Modeling anthropogenic affected sediment transport in a mid-sized European river catchment–extension of the sediment rating curve equation

Abstract

Land use and water resource management influence the suspended sediment concentration (SSC) in rivers. Fine sediments are an important driver for river development, even in coarse-material-rich rivers. In this study, the sediment rating curve approach is modified to predict SSC several river-km downstream of a sampling site. Further, the prediction is improved by adding sediment input, storage, and dilution effects through relevant anthropogenic measures through a model identification approach. Thus, the impact of the most severe anthropogenic measures, damming and changes in the length of a channel section for the Rur River, could be identified. Further, the impact of describing parameter changes for those measures on the SSC can be computed and considered in future water resource management. In this approach, particle swarm optimization was used to fit parameters in permutable test- and training data sets to identify linear extensions to the sediment rating curve. The input data consists of (1) SSC, which was obtained by sampling along the river section four times a year over approximately two years, (2) discharge data from river gauges supplemented by rainfall-runoff modeling between stations, (3) rainfall data from meteorological stations, and (4) sub-catchment characteristics like river section length and erosivity obtained with GIS. Via incorporating the river section length and sediment deposition in response to damming, we reduced the RMSE (root mean squared error) from 152.27 to 131.83% with a p-value of 0.073 in the Wilcoxon Signed Rank Test. Further integration of sub-catchment parameters like erosivity led to overfitting and decreased prediction accuracy. A catchment-wide prediction was achieved, but sub-catchments operate on different spatial scales with different connectivity behavior, which restricts the transferability of the equation. SSC-Q hystereses provide the first indications of characteristic sediment sources and were used to discuss connectivity behavior within the study area. They are recommended as part of a (sub-) catchment characterization for further studies.