Zonificación de amenazas por remoción en masa usando la metodología de Mora y Vahrson en La Cuenca del Río Las Ceibas: un enfoque comparativo con registros históricos
| dc.contributor.advisor | Paz Tenorio, Jorge Antonio | |
| dc.contributor.author | Sandoval Sierra, Elisa Mercedes | |
| dc.contributor.author | Torres Tovar, Rubiel Andres | |
| dc.contributor.googlescholar | https://scholar.google.com/citations?user=1K9-TEEAAAAJ&hl=es&oi=ao | |
| dc.contributor.googlescholar | https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001611449 | |
| dc.contributor.orcid | https://orcid.org/0000-0001-7071-7558 | |
| dc.date.accessioned | 2026-07-06T21:46:39Z | |
| dc.date.available | 2026-07-06T21:46:39Z | |
| dc.date.issued | 2026-07-06 | |
| dc.description | La cuenca del río Las Ceibas, ubicada en el departamento del Huila, ha sido históricamente afectada por procesos de remoción en masa, con más de 800 eventos registrados en distintos sectores del territorio. Estos fenómenos, asociados a condiciones físicas como la pendiente, la litología, la humedad del suelo, la sismicidad y la precipitación, configuran un escenario de amenaza persistente para los ecosistemas de la cuenca y para la población. El objetivo principal es validar la confiabilidad del modelo de Mora y Vahrson en la zonificación de amenazas por remoción en masa en la cuenca del río Las Ceibas, mediante la comparación de los resultados obtenidos con el inventario histórico de deslizamientos. Metodológicamente, la investigación se desarrolló con un enfoque geoespacial y comparativo, integrando factores condicionantes y detonantes establecidos en el modelo. El procesamiento y análisis de la información se realizó mediante tecnologías de sistemas de información geográfica, utilizando insumos oficiales como el Modelo de Elevación Digital Suministrado por la CAM a escala 1:25.000, la cartografía geológica del Servicio Geológico Colombiano a escala 1:100.000 y los registros hidrometeorológicos del IDEAM correspondientes a las estaciones ubicadas dentro y en el entorno inmediato de la cuenca. A estos insumos se sumaron los inventarios de históricos de remoción en masa obtenidos por el SGC y la CAM, los cuales se emplearon para la validación del modelo. Los resultados evidenciaron relación geoespacial entre las zonas clasificadas con amenaza moderada y media y la concentración de eventos históricos, lo que permitió confirmar la capacidad del modelo para representar patrones reales de ocurrencia de remociones en masa en la cuenca. En conclusión, el modelo de Mora y Vahrson aplicado a la cuenca demostró ser una herramienta confiable como insumo diagnóstico para la gestión del riesgo y el ordenamiento territorial a escala de cuenca, aportando criterios técnicos que pueden apoyar la toma de decisiones en territorios con condiciones geomorfológicas y climáticas complejas. | |
| dc.description.abstract | The Las Ceibas River watershed, located in the department of Huila, has historically been affected by Landslides, with more than 800 events recorded in different sectors of the territory. These phenomena, associated with physical conditions such as slope, lithology, soil moisture, seismicity, and precipitation, constitute a scenario of persistent hazard for the watershed’s ecosystems and the local population. The main objective of this study is to validate the reliability of the Mora and Vahrson model for landslide hazard zoning in the Las Ceibas River watershed by comparing the results obtained with the historical landslide inventory.Methodologically, the research was developed with a geospatial and comparative approach, integrating conditioning and triggering factors established in the model. The processing and analysis of the information were carried out through geographic