distanceTimeAnalysis: Visualizing the temporal evolution of flow variables

With the functions gathered in this module, flow variables of avalanche simulation results can be visualized in a distance versus time diagram, the so called thalweg-time diagram. The tt-diagram provides a way to identify main features of the temporal evolution of flow variables along the avalanche path. This is based on the ideas presented in [FFGS13] and [RKohler20], where avalanche simulation results have been transformed into the radar coordinate system to facilitate direct comparison, combined with the attempt to analyze simulation results in an avalanche path dependent coordinate system ([Fis13]). In addition to the tt-diagram, ana5Utils.distanceTimeAnalysis also offers the possibility to produce simulated range-time diagrams of the flow variables with respect to a radar field of view. With this, simulation results can be directly compared to radar measurements (for example moving-target-identification (MTI) images from [KohlerMS18]) in terms of front position and inferred approach velocity. The colorcoding of the simulated range-time diagrams show the average values of the chosen flow parameter (e.g. flow thickness (FT), flow velocity (FV)) at specified range gates. This colorcoding is not directly comparable to the MTI intensity given in the range-time diagram from radar measurements.


The data processing for the tt-diagram and the range-time diagram can be done during run time of com1DFA, or as a postprocessing step. However, the second option requires first saving and then reading all the required time steps of the flow variable fields, which is much more computationally expensive compared to the first option.

To run

During run-time of com1DFA:

  • in your local copy of com1DFA/com1DFACfg.ini in [VISUALISATION] set createRangeTimeDiagram to True and choose if you want a TTdiagram by setting this flag to True or in the case of a simulated range-time diagram to False

  • in your local copy of ana5Utils/distanceTimeAnalysisCfg.ini you can adjust the default settings for the generation of the diagrams

  • run to calculate mtiInfo dictionary (saved as pickle in avalancheDir/Outputs/com1DFA/distanceTimeAnalysis/mtiInfo_simHash.p) that contains the required data for producing the tt-diagram or range-time diagram

  • run or and set the preProcessedData flag to True

As a postprocessing step:

  • first you need to run com1DFA to produce fields of the desired flow variable (e.g. FT, FV) of sufficient temporal resolution (every second), for this in your local copy of com1DFACfg.ini add e.g. FT to the resType and change the tSteps to 0:1

  • have a look at and

  • in your local copy of ana5Utils/distanceTimeAnalysisCfg.ini you can adjust the default settings for the generation of the diagrams

The resulting figures are saved to avalancheDirectory/Outputs/ana5Utils.


Fig. 25 Thalweg-time diagram example: The y-axis contains the distance from the beta point along the avalanche path (projected on the horizontal plane), e.g. the thalweg. Dots represent the avalanche front with the slope being the approach velocity. Red star marks the maximal approach velocity (this approach velocity is also projected on the horizontal plane).


The tt-diagram requires info on an avalanche path (see ana3AIMEC: Aimec). The simulated range-time diagram requires info on the coordinates of the radar location (x0, y0), a point in the direction of the field of view (x1, y1), the aperture angle and the width of the range gates. The maximum approach velocity is indicated in the distance-time diagrams with a red star and is computed as the ratio of the distance traveled by the front and the respective time needed for a time step difference of at least minVelTimeStep which is set to 2 seconds as default. The approach velocity is a projection on the horizontal plane since the distance traveled by the front is also measured in this same plane.


Thalweg-time diagram

First, the flow variable result field is transformed into a path-following coordinate system, of which the centerline is the avalanche path. For this step, functions from ana3AIMEC are used. The distance of the avalanche front to the start of runout area point is determined using a user defined threshold of the flow variable. The front positions defined with this method for all the time steps are shown as black dots in the tt-diagram. The mean values of the flow variable are computed at cross profiles along the avalanche path for each time step and included in the tt-diagram as colored field. When computing the mean values, all the area where the flow variable is bigger than zero is taken into account. For this analysis, all available flow variables can be chosen, but the interpretation of the tt-diagram structures and the corresponding meaning of avalanche front may be different for flow thickness or flow velocity.

Simulated Range-Time diagram

The radar’s field of view is determined using its location, a point in the direction of the field of view and the horizontal (azimuth) aperture angle of the antenna. The elevation or vertical aperture angle is not yet included. The line-of-sight distance of every grid point in the simulation results to the radar location is computed. The simulation results which lie outside the radar’s field of view are masked. The distance of the avalanche front with respect to the radar location is determined for a user defined threshold in the flow variable and the average values of the result field for each range gate along the radar’s line of sight are computed. This data is plotted in a range-time diagram, where the black dots indicate the avalanche front, and the colored field indicates the mean values of the flow variable for the range gates at each time step.

