A new instrument to study ice nucleation, the Zurich Ice Nucleation Chamber (ZINC), has been constructed. It is a continuous flow diffusion chamber following the design by Rogers (1988) but has a flat parallel plate geometry. The instrument can operate at temperatures as low as 236 K with the current setup with ice supersaturations of up to 50%. The typical sample flow is 1 lpm with a total flow of 10 lpm using twice 4.5 lpm for sheath flows. FLU-ENT simulations were performed and are presented to discuss the flow, temperature, and humidity profiles within the main chamber. Activation experiments with silver iodide particles were used to validate the instrument against literature data. We report the onset of freezing for an activated fraction of 2% of all particles. The data exhibit an almost linear trend between 257 K (111.5% RHi) and 237 K (119% RHi) with very good agreement with literature data.

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For detecting accidental and illegal pollution by mineral oil, the German exclusive economic zone and surrounding waters have been monitored by aircraft operationally for more than 25 years. Aircraft surveillance uses predominantly Side-Looking-Airborne-Radar for visualization of the effect of oil to smoothen capillary waves. A set of near range sensors complements the remote sensing data available for the human operator to classify the detected features as "mineral oil", "natural phenomenon", "other substance" or "unknown" pollution.Today, as an add-on to aerial surveillance, the German Central Command of Maritime Emergencies uses the operational satellite service "CleanSeaNet" provided by the European Maritime Safety Agency: Radar satellite data is analyzed in near real time and alerts of potential pollution are sent out. Shortly after receiving the results, aircraft surveillance flights are started by the 3rd Naval Air Wing and the locations of the satellite alerts are checked. Thus, a combined system of satellite and aerial surveillance is in place. The German Federal Institute of Hydrology, BfG, has access to the data of the pollution events detected during these flights and the corresponding meta-data of flights and satellite images.In this work, a period of two years of this data is analyzed. The probability to detect pollutions is evaluated for (A) flight missions associated with satellite scenes, and (B) additional flights performed independently from satellite scenes. Thus, the influence of satellite alerts on the efficiency of aircraft monitoring is investigated. Coverage and coordination of the monitoring by aircraft and satellite are assessed and implications for the operational monitoring are discussed.

Riparian zones fulfill diverse ecological and economic functions. Sustainable management requires detailed spatial information about vegetation and hydromorphological properties. In this study, we propose a machine learning classification workflow to map classes of the thematic levels Basic surface types (BA), Vegetation units (VE), Dominant stands (DO) and Substrate types (SU) based on multispectral imagery from an unmanned aerial system (UAS). A case study was carried out in Emmericher Ward on the river Rhine, Germany. The results showed that: (I) In terms of overall accuracy, classification results decreased with increasing detail of classes from BA (88.9%) and VE (88.4%) to DO (74.8%) or SU (62%), respectively. (II) The use of Support Vector Machines and Extreme Gradient Boost algorithms did not increase classification performance in comparison to Random Forest. (III) Based on probability maps, classification performance was lower in areas of shaded vegetation and in the transition zones. (IV) In order to cover larger areas, a gyrocopter can be used applying the same workflow and achieving comparable results as by UAS for thematic levels BA, VE and homogeneous classes covering larger areas. The generated classification maps are a valuable tool for ecologically integrated water management.