Information content of snow hydrological signatures based on streamflow, precipitation and air temperature. Issue 12 (29th April 2020)

• Record Type: Journal Article
• Authors: Horner, Ivan; Branger, Flora; McMillan, Hilary; Vannier, Olivier; Braud, Isabelle
• Is Part Of: Hydrological processes. Volume 34:Issue 12(2020)
• Page Start: 2763
• Page End: 2779
• Publication Date: 2020-04-29
• Subjects: air temperature -- critical zone observatory -- hydrological signatures -- precipitation -- snow accumulation -- snow measurements -- snow melt -- snow processes -- snow storage -- southern sierra -- streamflow; Hydrology -- Periodicals; Hydrology -- Research -- Periodicals; Hydrologic models -- Periodicals; Hydrological forecasting -- Periodicals; 631.432
• DOI: 10.1002/hyp.13762
• Languages: English
• ISSNs: 0885-6087

Abstract

Abstract: Hydrological signatures that represent snow processes are valuable to gain insights into snow accumulation and snow melt dynamics. We investigated five snow signatures. Considering inter‐annual average of each calendar day, two slopes derived from the relation between streamflow and air temperature for different periods and streamflow peak maxima are used as signatures. In addition, two different approaches are used to compute inter‐annual average and yearly snow storage estimates. We evaluated the ability of these signatures to characterize average (a) snow melt dynamics and (b) snow storage. They were applied in 10 Critical Zone Observatory catchments of the Southern Sierra mountains (USA) characterized by a Mediterranean climate. The relevance and information content of the signatures are evaluated using snow depth and snow water equivalent measurements as well as inter‐catchment differences in elevation. The slopes quantifying the relations between streamflow and air temperature and the date of streamflow peak were found to characterize snow melt dynamics in terms of snow melt rates and snow melt affected areas. Streamflow peak dates were linked to the period of highest snow melt rates. Snow storage could be estimated both on average, considering all years, and for each year. Snow accumulation dynamics could not be characterized due to the lack of streamflow response during the snow accumulation period. The signatures were found potentially valuable to gain insights into catchment scale snow processes. In particular, when comparing catchments or observed and simulated data, they could provide insights into differences in terms of (a) snow melt rate and/or snow melt affected area over the snow melt season and (b) average or yearly snow storage. Requiring only widely available data, these hydrological signatures can be valuable for snow processes characterization, catchment comparison/classification or model development, calibration or evaluation. Abstract : A set of five hydrological signatures are evaluated by confronting them with snow measurements. One of our main results is that temperature/streamflow slopes during the snow melt season are linked to snow melt rate, snow cover extent and total snow accumulation.