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Deslizamientos de tierra en Tijuana, México: evaluación de la amenaza en un barrio de la zona urbana

dc.contributor.authorGallardo Amaya, Romel Jesús
dc.contributor.authorAngarita Uscategui, Pedro Nel
dc.contributor.authorOliva González, Aldo Onel
dc.coverage.spatialColombiaen_US
dc.date.accessioned2025-09-30T13:13:30Z
dc.date.available2025-09-30T13:13:30Z
dc.date.issued2023-10-01
dc.identifier.issn0123-921Xen_US
dc.identifier.urihttps://repositorioinstitucional.ufpso.edu.co/xmlui/handle/20.500.14167/5632
dc.description.abstractContexto: Los deslizamientos de tierra en Tijuana, México, provocan cada año la destrucción de una gran cantidad de estructuras e infraestructuras, produciendo cuantiosas pérdidas en diversos sectores de la economía. Método: En este estudio, se realiza una evaluación cuantitativa del peligro de deslizamientos de tierra en un barrio de la ciudad de Tijuana, el cual fue afectado por un deslizamiento en el año 2010 y actualmente presenta indicios de inestabilidad del terreno, alertando sobre la posibilidad de que ocurran nuevos deslizamientos. La amenaza fue calculada utilizando la probabilidad espacial, a partir de la susceptibilidad del terreno a los deslizamientos de tierra, y la probabilidad temporal se calculó utilizando una base de datos de eventos ocurridos en sitios cercanos al área de estudio. Se aplicaron métodos determinísticos basados en el análisis de estabilidad de taludes para calcular la susceptibilidad del terreno y se estimó la probabilidad temporal utilizando modelos de probabilidad que consideran la ocurrencia de eventos aleatorios independientes. Resultados: Se encontró que más del 50 % del área de estudio presenta una alta amenaza de deslizamientos de tierra para períodos de retorno de 5, 10, 15 y 20 años. Se comprobó además que la sismicidad, la topografía y las propiedades geotécnicas de los suelos son los factores que más influyen en la inestabilidad del terreno. Adicionalmente, se determinó que las áreas de potenciales deslizamientos de tierra se encuentran en suelos cuya resistencia se ha reducido debido a la presencia de flujos subterráneos producidos por el movimiento de agua a través de grietas y fracturas existentes en el terreno. Conclusiones: La aplicación del procedimiento descrito permitió cuantificar la amenaza de deslizamientos de tierra en el barrio estudiado para cuatro períodos de retorno. También permitió identificar los factores que más influyen en la ocurrencia de estos fenómenos. Los resultados obtenidos son un paso importante para analizar y evaluar el riesgo que representan los deslizamientos de tierra para las estructuras, infraestructuras y personas expuestas al impacto de estos fenómenos; y son una valiosa herramienta para tomar decisiones relacionadas con la gestión del riesgo y el establecimiento de regulaciones sobre el uso de suelo.en_US
dc.language.isospaen_US
dc.relationhttp://www.scielo.org.co/scielo.php?pid=S0123-921X2023000300070&script=sci_arttexten_US
dc.titleDeslizamientos de tierra en Tijuana, México: evaluación de la amenaza en un barrio de la zona urbanaen_US
dc.title.translatedLandslides in Tijuana, Mexico: hazard assessment in an urban Neighborhooden_US
dc.contributor.cvlacRomel Jesús Gallardo Amaya [0000883590]en_US
dc.contributor.cvlacPedro Nel Angarita Uscategui [0000883670]en_US
dc.contributor.cvlacAldo Onel Oliva González [0001804057]en_US
dc.contributor.googlescholarRomel Jesús Gallardo Amaya [kCbpxb4AAAAJ]en_US
dc.contributor.googlescholarPedro Nel Angarita Uscategui [0000-0002-7260-9523]en_US
dc.contributor.orcidRomel Jesús Gallardo Amaya [0000-0002-4740-4841]en_US
dc.contributor.orcidPedro Nel Angarita Uscategui [0000-0002-7260-9523]en_US
dc.contributor.orcidAldo Onel Oliva González [0000-0001-6119-8602]en_US
dc.contributor.researchgatePedro Nel Angarita Uscategui [Pedro_Angarita3]en_US
dc.contributor.scopusAldo Onel Oliva González [52364748400]en_US
dc.description.abstractenglishContext: Landslides in Tijuana, Mexico, destroy a large number of structures and infrastructures each year, producing large losses in various economic sectors. Method: In this study, we carry out a quantitative assessment of the hazards of landslides in a Tijuana neighborhood that was affected by a landslide in 2010 and currently shows signs of terrain instability, raising concerns about potential future landslides. The hazard assessment was calculated using the spatial probability, based on how susceptible the terrain was to landslides, and the temporal probability using a database of events that occurred at sites near te study area. We apply deterministic methods based on the analysis of