r.randomwalk v1, a multi-functional conceptual tool for mass movement routing
- 1Geomorphological Systems and Risk Research, Department of Geography and Regional Research, University of Vienna, Universitätsstraße 7, 1190 Vienna, Austria
- 2Institute of Applied Geology, University of Natural Resources and Life Sciences (BOKU), Peter-Jordan-Straße 70, 1190 Vienna, Austria
- 3Department of Geological Sciences, University of Canterbury, Private Bag 4800, Christchurch, New Zealand
- 4Department of Geomatics, National Cheng Kung University, 1 University Road, Tainan 701, Taiwan
Abstract. We introduce r.randomwalk, a flexible and multi-functional open-source tool for backward and forward analyses of mass movement propagation. r.randomwalk builds on GRASS GIS (Geographic Resources Analysis Support System – Geographic Information System), the R software for statistical computing and the programming languages Python and C. Using constrained random walks, mass points are routed from defined release pixels of one to many mass movements through a digital elevation model until a defined break criterion is reached. Compared to existing tools, the major innovative features of r.randomwalk are (i) multiple break criteria can be combined to compute an impact indicator score; (ii) the uncertainties of break criteria can be included by performing multiple parallel computations with randomized parameter sets, resulting in an impact indicator index in the range 0–1; (iii) built-in functions for validation and visualization of the results are provided; (iv) observed landslides can be back analysed to derive the density distribution of the observed angles of reach. This distribution can be employed to compute impact probabilities for each pixel. Further, impact indicator scores and probabilities can be combined with release indicator scores or probabilities, and with exposure indicator scores. We demonstrate the key functionalities of r.randomwalk for (i) a single event, the Acheron rock avalanche in New Zealand; (ii) landslides in a 61.5 km2 study area in the Kao Ping Watershed, Taiwan; and (iii) lake outburst floods in a 2106 km2 area in the Gunt Valley, Tajikistan.