Automated path generation

Computational modules like \(\alpha\beta\) (moduleCom2AB) or analysis modules like the Thalweg-time diagram (moduleAna5Utils) or Aimec (moduleAna3AIMEC) require an avalanche path as input. This avalanche path is usually created manually based on an expert opinion. The objective of this module is to automatically generate an avalanche path from a dense flow avalanche (DFA) simulation. The path is generated from the center of mass position of the dense material, so it is called the mass averaged path. It is extended towards the top of the release area and at the bottom. Therefore it covers the entire length of the avalanche with some buffer in the runout area.

The automatic path generation needs dense flow simulation results as input. These can be flow mass and flow thickness or particles for multiple time steps. com1DFA provides these already in the correct way.

We provide runComputeDFAPath, in which two options exist:

  1. DFA simulation results already exist: in this case, you want to provide these as inputs to the path generation function. The flag runDFAModule in runComputeDFAPath is set to False. You need to provide the avalanche directory in your local_avaframeCfg.ini file. This avalanche directory should already have Outputs/com1DFA with one or multiple simulation results. The simulation DEM is also required.

  2. No DFA simulation results exist: use com1DFA to generate the simulation results before generating a path. Change the runDFAModule flag in runComputeDFAPath to True. The default configuration for com1DFA is read. tSteps are adjusted, resType and simTypeList are modified before running com1DFA.

A mass averaged path is produced for each com1DFA simulation. The path is/are saved in avalancheDir/Outputs/DFAPath

  • go to AvaFrame/avaframe

  • copy ana5Utils/DFAPathGenerationCfg.ini to ana5Utils/local_DFAPathGenerationCfg.ini and edit (if not, default values are used)

  • run:

    python3 runScripts/

Mass average path

Any DFA simulation should be able to produce information about mass distribution for different time steps of the simulation (either flow thickness, mass, velocities… rasters or particles). This information is used to compute time dependent mass average quantities such as position (center of mass), velocity… For a flow quantity \(\mathbf{a}(\mathbf{x}, t)\), the associated mass averaged quantity is defined by:

\[\bar{\mathbf{a}}(t) = \int\limits_V \rho \mathbf{a}(\mathbf{x}, t)\,dV \approx \sum\limits_k m_k \mathbf{a}_k(t)\]

where \(m_k\) respectively \(\mathbf{a}_k(t)\) defines the mass respectively flow quantity of particle or raster cell \(k\). Applying the mass averaging to \((x, y, z)\) gives the mass average path profile.


The mass average path profiles does not necessarily lie on the topography

It is also possible to compute the mass averaged velocity squared \(\overline{\mathbf{u^2}}(t)\), kinetic energy \(\overline{\frac{1}{2}m\mathbf{u^2}}(t)\) or travel distance \(s\) (which are used in the ana1Tests:Energy line test).

The path is resampled at nCellsResample x cellsize and is extended towards the release area top to produce meaningful results when used in the com2AB module. Since results from the \(\alpha\beta\) analysis depend on the path profile start, moving the starting point of the profile will shift the \(\alpha\) upwards or downwards and affect the runout value.

Extending path towards the top (release)

There are two options available to extend the mass averaged path profile in the release area (extTopOption in the configuration file):

  1. Extend the path up to the highest point in the release (highest particle or highest cell depending on which particles or rasters are available).

  2. Extend the path towards the point that will lead to the longest runout. This point does not necessarily coincide with the highest point in the release area and corresponds to the point for which \((\Delta z - \Delta s \tan{\alpha})\) is maximum. \(\alpha\) corresponds to the angle of the runout line going from first to last point of the mass averaged line. \(\Delta z\) and \(\Delta s\) represent the vertical and horizontal distance between a point in the release and the first point of the mass averaged path profile.

Extending path towards the bottom (runout)

It is also necessary to extend the profile in the runout area. This is done by finding the direction of the path given by the few last points in the path in (x,y) (all points at a distance nCellsMinExtend x cellSize < distance < nCellsMaxExtend x cellSize)) and extending in this direction for a given percentage (factBottomExt) of the total length of the path \(s\).