This study presents a comprehensive dataset from Lake Greifen, Switzerland, collected between April 2018 and June 2023, using high-frequency automated monitoring systems. The dataset integrates meteorological data, nutrient chemistry, water column profiles for water physics, and plankton underwater imaging, offering insights into the lake's physical and biological processes. A dual-magnification dark field underwater microscope captured hourly plankton dynamics at 3 m depth, providing size, shape, and taxonomic information. A profiler with a multiparametric probe monitored water temperature, oxygen, and other key parameters from 1 to 17 m depth, while weekly nutrient sampling complemented the measurements. Data processing involved rigorous cleaning protocols to remove technical artefacts, ensuring data quality. Our dataset showcases the utility of integrating different approaches for high-frequency monitoring to detect lake temporal processes, from phytoplankton blooms to zooplankton vertical migration and seasonal shifts in water column stability. This dataset provides a unique resource for studying limnology and plankton community ecology. All data and related processing codes are publicly available for further research, supporting interdisciplinary studies.

Drinking water is becoming increasingly scarce as the world’s population grows and climate change continues. However, there is great potential to improve drinking water pipelines, as 30% of fresh water is lost between the supplier and consumer. While systematic process monitoring could play a crucial role in the early detection and repair of leaks, current practice requires manual inspection, which is both time-consuming and costly. This project envisages maintenance-free measurements at numerous locations within the underground infrastructure, a goal that is to be achieved through the use of a harvesting device mounted on the water pipe. This device extracts energy from the temperature difference between the water pipe and the soil using a TEG (thermoelectric generator), takes sensor measurements, processes the data and transmits it wirelessly via LoRaWAN. We built 16 harvesting devices, installed them in four locations and continuously evaluated their performance throughout the project. In this paper, we focus on two devices of a particular type. The data for a full year show that enough energy was available on 94% of the days, on average, to take measurements and transmit data. This study demonstrates that it is possible to power highly constrained sensing devices with energy harvesting in underground environments.

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.

The Dual Scripps Plankton Camera (DSPC) is a new approach for automated in-situ monitoring of phyto- and zooplankton communities based on a dual magnification dark-field imaging microscope. Here, we present the DSPC and its associated image processing while evaluating its capabilities in i) detecting and characterizing plankton species of different size and taxonomic categories and ii) measuring their abundance in both laboratory and field applications. In the laboratory, body size and abundance estimates by the DSPC significantly and robustly scaled with measurements derived by microscopy. In the field, a DSPC installed permanently at 3 m depth in Lake Greifensee (Switzerland) delivered images of plankton individuals, colonies, and heterospecific aggregates at hourly timescales without disrupting natural arrangements of interacting organisms, their microenvironment or their behavior. The DSPC was able to track the dynamics of taxa, mostly at the genus level, in the size range between ∼10 μm to ∼ 1 cm, covering many components of the planktonic food web (including parasites and potentially toxic cyanobacteria). Comparing data from the field-deployed DSPC to traditional sampling and microscopy revealed a general overall agreement in estimates of plankton diversity and abundances. The most significant disagreements between traditional methods and the DSPC resided in the measurements of zooplankton community properties. Our data suggest that the DSPC is better equipped to study the dynamics and demography of heterogeneously distributed organisms such as zooplankton, because high temporal resolution and continuous sampling offer more information and less variability in taxa detection and quantification than traditional sampling. Time series collected by the DSPC depicted ecological succession patterns, algal bloom dynamics and diel fluctuations with a temporal frequency and morphological resolution that was never observed by traditional methods. Access to high frequency, reproducible and real-time data of a large spectrum of the planktonic ecosystem expands our understanding of both applied and fundamental plankton ecology. We conclude the DSPC is robust for both research and water quality monitoring and suitable for stable long-term deployments.

Data collection in urban drainage systems comes with many challenges. However, many examples already exist, containing numerous useful lessons learned. This chapter therefore contains several urban drainage and stormwater management metrology case studies, selected to cover a wide range of scopes, scales, objectives, climates, data validation methods, and data storage approaches. The case studies are initiated by academics as well as by institutions from the water industry.

