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Summary: The European Alps are one region of the world where climate-driven changes are already perceptible, as exemplified by the general retreat of mountain glaciers over past decades. Temperatures have risen by up to 2°C since 1900 particularly at high elevations, a rate that is roughly three times the global-average 20th century warming. Regional climate models suggest that by 2100, winters in Switzerland may warm by 3–5°C and summers by 6–7°C according to greenhouse-gas emissions scenarios, while precipitation is projected to increase in winter and sharply decrease in summer. The impacts of these levels of climatic change will affect both the natural environment and a number of economic activities. Alpine glaciers may lose between 50% and 90% of their current volume and the average snowline will rise by 150m for each degree of warming. Hydrological systems will respond in quantity and seasonality to changing precipitation patterns and to the timing of snow-melt in the Alps, with a greater risk of flooding during the spring and droughts in summer and fall. The direct and indirect impacts of a warming climate will affect key economic sectors such as tourism, hydropower, agriculture and the insurance industry that will be confronted to more frequent natural disasters. This paper will thus provide an overview of the current state of knowledge on climatic change and its impacts on the Alpine world. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a comparative study on the mapping of temperature and precipitation fields in complex Alpine terrain. Its relevance hinges on the major impact that inadequate interpolations of meteorological forcings bear on the accuracy of hydrologic predictions regardless of the specifics of the models, particularly during flood events. Three flood events measured in the Swiss Alps are analyzed in detail to determine the interpolation methods which best capture the distribution of intense, orographically-induced precipitation. The interpolation techniques comparatively examined include: Inverse Distance Weighting (IDW), Ordinary Kriging (OK), and Kriging with External Drift (KED). Geostatistical methods rely on a robust anisotropic variogram for the definition of the spatial rainfall structure. Results indicate that IDW tends to significantly underestimate rainfall volumes whereas OK and KED methods capture spatial patterns and rainfall volumes induced by storm advection. Using numerical weather forecasts and elevation data as covariates for precipitation, we provide evidence for KED to outperform the other methods. Most significantly, the use of elevation as auxiliary information in KED of temperatures demonstrates minimal errors in estimated instantaneous rainfall volumes and provides instantaneous lapse rates which better capture snow/rainfall partitioning. Incorporation of the temperature and precipitation input fields into a hydrological model used for operational management was found to provide vastly improved outputs with respect to measured discharge volumes and flood peaks, with notable implications for flood modeling. [ABSTRACT FROM AUTHOR]

Summary: With the aim of calibrating a large number of catchments for a semi-distributed, process-based conceptual hydrological model, we introduce a straightforward yet robust automatic calibration procedure. Since identification of a global parameter optimum is not feasible in practical terms, the procedure presents a trade-off between computational time and algorithm complexity to identify, with reasonable effort, a parameter set that is well representative of the catchment’s dynamics. In its standard mode, the calibration combines three efficiency scores which are evaluated both for the entire calibration period and in terms of their annual and monthly variations. These scores are furthermore assessed only in their relevant value range, producing a comprehensive overall acceptability score which is used to guide an iterative parameter search algorithm. An additional set of four flood-sensitive scores is added, thereby improving results in the peak-flow range. Calibration was done for 140 mesoscale (roughly 10–1000km2) catchments in Switzerland, using the hydrological modelling system PREVAH (Precipitation–Runoff-EVApotranspiration-HRU related model) in hourly time steps. For 49 representative catchments with long gauge records, a median Nash–Sutcliffe efficiency (NSE) of 0.75 was achieved for the calibration period in standard mode. The limited loss in efficiency when moving to the validation period (median NSE: 0.72) proves the stability and representativity of the parameter sets identified, while a Monte-Carlo analysis underscores the effectiveness of our procedure. The Nash–Sutcliffe efficiencies for the additional flood calibration are slightly lower, but again almost equally high for the calibration (0.69) and the validation (0.67) period. Despite the concessions made to improve peak-flow results, the simulation’s hydrological plausibility was not compromised. The ultimate goal of our study is flood estimation in ungauged Swiss catchments through continuous simulation using PREVAH. With the extensive calibration task presented in this article, the foundation is laid for regionalisation of the tuneable model parameters, which will be addressed in the companion paper (), along with detailed flood estimation results. [Copyright &y& Elsevier]