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Resolving small‐scale forest snow patterns using an energy‐balance snow model with a 1‐layer canopy
Mazzotti, G., Essery, R., Moeser, C. D., & Jonas, T. (2020). Resolving small‐scale forest snow patterns using an energy‐balance snow model with a 1‐layer canopy. Water Resources Research, 56(1), e2019WR026129 (22 pp.). https://doi.org/10.1029/2019WR026129
Snow depth patterns in a high mountain Andean catchment from satellite optical tristereoscopic remote sensing
Shaw, T. E., Gascoin, S., Mendoza, P. A., Pellicciotti, F., & McPhee, J. (2020). Snow depth patterns in a high mountain Andean catchment from satellite optical tristereoscopic remote sensing. Water Resources Research, 56(2), e2019WR024880 (23 pp.). https://doi.org/10.1029/2019WR024880
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, 55(12), 10159-10178. 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, 55(11), 8881-8894. 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
Retrieval of snow water equivalent, liquid water content, and snow height of dry and wet snow by combining GPS signal attenuation and time delay
Koch, F., Henkel, P., Appel, F., Schmid, L., Bach, H., Lamm, M., … Mauser, W. (2019). Retrieval of snow water equivalent, liquid water content, and snow height of dry and wet snow by combining GPS signal attenuation and time delay. Water Resources Research, 55, 4465-4487. https://doi.org/10.1029/2018WR024431
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
Bias correction of airborne thermal infrared observations over forests using melting snow
Pestana, S., Chickadel, C. C., Harpold, A., Kostadinov, T. S., Pai, H., Tyler, S., … Lundquist, J. D. (2019). Bias correction of airborne thermal infrared observations over forests using melting snow. Water Resources Research, 55(12), 11331-11343. https://doi.org/10.1029/2019WR025699
Identification of source-water oxygen isotopes in trees toolkit (ISO-tool) for deciphering historical water use by forest trees
Sargeant, C. I., Singer, M. B., & Vallet-Coulomb, C. (2019). Identification of source-water oxygen isotopes in trees toolkit (ISO-tool) for deciphering historical water use by forest trees. Water Resources Research, 55(12), 10954-10975. https://doi.org/10.1029/2018WR024519
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
Snow depth Structure, fractal Behavior, and interannual consistency over Haut Glacier d'Arolla, Switzerland
Clemenzi, I., Pellicciotti, F., & Burlando, P. (2018). Snow depth Structure, fractal Behavior, and interannual consistency over Haut Glacier d'Arolla, Switzerland. Water Resources Research, 54(10), 7929-7945. https://doi.org/10.1029/2017WR021606
Water flux tracking with a distributed hydrological model to quantify controls on the spatiotemporal variability of transit time distributions
Remondi, F., Kirchner, J. W., Burlando, P., & Fatichi, S. (2018). Water flux tracking with a distributed hydrological model to quantify controls on the spatiotemporal variability of transit time distributions. Water Resources Research, 54(4), 3081-3099. https://doi.org/10.1002/2017WR021689
Variability of bed load transport during six summers of continuous measurements in two Austrian mountain streams (Fischbach and Ruetz)
Rickenmann, D. (2018). Variability of bed load transport during six summers of continuous measurements in two Austrian mountain streams (Fischbach and Ruetz). Water Resources Research, 54(1), 107-131. https://doi.org/10.1002/2017WR021376
Early formation of preferential flow in a homogeneous snowpack observed by micro-CT
Avanzi, F., Petrucci, G., Matzl, M., Schneebeli, M., & De Michele, C. (2017). Early formation of preferential flow in a homogeneous snowpack observed by micro-CT. Water Resources Research, 53(5), 3713-3729. https://doi.org/10.1002/2016WR019502
Influence of Slope-Scale Snowmelt on Catchment Response Simulated With the Alpine3D Model
Brauchli, T., Trujillo, E., Huwald, H., & Lehning, M. (2017). Influence of Slope-Scale Snowmelt on Catchment Response Simulated With the Alpine3D Model. Water Resources Research, 53(12), 10723-10739. https://doi.org/10.1002/2017WR021278
Near-surface turbulence as a missing link in modeling evapotranspiration-soil moisture relationships
Haghighi, E., & Kirchner, J. W. (2017). Near-surface turbulence as a missing link in modeling evapotranspiration-soil moisture relationships. Water Resources Research, 53(7), 5320-5344. https://doi.org/10.1002/2016WR020111
 

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