More than one‐third of the world's rivers cease to flow and go dry on a periodic basis—so‐called intermittent rivers. The frequency and duration of flow intermittency in running waters are increasing due to climate change and water demands for human use. Intermittency effects on stream biodiversity and ecosystem functioning are dramatic and are expected to become increasingly prevalent in alpine landscapes in the near future. This project used modified field sensors to measure flow intermittency, temperature, and water origin (groundwater, precipitation, glacier) at high spatio‐temporal resolution throughout an alpine fluvial network (Val Roseg, Switzerland). We continuously recorded water presence in 30 tributary streams and validated sensor performance with field‐collected measures. Three different flow regimes were observed in the network, including periodically intermittent, seasonally intermittent, and permanently flowing streams. Twenty‐four streams (80% of recorded streams) dried at least once during the sampling period. Principal components analysis along with generalized additive models showed alpine streams with low average temperature and high conductivity (groundwater‐fed) were prone to permanent flow, whereas streams with higher average temperature and low conductivity (glacier‐fed) typically had intermittent flow. The field sensors proved precise for simultaneously measuring flow intermittency, temperature, and water origin at high resolution throughout the river network. Overall, this approach provides an effective way to develop eco‐hydrological models that examine the effects of flow intermittency on biodiversity and ecosystem functioning in riverine networks.

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?

Collecting precise real-time information on urban drainage system performance is essential to identify, predict and manage critical loading situations, such as urban flash floods and sewer overflows. Although emerging low-power wireless communication techniques allow efficient data transfers with great above-ground performance, for underground or indoor applications a large coverage range is difficult to achieve due to physical and topological limitations, particularly in dense urban areas. In this paper, we first discuss range limitations of the LoRaWAN standard based on a systematic evaluation of a long-term operation of a sensor network monitoring in-sewer process dynamics. Analyses reveal an –. on average – five-fold higher data packet loss for sub-surface nodes, which steadily grows with increasing distance to the gateway. Secondly, we present a novel LPWAN concept based on the LoRa. technology that i) enhances transmission reliability, efficiency and flexibility in range-critical situations through meshed multi-hop routing, and ii) ensures a precise time-synchronization through optional GPS or DCF77 long-wave time signaling. We thirdly illustrate the usefulness of the newly developed concept by evaluating the radio transmission performance for two independent full-scale field tests. Test results show that the synchronous LoRa mesh network approach clearly outperforms the standard LoRaWAN technique with regard to the reliability of packet delivery when transmitting from range-critical locations. Hence, the approach is expected to generally ease data collection from difficult-to-access locations, such as underground areas.

Incubators are essential for a range of culture-based microbial methods, such as membrane filtration followed by cultivation for assessing drinking water quality. However, commercially available incubators are often costly, difficult to transport, not flexible in terms of volume, and/or poorly adapted to local field conditions where access to electricity is unreliable. The purpose of this study was to develop an adaptable, low-cost and transportable incubator that can be constructed using readily available components. The electronic core of the incubator was first developed. These components were then tested under a range of ambient temperature conditions (3.5 °C - 39 °C) using three types of incubator shells (polystyrene foam box, hard cooler box, and cardboard box covered with a survival blanket). The electronic core showed comparable performance to a standard laboratory incubator in terms of the time required to reach the set temperature, inner temperature stability and spatial dispersion, power consumption, and microbial growth. The incubator set-ups were also effective at moderate and low ambient temperatures (between 3.5 °C and 27 °C), and at high temperatures (39 °C) when the incubator set temperature was higher. This incubator prototype is low-cost (< 300 USD) and adaptable to a variety of materials and volumes. Its demountable structure makes it easy to transport. It can be used in both established laboratories with grid power or in remote settings powered by solar energy or a car battery. It is particularly useful as an equipment option for field laboratories in areas with limited access to resources for water quality monitoring.

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.