Periodic Reporting for period 1 - kelbus2 (Experimental and numerical study of long runout landslides)
Reporting period: 2020-01-15 to 2022-01-14
A main objective in landslide research is to predict how far they will travel, as every year they claim thousands of lives and leave behind lasting ecological hazards. Landslides are complex, and a complete understanding of landslides in principle requires accounting for all of these parameters. A systematic study of each one is difficult if not impossible for natural landslides, and the vast variety of parameters has even led to landslides and avalanches with very different material and parameter values to be treated as distinct systems, even if the basic geometry and physics appears to be similar.
The result of both the experimental and parallel numerical study was that a relevant parameter absent in prevalent theories of landslide runout was the landslide grain size. We made a radical improvement on our ability to predict landslide runout by using systematic laboratory experiments of granular flow with a simplified landslide geometry combined with a scaling analysis. We found that additionally accounting for the granular nature of the flow through the constituent grain size, and correctly accounting for the fall height, reveals a striking correlation of normalized runout with landslide size which when combined with field data extends to nearly ten orders of magnitude in size. We thus united seemingly disparate fields such as small-scale laboratory granular experiments, landslides, and snow avalanches, and dramatically enhanced runout prediction for dense flows. Our work thus alleviates the need for special theories and removes some of the mystery clouding the discussion of these fascinating, if extremely dangerous, phenomena.
In addition, we also determined the minimum landslide size required to observe this scaling, which we find is set by a combination of air drag, grain size, and fall height. The scaling of this minimum size was determined with the assumption that for small total volumes, landslides behave as a granular gas, while at large volumes they behave as a dense granular liquid. This result will help to guide the design of any future laboratory experiments aimed at understanding natural landslide behavior.
The result of both the experimental and parallel numerical study was that a relevant parameter absent in prevalent theories of landslide runout was the landslide grain size. We made a radical improvement on our ability to predict landslide runout by using systematic laboratory experiments of granular flow with a simplified landslide geometry combined with a scaling analysis. We found that additionally accounting for the granular nature of the flow through the constituent grain size, and correctly accounting for the fall height, reveals a striking correlation of normalized runout with landslide size which when combined with field data extends to nearly ten orders of magnitude in size. We thus united seemingly disparate fields such as small-scale laboratory granular experiments, landslides, and snow avalanches, and dramatically enhanced runout prediction for dense flows. Our work thus alleviates the need for special theories and removes some of the mystery clouding the discussion of these fascinating, if extremely dangerous, phenomena.
In addition, we also determined the minimum landslide size required to observe this scaling, which we find is set by a combination of air drag, grain size, and fall height. The scaling of this minimum size was determined with the assumption that for small total volumes, landslides behave as a granular gas, while at large volumes they behave as a dense granular liquid. This result will help to guide the design of any future laboratory experiments aimed at understanding natural landslide behavior.
We developed a simplified laboratory landslide setup using a flat inclined plane, a housing box for grains from which they can be released, and a flat section where they eventually come to rest. Using optical techniques developed in our laboratory, we were also able to measure in real time quantities such as the landslide thickness and speed, which are especially relevant for theories of granular rheology. We also began to develop a method for measuring the pressure underneath the landslide, a key feature of the theory for long landslide runout we were originally motivated to test. We accompanied our experiments with large-scale numerical simulations of granular landslides using the open-source DEM code LIGGGHTS.
We started by doing studies of landslide runout for a single fall height and grain size as well but changing systematically the landslide total volume. For a single grain size and fall height we observed the classical result that the runout distance increases with landslide volume. When we either changed the fall height or changed the grain size we found the same classical behavior, but when plotted in the traditional way (fall height divided by runout distance versus volume) we ended up with many distinct curves. This lack of agreement between the data caused by different fall height and diameter meant that the traditional plot, which is an attempt to account for the influence of the fall height and the volume on the runout distance, does not work. We thus performed a standard scaling analysis often used in the fields of applied mathematics, fluid mechanics, and physics, and revealed the true dependence of the runout distance on fall height, landslide size (which became the number of grains), and the average landslide grain size. Plotting in our new way, the normalized landslide runout distance for a wide range of parameter values collapse onto a common, universal curve.