slope stability to calculate susceptibility and estimate the temporal probability using probability models that consider the instances of independent random events. Results: It was found that more than 50 % of the studied area presents a high hazard of landslides for return periods of 5, 10, 15, and 20 years. Moreover, findings demonstrated that the seismicity, topography, and the geotechnical characteristics of the soils are the factors with major influence on ground instability. In addition, it was determined that the areas of potential landslides are in soils whose resistance has been reduced due to the presence of underground flows produced by the infiltration of water through existing cracks and fractures in the terrain. Conclusions: The application of the described procedure made it possible to quantify the hazards of landslides in the Laderas de Monterrey neighborhood for four return periods and to determine the factors that most influence the occurrences of these phenomena. The results obtained are an important step to analyze and evaluate the risk that landslides represent for structures, infrastructures, and people exposed to the impact of these phenomena. They are also a valuable tool for making informed decisions regarding risk management and the establishment of regulations on land use.en_US
dc.subject.proposaldeslizamiento de tierraen_US
dc.subject.proposalamenaza de deslizamientosen_US
dc.subject.proposaldeslizamientos urbanosen_US
dc.subject.proposalevaluación de amenazaen_US
dc.subject.keywordslandslidesen_US
dc.subject.keywordslandslide hazarden_US
dc.subject.keywordsurban landslidesen_US
dc.subject.keywordshazard assessmenten_US
dc.publisher.facultyFacultad ingenieríasen_US
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTen_US
dc.relation.referencesAbhirup D., Raju S., Biswajeet P., Ratiranjan J., Dowchu D. and Abdullah M. A. (2020). Tem poral Probability Assessment and Its Use in Landslide Susceptibility Mapping for Eastern Bhutan, Water, 12, 267, http://dx.doi.org/10.3390/w12010267en_US
dc.relation.referencesAcosta-Chang, J. G., Zepeda, G., Ruiz, E. (2009). Microzonificación sísmica de Tijuana, Informe final, CICESE.en_US
dc.relation.referencesBrenning A. (2005). Spatial prediction models for landslide hazards: review, compari son and evaluation, Nat Hazards Earth Syst Sci, 5, 853–862, https://doi.org/10.5194/ nhess-5-853-2005en_US
dc.relation.referencesCatani, F., Lagomarsino, D., Segoni, S., Tofani, V. (2013). Landslide susceptibility estimation by random forests technique: sensitivity and scaling issues, Nat Hazards Earth Syst Sci, 13, 2815–2831, https://doi.org/10.5194/nhess-13-2815-2013en_US
dc.relation.referencesCrovelli, R. A. (2000). Probability models for estimation of number and costs of landslides, (Open File Report 00-249). United States Geological Survey https://doi.org/10.3133/ofr00249en_US
dc.relation.referencesCruz-Castillo, M. (2002). Catálogo de las fallas regionales activas en el norte de Baja California, México, GEOS, Unión Geofísica Mexicana, A.C., 37– 41en_US
dc.relation.referencesCuanalo, O. A., Oliva, A. O., González, C. (2007). Estabilidad de laderas. Análisis mediante factores de valuación, Revista IngeoPres, 164, 38–44.en_US
dc.relation.referencesEscalante T., J.O.; Cáceres J., J.J. y Porras D., H. (2016). Orthomosaics and digital elevation models generated from images taken with UAV systems. Tecnura, 20(50), 119-140. https: //doi.org/10.14483/udistrital.jour.tecnura.2016.4.a09en_US
dc.relation.referencesFell, R., Corominas, J., Bonnard, C., Cascini, L., Leroi, E., Savage, W. (2008). On behalf of the JTC-1 Joint Technical Committee on Landslides and Engineered Slopes, Guidelines for landslide susceptibility, hazard and risk zoning for land-use planning, Engineering Geology, 102, 85-98 and commentary on 99-111, http://dx.doi.org/10.1016/j.enggeo.2008.03.022en_US
dc.relation.referencesGuzzetti, F., Reichenbach, P., Cardinali, M., Galli, M., and Ardizzone, F. (2005). Probabilistic landslide hazard assessment at the basin scale, Geomorphology, 72, 272–299, https://doi. org/10.1016/j.geomorph.2005.06.002en_US
dc.relation.referencesGuzzetti, F., Galli, M., Reichenbach, P., Ardizzone, F., and Cardinali, M. (2006). Landslide ha zard assessment in the Collazzone area, Umbria, Central Italy, Nat. Hazards Earth Syst. Sci., 6, 115–131, https://doi.org/10.5194/nhess-6-115-2006en_US
dc.relation.referencesGuzzetti, F., Mondini, A. C., Cardinali, M., Fiorucci, F., Santangelo, M., and Chang, K.-T. (2012). Landslide inventory maps: New tools for an old problem, Earth-Sci. Rev., 112, 42–66, https: //doi.org/10.1016/j.earscirev.2012.02.001en_US
