Articles | Volume 386
https://doi.org/10.5194/piahs-386-217-2024
https://doi.org/10.5194/piahs-386-217-2024
Post-conference publication
 | 
19 Apr 2024
Post-conference publication |  | 19 Apr 2024

Long-range streamflow prediction using a distributed hydrological model in a snowfed watershed

Abdul Moiz and Akiyuki Kawasaki

Cited articles

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Moiz, A., Zhongwang, W., Naseer, A., Kawasaki, A., Acierto, R. A., and Koike, T.: Improving snow-process modeling by evaluating reanalysis vertical temperature profiles using a distributed hydrological model, J. Geophys. Res.-Atmos., 127, e2021JD036174, https://doi.org/10.1029/2021JD036174, 2022. 
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Short summary
In this research we evaluate the skill of long-range forecasts generated using a state-of-the-art physically based hydrological model for a snowfed watershed (Kurobe) in Japan to support water resources management. We further assess the contribution of initial conditions (snow and soil moisture in the basin) towards the skills of the forecast and found that in April, May, June and July the initial conditions play an important role.