Demo on stream network modification

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Stream network modification
Stream network modification

A couple of months ago I posted a text on stream network modification which listed some of the ways to modify stream networks in TopoToolbox. These modifications include trimming, extractions, trunk river derivation, etc. Still, many of these functionalities remain somewhat shrouded given that they are all listed in the help section of the function STREAMobj/modify.m where they can be accessed using parameter name-value pairs. To assist users in understanding and finding these tools I have recently added a demo to TopoToolbox that includes some code and a visual output of the different modifications. Hope that this helps you finding the right tools for your analysis.

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Roads at risk: traffic detours from debris flows in southern Norway

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Estimated annual link risk expressed as vehicle km; main routes between seven large cities in southern Norway are marked in yellow (Meyer et al. 2015).
Estimated annual link risk expressed as vehicle km; main routes between seven large cities in southern Norway are marked in yellow (Meyer et al. 2015).

Our paper on debris-flow impacts on traffic in southern Norway is now published in Natural Hazards and Earth System Science. The manuscript was discussed in NHESSD and was only slightly modified compared to the discussion paper. In brief, Nele K. Meyer, I, Oliver Korup and Farrokh Nadim show that the functional vulnerability of Norway’s road network spatially centers in the mountainous interior of southern Norway, a region that needs to be traversed in order to connect the major cities. Debris flow hazard along some of these roads is high, thus generating high risk in terms of excess kilometers to be covered by car drivers if debris flows block road sections. Detour routes that circumnavigate single road blockages are especially long for local traffic, whereas long-distance travel remains largely unaffected given timely information on road blockages and alternative routes. Large-scale, high-intensity rainfall events, however, triggered numerous spatially clustered debris flows in the past, and we show that such event can indeed significantly affect long-distance travel.

Meyer, N.K., Schwanghart, W., Korup, O., Nadim, F. (2015): Roads at risk – traffic detours from debris flows in southern Norway. Nat. Hazards Earth Syst. Sci., 15, 985-995. [DOI: 10.5194/nhess-15-985-2015, Discussion paper DOI: 10.5194/nhessd-2-6623-2014]

Large landslides lie low: Excess topography in the Himalaya-Karakoram ranges

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In a just published article in Geology by Jan Blöthe, Oliver Korup and me, we show that the Himalaya-Karakoram Range exhibits an intriguing vertical stacking of erosional domains driven by mass-wasting and (peri-)glacial activity. We show that large bedrock failures preferably detach below the limit of sporadic alpine permafrost adjusting hillslope inclinations to rapid fluvial incision and postglacial stress fields in oversteepened valley flanks. Intense frost cracking above the permafrost limit in turn may result in high-frequency/low-magnitude rockfalls and avalanches, thus limiting the occurrence of low-frequency/high-magnitude rock-slope failures.

As part of the analysis, we introduced ‘excess topography’ as a new measure to characterize mountain topography. Here is an excerpt taken from the supplementary material that describes excess topography and how it is calculated from a DEM:

Excess topography measures for each grid cell in a digital elevation model (DEM) the rock-column height above an arbitrarily defined threshold slope surface. The threshold slope surface is an idealized surface that we derive from a given DEM. The threshold surface only contains inclinations that are lower or equal than the arbitrarily set threshold inclination. The elevations of the threshold surface are constrained by the DEM elevations and the threshold inclination such that (1) the elevation of the threshold and DEM input surface coincide for a given grid cell if the slopes between this grid cell and all others are less or equal the threshold slope; and (2) elevations of the threshold surface fall below the DEM input surface in grid cells rising above the surrounding topography at angles steeper than the threshold inclination. In case (2), we calculate the threshold surface elevation as the minimum elevation of all surrounding locations plus the maximum allowed topographic rise (threshold inclination) along the distance separating the locations.

A picture is worth a thousand words. Here you go:

Excess topography
Also check the animation below to see how the minimum filter with additional offsets works in 2D.
excesstopography

Excess topography can be calculated using the new function excesstopography in TopoToolbox. The function is quite simple. The most important algorithm that it requires – image morphology with a grayscale structuring element – is made available by the function ordfilt2 in the Image Processing Toolbox. Did you know this function? This function is extremely powerful and I can think of quite a lot of nice applications of DEM analysis. Since I said that graydist is my favorite function, ordfilt2 is my second favorite function.

Reference

Blöthe, J.H., Korup, O., Schwanghart, W. (2015): Large landslides lie low: Excess topography in the Himalaya-Karakorum ranges. Geology, 43, 523-526. [DOI:

** edited on May 23, 2015 to update reference **

** edited on June 23, 2015 to include free pdf download **

Visualization fun

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Ok, this doesn’t have a direct value for whatsoever, but it is just an example of how to have fun with the visualization tools in MATLAB. Note that you’ll need to download the function plot3d from github to run this example.

