Abstract. Stream temperature and discharge are key hydrological variables for ecosystem and water resource management and are particularly sensitive to climate warming. Despite the wealth of meteorological and hydrological data, few studies have quantified observed stream temperature trends in the Alps. This study presents a detailed analysis of stream temperature and discharge in 52 catchments in Switzerland, a country covering a wide range of alpine and lowland hydrological regimes. The influence of discharge, precipitation, air temperature, and upstream lakes on stream temperatures and their temporal trends is analysed from multi-decadal to seasonal timescales. Stream temperature has significantly increased over the past 5 decades, with positive trends for all four seasons. The mean trends for the last 20 years are +0.37±0.11 ∘C per decade for water temperature, resulting from the joint effects of trends in air temperature (+0.39±0.14 ∘C per decade), discharge (-10.1±4.6 % per decade), and precipitation (-9.3±3.4 % per decade). For a longer time period (1979–2018), the trends are +0.33±0.03 ∘C per decade for water temperature, +0.46±0.03°C per decade for air temperature, -3.0±0.5 % per decade for discharge, and -1.3±0.5 % per decade for precipitation. Furthermore, we show that snow and glacier melt compensates for air temperature warming trends in a transient way in alpine streams. Lakes, on the contrary, have a strengthening effect on downstream water temperature trends at all elevations. Moreover, the identified stream temperature trends are shown to have critical impacts on ecological and economical temperature thresholds (the spread of fish diseases and the usage of water for industrial cooling), especially in lowland rivers, suggesting that these waterways are becoming more vulnerable to the increasing air temperature forcing. Resilient alpine rivers are expected to become more vulnerable to warming in the near future due to the expected reductions in snow- and glacier-melt inputs. A detailed mathematical framework along with the necessary source code are provided with this paper.

Snow and hydrological modeling in alpine environments remains challenging because of the complexity of the processes affecting the mass and energy balance. This study examines the influence of snowmelt on the hydrological response of a high‐alpine catchment of 43.2 km2 in the Swiss Alps during the water year 2014–2015. Based on recent advances in Alpine3D, we examine how snow distributions and liquid water transport within the snowpack influence runoff dynamics. By combining these results with multiscale observations (snow lysimeter, distributed snow depths, and streamflow), we demonstrate the added value of a more realistic snow distribution at the onset of melt season. At the site scale, snowpack runoff is well simulated when the mass balance errors are corrected (R2 = 0.95 versus R2 = 0.61). At the subbasin scale, a more heterogeneous snowpack leads to a more rapid runoff pulse originating in the shallower areas while an extended melting period (by a month) is caused by snowmelt from deeper areas. This is a marked improvement over results obtained using a traditional precipitation interpolation method. Hydrological response is also improved by the more realistic snowpack (NSE of 0.85 versus 0.74), even though calibration processes smoothen out the differences. The added value of a more complex liquid water transport scheme is obvious at the site scale but decreases at larger scales. Our results highlight not only the importance but also the difficulty of getting a realistic snowpack distribution even in a well‐instrumented area and present a model validation from multiscale experimental data sets.

Abstract. Climate change is expected to strongly impact the hydrological and thermal regimes of Alpine rivers within the coming decades. In this context, the development of hydrological models accounting for the specific dynamics of Alpine catchments appears as one of the promising approaches to reduce our uncertainty of future mountain hydrology. This paper describes the improvements brought to StreamFlow, an existing model for hydrological and stream temperature prediction built as an external extension to the physically based snow model Alpine3D. StreamFlow's source code has been entirely written anew, taking advantage of object-oriented programming to significantly improve its structure and ease the implementation of future developments. The source code is now publicly available online, along with a complete documentation. A special emphasis has been put on modularity during the re-implementation of StreamFlow, so that many model aspects can be represented using different alternatives. For example, several options are now available to model the advection of water within the stream. This allows for an easy and fast comparison between different approaches and helps in defining more reliable uncertainty estimates of the model forecasts. In particular, a case study in a Swiss Alpine catchment reveals that the stream temperature predictions are particularly sensitive to the approach used to model the temperature of subsurface flow, a fact which has been poorly reported in the literature to date. Based on the case study, StreamFlow is shown to reproduce hourly mean discharge with a Nash-Sutcliffe efficiency (NSE) of 0.82 and hourly mean temperature with a NSE of 0.78.

