Towards a hydrogeomorphological understanding of proglacial catchments: an assessment of groundwater storage and release in an Alpine catchment

Proglacial margins form when glaciers retreat and create zones with distinctive ecological, geomorphological and hydrological properties in Alpine environments. There is extensive literature on the geomorphology and sediment transport in such areas as well as on glacial hydrology, but there is much less research into the specific hydrological behavior of the landforms that develop after glacier retreat in and close to proglacial margins. Recent reviews have highlighted the presence of groundwater stores even in such rapidly draining environments. Here, we describe the hydrological functioning of different superficial landforms within and around the proglacial margin of the Otemma glacier, a temperate Alpine glacier in the Swiss Alps; we characterize the timing and amount of the transmission of different water sources (rain, snowmelt, ice melt) to the landforms and between them, and we compare the relationship between these processes and the catchment-scale discharge. The latter is based upon a recession-analysis-based framework. In quantifying the relative groundwater storage volumes of different superficial landforms, we show that steep zones only store water on the timescale of days, while flatter areas maintain baseflow on the order of several weeks. These landforms themselves fail to explain the catchment-scale recession patterns; our results point towards the presence of an unidentified storage compartment on the order of 40 mm, which releases water during the cold months. We suggest attributing this missing storage to deeper bedrock flowpaths. Finally, the key insights gained here into the interplay of different landforms as well as the proposed analysis framework are readily transferable to other similar proglacial margins and should contribute to a better understanding of the future hydrogeological behavior of such catchments.</p

Downsizing parameter ensembles for simulations of rare floods

For extreme-flood estimation, simulation-based approaches represent an interesting alternative to purely statistical approaches, particularly if hydrograph shapes are required. Such simulation-based methods are adapted within continuous simulation frameworks that rely on statistical analyses of continuous streamflow time series derived from a hydrological model fed with long precipitation time series. These frameworks are, however, affected by high computational demands, particularly if floods with return periods > 1000 years are of interest or if modelling uncertainty due to different sources (meteorological input or hydrological model) is to be quantified. Here, we propose three methods for reducing the computational requirements for the hydrological simulations for extreme-flood estimation so that long streamflow time series can be analysed at a reduced computational cost. These methods rely on simulation of annual maxima and on analysing their simulated range to downsize the hydrological parameter ensemble to a small number suitable for continuous simulation frameworks. The methods are tested in a Swiss catchment with 10 000 years of synthetic streamflow data simulated thanks to a weather generator. Our results demonstrate the reliability of the proposed downsizing methods for robust simulations of rare floods with uncertainty. The methods are readily transferable to other situations where ensemble simulations are needed

On the links between sub-seasonal clustering of extreme precipitation and high discharge in Switzerland and Europe

River discharge is impacted by the sub-seasonal (weekly to monthly) temporal structure of precipitation. One example is the successive occurrence of extreme precipitation events over sub-seasonal timescales, referred to as temporal clustering. Its potential effects on discharge have received little attention. Here, we address this topic by analysing discharge observations following extreme precipitation events either clustered in time or occurring in isolation. We rely on two sets of precipitation and discharge data, one centred on Switzerland and the other over Europe. We identify “clustered” extreme precipitation events based on the previous occurrence of another extreme precipitation within a given time window. We find that clustered events are generally followed by a more prolonged discharge response with a larger amplitude. The probability of exceeding the 95th discharge percentile in 5 d following an extreme precipitation event is in particular up to twice as high for situations where another extreme precipitation event occurred in the preceding week compared to isolated extreme precipitation events. The influence of temporal clustering on discharge decreases as the clustering window increases; beyond 6–8 weeks the difference in discharge response with non-clustered events is negligible. Catchment area, streamflow regime and precipitation magnitude also modulate the response. The impact of clustering is generally smaller in snow-dominated and large catchments. Additionally, particularly persistent periods of high discharge tend to occur in conjunction with temporal clusters of precipitation extremes

Hydrological model performance and parameter estimation in the wavelet-domain

This paper proposes a method for rainfall-runoff model calibration and performance analysis in the wavelet-domain by fitting the estimated wavelet-power spectrum (a representation of the time-varying frequency content of a time series) of a simulated discharge series to the one of the corresponding observed time series. As discussed in this paper, calibrating hydrological models so as to reproduce the time-varying frequency content of the observed signal can lead to different results than parameter estimation in the time-domain. Therefore, wavelet-domain parameter estimation has the potential to give new insights into model performance and to reveal model structural deficiencies. We apply the proposed method to synthetic case studies and a real-world discharge modeling case study and discuss how model diagnosis can benefit from an analysis in the wavelet-domain. The results show that for the real-world case study of precipitation - runoff modeling for a high alpine catchment, the calibrated discharge simulation captures the dynamics of the observed time series better than the results obtained through calibration in the time-domain. In addition, the wavelet-domain performance assessment of this case study highlights the frequencies that are not well reproduced by the model, which gives specific indications about how to improve the model structure