information system technologies, using official inputs such as the Digital Elevation Model provided by CAM at a 1:25,000 scale, the geological cartography of the Colombian Geological Survey at a 1:100,000 scale, and the hydrometeorological records of IDEAM corresponding to the stations located within and in the immediate surroundings of the watershed. These inputs were complemented with the historical mass movement inventories obtained by the SGC and CAM, which were used for model validation.The results demonstrated a geospatial relationship between areas classified as moderate and medium hazard and the concentration of historical events, which confirmed the model’s ability to represent real patterns of landslides occurrence within the watershed. In conclusion, the Mora and Vahrson model proved to be a reliable tool as a diagnostic input for risk management and territorial planning at the watershed scale, providing technical criteria that can support decision-making in territories with complex geomorphological and climatic conditions. | |
| dc.description.degreelevel | Maestría | spa |
| dc.description.degreename | Magister en Gestión de Cuencas Hidrográficas | spa |
| dc.format.mimetype | application/pdf | |
| dc.identifier.citation | Sandoval Sierra, E.M y Torres Tovar, R.A (2026). Zonificación de amenazas por remoción en masa usando la metodología de Mora y Vahrson en La Cuenca del Río Las Ceibas: un enfoque comparativo con registros históricos. [Trabajo de Maestria, Universidad Santo Tomás]. Repositorio Institucional | |
| dc.identifier.instname | instname:Universidad Santo Tomás | spa |
| dc.identifier.reponame | reponame:Repositorio Institucional Universidad Santo Tomás | spa |
| dc.identifier.repourl | repourl:https://repository.usta.edu.co | spa |
| dc.identifier.uri | http://hdl.handle.net/11634/72878 | |
| dc.language.iso | spa | |
| dc.publisher | Universidad Santo Tomás | spa |
| dc.publisher.branch | CRAI-USTA Bogotá | |
| dc.publisher.faculty | Facultad de Ciencias Ambientales | spa |
| dc.publisher.program | Maestría Gestión de Cuencas Hidrográficas | spa |
| dc.relation.references | Abdollahi, M, Farshid Vahedifard, Ben A. (2024). Leshchinsky, Hydromechanical modeling of evolving post-wildfire regional-scale landslide susceptibility, Engineering Geology, Volume 335, 107538, ISSN 0013-7952, https://doi.org/10.1016/j.enggeo.2024.107538. | |
| dc.relation.references | Ait Omar, M., Etebaai, I., Taher, M., & Tawfik, A. (2025). Landslide susceptibility mapping in the Bokoya Massif, Northern Morocco: A geospatial and multi-factor analysis using the analytic hierarchy process (AHP). Scientific African, 30, e02980. https://doi.org/10.1016/j.sciaf.2025.e02980 | |
| dc.relation.references | Al-kordi, Abdulmohsen Al-Amri, Govinda raju. (2025) Landslide Susceptibility Mapping Using Geospatial, Analytical Hierarchy Process (AHP), and Binary Logistic Regression (BLR) Techniques- A Study of Wadi Habban Basin, Shabwah, Yemen, Results in Earth Sciences, , 100103, ISSN 2211-7148, https://doi.org/10.1016/j.rines.2025.100103. | |
| dc.relation.references | Alcántara Ayala, I., y Murillo García, F. (2008). Procesos de remoción en masa en México: hacia una propuesta de elaboración de un inventario nacional. Investigaciones Geográficas (Mx), 47-64. | |
| dc.relation.references | Aomei Zhang, Xianmin Wang, Witold Pedrycz, Qiyuan Yang, Xuewen Wang, Haixiang Guo. (2024). Near real-time spatial prediction of earthquake-triggered landslides based on global inventories from 2008 to 2022, Soil Dynamics and Earthquake Engineering, Volume 185, 2024,108890, ISSN 0267-7261, https://doi.org/10.1016/j.soildyn.2024.108890. | |
