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Projekt Druckansicht

Beobachtung und Modellierung der räumlichen und zeitlichen Variabilität von Schneeprozesses in der Übergangs-Schneezone

Antragsteller Professor Dr. Stefan Pohl (†)
Fachliche Zuordnung Hydrogeologie, Hydrologie, Limnologie, Siedlungswasserwirtschaft, Wasserchemie, Integrierte Wasserressourcen-Bewirtschaftung
Förderung Förderung von 2010 bis 2015
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 188012580
 
Erstellungsjahr 2015

Zusammenfassung der Projektergebnisse

The overall goal of the project was the improvement of our capability to forecast winter flooding events mainly due to rain on snow conditions (ROS) in mid elevation temperate climate mountain regions. This was to be achieved by analyzing the temporal and spatial variability of the snow cover and of the energy balance terms that lead to the melt of the snow cover. This goal along with other research focusses were fully met during the project. First of all, the observations during the project proved the importance of ROS events in temperate climate regions. Over the four winters 19 ROS events were recorded in the three research basins. The importance of snow meltwater contribution was shown as meltwater contributed on average 48% to flood runoff with a maximum contribution of 64%. The project showed that the innovative observational network approach of augmenting the (few) existing weather stations with numerous (up to 101) self-developed cost efficient snow monitoring stations (SnoMoS) was very well suited to study the temporal and spatial heterogeneities of the snow cover and the energy balance terms. The SnoMoS can continuously record the snow depth and most of the climate variables needed to calculate a full melt energy balance. The project showed that the SnoMoS reliably provided high quality data and are well suited for the intended purpose. The network was augmented by installing 45 interval cameras that provided important data on snow depth, snow interception in the forest canopy, snow albedo, and state of precipitation. Finally, manual snow surveys were carried out at regular intervals to observe snow depth and small scale spatial variability. The observed snow cover variability proved that this factor is very important in medium elevation mountain ranges and has to be considered in hydrological modelling and flood forecasting. A multiple linear regression analysis showed that elevation, aspect, and land cover explained most (up to 80%) of the variability in the snow cover. Additionally, local topographic features (f.e. closed bowls or cirques) were identified as important features. The recordings also proved that forests have a major impact on snow accumulation and ablation and that there are significant differences between different forest types. The analysis of the spatially variable snowmelt energy balance during ROS events proved the importance of the turbulent fluxes and the net long wave radiation during these events. It also showed that the overall melt energy sums were very similar in open and forested locations and that the melt energy was consistently positive even during the nighttime hours. This is very important for flood formation as this means, that the whole basin may continuously contribute meltwater to runoff during these conditions. The analysis of runoff water origin during ROS events showed that a basin usually starts to contribute at the lowest locations and that the contributing area expands from there. It also showed that despite the interception of liquid and solid precipitation in the forest canopy, forest areas still contributed almost equal amounts of runoff water to flood runoff compared to open areas. Again this is crucial for runoff formation as the whole basin contributes significantly to runoff. The study also showed that, depending on its pre-event condition, a snow cover may initially act as a buffer as it may store considerable quantities of rainwater if the snow cover was dry and cold prior to the event. On the other hand a warm already saturated snow cover may worsen a flood runoff very quickly. This indicates that hydrologic flood forecast models should include not only the amount of snow present in the area but also its state. The knowledge and data gathered during the project is and will be used in the future to improve hydrologic model of all complexities. The designed SnoMoS sensors will be used in a variety of settings by multiple research groups to continuously monitor the evolution of the snow cover. The project generated a lot of interest in the local communities and amongst the local farmers on whose lands the stations were set up. Two articles were published in the local paper explaining the goals and methods of the project. They can be found at: http://www.badische-zeitung.de/oberried/warnungen-erfolgen-frueher--80518643.html http://www.badische-zeitung.de/neues-fuer-kinder/vorsicht-tauwetter--69347649.html Overall, the project can be considered a great success. Almost all of the goals of the study were met. The project introduced a new observation network approach to the snow hydrology community that is now being employed in numerous studies. Furthermore the dataset gathered has and will be used extensively for the validation and improvement of hydrologic models.

Projektbezogene Publikationen (Auswahl)

 
 

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