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Accurate long-term inflow forecasts are essential for optimal planning of hydropower production. In snow-rich regions, where spring snowmelt is often the largest reservoir of water, inflow forecasts may be improved by assimilating snow observations to achieve more accurate initial states for the hydrological models prior to the prognosis. In this study, we test whether an ensemble Kalman based approach is useful for this purpose for a mountainous catchment in Norway. For 15 years, annual snow observations near peak accumulation at three locations were assimilated into a distributed hydrological model. After the update, the model was run for a 4-month forecasting period with inflows compared to a base case scenario that omitted the snow observations. The assimilation framework improved the forecasts in several years, and in two of the years, the improvement was very large compared to the base case simulation. At the same time, the filter did not degrade the forecasts largely, indicating that though the updating might slightly degrade performance in some years, it maintains the potential for large improvements in others. Thus, the framework proposed here is a viable method for improving snow-related deficiencies in the initial states, which translates to better forecasts. [ABSTRACT FROM AUTHOR]

Abstract: We investigate the source regions of the three polychlorinated biphenyl congeners (PCBs) 28, 101, and 180 measured at the Arctic stations Alert and Zeppelin, and at Birkenes, which is located in southern Norway. Although the Arctic is remote from the main use areas of these chemicals, PCBs have been found in Arctic air, seawater and biota, which has caused concerns for human and environmental health. We used 20-day backward calculations of the Lagrangian Particle Dispersion Model FLEXPART to identify the origin of air masses associated with the 20% highest and lowest measured PCB concentrations. At Birkenes, high concentrations are clearly associated with air masses arriving from known source regions (primarily in Europe and Russia), whereas low concentrations are correlated with atmospheric transport from regions with low primary emissions. At Zeppelin, the influence from known source regions is also enhanced when high PCB-28 and PCB-101 concentrations were measured. At Alert, in contrast, there is no clear link between high/low PCB concentrations and atmospheric transport from source/non-source regions. Additionally, we combined the atmospheric transport patterns with PCB emission data to identify important source regions and their seasonal variability. For the Arctic stations, Western Russia is the dominant source region for PCB-28 and PCB-101. Central Europe is the most important source region for PCB-180, but sources in the US contribute up to 15% to PCB-180 measured at Alert. [Copyright &y& Elsevier]