In fact, we observed that for small landslide volumes the scaling analysis breaks down, which is not uncommon. A given scaling does not always work for all ranges of a parameter. We were able to determine when this breaks down as a function of landslide size, fall height, grain diameter, and the viscosity of the surrounding air, by assuming that the breakdown is caused by a transition from a granular gas to granular liquid behavior. This observation of a granular phase transition is novel in its own right, but the scaling result that we found is also of practical value in designing laboratory experiments to study natural landslides. The scaling of the landslide runout as well as its breakdown are in a publication under review.
Finally, using the new scaling that we found as a foundation, we began to add new parameters into our experiments that are also of relevance to natural landslides. Our original experiments were performed on a flat, smooth substrate, but natural landslides have a variety of complicated terrain. To account for this systematically we performed a large number of experiments for which we varied the roughness of the substrate. We did this by attaching standard sandpaper, which we characterized using a microscope, as well as our own laboratory-made rough substrates. Again using the same standard scaling analysis revealed a new dependence on the ratio of grain size to roughness. This result is not only of interest to landslide runout prediction, but it also continuously bridges the gap between two standard laboratory approaches: the smooth and rough substrates. This work is being written up into a manuscript for publication.
We started by doing studies of landslide runout for a single fall height and grain size as well but changing systematically the landslide total volume. For a single grain size and fall height we observed the classical result that the runout distance increases with landslide volume. When we either changed the fall height or changed the grain size we found the same classical behavior, but when plotted in the traditional way (fall height divided by runout distance versus volume) we ended up with many distinct curves. This lack of agreement between the data caused by different fall height and diameter meant that the traditional plot, which is an attempt to account for the influence of the fall height and the volume on the runout distance, does not work. We thus performed a standard scaling analysis often used in the fields of applied mathematics, fluid mechanics, and physics, and revealed the true dependence of the runout distance on fall height, landslide size (which became the number of grains), and the average landslide grain size. Plotting in our new way, the normalized landslide runout distance for a wide range of parameter values collapse onto a common, universal curve.
In fact, we observed that for small landslide volumes the scaling analysis breaks down, which is not uncommon. A given scaling does not always work for all ranges of a parameter. We were able to determine when this breaks down as a function of landslide size, fall height, grain diameter, and the viscosity of the surrounding air, by assuming that the breakdown is caused by a transition from a granular gas to granular liquid behavior. This observation of a granular phase transition is novel in its own right, but the scaling result that we found is also of practical value in designing laboratory experiments to study natural landslides. The scaling of the landslide runout as well as its breakdown are in a publication under review.
Finally, using the new scaling that we found as a foundation, we began to add new parameters into our experiments that are also of relevance to natural landslides. Our original experiments were performed on a flat, smooth substrate, but natural landslides have a variety of complicated terrain. To account for this systematically we performed a large number of experiments for which we varied the roughness of the substrate. We did this by attaching standard sandpaper, which we characterized using a microscope, as well as our own laboratory-made rough substrates. Again using the same standard scaling analysis revealed a new dependence on the ratio of grain size to roughness. This result is not only of interest to landslide runout prediction, but it also continuously bridges the gap between two standard laboratory approaches: the smooth and rough substrates. This work is being written up into a manuscript for publication.
As described in the previous sections, and at the risk over-simplifying, the state of the art in landslide research was that landslide runout increases with landslide volume and fall height and at very large volumes a new mechanism arises to make landslides go even further. Our main result was to find quantitatively how landslide runout depends on landslide size, fall height, and additionally grain size diameter. Because the scaling we found works for both very small and very large landslides, which presumably had a special mechanism at work to increase their runout distance, a corollary of our main finding is that no special mechanism is required to explain the runout of large landslides. Nevertheless we can not rule out any such mechanism based on our observations. This result will hopefully complement and improve standard approaches to estimating landslide hazard. These typically involve historical data of landslide size for a given mountain, which thus determines the maximum fall height. The correlation with just these two parameters is poor. If the material that will eventually becomes the landslides is also investigated to determine the grain size distribution, the prediction for the runout distance can be substantially improved, thus providing better information for hazard prevention.