| dc.relation.references | Apu, S.I., Sharmili, N., Gazi, M.Y. et al. (2025). Remote Sensing and GIS-Based Landslide Susceptibility Mapping in a Hilly District of Bangladesh: A Comparison of Different Geospatial Models. J Indian Soc Remote Sens 53, 531–548 https://doi.org/10.1007/s12524-024-01988-x | |
| dc.relation.references | Arcila, M. García, J., Montejo, J., Eraso, J., Valcarcel, J., Mora, M., Viganò, D., Pagani, M. y Díaz, F. (2020). Modelo nacional de amenaza sísmica para Colombia. Bogotá: Servicio Geológico Colombiano y Fundación Global Earthquake Model. https://doi.org/10.32685/9789585279469 | |
| dc.relation.references | Asnake Boyana Ayele, Abiyot Legesse Tura, Abera Uncha Utallo, Abren Gelaw Mekonnen, (2025). Spatial assessments of landslide hazard vulnerability using decision support system in the Sile-Sago Watershed, Lake Chamo Rift Valley Basin, Ethiopia, Environmental Challenges, Volume 18, 101057, ISSN 2667-0100, https://doi.org/10.1016/j.envc.2024.101057 | |
| dc.relation.references | Barrantes Castillo, G., Barrantes Sotela, O., & Núñez Román, O. (2011). Efectividad de la metodología Mora-Vahrson modificada en el caso de los deslizamientos provocados por el terremoto de Cinchona, Costa Rica. Revista Geográfica de América Central, (47), 141–162. https://www.redalyc.org/pdf/4517/451745770006.pdf | |
| dc.relation.references | Berber, Samet. Sener Ceryan, Murat Ercanoglu. (2025). Comprehensive landslide hazard assessment using spatial, temporal and size probabilities combined with landslide density analysis in Çanakkale (NW Türkiye), Advances in Space Research, ISSN 0273-1177, https://doi.org/10.1016/j.asr.2025.04.048 | |
| dc.relation.references | Calpa, Fabricio Fernández, Euripedes A. Vargas, Guilherme J.C. Gomes, Raquel Q. Velloso, Marcelo Miqueletto, Marcos Massao Futai. (2026). Multi-failure numerical analysis of rainfall-triggered landslides at the basin-scale, Computers and Geotechnics, Volume 189, 107622, ISSN 0266-352X, https://doi.org/10.1016/j.compgeo.2025.107622. | |
| dc.relation.references | Chand Rai, Vijendra Kumar Pandey, Kaushal Kumar Sharma, Sanjeev Sharma. (2024). Landslide susceptibility analysis in the Bhilangana Basin (India) using GIS-based machine learning methods, Geosystems and Geoenvironment, Volume 3, Issue 2, 100253, ISSN 2772-8838, https://doi.org/10.1016/j.geogeo.2024.100253 | |
| dc.relation.references | Chung, C. F., Park, S., & Lee, S. (2021). Assessment of landslide susceptibility using topographic and geomorphological parameters derived from high-resolution DEM data. Geomorphology, 386, 107745. https://doi.org/10.1016/j.geomorph.2021.107745 | |
| dc.relation.references | Congreso de Colombia. (2012). Ley 1523 de 2012. Por la cual se adopta la política nacional de gestión del riesgo de desastres y se establece el Sistema Nacional de Gestión del Riesgo de Desastres y se dictan otras disposiciones. https://www.funcionpublica.gov.co/eva/gestornormativo/norma.php?i=47141 | |
| dc.relation.references | Consejo de Neiva. (2009). Acuerdo 026 de 2009. Por Medio Del Cual Se Revisa Y Ajusta El Acuerdo Numero 016 De 2000 Que Adopta El Plan De Ordenamiento Territorial De Neiva | |
| dc.relation.references | Corporación Autónoma Regional del Alto Magdalena – CAM. (2016). Plan de Ordenación Manejo de la Cuenca Hidrográfica del Río Loro, Río Las Ceibas y Otros Directos al Magdalena (MD) (Código 2111-01). Fase de aprestamiento. https://www.cam.gov.co/media/filer_public/3f/bd/3fbd4ea1-550d-47a3-9f6f-593def6af2de/1_aprestamiento_pomca_vp.pdf | |
| dc.relation.references | Corporación Autónoma Regional del Alto Magdalena – CAM. (2023). Resolución No 1096 del 2 de mayo del 2023. Por medio de la cual se aprueba un POMCA. https://www.cam.gov.co/media/filer_public/db/0d/db0d5b69-47b8-46a2-b24f-0ae78012694a/res_1096_02_05_2023.pdf | |
