Vol. 35 (2025): Volumen 35
Artículos de Investigación

Impact on urban areas of river flooding associated with extreme precipitation events: a case study of Las Liebres creek in León, Guanajuato

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  • Ismael Orozco Medina,
  • Alexander José Diaz Buelvas,
  • Jesús López de la Cruz ,
  • Joanna Alicia Gutiérrez Pérez
DOI: https://doi.org/10.15174/au.2025.4267

Published 2025-03-26

How to Cite

Orozco Medina, I., Diaz Buelvas, A. J., López de la Cruz , J., & Gutiérrez Pérez , J. A. (2025). Impact on urban areas of river flooding associated with extreme precipitation events: a case study of Las Liebres creek in León, Guanajuato . Acta Universitaria, 35. https://doi.org/10.15174/au.2025.4267

Abstract

Floods are the deadliest natural hazards and cause the most extensive damage each year worldwide. This study focuses on evaluating the impact of riverine floods from the Las Liebres stream using a methodology that combines hydraulic modeling, hydrological modeling, and the projection of extreme precipitation events for different return periods, employing frequency analysis with stationary and non-stationary parameters. The results project maximum precipitation events of up to 110 mm with a return period of 100 years, generating a flow rate of approximately 80 m³/s and flooding 13.2% of the urban area of the basin. These floods affect mobility, critical infrastructure, access to basic services, and emergency response capabilities.