dc.relation.referencesHungr, O. (1997). Some methods of landslide hazard intensity mapping. In Cruden & Fell (eds) Landslide Risk Assessment, Balkema, 215-226en_US
dc.relation.referencesMalamud, B. D., Turcotte, D. L., Guzzetti, F., and Reichenbach, P. (2004). Landslide inventories and their statistical properties, Earth Surface Processes and Landforms, 29(6), 687–711, https: //doi.org/10.1002/esp.1064en_US
dc.relation.referencesMavrouli, O., Corominas, J., Ibarbia, I., Alonso, N., Jugo, I., Ruiz, J., Luzuriaga, S., and Navarro, J. A. (2019). Integrated risk assessment due to slope instabilities in the roadway network of Gipuzkoa, Basque Country, Nat. Hazards Earth Syst. Sci., 19, 399–419, https://doi.org/ 10.5194/nhess-19-399-2019en_US
dc.relation.referencesNTC. (2017). Normas Técnicas Complementarias de la Ley de Edificaciones del Estado de Baja Califor nia, Seguridad Estructural en materia de Diseño Sísmico, SIDURT, Estado de Baja California, México.en_US
dc.relation.referencesSheng F., Lixia Ch., Tsehaie W., Kunlong Y., Lei G., Deying L., Juan D., Chao Z., Yong X., and Zhipeng L. (2020). Landslide hazard probability and risk assessment at the community level: a case of western Hubei, China, Nat. Hazards Earth Syst. Sci., 20, 581–601, https:// doi.org/10.5194/nhess-20-581-2020en_US
dc.relation.referencesSilva, M.; T. William Lambe, Hon. M.; and W. Allen Marr, F. (2008). Probability and Risk of Slope Failure, Journal of Geotechnical and Geoenvironmental Engineering, 134(12), https://ascelibrary.org/doi/10.1061/%28ASCE%291090-0241%282008%29134% 3A12%281691%29en_US
dc.relation.referencesSLOPE/W. (2012). Stability Modeling with SLOPE/W, An Engineering Methodology, July edition, GEO_SLOPE International.en_US
dc.relation.referencesStark, C. P. and Hovius, N. (2001). The characterization of landslide size distributions, Geophys. Res. Lett., 28(6), 1091–1094, https://doi.org/10.1029/2000GL008527en_US
dc.relation.referencesOliva, A. O., Mascareño, D., Álvarez I. N., González, C. and Álvarez A. E. (2014). Hillside ins tability in the Tijuana metropolitan area. Analysis of landslide-provoked building collap se. Engineering Failure Analysis, 46, 166–178. https://doi.org/10.1016/j.engfailanal.2014. 08.004en_US
dc.relation.referencesOliva G., y Gallardo A., R. J. (2018). Evaluación del Riesgo por Deslizamiento de una Ladera en la Ciudad de Tijuana, Mexico. Revista Tecnura, 22(55), 34-50. https://doi.org/10.14483/ 22487638.12063en_US
dc.relation.referencesOliva-González, A. O., Ruiz-Pozo, A. F., Gallardo-Amaya, R. J. and Jaramillo, H. Y. (2019). Landslide risk assessment in slopes and hillsides. Methodology and application in a real case, DYNA, 86(208), 143 – 152, http://doi.org/10.15446/dyna.v86n208.72341en_US
dc.relation.referencesOliva, A. O., Berumen, M. A., Gallardo, R. J. and Jaramillo, H. Y. (2019). Terrain instability in the Tijuana metropolitan area: Analysis of a failure in the access road to an industrial park, Engineering Failure Analysis, 104, 354-370. https://doi.org/10.1016/j.engfailanal.2019.05. 040en_US
dc.relation.referencesParra Ortega, C. A., Quintana-Cabeza, C., Mosquera-Téllez, J. (2022). Modeling of Mass Mo vement Phenomena to Determine the Depth of Rainfall Infiltration into the Soil. Tecnura, 26(72), 78–102. https://doi.org/10.14483/22487638.17743en_US
dc.relation.referencesReichenbach, P., Rossi, M., Malamud, B.D., Mihir, M., Guzzetti, F. (2018). A review of statis tically based landslide susceptibility models, Earth-Sci. Rev., 180, 60–91, https://doi.org/ 10.1016/j.earscirev.2018.03.001en_US
dc.relation.referencesQiao, S., Qin, S., Chen, J., Hu, X., and Ma, Z. (2019). The Application of a Three-Dimensional Deterministic Model in the Study of Debris Flow Prediction Based on the Rainfall Unstable Soil Coupling Mechanism, Processes, 7, 99, https://doi.org/10.3390/pr7020099en_US
dc.relation.referencesUN-ISDR. (2004). Living with risk: a global review of disaster reduction initiatives. Uni ted Nations Office for Disaster Risk Reduction, https://www.undrr.org/publication/ living-risk-global-review-disaster-reduction-initiativesen_US
dc.relation.referencesVan Westen, C. J., Castellanos, E., and Kuriakose, S. L. (2008). Spatial data for landslide sus ceptibility, hazard, and vulnerability assessment: An overview, Eng. Geol., 102, 112–131, https://doi.org/10.1016/j.enggeo.2008.03.010en_US
dc.relation.referencesVan Westen, C. J., Alkema, D., Damen, M. C. J., Kerle, N., and Kingma, N. C. (2011). Multi hazard risk assessment distance education course, Guide book. United Nations University – ITC School on Disaster Geoinformationen_US
dc.identifier.DOIhttps://doi.org/10.14483/22487638.17882en_US


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