Published

2017-05-01

Determination of landslide susceptibility in linear infrastructure. Case: aqueduct network in Palacé, Popayan (Colombia)

Determinación de la susceptibilidad por movimientos en masa en infraestructura lineal. Caso: red de acueducto de Palacé, Popayán (Colombia)

Keywords:

Geomorphometry, mass removal processes, landscape parameters, logistic regression, accuracy (en)
Geomorfometría, procesos de remoción en masa, parámetros del terreno, regresión logística, exactitud (es)

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This research aimed to predict the occurrence of mass movements in the aqueduct network of Palacé, in the municipality of Popayan (Colombia). We evaluated the quality of SRTM and ASTER digital terrain models by comparing them with contour lines using a map scale of 1: 25000. The landscape parameters derived from the SRTM-DEM were analyzed with a multivariate procedure using algorithms implemented in free software, along with thematic information of the study area (coverage, distance to faults, rivers and precipitation). We selected non-redundant variables with the non-parametric ACP technique, and obtained a susceptibility prediction model using logistic regression, with two types of variables: dependent (landslides inventory from field observation) and independent (slope, slope length factor, topographic wetness index, flow path length, soil units and rate of convergence) resulting in a susceptibility map, reclassified into categories according to the values of probability. The prediction model could not be quantitatively assessed because of the absence of studies with a semi-detailed scale, but the estimation of the mean square error of elevation, from which the terrain parameters were derived, the level of detail and the performance of the classifier with ROC curve, yielded a zoning consistent with the findings of the field visits.
Esta investigación busca predecir la ocurrencia de movimientos en masa en la red de acueducto Palacé, en el municipio de Popayan (Cauca). Se evaluó la calidad de los modelos digitales del terreno SRTM y ASTER, comparándolos con curvas de nivel a escala 1:25000. Los parámetros del terreno, derivados del modelo DEM-SRTM, fueron analizados de forma multivariada mediante algoritmos implementados en software libre, junto con información temática de la zona de estudio (cobertura, distancia a fallas, a los ríos y la precipitación). Mediante la técnica no paramétrica del ACP se seleccionaron variables no redundantes, y se obtuvo un modelo de predicción de susceptibilidad mediante regresión logística utilizando variables dependientes (inventario de deslizamiento a partir del recorrido de campo) e independientes, correspondientes al terreno: la pendiente, el factor longitud de pendiente, el índice topográfico de humedad, la longitud de ruta de flujo, los suelos y el índice de convergencia. Esto permitió la obtención de un mapa de susceptibilidad que se reclasificó en categorías de acuerdo con valores de probabilidad obtenidos. El modelo de predicción no pudo evaluarse cuantitativamente al no haber estudios a escala semi-detallada, pero la estimación del error cuadrático medio de la elevación, desde la cual se derivaron los parámetros del terreno, el nivel de detalle obtenido y el desempeño del clasificador con la curva ROC, arrojó una zonificación concordante con lo encontrado en las visitas de campo realizadas.

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How to Cite

Determination of landslide susceptibility in linear infrastructure. Case: aqueduct network in Palacé, Popayan (Colombia). (2017). Ingeniería E Investigación, 37(2), 17-24. https://doi.org/10.15446/ing.investig.v37n2.59654

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