Abstract

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.

Highlights

  • Mass movement processes such as landslides, debris flows, rock avalanches, or snow avalanches may lead to damages or even disasters when interacting with society

  • We introduce r.randomwalk, a flexible and multifunctional 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

  • We have introduced the open-source GIS tool r.randomwalk, designed for conceptual modelling of the propagation of mass movements. r.randomwalk offers built-in functions for considering uncertainties and for validation

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Summary

Introduction

Mass movement processes such as landslides, debris flows, rock avalanches, or snow avalanches may lead to damages or even disasters when interacting with society. Computer models predicting travel distances, hazardous areas, impact energies, or travel times may help the society to mitigate the effects of such processes and, to reduce the risk and the losses (Hungr et al, 2005). Since the processes are complex in detail and the input parameters are uncertain, simplified conceptual models for the motion of mass flows are today used in combination with GIS (Geographic Information System). These models may be used for single events. They are useful to indicate potential impact areas at broader scales. Monte Carlo techniques (random walks, Pearson, 1905; Gamma, 2000) or multiple flow direction algorithms (Horton et al, 2013) are employed to simulate the lateral spreading of the flow

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