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Integrating automated water samplers into wireless sensor networks (WIRESAM)

Das Projekt "Integrating automated water samplers into wireless sensor networks (WIRESAM)" wird vom Umweltbundesamt gefördert und von Universität Zürich, Geographisches Institut durchgeführt. In environmental sciences field locations are often remote, difficult - and at times dangerous - to access (time-restricted access). Sensor-logger units and water samplers, which record data automatically, can partly overcome these restrictions. For water samplers the triggering of the sampling is a core issue. Typically, the onset of sampling is initiated by a single on-site sensor (e.g. when reaching/exceeding a water level threshold). Up-to-date, water samplers have not been linked to each other or integrated in a sensor network (e.g. on-site water level sensors, off-site rain gauges and upstream water quality sensors). This project intends to integrate a suit of water samplers installed along a stream into a sensor network installed in the same catchment. This approach allows new possibilities of sampling, as the applied sampling strategy (e.g. triggering of the samplers) can be step-wise adapted, coordinated, and optimised based on online data generated by the catchment-wide sensor network. As a result of this project, water quantity sensor data can be linked to water quality sampling data on a new level, enabling scientists to implement sampling strategies based on online-interpretation of sensor data (e.g. by a hydrological or environmental model).

Comparison of sampling strategies for solute load estimates

Das Projekt "Comparison of sampling strategies for solute load estimates" wird vom Umweltbundesamt gefördert und von Universität Zürich, Geographisches Institut durchgeführt. To assess the status and actual trends of surface water bodies as proposed by the EU water framework directive, reliable monitoring strategies are fundamental. However, in research and governmental water quality monitoring studies, clear guidelines for experimental design of monitoring campaigns are often unavailable, leading to flawed or ambiguous data sets. Not only are the data difficult to interpret, but incorrect conclusions and resulting policy recommendations can have far-reaching implications. Inadequate sampling devices or strategies are often responsible for sampling artifacts. These artifacts can obscure real variations in the environment. This is especially critical when considering nutrients, pollutants or environmental tracers, which vary with discharge fluctuations. In this project we compare sampling strategies, methods, and new devices using case studies from research catchments in Switzerland and Germany and an international watershed (Lake Constance). We evaluate time, water level and volume proportional integrative sampling strategies active with grab sampling for solute load estimates with emphasis on nutrient fluxes during pronounced discharge events. We compare various active samplers (event-triggered sampling, time-proportional composite sampling, volume-proportional composite sampling) with passive samplers for several events in different catchments.

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