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Summary This paper investigates the degree of complexity required in a snow accounting routine to ultimately simulate flows at the catchment outlet. We present a simple, parsimonious and general snow accounting routine (SAR), called Cemaneige, that can be associated with any precipitation-runoff model to simulate discharge at the catchment scale. To get results of general applicability, this SAR was tested on a large set of 380 catchments from four countries (France, Switzerland, Sweden and Canada) and combined with four different hydrological models. Our results show that five basic features provide a good reliability and robustness to the SAR, namely considering: (1) a transition range of temperature for the determination of the solid fraction of precipitation; (2) five altitudinal bands of equal area for snow accumulation; (3) the cold-content of the snowpack (with a parameter controlling snowpack inertia); (4) a degree-day factor controlling snowmelt; (5) uneven snow distribution in each band. This general SAR includes two internal states (the snowpack and its cold-content). Results also indicate that only two free parameters (snowmelt factor and cold-content factor) are warranted in a SAR at the daily time step and that further complexity is not supported by improvements in flow simulation efficiency. To justify the reasons for considering the five features above, a sensitivity analysis comparing Cemaneige with other SAR versions is performed. It analyses the snow processes which should be selected or not to bring significant improvement in model performances. Compared with the six existing SARs presented in the companion article ( Valéry et al., 2014 ) on the 380 catchments set, Cemaneige shows better performance on average than five of these six SARs. It provides performance similar to the sixth SAR (MORD4) but with only half its number of free parameters. However, CemaNeige still appears perfectible on mountainous catchments (France and Switzerland) where the lumped SAR, MORD4, outperforms Cemaneige. Cemaneige can easily be adapted for simulation on ungauged catchments: fixing its two parameters to default values much less degrades performances than the other best performing SAR. This may partly due to the Cemaneige parsimony. [ABSTRACT FROM AUTHOR]

Summary This paper analyzes the behavior of hydrological snow accounting routines (SARs) used in combination with hydrological models to simulate streamflow at the catchment scale. To reach conclusions as general as possible, we compare the performance of six existing SARs combined with two different precipitation-runoff models. The SARs are temperature-based, have different levels of complexity (understood here as the number of optimized parameters and model functions), include various processes and also differ by the way they account for the spatial heterogeneity of snow cover. The SARs were tested on a set of 380 catchments significantly affected by snow and located in four countries (France, Switzerland, Sweden and Canada), showing different climatic conditions and altitude ranges. The value of each SAR is evaluated solely in terms of flow simulation quality at the catchment outlet. Several efficiency criteria are used, some of them specifically focusing on the time periods affected by snow accumulation and melt. As expected, the use of a snow accounting routine on snow-affected catchments significantly improves model efficiency, and this is true even for the simplest SARs. More interestingly, our results show that the most complex SAR does not yield the highest performance. Surprisingly, a lumped routine (i.e. without distribution in elevation bands) appears to be the most efficient on average on the whole catchment set. Results seem particularly sensitive to the spatial variability of processes in the snowpack and to the determination of the precipitation phase (solid or liquid). One critical point remains the identification of the solid precipitation correction factor necessary to compensate for snowfall measurement errors. In the companion article, we further investigate the sensitivity of model results to the description of snow processes in the SAR and try to identify the most important components of a parsimonious and general SAR. [ABSTRACT FROM AUTHOR]

Closing the water balance of mountainous catchments may sometimes become tricky, even before applying a hydrological model. In this paper, we focus on mountainous, snow-affected catchments and try to understand the reasons for the “unrealistic” hydrological behaviours that they sometimes show: when annual runoff is greater than the annual areal precipitation estimate, something is obviously wrong, but finding the appropriate means to adjust the water balance is far from a trivial matter. This paper aims to improve our knowledge of the water balance of mountainous and snow-affected catchments in two different countries: Sweden and France. We use a simple non-dimensional framework to detect outliers and then propose an regionalization of precipitation and air temperature in order to better estimate inputs over high-altitude catchments. Since we are interested in catchment water balance, we evaluate our regionalized input estimates by comparing them to streamflow measurements. The results are mixed: in Sweden, our approach is successful because it can make most outlier catchments become regular ones; but in France it is disappointing because it does not solve most of the water balance problems identified. However, for both countries, the regionalization approach significantly improves the performance of a rainfall-runoff model at a daily time step. Citation Valery, A., Andreassian, V. & Perrin, C. (2010) Regionalization of precipitation and air temperature over high-altitude catchments - learning from outliers. Hydrol. Sci. J. 55(6), 928-940. [ABSTRACT FROM AUTHOR]

Highlights: [•] We intercompare 5 distributed hydrologic models on 2 basins in the western US. [•] Participants from France, Italy, Spain and the USA. [•] A widely-used operational lumped model is used as the performance benchmark. [•] Distributed models provided some improvements compared to the benchmark. [•] No strong trend was seen between modeling resolution and simulation performance. [ABSTRACT FROM AUTHOR]