scholarly journals A New Approach to Mapping Landslide hazards: a probabilistic integration of empirical and physically based models in the North Cascades of Washington, USA - Research Data

2019 ◽  
Vol 19 (11) ◽  
pp. 2477-2495
Author(s):  
Ronda Strauch ◽  
Erkan Istanbulluoglu ◽  
Jon Riedel

Abstract. We developed a new approach for mapping landslide hazards by combining probabilities of landslide impacts derived from a data-driven statistical approach and a physically based model of shallow landsliding. Our statistical approach integrates the influence of seven site attributes (SAs) on observed landslides using a frequency ratio (FR) method. Influential attributes and resulting susceptibility maps depend on the observations of landslides considered: all types of landslides, debris avalanches only, or source areas of debris avalanches. These observational datasets reflect the detection of different landslide processes or components, which relate to different landslide-inducing factors. For each landslide dataset, a stability index (SI) is calculated as a multiplicative result of the frequency ratios for all attributes and is mapped across our study domain in the North Cascades National Park Complex (NOCA), Washington, USA. A continuous function is developed to relate local SI values to landslide probability based on a ratio of landslide and non-landslide grid cells. The empirical model probability derived from the debris avalanche source area dataset is combined probabilistically with a previously developed physically based probabilistic model. A two-dimensional binning method employs empirical and physically based probabilities as indices and calculates a joint probability of landsliding at the intersections of probability bins. A ratio of the joint probability and the physically based model bin probability is used as a weight to adjust the original physically based probability at each grid cell given empirical evidence. The resulting integrated probability of landslide initiation hazard includes mechanisms not captured by the infinite-slope stability model alone. Improvements in distinguishing potentially unstable areas with the proposed integrated model are statistically quantified. We provide multiple landslide hazard maps that land managers can use for planning and decision-making, as well as for educating the public about hazards from landslides in this remote high-relief terrain.


2019 ◽  
Author(s):  
Ronda Strauch ◽  
Erkan Istanbulluoglu ◽  
Jon Riedel

Abstract. We developed a new approach for mapping landslide hazard by combining probabilities of landslide impact derived from a data-driven statistical approach and process-based model of shallow landsliding. Our statistical approach integrates the influence of seven site attributes on observed landslides using a frequency ratio method. Influential attributes and resulting susceptibility maps depend on the observations of landslides considered: all types of landslides, debris avalanches only, or source areas of debris avalanches. These observational datasets reflect the capture of different landslide processes or components, which relate to different landslide-inducing factors. Slopes greater than 35° are more frequently associated with landslide initiation, while higher landslide hazards at gentler slopes (< 30°) reflect depositional processes from observations of all landslide types or debris avalanches. Source areas are associated with mid to high elevations (1,400 to 1,800 m), where they are linked to ecosystem transition (e.g., forest to barren), while all landslides types and debris avalanches show increasing frequency in lower elevations (< 1,200 m). Slope is a key attribute in the initiation of landslides, while lithology is mainly linked to transport and depositional processes. East (west) aspect is a positive (negative) landslide-influencing factor, likely due to differences in forest cover and associated root cohesion, and evapotranspiration. The empirical model probability derived from debris avalanche source area is combined probabilistically with a previously developed processed-based probabilistic model to produce an integrated probability of landslide hazard for initiation that includes mechanisms not captured by the infinite slope stability model. We apply our approach in North Cascades National Park Complex in Washington, USA, to provide multiple landslide hazard maps that land managers can use for planning and decision making, as well as educating the public about hazards from landslides in this remote high-relief terrain.


10.1029/ft307 ◽  
1989 ◽  
Author(s):  
R. W. Tabor ◽  
R. A. Haugerud ◽  
E. H. Brown ◽  
R. S. Babcock ◽  
R. B. Miller

2017 ◽  
Author(s):  
Kirsten B. Sauer ◽  
◽  
Stacia M. Gordon ◽  
Robert B. Miller ◽  
Jeffrey Vervoort ◽  
...  

Lithosphere ◽  
2014 ◽  
Vol 6 (6) ◽  
pp. 473-482 ◽  
Author(s):  
Thibaud Simon-Labric ◽  
Gilles Y. Brocard ◽  
Christian Teyssier ◽  
Peter A. van der Beek ◽  
Peter W. Reiners ◽  
...  

2016 ◽  
Vol 663 ◽  
pp. 204-212 ◽  
Author(s):  
Azadeh Fahimi ◽  
Timothy S. Evans ◽  
Jeff Farrow ◽  
David A. Jesson ◽  
Mike J. Mulheron ◽  
...  

2017 ◽  
Vol 49 (4) ◽  
pp. 971-988 ◽  
Author(s):  
Franck Lespinas ◽  
Ashu Dastoor ◽  
Vincent Fortin

Abstract This study presents an evaluation of the performance of the dynamically dimensioned search (DDS) algorithm when calibrating the hydrological component of the Visualizing Ecosystems for Land Management Assessments (VELMA) ecohydrological model. Two calibration strategies were tested for the initial parameter values: (1) a ‘high-cost strategy’, where 100 sets of initial parameter values were randomly chosen within the overall parameter space, and (2) a ‘low-cost strategy’, where a unique set of initial parameter values was derived from the available field data. Both strategies were tested for six different values of the maximum number of model evaluations ranging between 100 and 10,000. Results revealed that DDS is able to converge rapidly to a good parameter calibration solution of the VELMA hydrological component regardless of the parameter initialization strategy used. The accuracy and convergence efficiency of the DDS algorithm were, however, slightly better for the low-cost strategy. This study suggests that initializing the parameter values of complex physically based models using information on the watershed characteristics can increase the efficiency of the automatic calibration procedures.


2006 ◽  
Vol 28 (2) ◽  
pp. 302-322 ◽  
Author(s):  
Robert B. Miller ◽  
Scott R. Paterson ◽  
Hermann Lebit ◽  
Helge Alsleben ◽  
Catalina Lüneburg
Keyword(s):  

2020 ◽  
Vol 162 (1) ◽  
pp. 127-143 ◽  
Author(s):  
Grant L. Harley ◽  
R. Stockton Maxwell ◽  
Bryan A. Black ◽  
Matthew F. Bekker
Keyword(s):  

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