Abstract
Climate change can escalate rainfall intensity and cause further increase in sediment transport in arid lands which in turn can adversely affect water quality. Hence, there is a strong need to predict the fate of sediments in order to provide measures for sound erosion control and water quality management. The presence of microtopography on hillslopes influences processes of runoff generation and erosion, which should be taken into account to achieve more accurate modelling results. This study presents a physically based mathematical model for erosion and sediment transport coupled to one-dimensional overland flow equations that simulate rainfall-runoff generation on the rill and interrill areas of a bare hillslope. Modelling effort at such a fine resolution considering the flow connection between interrill areas and rills is rarely verified. The developed model was applied on a set of data gathered from an experimental setup where a 650 cm×136 cm erosion flume was pre-formed with a longitudinal rill and interrill having a plane geometry and was equipped with a rainfall simulator that reproduces natural rainfall characteristics. The flume can be given both longitudinal and lateral slope directions. For calibration and validation, the model was applied on the experimental results obtained from the setup of the flume having 5% lateral and 10% longitudinal slope directions under rainfall intensities of 105 and 45 mm/h, respectively. Calibration showed that the model was able to produce good results based on the R 2 (0.84) and NSE (0.80) values. The model performance was further tested through validation which also produced good statistics (R 2=0.83, NSE=0.72). Results in terms of the sedigraphs, cumulative mass curves and performance statistics suggest that the model can be a useful and an important step towards verifying and improving mathematical models of erosion and sediment transport.
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Arguelles, A.C.C., Jung, M., Mallari, K.J.B. et al. Evaluation of an erosion-sediment transport model for a hillslope using laboratory flume data. J. Arid Land 6, 647–655 (2014). https://doi.org/10.1007/s40333-014-0066-9
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DOI: https://doi.org/10.1007/s40333-014-0066-9