Till Francke, Sandra Werb, Erik Sommerer, José Andrés Lopez-Tarazon

• The Isabena catchment (445 km(2)), Spain, features highly diverse spatial heterogeneity in land use, lithology and rainfall. Consequently, the relative contribution in terms of water and sediment yield varies immensely between its subcatchments, and also temporally. This study presents the synthesis of similar to 2.5 years of monitoring rainfall, discharge and suspended sediment concentration (SSC) in the five main subcatchments of the Isabena and its outlet. Continuous discharge at the subcatchment outlets, nine tipping bucket rainfall and automatic SSC samplers (complemented by manual samples), were collected from June 2011 until November 2013. The water stage records were converted to discharge using a rating curve derived with Bayesian regression. For reconstructing sediment yields, the data from the intermittent SSC sampling needed to be interpolated. We employed non-parametric multivariate regression (Quantile Regression Forests, QRF) using the discharge and rainfall data plus different aggregation levels of these as ancillaryThe Isabena catchment (445 km(2)), Spain, features highly diverse spatial heterogeneity in land use, lithology and rainfall. Consequently, the relative contribution in terms of water and sediment yield varies immensely between its subcatchments, and also temporally. This study presents the synthesis of similar to 2.5 years of monitoring rainfall, discharge and suspended sediment concentration (SSC) in the five main subcatchments of the Isabena and its outlet. Continuous discharge at the subcatchment outlets, nine tipping bucket rainfall and automatic SSC samplers (complemented by manual samples), were collected from June 2011 until November 2013. The water stage records were converted to discharge using a rating curve derived with Bayesian regression. For reconstructing sediment yields, the data from the intermittent SSC sampling needed to be interpolated. We employed non-parametric multivariate regression (Quantile Regression Forests, QRF) using the discharge and rainfall data plus different aggregation levels of these as ancillary predictors. The subsequent Monte Carlo simulations allowed the determination of monthly sediment yields and their uncertainty. The Isabena catchment shows high erosion dynamics with great variability in space and time, with stark contrasts even between adjacent subcatchments. The natural conditions make water and sediment monitoring and instrumentation very challenging; the measurement of discharge is particularly prone to considerable uncertainties. The QRF method employed for reconstructing sedigraphs and monthly yields proved well suited for the task.…