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References

  1. Ahmad, T., Pandey, A. C., & Kumar, A. (2019). Evaluating urban growth and its implication on flood hazard and vulnerability in Srinagar city, Kashmir Valley, using geoinformatics. Arabian Journal of Geosciences, 12(308). https://doi.org/10.1007/s12517-019-4458-1
  2. Amat, J. (2020). GAMLSS: modelos aditivos generalizados para posición, escala y forma. Rpubs.com. https://rpubs.com/Joaquin_AR/603234
  3. Barredo, J. I. (2007). Major flood disasters in Europe: 1950–2005. Natural Hazards, 42, 125–148. https://doi.org/10.1007/s11069-006-9065-2
  4. Bladé, E., Cea, L., Corestein, G., Escolano, E., Puertas, J., Vázquez-Cendón, E., Dolz, J., & Coll, A. (2014). Iber: herramienta de simulación numérica del flujo en ríos. Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, 30(1), 1-10. https://doi.org/10.1016/j.rimni.2012.07.004.
  5. Chen, Z., Yin, L., Chen, X., Wei, S., & Zhu, Z. (2015). Research on the characteristics of urban rainstorm pattern in the humid area of Southern China: a case study of Guangzhou City. International Journal of Climatology, 35, 4370-4386. https://doi.org/10.1002/joc.4294
  6. Centro de Investigaciones sobre la Epidemiología de los Desastres (CRED)-Oficina de las Naciones Unidas para la Reducción del Riesgo de Desastres (UNDRR). (2020). El costo humano de los desastres: una mirada a los úlitmos 20 años 2000-2019. UNDRR. https://agua.org.mx/biblioteca/el-costo-humano-de-los-desastres-una-mirada-a-los-ultimos-20-anos-undrr/
  7. Dharmarathne, G., Waduge, A. O., Bogahawaththa, M., Rathnayake, U., & Meddage, D. P. P. (2024). Adapting cities to the surge: a comprehensive review of climate-induced urban flooding. Results in Engineering, 22, 1-15. https://doi.org/10.1016/j.rineng.2024.102123
  8. Duhan, D., & Pandey, A. (2013). Statistical analysis of long term spatial and temporal trends of precipitation during 1901–2002 at Madhya Pradesh, India. Atmospheric Research, 122, 136-149. https://doi.org/10.1016/j.atmosres.2012.10.010
  9. Guha-Sapir, D., Hoyois, P., Wallemacq, P., & Bellow, R. (2017). Annual disaster statistical review 2016: the numbers and trends. Centre for Research on the Epidemiology of Disasters (CRED) Institute of Health and Society (IRSS) Université catholique de Louvain– Brussels, Belgium. https://reliefweb.int/report/world/annual-disaster-statistical-review-2016-numbers-and-trends
  10. Hammond, M. J., Chen, A. S., Djordjević, S., Butler, D., & Mark, O. (2015). Urban flood impact assessment: a state-of-the-art review. Urban Water Journal, 12, 14–29. https://doi.org/10.1080/1573062X.2013.857421
  11. Hernández, F., Naranjo-Dueñas, G., & Monsalve-Lugo, E. (2017). Estimación del rendimiento de orellana mediante modelos Gamlss. Revista de la Facultad de Ciencias, 6(1), 67-82. https://doi.org/10.15446/rev.fac.cienc.v6n1.61119
  12. Huang, X., Swain, D. L., & Hall, A. D. (2020). Future precipitation increase from very high resolution ensemble downscaling of extreme atmospheric river storms in California. Science Advances, 6(29), 1-16. https://doi.org/10.1126/sciadv.aba1323
  13. Ionita, M., & Nagavciuc, V. (2021). Extreme floods in the eastern part of Europe: large-scale drivers and associated impacts. Water, 13(8), 1122. https://doi.org/10.3390/w13081122
  14. Jonkman, S. N., & Kelman, I. (2005). An analysis of the causes and circumstances of flood disaster deaths. Disasters, 29(1), 75–97. https://doi.org/10.1111/j.0361-3666.2005.00275.x
  15. Kreibich, H., Bubeck, P., Kunz, M., Mahlke, H., Parolai, S., Khazai, B., Daniell, J., Lakes, T., & Schröter, K. (2014). A review of multiple natural hazards and risks in Germany, Natural Hazards, 74, 2279–2304. https://doi.org/10.1007/s11069-014-1265-6
  16. Kumar, N., Kumar, M., Sherring, A., Suryavanshi, S., Ahmad, A., & LaI, D. (2020). Applicability of HEC-RAS 2D and GFMS for flood extent mapping: a case study of Sangam area, Prayagraj, India. Modeling Earth Systems Environment, 6, 397-405. https://doi.org/10.1007/s40808-019-00687-8
  17. Kundzewicz, Z. W., Kanae, S., Seneviratne, S. I., Handmer, J., Nicholls, N., Peduzzi, P., Mechler, R., Bouwer, L. M., Arnell, N., Mach, K., Muir-Wood, R., Brakenridge, G. R., Kron, W., Benito, G., Honda, Y., Takahashi, K., & Sherstyukov, B. (2013). Flood risk and climate change: global and regional perspectives. Hydrological Sciences Journal, 59(1), 1–28. https://doi.org/10.1080/02626667.2013.857411
  18. López, M., Magaña, V., & Perez, T. (2022). Riesgo de inundaciones urbanas repentinas en la zona Metropolitana de Guadalajara, México. Investigaciones Geográficas, (108), 1-21. https://doi.org/10.14350/rig.60547
  19. Louise, R., Kharb, A., & Tubeuf, S. (2023). The untold story of missing data in disaster research: a systematic review of the empirical literature utilising the Emergency Events Database (EM-DAT). Environmental Research Letters, 18(10), 103006, 1-10. https://doi.org/10.1088/1748-9326/acfd42
  20. Marco, J. B., & Cayuela, A. (1994). Urban flooding: the flood-planned city concept. En G. Rossi, N. Harmancioğlu, & V. Yevjevich, (eds.), Coping with floods (pp. 705-715). Springer. https://doi.org/10.1007/978-94-011-1098-3_43
  21. Matías, L. G., & Ramírez, N. D. (2022). Catálogo de inundaciones 2021. Subdirección de Riesgos por Inundación Dirección de Investigación. https://www1.cenapred.unam.mx/DIR_INVESTIGACION/2022/XLI/RI/220221_RIAct23_Catalogoinundaciones2021.pdf
  22. Merlos, F. (2017). Manual de usuario SIHIMAX 1.56. https://www.hydrobits.com/programas/manuales.html
  23. Organización de las Naciones Unidas (ONU). (2020). América Latina y el Caribe: la segunda región más propensa a los desastres. https://news.un.org/es/story/2020/01/1467501
  24. Organización de las Naciones Unidas (ONU). (2024). Las inundaciones en Brasil afectan a más de 1,7 millones de personas. https://news.un.org/es/story/2024/05/1529696
  25. Pendergrass, A. G., & Hartmann, D. L. (2014). Changes in the distribution of rain frequency and intensity in response to global warming. Journal of Climate, 27(22), 8372–8383. https://doi.org/10.1175/jcli-d-14-00183.1
  26. Pfahl, S., O'Gorman, P. A., & Fischer, E. M. (2017). Understanding the regional pattern of projected future changes in extreme precipitation. Nature Climate Change, 7(6), 423–427. https://doi.org/10.1038/nclimate3287
  27. Ramly, S., & Tahir, W. (2016). Application of HEC-GeoHMS and HEC-HMS as rainfall–runoff model for flood simulation. En W. Tahir, P. Abu Bakar, M. Wahid, S. Mohd Nasir, & W. Lee (eds.), ISFRAM 2015 (pp. 181-192). Springer. https://doi.org/10.1007/978-981-10-0500-8_15
  28. Schär, C., Ban, N., Fischer, E. M., Rajczak, J., Schmidli, J., Frei, C., Giorgi, F., Karl, T. R., Kendon, E. J., Klein, A. M. G., O’Gorman, P. A., Sillmann, J., Zhang, X., & Zwiers, F. W. (2016). Percentile indices for assessing changes in heavy precipitation events. Climatic Change, 137, 201–216. https://doi.org/10.1007/s10584-016-1669-2
  29. Singh, S. K., Pandey, A. C., & Nathawat, M. S. (2011). Rainfall variability and spatio temporal dynamics of flood inundation during the 2008 Kosi Flood in Bihar State, India. Asian Journal of Earth Sciences, 4(1), 9-19. https://doi.org/10.3923/ajes.2011.9.19
  30. Stedinger, J. R., Vogel, R. M., & Foufoula-Georgiou, E. (1993). Frequency analysis of extreme events. En D. R. Maidment (ed.), Handbook of hydrology (pp. 1-66). McGraw-Hill Inc. https://sites.tufts.edu/richardvogel/files/2019/04/frequencyAnalysis.pdf
  31. Visser, J. B., Wasko, C., Sharma, A., & Nathan, R. (2023). Changing storm temporal patterns with increasing temperatures across Australia. Journal of Climate, 36(18), 6247-6259. https://doi.org/10.1175/JCLI-D-22-0694.1
  32. World Meteorological Organization (WMO). (2007). Economic aspects of integrated flood management. https://www.floodmanagement.info/publications/policy/ifm_economic_aspects/Economic_Aspects_of_IFM_En.pdf
  33. World Meteorological Organization (WMO). (2021). 2021 state of climate services water. https://library.wmo.int/records/item/57630-2021-state-of-climate-services-water?offset=2
  34. Zand, M., Gholamrezaei, S., Daryabari, S. J., & Alijani, B. (2023). Detection of climate change by analyzing the occurrence of Extreme-climatic events in the west and southwest of Iran. Journal of Climate Research, 14(54), 37-54. https://clima.irimo.ir/article_172643.html?lang=en

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