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How can stream bank erosion be predicted on small water courses?Veri?cation of BANCS model on the Kubrica watershed

International Journal of Sediment Research 2021年第3期36卷 419-429页

作者： Zuzana Allmanová Máaria Vl?kováa Martin Jankovsky Michal Allman Jáan Mergani? Department of Forest Harvesting Logistics and Ameliorations Faculty of Forestry Technical University in Zvolen Department of Forestry Technology and Constructions Faculty of Forestry and Wood Sciences Czech University of Life Sciences Prague

The current paper deals with the evaluation of the BANCS erosion prediction model and its two componentsethe bank erosion hazard index（BEHI） and Near-bank Stress（NBS） indices. To construct the erosion prediction curves, 18 experimental sections were established on the Kubrica Stream, district of Trencín, Slovakia. Each section was assessed through the NBS index and BEHI index and real annual bank erosion was measured using erosion toe pins. Subsequently, the relations between the BEHI and real annual bank erosion was assessed through regression and correlation analyses. The relation proved to be moderately strong, with the correlation coefficient（R） reaching 0.47. Further, the relation between the NBS index and real annual bank erosion was evaluated, which was also moderately strong, with R= *** on the measured data, two erosion prediction curves were constructed, the first for moderate BEHI, with R= 0.69 and coefficient of determination（R2） of 0.47 and the second for high BEHI with R=0.74 and R2= 0.55. The prediction curves were based on data from one year of measurements and can, therefore, be used only for discharges that occurred within that year and in the region where the model was developed. In the current case, according to runoff Curve Numbers（CN）, the real culmination discharge was Q ? 1.88 m3/s, which is roughly equivalent to 1.5-year recurrence interval flow（Q1.5）.

关键词： bank erosion bank assessment for non-point source consequences of sediment (BANCS) bank erosion hazard index Near-bank stress index erosion prediction curves

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