pyTopRunDF

Background

A two dimensional runout simulation tool for debris flows to predict inundation areas on torrential fans. Calculations are based on a semi-empirical runout prediction model for volcanic mudflows (lahars) as proposed by Iverson et al. (1998).
They determined power-law relationships between the planimetric area of the deposits (B) and the deposit volume (V) by assuming geometric similarity:

$V=B\overline{h}$

with $B$ the deposited area and $\overline{h}$ the average deposition height.

Iverson et al. (1998) suggest geometric similarity between $B$ and $\overline{h}$ by assuming a constant ratio $\epsilon$ which yields to:

Thus the potential deposition area $B$ can be estimated based on the event volume $V$ and $k_B$, a coefficient which represents an average mobility of the mass movement containing some information on the flow properties during depositional phase.

$B=k_BV^{2/3}$

Range of mobility coefficients $k_B$ of alpine mass movements

Study	Process Type	$k_B$
Crosta (2003)	Granular debris flows	6
Scheidl and Rickenmann (2010)	Granular debris flows (IT)	18
Griswold (2004)	Debris flows	19
Berti (2007)	Debris flows	30
Scheidl and Rickenmann (2010)	Debris flows (CH)	32
Scheidl and Rickenmann (2010)	Debris flows (AUT)	45
Capra (2002)	Earth slides	51
Scheidl and Rickenmann (2010)	Debris floods (AUT)	57
Waythomas (2000)	Volcanic earth flows	92
Iverson et al. (1998).	Lahars	200

Features

• Model potential 2D debris-flow deposition (heights) based on a given event volume and one parameter ($k_B$).
• Fast calculation.
• Accounts for the fan topography.
• Designed for preliminary hazard zoning.

Instructions

• See instructions

Requirements

• Python 3.8 or higher
• pip (Python package manager)

How to Run

Step 1: Clone the Repository

First, clone this repository to your local machine:

git clone <https://github.com/schidli/pyTopRunDF.git>

cd pyTopRunDF

Step 2: Create a Virtual Environment

Create a virtual environment to isolate the dependencies:

python -m venv pytoprundf

Activate the virtual environment

• on Windows:

pytoprundf\Scripts\activate

• on MacOS/Linux:

source pytoprundf\Scripts\activate

Step 3: Install Dependencies

Install the required Python packages using the requirements.txt file:

pip install -r requirements.txt

Step 4: Run the Script

Run the main script:

python batch_select_process.py

Step 5: View the Results

The script will generate output files (e.g., depo.asc) and display a plot of the result for each input scenario. Check the output directory for the generated files.

Project Structure:

pyTopRunDF/
├── batch_selected_process.py:      Start script.
├── TopRunDF.py:                    Main script for the simulation.
├── Scenarios/
│   ├── Scenario_1/                 Input scenarios
│   │   ├── topofan.asc:            Input digital terrain model (DTM) of scenario1.
│   │   └── input.json:             Input data file of scenario1.
│   ├── Scenario_2/
│   │   ├── topofan.asc:            Input digital terrain model (DTM) of scenario2.
│   │   └── input.json:             Input data file of scenario2.
│   ├── Scenario.../
├── Outputs/
│   ├── Scenario_1/
│   │   ├── depo.asc:               Output deposition raster of sceanrio1.
│   │   └── <eventname>_deposition.png:  Resultplot of scenario1.
│   ├── Scenario.../ 
├── RandomSingleFlow.py:            External Python file for random walk logic.
├── PlotResult.py:                  External Python file for plot logic.
└── requirements.txt:               Python dependencies.