Modeling shallow landslides triggered by rainfall in tropical and mountainous terrains
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Trabajo de grado - Maestría
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InglésPublication Date
2013-02Metadata
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Landslides are one of the most common causes of fatalities and economic losses worldwide (Schuster, 1996), therefore the capacity to predict these movements has been a topic of great interest to scientific community (Caine, 1980; Montgomery & Dietrich, 1994; Finlay et al., 1997; Iverson, 2000; Aleotti, 2004; Crosta & Frattinni, 2008; Sidle & Ochiai, 2006). Although landslides do represent changes in terrain morphology within the natural and continuous geomorphologic cycle (Scheidegger, 1998) its occurrence and losses associated in the last decades has been closely tied to world population growth and consequent urban expansion on susceptible slopes to landslides. The urban population of developing countries has increased by 5 in 40 years and continues increasing rapidly (UNFP, 2007). The greatest landslide losses occur in the Ring of Fire countries (Alcantara - Ayala, 2002). Estimation made by Varnes (1981) indicates that 89% of deaths, due to landslides, are located in those countries. Data presented by Sidle & Ochiai (2006) pointed to Nepal, Japan and China as the countries with the biggest number of landslide fatalities per year, with values between 190 and 150; in Latin America, Brazil lead the ranking with an average of 88 people killed per year. In economic terms, Japan is the country most affected by landslides, with an estimated loss of 4 billion dollars annually, followed by Italy, India and the United States with losses ranging from 1 to 2 billion dollars per year (Cruden et al., 1989; Schuster, 1996; Schuster & Highland, 2001; Sidle & Ochiai, 2006). Unfortunately Colombia has no accurate databases to estimate this statistics. Numerous studies have been developed in recent years that have allowed an increasing understanding of the causes that involve these morphodynamic processes. However, because of the complexity involved in landslide occurrence, a great uncertainty still exists in predicting this kind of events. (Texto tomado de la introducción)Keywords
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