Preprints
https://doi.org/10.5194/hess-2017-419
https://doi.org/10.5194/hess-2017-419

  17 Jul 2017

17 Jul 2017

Review status: this discussion paper is a preprint. It has been under review for the journal Hydrology and Earth System Sciences (HESS). The manuscript was not accepted for further review after discussion.

A Process–Based Rating Curve to model suspended sediment concentration in Alpine environments

Anna Costa, Daniela Anghileri, and Peter Molnar Anna Costa et al.
  • Institute of Environmental Engineering, ETH Zurich, 8093 Zurich, Switzerland

Abstract. A Process-Based Rating Curve (PBRC) approach to simulate mean daily suspended sediment concentration (SSC) as a function of different sediment sources and their activation by erosive rainfall (ER), snowmelt (SM), and icemelt (IM) in an Alpine catchment is presented. Similarly to the traditional rating curve, the PBRC relates SSC to the three main hydroclimatic variables through power functions. We obtained the hydroclimatic variables from daily gridded datasets of precipitation and temperature, implementing a degree-day model to simulate spatially distributed snow accumulation and snow-ice melt. We calibrated the PBRC parameters by an Iterative Input Selection algorithm to capture the characteristic response time lags, and by a gradient-based nonlinear optimization method to minimize the errors between SSC observations and simulations. We apply our approach in the upper Rhône Basin, a large Alpine catchment in Switzerland. Results show that all three hydroclimatic processes ER, SM, and IM are significant predictors of mean daily SSC (explaining 75 %, 12 % and 3 % of the total observed variance). Despite not using discharge in prediction, the PBRC performs better than the traditional rating curve, especially during validation at the daily scale and in reproducing SSC seasonality. The characteristic time lags of the three variables in contributing to SSC reflect the typical flow concentration times of the corresponding hydrological processes in the basin. Erosive rainfall determines the daily variability of SSC, icemelt generates the highest SSC per unit of runoff, and snowmelt-driven fluxes represent the largest contribution to total suspended sediment yield. Finally, we show that the PBRC is able to simulate changes in SSC in the past 40 years in the Rhône Basin connected to air temperature rise, even though these changes are more gradual than those detected in observations. We argue that a sediment source perspective on suspended sediment transport such as the PBRC may be more suitable than traditional discharge-based rating curves to explore climate-driven changes in fine sediment dynamics in Alpine catchments. The PBRC approach can be applied to any Alpine catchment with a pluvio-glacio-nival hydrological regime and adequate hydroclimatic datasets.

Anna Costa et al.

 
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Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Anna Costa et al.

Anna Costa et al.

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Latest update: 27 Feb 2021
Short summary
We develop a novel rating curve to simulate suspended sediment concentration (SSC) in Alpine catchments (Process-Based Rating Curve, PBRC). Instead of relating SSC to discharge, as in traditional approaches, we model SSC by differentiating the potential contributions of the main erosional and transport processes of Alpine environments: erosive rainfall, snowmelt, and icemelt. We show that PBRC significantly improves predictions of SSC, especially when analysing climate-induced changes.