DEM = GRIDobj('srtm_bigtujunga30m_utm11.tif');
FD  = FLOWobj(DEM,'preprocess','carve');
S   = STREAMobj(FD,'minarea',1000);
S   = klargestconncomps(S);
RGB = imageschs(DEM,DEM,'colormap','landcolor');
[x,y] = getcoordinates(DEM);

surface('XData',x,'YData',y,...
        'ZData',repmat(min(DEM),numel(y),numel(x)),...
		'CData',double(RGB)/255,...
        'FaceColor','texturemap','EdgeColor','none');
hold on
plot3d(S,DEM)
axis image
exaggerate(gca,2)
axis off
hold off

plot3d

GM11.3/SC48 Quantitative interrogation of high-resolution DTMs

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Mon, 13 Apr, 13:30–15:00 / Room G2

Analysing bedrock river profiles using chi-plots

Digital elevation models (DEMs) are the foundation of many studies in geomorphology. Methods to quantitatively interrogate these data are thus one of the keys to understanding the processes that shape the Earth and their driving forces. River profiles in particular have attracted the attention of geomorphologists as their shape reflects the tectonic and climatic past. Extracting and analysing river profiles from DEMs, however, is challenged by noisy topographic data often affected by artifacts.

In this workshop, we will explore various techniques to extract and analyse river profiles from DEMs to account for the problems associated with DEMs in high mountain landscapes. We will use TopoToolbox, a software written in MATLAB language for the analysis of DEMs (Schwanghart and Scherler, 2014) and go through the entire work flow including preprocessing a DEM and deriving and modifying river networks. Finally, we aim at calculating Chi-plots, a new technique to analyse bedrock river profiles and alternative to slope-area plots which is less sensitive to noisy topographic data (Perron and Royden, 2012).

Participants are invited to bring their own laptops to work hands-on on the data and code. TopoToolbox requires MATLAB with a version newer than R2011b including the Image Processing Toolbox. Basic knowledge in MATLAB is an advantage but not a requirement.

Software

Download the latest working-copy of TopoToolbox here.

Data

Download data for Exercise 1 and 2 here.

Download output of a Landscape Evolution Model (transient signal as a result of baselevel lowering) here.

Presentation

A pdf of the presentation can be downloaded here.

References

Harkins N, Kirby E, Heimsath A, Robinson R, Reiser U. 2007. Transient fluvial incision in the headwater of the Yellow River, northeastern Tibet, China. Journal of Geophysical Research 112 : F03S04–F03S04. [DOI: 10.1029/2006JF000570]

Perron JT, Royden L. 2013. An integral approach to bedrock river profile analysis. Earth Surface Processes and Landforms 38 : 570–576. [DOI: 10.1002/esp.3302]

Royden L, Perron JT. 2013. Solutions of the stream power equation and application to the evolution of river longitudinal profiles. Journal of Geophysical Research 118 : 1–22.

Schwanghart, W., Scherler, D. (2014): TopoToolbox 2 – MATLAB-based software for topographic analysis and modeling in Earth surface sciences. Earth Surface Dynamics, 2, 1-7. [DOI: 10.5194/esurf-2-1-2014]

Willett SD, McCoy SW, Perron JT, Goren L, Chen C-Y. 2014. Dynamic Reorganization of River Basins. Science 343 : 1248765. [DOI: 10.1126/science.1248765]

Please leave a comment or send me an email if you want to provide feedback on this short course.

New code repository on GitHub

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The CSDMS decided to move its code repository to GitHub. I think that this is a good decision. GitHub is more user-friendly and allows for easier collaboration than the previous system. I had my own account at GitHub before. Thus I forked the CSDMS TopoToolbox repository to my account. Dirk Scherler and I will work on this repository in the future, but we will merge major updates back to CSDMS repository.

Does this matter to you? Yes. If you want to download the latest release, go to /topotoolbox. If you want to download the latest working-copy, go here: /topotoolbox.

Graph theory in the Geosciences

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In a recent paper, Tobias Heckmann, I and Jonathan Phillips reviewed applications of graph theory in geomorphology. In a now published paper in Earth-Science Reviews, we take an even broader view by looking at graph theoretical applications in the geosciences in general. Specifically, we reviewed three areas of application: spatially explicit modelling, small-world networks, and structural models of Earth surface systems. We identify several factors that make graph theory especially well suited to the geosciences: inherent complexity of Earth surface systems, the increasing demand for exploration of very large data sets, focus on spatial fluxes and interactions, and the increasing attention to system state transitions.

Phillips, J.D., Schwanghart, W., Heckmann, T. (2014): Graph theory in the geosciences. Earth Science Reviews, 143, 147–160. [DOI: 10.1016/j.earscirev.2015.02.002]