| dc.relation.references | Corporación Autónoma Regional del Alto Magdalena -CAM. (20231). Plan de Ordenación y Manejo de la Cuenca Hidrográfica del Río Loro, Río Las Ceibas y Otros Directos al Magdalena.https://www.cam.gov.co/transparencia/recurso-hidrico/ | |
| dc.relation.references | Cruden, & Varnes (1996). Landslide types and processes. En A. K. Turner & R. L. Schuster (Eds.), Landslides: Investigation and mitigation (pp. 36–75). Transportation Research Board, National Academy Press. https://onlinepubs.trb.org/Onlinepubs/sr/sr247/sr247-003.pdf | |
| dc.relation.references | Emre Özşahin, Çağlar Kıvanç Kaymaz. (2014). Avalanche Susceptibility and Risk Analysis of Eastern Anatolian Region Using GIS, Procedia - Social and Behavioral Sciences, Volume 120, , Pages 663-672, ISSN 1877-0428, https://doi.org/10.1016/j.sbspro.2014.02.147 | |
| dc.relation.references | Gómez, Edier Aristizábal, Edwin F. García, Diver Marín, Santiago Valencia, Mariana Vásquez. (2023). Landslides forecasting using satellite rainfall estimations and machine learning in the Colombian Andean region, Journal of South American Earth Sciences, Volume 125, 104293, ISSN 0895-9811, https://doi.org/10.1016/j.jsames.2023.104293 | |
| dc.relation.references | Gómez-Miranda, I. N., Restrepo-Estrada, C., Builes-Jaramillo, A., & Porto de Albuquerque, J. (2025). Advanced AI techniques for landslide susceptibility mapping and spatial prediction: A case study in Medellín, Colombia | |
| dc.relation.references | Guzzetti, F., Cardinali, M. Reichenbach, P. Carrara, A. (2000).Comparing landslides maps: A case study in the upper Tiber River Basin, central Italy. Environmental Management. 25:3, 247-363 | |
| dc.relation.references | H.X. Lan, C.H. Zhou, L.J. Wang, H.Y. Zhang, R.H. Li. (2004) Landslide hazard spatial analysis and prediction using GIS in the Xiaojiang watershed, Yunnan, China, Engineering Geology, Volume 76, Issues 1–2, Pages 109-128, ISSN 0013-7952, https://doi.org/10.1016/j.enggeo.2004.06.009 | |
| dc.relation.references | Hao Ma, Fawu Wang. (2025). Factors controlling the formation and movement of clustered shallow landslides triggered by the extreme rainstorm in July 2023 in Beijing, China, Geomorphology, Volume 478, 109728, ISSN 0169-555X, https://doi.org/10.1016/j.geomorph.2025.109728 | |
| dc.relation.references | Henriques, C., Zêzere, J. L., & Trigo, R. M. (2015). The role of the lithological setting on the landslide pattern in southern Portugal. Geomorphology, 233, 1–11. https://doi.org/10.1016/j.geomorph.2015.01.011 | |
| dc.relation.references | Hualin Li, Shouhong Zhang, Jianjun Zhang, Wenlong Zhang, Zhuoyuan Song, Peidan Yu, Chenxin Xie. (2023). A framework for identifying priority areas through integrated eco-environmental risk assessment for a holistic watershed management approach, Ecological Indicators, Volume 146, 109919. https://doi.org/10.1016/j.ecolind.2023.109919 | |
| dc.relation.references | Jen, W.-H., & Chen, Y.-C. (2026). Photogrammetric reconstruction of multi-decadal topographic changes from historical aerial imagery for landslide and debris-flow hazard assessment. Remote Sensing Applications: Society and Environment, 41, Article 101866. https://doi.org/10.1016/j.rsase.2025.101866 | |
| dc.relation.references | Kang, D., Dan, S., Hua, Z., Jingyi, L., Chenlu, W., Zhenguo, W., Shaohua, W. (2025). Study on landslide hazard risk in Wenzhou based on slope units and machine learning approaches Scientific Reports, 15 (1), art. no. 7511, DOI: 10.1038/s41598-025-91669-7 | |
| dc.relation.references | Keh-Jian Shou, Chih-Ming Yang. (2015). Predictive analysis of landslide susceptibility under climate change conditions — A study on the Chingshui River Watershed of Taiwan, Engineering Geology, Volume 192, 2015, Pages 46-62, ISSN 0013-7952, https://doi.org/10.1016/j.enggeo.2015.03.012 | |
