This paper addresses the signatures of catchment geomorphology on base flow recession curves. Its relevance relates to the implied predictability of base flow features, which are central to catchment‐scale transport processes and to ecohydrological function. Moving from the classical recession curve analysis method, originally applied in the Finger Lakes Region of New York, a large set of recession curves has been analyzed from Swiss streamflow data. For these catchments, digital elevation models have been precisely analyzed and a method aimed at the geomorphic origins of recession curves has been applied to the Swiss data set. The method links river network morphology, epitomized by time‐varying distribution of contributing channel sites, with the classic parameterization of recession events. This is done by assimilating two scaling exponents, β and bG, with |dQ/dt| ∝ Qβ where Q is at‐a‐station gauged flow rate and N(l) ∝ N(l)∝G(l)bG where l is the downstream distance from the channel heads receding in time, N(l) is the number of draining channel reaches located at distance l from their heads, and G(l) is the total drainage network length at a distance greater or equal to l, the active drainage network. We find that the method provides good results in catchments where drainage density can be regarded as spatially constant. A correction to the method is proposed which accounts for arbitrary local drainage densities affecting the local drainage inflow per unit channel length. Such corrections properly vanish when the drainage density become spatially constant. Overall, definite geomorphic signatures are recognizable for recession curves, with notable theoretical and practical implications.

[1] We propose an approach to spatial modeling of extreme rainfall, based on max-stable processes fitted using partial duration series and a censored threshold likelihood function. The resulting models are coherent with classical extreme-value theory and allow the consistent treatment of spatial dependence of rainfall using ideas related to those of classical geostatistics. We illustrate the ideas through data from the Val Ferret watershed in the Swiss Alps, based on daily cumulative rainfall totals recorded at 24 stations for four summers, augmented by a longer series from nearby. We compare the fits of different statistical models appropriate for spatial extremes, select that best fitting our data, and compare return level estimates for the total daily rainfall over the stations. The method can be used in other situations to produce simulations needed for hydrological models, and in particular, for the generation of spatially heterogeneous extreme rainfall fields over catchments.

In high-altitude alpine catchments, diurnal streamflow cycles are typically dominated by snowmelt or ice melt. Evapotranspiration-induced diurnal streamflow cycles are less observed in these catchments but might happen simultaneously. During a field campaign in the summer 2012 in an alpine catchment in the Swiss Alps (Val Ferret catchment, 20.4 km 2 , glaciarized area: 2%), we observed a transition in the early season from a snowmelt to an evapotranspiration-induced diurnal streamflow cycle in one of two monitored subbasins. The two different cycles were of comparable amplitudes and the transition happened within a time span of several days. In the second monitored subbasin, we observed an ice meltdominated diurnal cycle during the entire season due to the presence of a small glacier. Comparisons between ice melt and evapotranspiration cycles showed that the two processes were happening at the same times of day but with a different sign and a different shape. The amplitude of the ice melt cycle decreased exponentially during the season and was larger than the amplitude of the evapotranspiration cycle which was relatively constant during the season. Our study suggests that an evapotranspirationdominated diurnal streamflow cycle could damp the ice melt-dominated diurnal streamflow cycle. The two types of diurnal streamflow cycles were separated using a method based on the identification of the active riparian area and measurement of evapotranspiration.

[1] Streamflow time series are important for inference and understanding of the hydrological processes in alpine watersheds. Because streamflow is expensive to continuously measure directly, it is usually derived from measured water levels, using a rating curve modeling the stage-discharge relationship. In alpine streams, this practice is complicated by the fact that the streambed constantly changes due to erosion and sedimentation by the turbulent mountain streams. This makes the stage-discharge relationship dynamic, requiring frequent discharge gaugings to have reliable streamflow estimates. During an ongoing field study in the Val Ferret watershed in the Swiss Alps, 93 streamflow values were measured in the period 2009-2011 using salt dilution gauging with the gulp injection method. The natural background electrical conductivity in the stream, which was measured as by-product of these gaugings, was shown to be a strong predictor for the streamflow, even marginally outperforming water level. Analysis of the residuals of both predictive relations revealed errors in the gauged streamflows. These could be corrected by filtering disinformation from erroneous calibration coefficients. In total, extracting information from the auxiliary data enabled to reduce the uncertainty in the rating curve, as measured by the root-mean-square error in log-transformed streamflow relative to that of the original stage-discharge relationship, by 43.7%.

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