen, diskutieren wir in diesem Beitrag. Grundlage dafür sind unsere Erfahrungen beim Aufbau und dem bis dato einjährigen Betrieb eines Drahtlossensornetzwerks in einem mittelgroßen Schweizer Siedlungsentwässerungsnetz mit einer Sensordichte von über einem Sensor pro Hektar und einer Überwachungsfrequenz von fünf Minuten. Im Einzelnen erörtern wir i) das zugrundeliegende Monitoringkonzept, ii) die technische Spezifikation der Sensorik und der Datenübertragungstechnologie LoRaWANTM und iii) die bisherigen Erfahrungen zur Systemperformance, illustriert durch ein Anwendungsbeispiel.

The data sets described in this paper provide a basis for developing and testing new methods for monitoring and modelling urban pluvial flash floods. Pluvial flash floods are a growing hazard to property and inhabitants’ well-being in urban areas. However, the lack of appropriate data collection methods is often cited as an impediment for reliable flood modelling, thereby hindering the improvement of flood risk mapping and early warning systems. The potential of surveillance infrastructure and social media is starting to draw attention for this purpose. In the floodX project, 22 controlled urban flash floods were generated in a flood response training facility and monitored with state-of-the-art sensors as well as standard surveillance cameras. With these data, it is possible to explore the use of video data and computer vision for urban flood monitoring and modelling. The floodX project stands out as the largest documented flood experiment of its kind, providing both conventional measurements and video data in parallel and at high temporal resolution. The data set used in this paper is available at https://doi.org/10.5281/zenodo.830513.