| dc.relation.references | Keh-Jian Shou, Jia-Fei Lin. (2020). Evaluation of the extreme rainfall predictions and their impact on landslide susceptibility in a sub-catchment scale, Engineering Geology, Volume 265, 105434. https://doi.org/10.1016/j.enggeo.2019.105434 | |
| dc.relation.references | Ken-ichiro Shimizu, Kazuo Asahiro. (2026). The influence of orchard and forest management on rainfall-induced landslides: A study of Hiraenoki Community in southwestern Japan, Trees, Forests and People, Volume 23, 101103, ISSN 2666-7193, https://doi.org/10.1016/j.tfp.2025.101103 | |
| dc.relation.references | Khan,I Ashutosh Kainthola, Harish Bahuguna, Rayees Ahmed, Mohamed Abioui. (2025). Unravelling the impact of landslide inventory on landslide susceptibility in the Indian Himalaya, Physics and Chemistry of the Earth, Parts A/B/C, Volume 139, 103930, ISSN 1474-7065, https://doi.org/10.1016/j.pce.2025.103930 | |
| dc.relation.references | Lee, S., Kang, T., Kim, M., Ko, H., & An, H. (2025). Evaluation of spatiotemporal effects of soil depth on shallow landslides and debris flows via coupled numerical analysis. Progress in Disaster Science, 28, 100470. https://doi.org/10.1016/j.pdisas.2025.100470 | |
| dc.relation.references | Li, Y., Wang, J., & Wu, C. (2023). Influence of relative relief and topographic roughness on landslide distribution in mountainous regions of Southwest China. CATENA, 226, 107012. https://doi.org/10.1016/j.catena.2023.107012 | |
| dc.relation.references | Lijun Qian, Lihua Ou, Guoxin Li, Ying Chen, Bo Qian. (2025). Optimizing the application of machine learning models in predicting landslide susceptibility using the information value model in Junlian County of Sichuan Basin, Advances in Space Research, , ISSN 0273-1177, https://doi.org/10.1016/j.asr.2025.05.020 | |
| dc.relation.references | Liu, F., Zhang, T., Deng, Y., Qian, F., & Yang, N. (2024). Landslide susceptibility prediction based on landform predisposing indexes: An example from the Beiluo River Basin. Advances in Space Research, 74, 5348–5370. https://doi.org/10.1016/j.asr.2024.08.003 | |
| dc.relation.references | Lopez, M., García, D., & Pérez, S. (2020). Aplicación del método Mora-Vahrson para evaluar la susceptibilidad a deslizamiento en el municipio de Manaure, Cesar, Colombia. Revista de Estudios Latinoamericanos sobre reducción de riesgo https://www.revistareder.com/ojs/index.php/reder/article/view/50/53 | |
| dc.relation.references | López, R, Amat D. Zuluaga, Felipe Gómez, Luis Tapia. (2020). Aplicación del Método Mora-Vahrson para Evaluar la Susceptibilidad a Deslizamiento en el Municipio de Manaure, Cesar, Colombia, Vol 4 , ISSN 0719-8477, https://doi.org/10.55467/reder.v4i2.50 | |
| dc.relation.references | Maestre, J., Pérez, R., & Díaz, L. (2023). Análisis de susceptibilidad por movimientos en masa implementando el método Mora-Vahrson modificado para el corregimiento de Chemesquemena (Cesar, Colombia). Revista de Geomorfología Aplicada. https://doi.org/10.14483/22487638.19951 | |
| dc.relation.references | Marin, R. J., García, E. F., & Aristizábal, E. (2020). Effect of basin morphometric parameters on physically-based rainfall thresholds for shallow landslides. Engineering Geology, 278, 105855. https://doi.org/10.1016/j.enggeo.2020.105855 | |
| dc.relation.references | Ministerio de Ambiente y Desarrollo Sostenible. (2012) Decreto 1640 de 2012. Por medio del cual se reglamentan los instrumentos para la planificación, ordenación y manejo de las cuencas hidrográficas y acuíferos, y se dictan otras disposiciones. Agosto, 2, 2012 Consultado en: https://www.funcionpublica.gov.co/eva/gestornormativo/norma.php?i =49987 | |
| dc.relation.references | Miranda, C. Restrepo-Estrada, A. Builes-Jaramillo, João Porto de Albuquerque. (2025) Advanced AI techniques for landslide susceptibility mapping and spatial prediction: A case study in Medellín, Colombia, Applied Computing and Geosciences, Volume 25, , 100226, ISSN 2590-1974, https://doi.org/10.1016/j.acags.2025.100226 | |
