Presentation
This project, funded by the Swiss National Science Foundation, is a combined experimental and modelling study to provide better understanding of the physical mechanisms of sediment transport and soil erosion at the laboratory scale.
The particular objectives of the study are:
- Carry out experiments on the effect of rock fragments on soil erosion and to devise an appropriate form of the Hairsine-Rose (HR) erosion model that takes into account the effect on erosion predictions of rocks on the surface of the soil.
- Use the model to simulate 2D flow data around the stones and thereby validate the hydraulic conditions on the 2D erosion soil model.
- To carry out experiments and to devise upscaling methods to extend the Hairsine-Rose model to larger scales.
To achieve these, flume experiments wil be performed at EPFL with an artificial rainfall-runoff model.
Experimental Investigations
 |
 |
|
Schematic overview of EPFL’s erosion flume by Meerveld et al. (2008) |
Photo of the EPFL erosion flume in situ |
Digital Terrain Model (DTM)
A digital terrain model (DTM) also known as digital elevation model (DEM) is a digital representation of ground surface topography or terrain, which can be represented as a raster (a grid of squares) or as a triangular irregular network. DTMs are commonly built using remote sensing techniques, but they may also be built from land surveying. In this particular case, it is used to express the flumes before and after the experiment of flow modelling.
Modelling
Soil erosion as a result of rainfall and overland flow is a serious environmental problem involving different complex processes that drive observed sediment transport. Soil loss and its associated impacts affect agricultural productivity, the natural environment and infrastructure security. Despite the complexities involved, process-based erosion modeling has proven to be an efficient tool for the description and prediction of soil erosion and sediment transport.
Process-based erosion models are used to forecast sediment transport concentration as it varies temporally and spatially. Of the erosion models available, the one-dimensional Hairsine-Rose (H-R) (Hairsine and Rose, 1991; 1992a,b) erosion model describes time-varying suspended sediment concentrations of multiple particle sizes, and accounts for key soil erosion mechanisms: rainfall detachment, overland-flow entrainment and gravity deposition. The H-R model, in contrast to other process-based erosion models, considers erosion and deposition processes separately by taking account of the contributions of the individual size classes to the total sediment concentration. This is a crucial feature of the model, since it is well known that sediment erosion and transport is size class-dependent. The H-R model has been evaluated under different experimental conditions, and has been shown to explain reliably experimental data in a consistent manner. It is thus appropriate to extend the applicability of the 1D H-R model to more realistic conditions and at different circumstances.
Measured and fitted of rainfall-driven erosion at high rainfall intensity (60 mm/h) and with a gentle slope (2.2%). The above graphs show total sediment and sediment concentrations for individual size classes (g/l) as a function of time (min).
Soil erosion as a result of rainfall and overland flow is a serious environmental problem involving different complex processes that drive observed sediment transport. Soil loss and its associated impacts affect agricultural productivity, the natural environment and infrastructure security. Despite the complexities involved, process-based erosion modeling has proven to be an efficient tool for the description and prediction of soil erosion and sediment transport.
Process-based erosion models are used to forecast sediment transport concentration as it varies temporally and spatially. Of the erosion models available, the one-dimensional Hairsine-Rose (H-R) (Hairsine and Rose, 1991; 1992a,b) erosion model describes time-varying suspended sediment concentrations of multiple particle sizes, and accounts for key soil erosion mechanisms: rainfall detachment, overland-flow entrainment and gravity deposition. The H-R model, in contrast to other process-based erosion models, considers erosion and deposition processes separately by taking account of the contributions of the individual size classes to the total sediment concentration. This is a crucial feature of the model, since it is well known that sediment erosion and transport is size class-dependent. The H-R model has been evaluated under different experimental conditions, and has been shown to explain reliably experimental data in a consistent manner. It is thus appropriate to extend the applicability of the 1D H-R model to more realistic conditions and at different circumstances.
Measured and fitted of rainfall-driven erosion at high rainfall intensity (60 mm/h) and with a gentle slope (2.2%). The above graphs show total sediment and sediment concentrations for individual size classes (g/l) as a function of time (min).
Publications
Jomaa, Seifeddine ; Barry, David Andrew ; Sander, G. C. ; Heng, B. C. P.
Presented at: Union EGU spring meeting, Vienna, AT, April 24-29, 2009.
Soil erosion affects agricultural productivity, the natural environment and infrastructure security. Soil loss and its associated impacts are important environmental problems. Consequently, model-based predictions of erosion are beneficial for a variety of applications. Process-based erosion models are used to forecast sediment transport concentration as it varies temporally and spatially. Of these, the one-dimensional Hairsine-Rose model describes multiple particle size classes, rainfall detachment, flow-driven entrainment and deposition. This model has been evaluated for different experiments, and has been shown to reliably explain experimental data in a consistent manner. It is common on both the hillslope and laboratory scales to apply one-dimensional erosion models even though the overland flow and sediment transport is two-dimensional. One-dimensional parameter determinations, which are based typically on outflow data, implicitly average the two-dimensional flow.
Here we compare experimentally and numerically this averaging process for the Hairsine-Rose model. For this purpose, laboratory experiments were performed using different configurations of the 2 m × 6 m EPFL erosion flume. The flume was divided into 4 smaller flumes, with widths of 1 m, 0.5 m, and 2 × 0.25 m, but otherwise identical. A series of experiments was to provide data sets for analysis by the Hairsine-Rose model. After running the experiments, the amount of the eroded sediment in each subplot was assessed by comparing the temporal variation of eroded mass to evaluate the effect of, and sensitivity to, transverse width on erosion dynamics. The surface elevation changes due to erosion were examined to provide further understanding of the erosion data. A high resolution laser scanner provided details of the soil surface in the form of digital terrain maps before and after the experiment.
This method presents a promising way for identification of spatial distribution pattern of eroded soil. In addition, we ran simulations using a fully two dimensional implementation of the Hairsine-Rose model for erosive flows with varying topography with spatially dependent flow and erosion input parameters to produce both outflow hydrographs and suspended sediment graphs. The data were integrated transversely and, as for the experimental data, the one-dimensional Hairsine-Rose model was used to fit the integrated data and so provide parameter estimates to compare with the two-dimensional input values.
Reference: ECOL-POSTER-2009-014
References
[1] P. B. Hairsine, and C. W. Rose (1991), Rainfall detachment and deposition: sediment transport in the absence of flow-driven processes, Soil Science Society of America Journal 55(2):320-324.
[2] P. B. Hairsine, and C. W. Rose (1992), Modeling water erosion due to overland flow using physical principles, 1, Sheet flow, Water Resources Research 28(1):237-243.
[3] P. B. Hairsine and C. W. Rose (1992), Modeling water erosion due to overland flow using physical principles, 2, Rill flow, Water Resources Research 28(1):245-250.
[4] H. J. Tromp-van Meerveld, J.-Y. Parlange, D. A. Barry, M. F. Tromp, G. C. Sander, M. T. Walter, and M. B. Parlange (2008), Influence of sediment settling velocity on mechanistic soil erosion modeling, Water Resources Research 44, W06,401+, doi: 10.1029/2007WR006361.