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Abstract. Climate change is expected to strongly impact the hydrological and thermal regimes of Alpine rivers within the coming decades. In this context, the development of hydrological models accounting for the specific dynamics of Alpine catchments appears as a one of the promising approaches to reduce our uncertainty on future mountain hydrology. This paper describes the improvements brought to StreamFlow, an existing model for hydrological and stream temperature prediction built as an external extension to the physically-based snow model Alpine3D. StreamFlow's source code has been entirely written anew, taking advantage of object-oriented programming to significantly improve its structure and ease the implementation of future developments. The source code is now publicly available online, along with a complete documentation. A special emphasis has been put on modularity during the re-implementation of StreamFlow, so that many model aspects can be represented using different alternatives. For example, several options are now available to model the advection of water within the stream. This allows for an easy and fast comparison between different approaches and helps in defining more reliable uncertainty estimates of the model forecasts. In particular, a case study in a Swiss Alpine catchment reveals that the stream temperature predictions are particularly sensitive to the approach used to model the temperature of subsurface runoff, a fact which has been poorly reported in the literature to date. Based on the case study, StreamFlow is shown to reproduce hourly mean discharge with a Nash–Sutcliffe efficiency (NSE) of 0.82, and hourly mean temperature with a NSE of 0.78.

Abstract. Stream temperature is a key hydrological variable for ecosystem and water resources management and is particularly sensitive to climate warming. Despite the wealth of meteorological and hydrological data, few studies have quantified observed stream temperature trends in the Alps. This study presents a detailed analysis of stream temperatures in 52 catchments in Switzerland, a country covering a wide range of alpine and lowland hydrological regimes. The influence of discharge, precipitation, air temperature and upstream lakes on stream temperatures and their temporal trends is analysed from multi-decade to seasonal time scales. Stream temperature has significantly increased over the past 5 decades, with positive trends for all four seasons. The mean trends for the last 20 years are +0.37 °C per decade for water temperature, resulting from joint effects of trends in air temperature (+0.39 °C per decade) in discharge (−10.1 % per decade) and in precipitation (−9.3 % per decade). For a longer time period (1979–2018), the trends are +0.33 °C per decade for water temperature, +0.46 °C per decade for air temperature, −3.0 % per decade for discharge and −1.3 % per decade for precipitation. We furthermore show that in alpine streams, snow and glacier melt compensates air temperature warming trends in a transient way. Lakes, on the contrary have a strengthening effect on downstream water temperature trends at all elevations. The identified stream temperature trends are furthermore shown to have critical impacts on ecological temperature thresholds, especially in lowland rivers, suggesting that these are becoming more vulnerable to the increasing air temperature forcing. Resilient alpine rivers are expected to become more vulnerable to warming in the near future due to the expected reductions in snow- and glacier melt inputs.

Abstract. In steep and complex mountainous terrain, robust simulations of snow accumulation and ablation are crucial to a wide range of applications, especially those related to hydrology and ecology. Whilst new opportunities exist to integrate high-resolution spatio-temporal observations in the estimation of uncertain parameters in (a.k.a. “calibration” of) sophisticated, process-rich snow models, they have not yet been fully exploited. Here, with a view towards improving representations of snow and ultimately meltwater dynamics in rugged topography, a novel approach to the calibration of a high-resolution energy balance-based snow model that additionally accounts for gravitational snow redistribution is presented. Several important but uncertain parameters are estimated using an efficient, gradient-based method with respect to two complementary types of snow observations – snow extent maps derived from Landsat 8 images, and snow water equivalent (SWE) time-series reconstructed at two contrasting locations. When assessed on a per-pixel basis over 17 days that together encompass practically the full range of possible snow cover conditions, snow patterns were reproduced with a mean accuracy of 85 %. The spatial performance metrics obtained compare favourably with those previously reported, whilst the temporal evolution of SWE at the stations was also satisfactorily simulated. Uncertainty and data worth analyses revealed that: i) the propensity for model predictions to be erroneous was substantially reduced by the calibration process, ii) pre-calibration uncertainty was largely associated with two parameters that were introduced to modify the longwave component of the energy balance, but this uncertainty was greatly diminished by calibration, and iii) the lower elevation SWE time-series was particularly valuable despite the comparatively small number of observations at this site. Alongside a gridded snowmelt dataset, commensurate estimates of firn melt, ice melt, liquid precipitation, and potential evapotranspiration were also produced. Our study demonstrates the growing potential of combining observation technologies and state-of-the-art inverse approaches to both constrain and quantify the uncertainty associated with simulations of alpine snow dynamics.

The present supplementary material is complementing the key elements of the study presented in the main part of this work. It either expands on results which were too voluminous for the main article or gives elements for better understanding and potential reproduction of the results. Often, the article only shows pertinent examples while the larger body of corresponding results is included here. The first part is a collection of additional tables and figures related to the data and methods presented (Section S1), followed by more figures, detailing and complementing the main results in the article (Section