| dc.relation.references | Mondini, A, Fausto Guzzetti, Massimo Melillo, Antonio Pievatolo. (2025) Short to long term space-time prediction of rain-induced landslides under uncertainty, Science of The Total Environment, Volume 984, 179453, ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2025.179453 | |
| dc.relation.references | Mora, S. & Vahrson, W. (1993). Determinación a priori de la amenaza de deslizamientos sobre grandes áreas, utilizando indicadores morfodinámicos. En: Memoria sobre el Primer Simposio. Bogotá, Colombia. pp. 259-273 | |
| dc.relation.references | Olarte, J. (2017). Clasificación de movimientos en masa y su distribución en terrenos geológicos en Colombia. Servicio Geológico Colombiano. https://libros.sgc.gov.co/index.php/editorial/catalog/view/36/31/381 | |
| dc.relation.references | Pacheco Quevedo, R., Velastegui-Montoya, A., Montalván-Burbano, N. et al. (2023). Land use and land cover as a conditioning factor in landslide susceptibility: a literature review. Landslides, 20, 2537-2551. https://doi.org/10.1007/s10346-022-02020-4 | |
| dc.relation.references | Paz Tenorio et al, (2011). Los procesos de remoción en masa; génesis, limitaciones y efectos en el crecimiento urbano de la ciudad de tuxtla gutiérrez, chiapas, México. Revista Geográfica de América Central. Número Especial EGAL, 2011- Costa Rica. Pp 12-13. https://www.redalyc.org/pdf/4517/451744820602.pdf | |
| dc.relation.references | Paz Tenorio, J. A., González Herrera, R., Gómez Ramírez, M., & Velasco Herrera, J. A. (2017). Metodología para elaborar mapas de susceptibilidad a procesos de remoción en masa, análisis del caso ladera sur de Tuxtla Gutiérrez, Chiapas. Investigaciones Geográficas, 92, 1-16. https://doi.org/10.14350/rig.52822 | |
| dc.relation.references | Peifeng Ma, Li Chen, Chang Yu, Qing Zhu, Yulin Ding, Zherong Wu, Hongsheng Li, Changyao Tian, Xuanmei Fan. (2025). Dynamic landslide susceptibility mapping over last three decades to uncover variations in landslide causation in subtropical urban mountainous areas, Remote Sensing of Environment, Volume 326, 114800, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2025.114800 | |
| dc.relation.references | Pengju Pu, Jianjun Hao, Dingding Ma, Jiangting Yan. (2023) Digital Design and Data Management System for Network APP Based on GIS Technology, Procedia Computer Science, Volume 228, Pages 1110-1119, ISSN 1877-0509, doi.org/10.1016/j.procs.2023.11.145 | |
| dc.relation.references | Pichawut Manopkawee, Niti Mankhemthon. (2025) Landslide susceptibility assessment using the frequency ratio model in the Mae Chan River watershed, northern Thailand, Quaternary Science Advances, Volume 17, 100263, ISSN 2666-0334, https://doi.org/10.1016/j.qsa.2024.100263 | |
| dc.relation.references | Pollock, Joseph Wartman. (2025). MM 3: Multimodal framework for regional-scale quantitative landslide risk analysis, MethodsX, Volume 14, 103218, ISSN 2215-0161, https://doi.org/10.1016/j.mex.2025.103218 | |
| dc.relation.references | Pourghasemi, H. R., & Rahmati, O. (2018). Investigating the efficiency of statistical and machine-learning models for landslide susceptibility assessment: A case study in Iran. CATENA, 163, 184–197. https://doi.org/10.1016/j.catena.2017.12.029 | |
| dc.relation.references | Pradhan, B., Sameen, M. I., & Lee, S. (2022). Spatial prediction of landslide susceptibility integrating terrain attributes and triggering factors: A global review. Earth-Science Reviews, 231, 104089. https://doi.org/10.1016/j.earscirev.2022.104089 | |
