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    Investigating the Role of Snow Water Equivalent on Streamflow Predictability during Drought

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    JHM-D-21-0229.1.pdf (3.515Mb)
    Date
    2022
    Author
    Parthkumar A. Modi
    Eric E. Small
    Joseph Kasprzyk
    Ben Livneh
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    Abstract
    Snowpack provides the majority of predictive information for water supply forecasts (WSFs) in snow-dominated basins across the western United States. Drought conditions typically accompany decreased snowpack and lowered runoff efficiency, negatively impacting WSFs. Here, we investigate the relationship between snow water equivalent (SWE) and April–July streamflow volume (AMJJ-V) during drought in small headwater catchments, using observations from 31 USGS streamflow gauges and 54 SNOTEL stations. A linear regression approach is used to evaluate forecast skill under different historical climatologies used for model fitting, as well as with different forecast dates. Experiments are constructed in which extreme hydrological drought years are withheld from model training, that is, years with AMJJ-V below the 15th percentile. Subsets of the remaining years are used for model fitting to understand how the climatology of different training subsets impacts forecasts of extreme drought years. We generally report overprediction in drought years. However, training the forecast model on drier years, that is, below-median years (
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    http://yetl.yabesh.ir/yetl1/handle/yetl/4289648
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