Predicting the probability and volume of postwildfire debris flows in the intermountain western United States

2009 ◽  
Vol 122 (1-2) ◽  
pp. 127-144 ◽  
Author(s):  
S. H. Cannon ◽  
J. E. Gartner ◽  
M. G. Rupert ◽  
J. A. Michael ◽  
A. H. Rea ◽  
...  
Keyword(s):  
United States ◽  
Debris Flows ◽  
Western United States

Minimizing economic impacts from post-fire debris flows in the western United States

2016 ◽  
Vol 83 (1) ◽  
pp. 149-176 ◽  
Author(s):  
Kevin McCoy ◽  
Vitaliy Krasko ◽  
Paul Santi ◽  
Daniel Kaffine ◽  
Steffen Rebennack
Keyword(s):  
United States ◽  
Debris Flows ◽  
Economic Impacts ◽  
Western United States ◽  
Fire Debris

The Timing of Susceptibility to Post-Fire Debris Flows in the Western United States

2015 ◽  
Vol 21 (4) ◽  
pp. 277-292 ◽  
Author(s):  
JEROME V. DeGRAFF ◽  
SUSAN H. CANNON ◽  
JOSEPH E. GARTNER
Keyword(s):  
United States ◽  
Debris Flows ◽  
Western United States ◽  
Fire Debris

scholarly journals Evaluation of predictive models for post-fire debris flow occurrence in the western United States

2018 ◽  
Vol 18 (9) ◽  
pp. 2331-2343 ◽  
Author(s):  
Efthymios I. Nikolopoulos ◽  
Elisa Destro ◽  
Md Abul Ehsan Bhuiyan ◽  
Marco Borga ◽  
Emmanouil N. Anagnostou
Keyword(s):  
United States ◽  
Random Forest ◽  
Debris Flow ◽  
Predictive Models ◽  
Debris Flows ◽  
The United States ◽  
Western United States ◽  
Economic Losses ◽  
United States Geological Survey ◽  
Fire Debris

Abstract. Rainfall-induced debris flows in recently burned mountainous areas cause significant economic losses and human casualties. Currently, prediction of post-fire debris flows is widely based on the use of power-law thresholds and logistic regression models. While these procedures have served with certain success in existing operational warning systems, in this study we investigate the potential to improve the efficiency of current predictive models with machine-learning approaches. Specifically, the performance of a predictive model based on the random forest algorithm is compared with current techniques for the prediction of post-fire debris flow occurrence in the western United States. The analysis is based on a database of post-fire debris flows recently published by the United States Geological Survey. Results show that predictive models based on random forest exhibit systematic and considerably improved performance with respect to the other models examined. In addition, the random-forest-based models demonstrated improvement in performance with increasing training sample size, indicating a clear advantage regarding their ability to successfully assimilate new information. Complexity, in terms of variables required for developing the predictive models, is deemed important but the choice of model used is shown to have a greater impact on the overall performance.

scholarly journals Evaluation of predictive models for post-fire debris flows occurrence in the western United States

2018 ◽  
Author(s):  
Efthymios I. Nikolopoulos ◽  
Elisa Destro ◽  
Md Abul Ehsan Bhuiyan ◽  
Marco Borga ◽  
Emmanouil N. Anagnostou
Keyword(s):  
United States ◽  
Random Forest ◽  
Predictive Models ◽  
Debris Flows ◽  
Training Sample ◽  
Western United States ◽  
Economic Losses ◽  
United States Geological Survey ◽  
Learning Approaches ◽  
Fire Debris

Abstract. Rainfall-induced debris flows in recently burned mountainous areas cause significant economic losses and human casualties. Currently, prediction of post-fire debris flows is widely based on the use of power-law thresholds and logistic regression models. While these procedures have served with certain success in existing operational warning systems, in this study we investigate the potential to improve the efficiency of current predictive models with machine-learning approaches. Specifically, the performance of a new predictive model based on random forest algorithm is compared against current techniques for the prediction of post-fire debris flow occurrence in the western United States. The analysis is based on a database on post-fire debris flows recently published by United States Geological Survey. Results show that predictive models based on random forest exhibit systematic and considerably improved performance with respect to the other models examined. In addition, the random forest-based models demonstrated improvement in performance with increasing training sample size, indicating a clear advantage regarding their ability to successfully assimilate new information. Complexity, in terms of variables required for developing the predictive models, deems important but the choice of model used is shown to have a greater impact on the overall performance.

Writing Time in Metaphors

2018 ◽  
Author(s):  
Jennifer J. Smith
Keyword(s):  
United States ◽  
The United States ◽  
Western United States ◽  
Entire System ◽  
Language And Culture ◽  
Space Race ◽  
Do So

Coherence of place often exists alongside irregularities in time in cycles, and chapter three turns to cycles linked by temporal markers. Ray Bradbury’s The Martian Chronicles (1950) follows a linear chronology and describes the exploration, conquest, and repopulation of Mars by humans. Conversely, Louise Erdrich’s Love Medicine (1984) jumps back and forth across time to narrate the lives of interconnected families in the western United States. Bradbury’s cycle invokes a confluence of historical forces—time as value-laden, work as a calling, and travel as necessitating standardized time—and contextualizes them in relation to anxieties about the space race. Erdrich’s cycle invokes broader, oppositional conceptions of time—as recursive and arbitrary and as causal and meaningful—to depict time as implicated in an entire system of measurement that made possible the destruction and exploitation of the Chippewa people. Both volumes understand the United States to be preoccupied with imperialist impulses. Even as they critique such projects, they also point to the tenacity with which individuals encounter these systems, and they do so by creating “interstitial temporalities,” which allow them to navigate time at the crossroads of language and culture.

Women's Studies in the Western United States

NWSA Journal ◽  
2004 ◽  
Vol 16 (2) ◽  
pp. 180-189
Author(s):  
Karen L. Salley ◽  
Barbara Scott Winkler ◽  
Megan Celeen ◽  
Heidi Meck
Keyword(s):  
United States ◽  
Women's Studies ◽  
Western United States ◽  
Women’S Studies
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