| dc.relation.references | Quanpeng Ji, (2024). Computer graphics processing technology based on GIS model and its application, Systems and Soft Computing, Volume 6, , 200173, ISSN 2772-9419, doi.org/10.1016/j.sasc.2024.200173 | |
| dc.relation.references | Quesada Roman & Sergio Feoli Boraschi. (2018). Comparación de la Metodología Mora-Vahrson y el Método Morfométrico para Determinar Áreas Susceptibles a Deslizamientos en la Microcuenca del Río Macho, Costa Rica, Revista Geográfica de América Central, Volumen 2, Pp. 17-45, http://dx.doi.org/10.15359/rgac.61-2.1 | |
| dc.relation.references | Rani, R., Dahal, A., Berti, M., & Lombardo, L. (2026). Transformer, more than meets the eye: A deep learning approach to integrate rainfall time-series in multi-type landslide probability modelling. Geoscience Frontiers, 17, 102295. https://doi.org/10.1016/j.gsf.2026.102295 | |
| dc.relation.references | Rapolla, A. V. Paoletti, M. Secomandi. (2010). Seismically-induced landslide susceptibility evaluation: Application of a new procedure to the island of Ischia, Campania Region, Southern Italy, Engineering Geology, Volume 114, Issues 1–2, Pages 10-25, ISSN 0013-7952, https://doi.org/10.1016/j.enggeo.2010.03.006 | |
| dc.relation.references | Roberto J. Marin, María Fernanda Velásquez, (2020) Influence of hydraulic properties on physically modelling slope stability and the definition of rainfall thresholds for shallow landslides, Geomorphology, Volume 351, 106976, ISSN 0169-555X, https://doi.org/10.1016/j.geomorph.2019.106976 | |
| dc.relation.references | Rodríguez, J. G., Quintana Cabeza, C. D., Rivera Alarcón, H. U., & Mosquera Téllez, J. (2013). Zonificación del peligro de remoción en masa en las zonas urbanas según método de análisis Mora y Vahrson: estudio de caso. Revista Ambiental Agua, Aire y Suelo, 4(1), 13–22. https://ojs.unipamplona.edu.co/index.php/aaas/es/article/view/2013 | |
| dc.relation.references | Salehpour Jam, A., Mosaffaie, J., & Tabatabaei, M. R. (2023). Raster-based landslide susceptibility mapping using compensatory MADM methods. Environmental Modelling & Software, 159, Article 105567. https://doi.org/10.1016/j.envsoft.2022.105567 | |
| dc.relation.references | Servicio Geológico Colombiano (SGC). (2025). Base de datos de sismicidad histórica y reciente. Periodo 1993–2025. Subdirección de Geología Básica. | |
| dc.relation.references | Servicio Geológico Colombiano. (2013). Metodología de la zonificación de susceptibilidad y amenaza por movimientos en masa escala 1:100.000. https://acortar.link/fwSzDZ | |
| dc.relation.references | Servicio Geológico Colombiano. (2025, septiembre 11). Respuesta al radicado SGC 2025-280-008545-1. Solicitud de información sobre aceleración sísmica PGA (Tr). Dirección de Geoamenazas. Radicado No. 2025-600-010838-2 | |
| dc.relation.references | Shihao Xiao, Limin Zhang, Te Xiao, Ruochen Jiang, Dalei Peng, Wenjun Lu, Xin He, (2024). Landslide Damming Threats Along the Jinsha River, China, Engineering, Volume 42, Pages 326-339, ISSN 2095-8099, https://doi.org/10.1016/j.eng.2024.07.001 | |
| dc.relation.references | Shou, K.-J., & Lin, J.-F. (2020). Evaluation of the extreme rainfall predictions and their impact on landslide susceptibility in a sub-catchment scale. Engineering Geology, 265, 105434. https://doi.org/10.1016/j.enggeo.2019.105434 | |
| dc.relation.references | Sk Asraful Alam, Sujit Mandal, Ramkrishna Maiti, (2025). Geospatial intelligence for landslide susceptibility and risk analysis: Insights from NH31A and east Sikkim Himalaya settlements, Natural Hazards Research, Volume 5, Issue 1, Pages 187-208, ISSN 2666-5921, https://doi.org/10.1016/j.nhres.2024.10.001 | |
| dc.relation.references | Tsedal Mulugeta, Leulalem Shano, Muralitharan Jothimani. (2024). Landslide susceptibility modeling in the Kulfo river catchment, rift valley, Ethiopia: An integrated geospatial and statistical analysis, Quaternary Science Advances, Volume 14, 100191. https://doi.org/10.1016/j.qsa.2024.100191 | |
