Preprints
https://doi.org/10.5194/hess-2023-300
https://doi.org/10.5194/hess-2023-300
16 Jan 2024
 | 16 Jan 2024
Status: this preprint is currently under review for the journal HESS.

Inferring sediment-discharge event types in an alpine catchment from sub-daily time series

Amalie Skålevåg, Oliver Korup, and Axel Bronstert

Abstract. Fluvial sediment dynamics in mountain rivers are changing rapidly in a degrading cryosphere, raising the potential for erosive rainfall and runoff, and detrimental effects on downstream areas. Hence, we need to understand better what characterises and drives episodic pulses of water and suspended solids in rivers. Here, we infer different types of such sediment-discharge events from 959 automatically detected events based on 16 metrics derived from 15-min time series of streamflow and suspended sediment concentrations from the Vent-Rofental in the High Ötztal Alps, Austria. We use principal component analysis to extract uncorrelated event characteristics and cluster event types with a Gaussian mixture model. We interpret thus inferred event types with catchment metrics describing antecedent conditions, hydrometeorological forcing, and catchment freezethaw state and snowcover. We find event magnitude, hysteresis, and event shape complexity to be the main factors characterising the overall event regime. The most important characteristics distinguishing the event types are suspended sediment and streamflow magnitude, and event shape complexity. Sediment-discharge hysteresis is less relevant for discerning event types. We derive four event types that we attribute to (1) compound rainfall-melt extremes, (2) glacier and seasonal snow melt, (3) freezethaw-modulated snow-melt and precipitation events, and (4) late season glacier melt. Higher magnitude glacier and snow melt events were the most frequent and contributed some 40 % to annual suspended sediment yield on average; compound rainfall-melt extremes were rarest, but contributed the second highest proportion (26 %). Our approach represents a reproducible method for objectively estimating the variety of event-scale suspended sediment dynamics in mountain rivers, which can provide insights into the contribution of different drivers to annual sediment yields in current and future regimes. Our findings highlight the importance of both meltwater and rainfall-runoff as drivers of high magnitude suspended sediment fluxes in mountain rivers.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Amalie Skålevåg, Oliver Korup, and Axel Bronstert

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2023-300', Anonymous Referee #1, 26 Jan 2024
    • AC1: 'Reply on RC1', Amalie Skålevåg, 25 Mar 2024
  • RC2: 'Comment on hess-2023-300', Anonymous Referee #2, 21 Feb 2024
    • AC2: 'Reply on RC2', Amalie Skålevåg, 25 Mar 2024
Amalie Skålevåg, Oliver Korup, and Axel Bronstert

Data sets

Sediment-discharge event types in Vent-Rofental, Austria Amalie Skålevåg https://doi.org/10.23728/b2share.4806f852f25541b4a3206b0d8110907c

Model code and software

Inferring sediment-discharge event types with clustering Amalie Skålevåg https://github.com/skalevag/hysevt/releases/tag/v0.1

Amalie Skålevåg, Oliver Korup, and Axel Bronstert

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Short summary
We present a cluster-based approach for inferring sediment discharge event types from suspended sediment concentration and streamflow. Applying it to a glacierised catchment, we find event magnitude and shape complexity to be key characteristics separating event types, while hysteresis is less important. The four event types are attributed to compound rainfall-melt extremes, high snow- and glacier melt, freezethaw modulated snow-melt and precipitation, and late season glacier melt.