Data set accompanying the manuscript "Projecting sediment export from two highly glacierized alpine catchments under climate change: Exploring non-parametric regression as an analysis tool", Schmidt, L.K., Francke, T., Grosse, P.M. and Bronstert, A.

The data set contains 1. the code of the quantile regression forest (QRF) model applied in the above mentioned manuscript to project suspended sediment concentrations and yields in the period 2007 - 2100 at the two nested gauges Vernagt (VF) and Vent (V) in the Upper Ötztal, Austria,

1. the preprocessed input data:
2. measurement data: discharge, precipitation, air temperature and suspended sediment concentrations derived from turbidity measurements

3. projections: EURO-CORDEX-derived precipitation and air temperature projections (downscaled and bias-corrected by Hanzer et al., 2018) as well as discharge projections as a result of the physically-based hydroclimatological and snow model AMUNDSEN (Hanzer et al., 2018) for both gauges, and

4. the QRF model results for each RCP-GCM-RCM combination.

5. The QRF model code is a modified version of the model published under DOI 10.23728/b2share.78cdc99c8d454d8894c086a01f561627, which is based on this code: https://github.com/TillF/ssc_prediction (Jan 18th 2022). Modifications:

6. perform seasonal quantile mapping of the AMUNDSEN discharge projections

7. loop to compute ancillary predictors and apply QRF models trained for the two gauges in a previous publication (Schmidt et al., 2023) to each RCP-GCM-RCM combination.

8. The measurement are unmodified (as published under DOI 10.23728/b2share.78cdc99c8d454d8894c086a01f561627).

9. The model results can be found in the folder GAUGE_NAME/scenario_calc/RCP_GCM_RCM_combination/5_model_application/MC_01

10. in daily resolution as one table per year (e.g. flood_periods_quantForest_GAUGE_NAME_hist1.txt)
11. aggregated to annual suspended sediment yields (flood_periods_quantForest_GAUGE_NAME.txt)