| dc.relation.references | Utthasini, M., Ilampooranan, I., Singh, S. K., Kanga, S., Kumar, P., Halder, K., Pradhan, B., Srivastava, A. K., Chatterjee, R. S., Chakrabortty, R., Ali, T., & Meraj, G. (2026). Enhancing landslide susceptibility mapping in the Himalayas: Geospatial and machine learning with explainable AI (XAI). Gondwana Research, 149, 262–290. https://doi.org/10.1016/j.gr.2025.08.003 | |
| dc.relation.references | Vipin Chauhan, Laxmi Gupta, Jagabandhu Dixit. (2025) Machine learning and GIS-based multi-hazard risk modeling for Uttarakhand: Integrating seismic, landslide, and flood susceptibility with socioeconomic vulnerability, Environmental and Sustainability Indicators, Volume 26, 2025, 100664, ISSN 2665-9727, https://doi.org/10.1016/j.indic.2025.100664 | |
| dc.relation.references | Vuillez, Marj Tonini, Karen Sudmeier-Rieux, Sanjaya Devkota, Marc-Henri Derron, Michel Jaboyedoff. (2018). Land use changes, landslides and roads in the Phewa Watershed, Western Nepal from 1979 to 2016, Applied Geography, Volume 94, Pages 30-40, ISSN 0143-6228, https://doi.org/10.1016/j.apgeog.2018.03.003 | |
| dc.relation.references | Yafeng Lu, Wenguang Chen, Xiaoqing Chen, Zhengyang Li. (2025) Effects of microclimate on soil moisture distribution in complex topography at the small watershed scale in the Anning River Region, Southwest China, Journal of Hydrology: Regional Studies, Volume 59, 102381, ISSN 2214-5818, https://doi.org/10.1016/j.ejrh.2025.102381 | |
| dc.relation.references | Yan Chong, Guan Chen, Xingmin Meng, Shiqiang Bian, Fengchun Huang, Linxin Lin, Dongxia Yue, Yi Zhang, Fuyun Guo. (2023). Formation mechanism and quantitative risk analysis of the landslide-induced hazard chain by an integrated approach for emergency management: A case study in the Bailong River basin, China, CATENA, Volume 233, , 107522, ISSN 0341-8162, https://doi.org/10.1016/j.catena.2023.107522 | |
| dc.relation.references | Zhao Binru, Dai Qiang, Han Dawei, Dai Huichao, Mao Jingqiao, Zhuo Lu. (2019) Probabilistic thresholds for landslides warning by integrating soil moisture conditions with rainfall thresholds Journal of Hydrology, 574, pp. 276 – 287. https://doi.org/10.1016/j.jhydrol.2019.04.062 | |
| dc.rights | Attribution-NonCommercial-NoDerivs 2.5 Colombia | en |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
| dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | |
| dc.rights.local | Abierto (Texto Completo) | spa |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/2.5/co/ | |
| dc.subject.keyword | Zoning | |
| dc.subject.keyword | Hazards | |
| dc.subject.keyword | Landslides | |
| dc.subject.keyword | Model Mora and Vahrson | |
| dc.subject.keyword | Las Ceibas River | |
| dc.subject.keyword | Watershed | |
| dc.subject.lemb | Gestión de Cuencas Hidrográficas | |
| dc.subject.lemb | Ordenamiento territorial | |
| dc.subject.lemb | Geomorfología | |
| dc.subject.proposal | Zonificación | |
| dc.subject.proposal | Amenazas | |
| dc.subject.proposal | Remoción en Masa | |
| dc.subject.proposal | Modelo Mora y Vahrson | |
| dc.subject.proposal | Cuenca Río Las Ceibas | |
| dc.title | Zonificación de amenazas por remoción en masa usando la metodología de Mora y Vahrson en La Cuenca del Río Las Ceibas: un enfoque comparativo con registros históricos | |
| dc.type | master thesis | |
| dc.type.coar | http://purl.org/coar/resource_type/c_bdcc | |
| dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | |
| dc.type.drive | info:eu-repo/semantics/masterThesis | |
| dc.type.local | Tesis de maestría | spa |
| dc.type.version | info:eu-repo/semantics/acceptedVersion |
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