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  • (-) Organizational Unit = Mountain Hydrology and Mass Movements
  • (-) Publication Year = 2019 - 2019
  • (-) Keywords ≠ glacier runoff
  • (-) Keywords ≠ assessment
  • (-) Journal = Water Resources Research
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The value of subseasonal hydrometeorological forecasts to hydropower operations: how much does preprocessing matter?
Anghileri, D., Monhart, S., Zhou, C., Bogner, K., Castelletti, A., Burlando, P., & Zappa, M. (2019). The value of subseasonal hydrometeorological forecasts to hydropower operations: how much does preprocessing matter? Water Resources Research. https://doi.org/10.1029/2019WR025280
The relative importance of different flood‐generating mechanisms across Europe
Berghuijs, W. R., Harrigan, S., Molnar, P., Slater, L. J., & Kirchner, J. W. (2019). The relative importance of different flood‐generating mechanisms across Europe. Water Resources Research, 55(6), 4582-4593. https://doi.org/10.1029/2019WR024841
Future trends in the interdependence between flood peaks and volumes: hydro‐climatological drivers and uncertainty
Brunner, M. I., Hingray, B., Zappa, M., & Favre, A. ‐C. (2019). Future trends in the interdependence between flood peaks and volumes: hydro‐climatological drivers and uncertainty. Water Resources Research, 55(6), 4745-4759. https://doi.org/10.1029/2019WR024701
Proneness of European catchments to multiyear streamflow droughts
Brunner, M. I., & Tallaksen, L. M. (2019). Proneness of European catchments to multiyear streamflow droughts. Water Resources Research. https://doi.org/10.1029/2019WR025903
Comparing aerial lidar observations with terrestrial lidar and snow‐probe transects from NASA's 2017 SnowEx campaign
Currier, W. R., Pflug, J., Mazzotti, G., Jonas, T., Deems, J. S., Bormann, K. J., … Lundquist, J. D. (2019). Comparing aerial lidar observations with terrestrial lidar and snow‐probe transects from NASA's 2017 SnowEx campaign. Water Resources Research, 55(7), 6285-6294. https://doi.org/10.1029/2018WR024533
High‐resolution snowline delineation from Landsat imagery to infer snow cover controls in a Himalayan catchment
Girona‐Mata, M., Miles, E. S., Ragettli, S., & Pellicciotti, F. (2019). High‐resolution snowline delineation from Landsat imagery to infer snow cover controls in a Himalayan catchment. Water Resources Research, 55(8), 6754-6772. https://doi.org/10.1029/2019WR024935
Influence of spatial resolution on snow cover dynamics for a coastal and mountainous region at high latitudes (Norway)
Magnusson, J., Eisner, S., Huang, S., Lussana, C., Mazzotti, G., Essery, R., … Beldring, S. (2019). Influence of spatial resolution on snow cover dynamics for a coastal and mountainous region at high latitudes (Norway). Water Resources Research, 55(7), 5612-5630. https://doi.org/10.1029/2019WR024925
Revisiting snow cover variability and canopy structure within forest stands: insights from airborne lidar data
Mazzotti, G., Currier, W. R., Deems, J. S., Pflug, J. M., Lundquist, J. D., & Jonas, T. (2019). Revisiting snow cover variability and canopy structure within forest stands: insights from airborne lidar data. Water Resources Research, 55(7), 6198-6216. https://doi.org/10.1029/2019WR024898
The bias detecting ensemble: a new and efficient technique for dynamically incorporating observations into physics‐based, multi‐layer, snow models
Winstral, A., Magnusson, J., Schirmer, M., & Jonas, T. (2019). The bias detecting ensemble: a new and efficient technique for dynamically incorporating observations into physics‐based, multi‐layer, snow models. Water Resources Research, 55, 613-631. https://doi.org/10.1029/2018WR024521