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Lack of water use data at the user scale is frequently noted in integrated water management and water demand modelling studies. This situation affects particularly mountain tourist areas, where high seasonal water demand related to the variation of temporary population are rarely documented. Irrigation is also a major water use in moutain territories but is not commonly measured. This paper proposes a framework for local-scale monitoring of seasonal water use behaviours and their territorial inprint. A monitoring strategy was developed to collect water demand data at thin spatio-temporal scales which were analysed using two concepts: (i) the water use regime, describing the dynamics of water uses throughout the year using normalised values, and (ii) the water use density, expressing the territorial footprint of a water use, in terms of unit area. This strategy was applied in the alpine tourist municipality of Montana (Switzerland). A two-year monitoring campaign of irrigation and drinking water uses was carried out combining in-field measurement (water metres) with interviews of water users. The temporal resolution of the collected water use dataset (bi-weekly, daily) was sufficient to assess the specific water demand patterns and the short-term water use peaks responsible for water stress in Alpine tourist regions. It provided the first irrigation monitoring in the area and a classification of drinking water data according to their spatial distribution, the type of building and the permanency of residents. The water use density method gives a new prespective on the spatial intensity of water uses, highlighting the importance of garden irrigation in Montana. Also, the water use regime method identified July as the period of water demand peaking. The monitoring of water uses at such thin temporal scale constitutes the necessary dataset for the creation of water balance models that accurately reproduce the effective water use behaviours. [ABSTRACT FROM AUTHOR]

Measurements from load tests may lead to numerical models that better reflect structural behavior. This kind of system identification is not straightforward due to important uncertainties in measurement and models. Moreover, since system identification is an inverse engineering task, many models may fit measured behavior. Traditional model updating methods may not provide the correct behavioral model due to uncertainty and parameter compensation. In this paper, a multimodel approach that explicitly incorporates uncertainties and modeling assumptions is described. The approach samples thousands of models starting from a general parametrized finite-element model. The population of selected candidate models may be used to understand and predict behavior, thereby improving structural management decision making. This approach is applied to measurements from structural performance monitoring of the Langensand Bridge in Lucerne, Switzerland. Predictions from the set of candidate models are homogenous and show an average discrepancy of 4-7% from the displacement measurements. The tests demonstrate the applicability of the multimodel approach for the structural identification and performance monitoring of real structures. The multimodel approach reveals that the Langensand Bridge has a reserve capacity of 30% with respect to serviceability requirements. [ABSTRACT FROM AUTHOR]

We describe the implementation details of the colour reconnection model in the event generator Herwig++. We study the impact on final-state observables in detail and confirm the model idea from colour preconfinement on the basis of studies within the cluster hadronization model. Moreover, we show that the description of minimum bias and underlying event data at the LHC is improved with this model and present results of a tune to available data. [ABSTRACT FROM AUTHOR]

Abstract: With the intention of developing a new data analysis method using virtual experiments we have built a detailed virtual model of the cold triple-axis spectrometer RITA-II at PSI, Switzerland, using the McStas neutron ray-tracing package. The parameters characterising the virtual instrument were carefully tuned against real experiments. In the present paper we show that virtual experiments reproduce experimentally observed linewidths within 1–3% for a variety of samples. Furthermore we show that the detailed knowledge of the instrumental resolution found from virtual experiments, including sample mosaicity, can be used for quantitative estimates of linewidth broadening resulting from, e.g., finite domain sizes in single-crystal samples. [Copyright &y& Elsevier]