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[1] Thirty-three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up to two winter snow seasons. Modeled estimates of snow water equivalent (SWE) or depth were compared to observations at forest and open sites at each location. Precipitation phase and duration of above-freezing air temperatures are shown to be major influences on divergence and convergence of modeled estimates of the subcanopy snowpack. When models are considered collectively at all locations, comparisons with observations show that it is harder to model SWE at forested sites than open sites. There is no universal ''best'' model for all sites or locations, but comparison of the consistency of individual model performances relative to one another at different sites (and vice versa). Calibration of models at forest sites provides lower errors than uncalibrated models at three out of four locations. However, benefits of calibration do not translate to subsequent years, and benefits gained by models calibrated for forest snow processes are not translated to open conditions.

This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come. ARTICLE HISTORY

A comprehensive, physically based model of snow accumulation, redistribution, sublimation, and melt for open and forested catchments was assembled, based on algorithms derived from hydrological process research in Russia and Canada. The model was used to evaluate the long-term snow dynamics of a forested and an agricultural catchment in northwestern Russia without calibration from snow observations. The model was run with standard meteorological variables for the two catchments, and its results were tested against regular surface observations of snow accumulation throughout the winter and spring period for 17 seasons. The results showed mean errors in comparison to observations of less than 3% in estimating snow water equivalent during the winter and melt seasons. Snow surface evaporation and blowing snow were found to be small components of the mass balance, but intercepted snow sublimation removed notable amounts of snow over the winter from the forested catchment. Average snow accumulation was 15% higher in the open catchment, largely due to a lack of intercepted snow sublimation. Melt rates were 23% higher in the open than in the forest, but the effect on melt duration was suppressed by the smaller premelt accumulation in the forest. Only a moderate sensitivity of snow accumulation to forest leaf area was found, while a substantial variation was observed from season to season with changing weather patterns. This suggests that the ensemble of snow processes is more sensitive to variations in atmospheric processes than in vegetation cover. The success in using algorithms from both Canada and Russia in modeling snow dynamics suggests that there may be a potential for large-scale transferability of the modeling techniques.