Citas bibligráficas
Maldonado, A., (2021). Identificación de zonas de riesgo por deslizamientos de laderas debido a la saturación de suelos en la microcuenca Mariño, Abancay [Universidad Nacional Agraria La Molina]. https://hdl.handle.net/20.500.12996/4744
Maldonado, A., Identificación de zonas de riesgo por deslizamientos de laderas debido a la saturación de suelos en la microcuenca Mariño, Abancay []. : Universidad Nacional Agraria La Molina; 2021. https://hdl.handle.net/20.500.12996/4744
@mastersthesis{renati/248938,
title = "Identificación de zonas de riesgo por deslizamientos de laderas debido a la saturación de suelos en la microcuenca Mariño, Abancay",
author = "Maldonado Mendivil, Angel",
publisher = "Universidad Nacional Agraria La Molina",
year = "2021"
}
This research has been developed to identify the risk areas due to landslides due to the saturation of the soil generated by rainfall in the Mariño river micro-basin, located in the province of Abancay and the department of Apurímac, where it is analyzed and identifies the problem of mass movements through an integrative approach between saturation conditions and landslides, evaluating slope stability by the infinite slope stability model using SINMAP (Stability Index Mapping) program, this being the application of a deterministic and probabilistic method in the environment of a geographic information system, for which the geotechnical and geohydraulic data available for the study area was collected in order to create a susceptibility map to the danger of landslides. The analysis was carried out on a regional scale through a geographic information system, obtaining detailed information through satellite images to obtain the geological, hydrological, and geomorphological characteristics and complementing it with a field evaluation. For the validation of this study, the SINMAP model was calibrated based on the literature of the values obtained and a detailed inventory of surface landslides that occurred during the last 60 years, being the simulated scenario with eight calibration regions or land uses, the simulation was quite successful describing the landslides due to slope failure in the study area, identifying 70.69% of the landslides, out of a total of 58 inventoried landslides in areas classified as unstable. The reliability of the simulation was evaluated using a classification model by analyzing the ROC curve with 96.7% global precision.
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