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Risk Zone Prediction in Meandering Rivers by Using a Multivariate Approach
The formulation of Kinoshita curves takes into account a number of physiographic characteristics and the configuration of the river; however, it is the curve amplitude, the one that represents the main characteristic of this formulation. This main feature is known as the angular sinuosity coefficient (). In this paper an alternative expression for meander prediction formulation, based on a stochastic multivariate analysis of the geomorphologic and physiographic characteristics of a river is proposed. Stochastic models are used to simulate 3,480 occurrences of the sixteen characteristics proposed to characterize the meandering of Cahuacan River in the Mexican state of Chiapas. The prioritization of the variables obtained through an empirical orthogonal functions (EOF) analysis clearly showed the existence of three groups of parameters, which altogether explain the behavior of the meandering of Cahuacan River. The first group is formed by the morphologic characteristics of the river. The second group corresponds to the hydrologic features of the basin, and the third one to the morphologic and geometric characteristics of the river. The computation of the confidence limits, although from a statistical approach, constitutes a good tool to consolidate the arguments that define the zones at potential risk. The stochastic simulation of the future conditions of the river allows the precise definition of the zones directly in the field.
Risk Zone Prediction in Meandering Rivers by Using a Multivariate Approach
The formulation of Kinoshita curves takes into account a number of physiographic characteristics and the configuration of the river; however, it is the curve amplitude, the one that represents the main characteristic of this formulation. This main feature is known as the angular sinuosity coefficient (). In this paper an alternative expression for meander prediction formulation, based on a stochastic multivariate analysis of the geomorphologic and physiographic characteristics of a river is proposed. Stochastic models are used to simulate 3,480 occurrences of the sixteen characteristics proposed to characterize the meandering of Cahuacan River in the Mexican state of Chiapas. The prioritization of the variables obtained through an empirical orthogonal functions (EOF) analysis clearly showed the existence of three groups of parameters, which altogether explain the behavior of the meandering of Cahuacan River. The first group is formed by the morphologic characteristics of the river. The second group corresponds to the hydrologic features of the basin, and the third one to the morphologic and geometric characteristics of the river. The computation of the confidence limits, although from a statistical approach, constitutes a good tool to consolidate the arguments that define the zones at potential risk. The stochastic simulation of the future conditions of the river allows the precise definition of the zones directly in the field.
Risk Zone Prediction in Meandering Rivers by Using a Multivariate Approach
Gutierrez, Alfonso (author) / Contreras, Vladimir (author) / Ramirez, Aldo I. (author) / Mejia, Roberto (author)
2012-04-13
Article (Journal)
Electronic Resource
Unknown
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