Quantification of reliability of roofs subjected to snow loadsdetermined by hydrological models

Snow loads exert a significant influence on the structural integrity of buildings in the northern hemisphere, necessitating precise assessment methodologies to ensure the reliability of roofs under this environmental stressor. The determination of roof snow load is intricately linked to evaluating the weight of accumulated snow on the roof surface, a critical consideration in the design and construction of buildings. The reliability of a roof structure is conventionally gauged through the computation of the reliability index, denoted as beta. This index integrates the characteristic ground snow load and an estimation of the associated accuracy, forming a crucial metric for structural engineers. Traditionally, the characteristic ground snow load is determined by fitting a series of yearly maximum ground snow load data to a Gumbel distribution, enabling the extraction of the 50-year return period value. This process traditionally relies on data obtained from weather stations, where meticulous measurements of snow depth are conducted alongside either direct measurements or modeling of snow density. However, the landscape of snow load determination is evolving with the advent of more sophisticated hydrological models. In this context, the paper investigates the impact of transitioning from traditional station data to utilizing gridded simulation data for estimating the characteristic snow load on the ground. The hydrological model "SeNorge" serves as a pivotal tool in this investigation, offering simulated ground snow load data at a 1 km grid. The objective is to scrutinize whether this shift in methodology affects the reliability of buildings and infrastructure subjected to snow loads. The study extends its reach across various climatic zones in Norway, comparing results obtained from the hydrological model with measured data from diverse sources. The fundamental question is whether the adoption of simulated ground snow load data, as generated by advanced hydrological models, translates into a corresponding level of reliability when compared to the established paradigm of utilizing standardized ground snow load data. The results demonstrate a variable uncertainty in the quantification of the snow load depending on the climate region and elevation. When this uncertainty is applied to a reliability calculation a straightforward application of hydrological model may not maintain the same level of reliability as the traditional approach employing standardized ground snow load data. The shift in the structural reliability implies that the partial factors should be adjusted achieve the target reliability criteria when moving from measured to simulated snow load maps. This revelation holds substantial implications for the engineering community, urging a cautious approach to the adoption of newer methodologies in snow load assessments.