Determination of probabilities for the generation of high-discharge flows in the middle basin of Elqui River, Chile

Iván P. Vergara Dal Pont (), Fernanda A. Santibañez Ossa, Diego Araneo, Francisco J. Ferrando Acuña and Stella M. Moreiras
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Iván P. Vergara Dal Pont: CONICET-IANIGLA
Fernanda A. Santibañez Ossa: Universidad de Chile
Diego Araneo: CONICET-IANIGLA
Francisco J. Ferrando Acuña: Universidad de Chile
Stella M. Moreiras: CONICET-IANIGLA

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2018, vol. 93, issue 1, No 26, 546 pages

Abstract: Abstract The probabilities for the generation of hyperconcentrated flows, and debris and mud flows in the middle basin of Elqui River (Chile) are determined. The objective was achieved collecting, for a period of 14 years, the precipitation events generating high-discharge flows, as well as the larger precipitation events that did not generate this process. For each of these events, data of peak 1-h storm precipitation, temperature (representing the zero-isotherm altitude) and antecedent precipitation of 1, 5 and 10 days were collected from three meteorological stations. Initially, an ordinal logistic regression model for each antecedent precipitation was fitted, but all were discarded due to the low significance of these variables in the generation of the models. This result allowed to infer that the high-discharge flows of the region are generated mainly by runoff and not by deep-seated or shallow landslides. Subsequently, a new model with the remaining variables was performed, which was statistically validated. From this, it was considered prudent to take as thresholds for the occurrence of hyperconcentrated flows, and debris and mud flows, their respective probabilities of 50%. For these thresholds, the model had an efficiency in the prediction of high-discharge flows of 90%. Finally, the partial correlation coefficients of each significant predictor variable with respect to the dependent were calculated, establishing that the temperature has greater influence than the peak 1-h storm precipitation.

Keywords: Meteorological thresholds; Geoclimatic hazard; Ordinal logistic regression; Debris flows (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s11069-018-3313-0

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