No abstract

[1] The spatial and temporal (event and seasonal timescale) variability of major runoff components in the mountainous Brugga basin (Black Forest, Germany) were examined. The mesoscale (40 km 2 ) study basin represented an extraordinary challenge as comparable studies have been undertaken mainly in smaller headwater basins. Discharge data, tracer concentrations of 18 O, 3 H, CFCs, and dissolved silica, and major anions and cations were analyzed during single events and over a period of 3 years. Three main runoff components were defined: event water with a residence time of several hours to a few days contributed up to 50% during flood peaks, quantified by a classical hydrograph separation technique using 18 O. However, this component is of minor importance for longer periods, comprising $11.1% of total runoff as estimated for the period August 1995 to April 1998. The other two flow components originated from shallow and deep groundwater. Source areas for these are the upper drift and debris cover for the shallow groundwater and the deeper drift, weathering zone and hard rock aquifer for the deep groundwater. Mean residence times ranged from 28 to 36 months on the basis of 18 O data for the shallow groundwater and from 6 to 9 years on the basis of 3 H and CFC data for the deep groundwater. The importance of the upper drift and debris cover of the slopes for runoff generation at the test site was clearly demonstrated at the seasonal timescale, showing a contribution of 69.4% based on a mixing model with a monthly time step. The deep groundwater contribution was 19.5%. With this information a conceptual model of runoff generation for the study site was constructed.

No abstract

No abstract

13C was assumed to be concertedly influenced by Gs and photosynthetically active radiation (PAR) (as a proxy for photosynthetic capacity). We conclude that isotope signatures can be used as effective tools (1) to characterize the seasonal dynamics in source and xylem water, and (2) to assess environmental effects on transpiration and Gs of Scots pine, thus helping to understand and predict potential impacts of climate change on trees and forest ecosystems.