Precipitation Patterns Associated with Monthly Mean Discharge Extremes in Corrientes Province (Argentina)

Authors

  • Pedro Blanco Centro de Investigaciones del Mar y la Atmósfera (CIMA) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad de Buenos Aires (UBA)

DOI:

https://doi.org/10.30972/geo.21427655

Keywords:

Streamflow, Gauging stations, Paraná River, ERA5, Excesses and deficits

Abstract

Precipitation patterns associated with monthly mean discharge extremes in the main rivers of Corrientes Province, Argentina (1980-2022), were characterized. Monthly mean discharge data from six gauging stations were used to identify cases where the monthly mean discharge was below the 5th percentile (P05) or above the 95th percentile (P95), defining the extremes based on the “peaks over threshold” criterion. These extremes were classified by their geographical extent as localized, intermediate, and generalized extremes. Using monthly precipitation data from the ERA5 Reanalysis, anomaly fields were calculated, and similar patterns were grouped with the k-means algorithm. Four precipitation patterns were identified for localized extremes, three for intermediate extremes, and two for generalized extremes. Discharges below P05 are associated with negative precipitation anomalies, while discharges above P95 are linked to positive anomalies. However, this relationship is not linear due to local factors.

References

Abbas, O. A. (2008). Comparisons between data clustering algorithms. The International Arab Journal of Information Technology, 5(3), 320-325. https://iajit.org/portal/PDF/vol.5,no.3/15-191.pdf

Arshad, M., Ma, X., Yin, J., Ullah, W., Liu, M. y Ullah, I. (2021). Performance evaluation of ERA-5, JRA-55, MERRA-2, and CFS-2 reanalysis datasets, over diverse climate regions of Pakistan. Weather and Climate Extremes, 33(100373). https://doi.org/10.1016/j.wace.2021.100373

Asadieh, B. y Krakauer, N. Y. (2017). Global change in streamflow extremes under climate change over the 21st century. Hydrology and Earth System Sciences, 21(11), 5863-5874. https://doi.org/10.5194/hess-21-5863-2017

Ashraf, M. S., Ahmad, I., Khan, N. M., Zhang, F., Bilal, A. y Guo, J. (2021). Streamflow variations in monthly, seasonal, annual and extreme values using Mann-Kendall, Spearmen’s Rho and innovative trend analysis. Water Resources Management, 35, 243-261. https://doi.org/10.1007/s11269-020-02723-0

Bačová-Mitková, V. y Onderka, M. (2010). Analysis of extreme hydrological events on the Danube using the peak over threshold method. Journal of Hydrology and Hydromechanics, 58(2), 88-101. https://doi.org/10.2478/v10098-010-0009-x

Baeza Sanz, D., Martínez-Capel, F. y García de Jalón Lastra, D. (2003). Variabilidad temporal de caudales: aplicación a la gestión de ríos regulados. Ingeniería del agua, 10(4), 469-478. https://doi.org/10.4995/ia.2003.2590

Barros, V. y Camilloni, I. (2020). La Argentina y el cambio climático: de la física a la política. EUDEBA.

Bezak, N., Brilly, M. y Šraj, M. (2014). Comparison between the peaks-over-threshold method and the annual maximum method for flood frequency analysis. Hydrological Sciences Journal, 59(5), 959-977. https://doi.org/10.1080/02626667.2013.831174

Blanco, P. S. (2022). Estacionalidad del Río Paraná a la altura de Corrientes-Argentina durante eventos de bajantes históricas (1910-2021). Investigaciones y ensayos geográficos, (19), 13-30. http://hdl.handle.net/11336/214806

Bruniard, E. (1992). Hidrografía. Procesos y tipos de escurrimiento superficial. CEYNE.

Camilloni, I., Barro, V., Moreiras, S., Poveda, G. y Tomasella, J. (2020). Inundaciones y sequías. En: J. Moreno, C. Laguna-Defior, V. Barros, E. Calvo Buendía, J. Marengo, y U. Oswald Spring (Eds.), Adaptación frente a los riesgos del cambio climático en los países iberoamericanos (pp. 391-417). McGraw-Hill.

Capitanelli, R. (1992). Los ambientes naturales del territorio argentino. Un sistema basado en la diversidad. En J. A. Roccatagliata (Ed.), La Argentina: Geografía General y los marcos regionales (pp. 63-120). Planeta.

Carril, A., Cavalcanti, I., Menendez, C., Sörensson, A., López-Franca, N., Rivera, J., Robledo, F., Zaninelli, P., Ambrizzi, T., Penalba, O., da Rocha, R., Sanchez, E., Bettolli, M., Pessacg, N., Renom, M., Ruscica, R., Solman, S., Tencer, B., Grimm, A., ... Zamboni, L. (2016). Extreme events in the La Plata basin: a retrospective analysis of what we have learned during CLARIS-LPB project. Climate Research, 68(2-3), 95-116. http://dx.doi.org/10.3354/cr01374

Carvalho, M. J., Melo-Gonçalves, P., Teixeira, J. C. y Rocha, A. (2016). Regionalization of Europe based on a k-means Cluster Analysis of the climate change of temperatures and precipitation. Physics and Chemistry of the Earth, 94, 22-28. https://doi.org/10.1016/j.pce.2016.05.001

Chauluka, F., Singh, S., y Kumar, R. (2021). Rainfall and streamflow trends of thuchila river, southern Malawi. Materials Today: Proceedings, 34, 846-855. https://doi.org/10.1016/j.matpr.2020.06.228

Clarke, R. (2006). Análisis estadístico de eventos extremos en un contexto no estacionario. En: V. Barros, R. Clarke, y P. Silva Dias (Eds.), El cambio climático en la Cuenca del Plata (pp. 209-226). Centro de Investigaciones del Mar y la Atmósfera, CONICET.

Cui, M. (2020). Introduction to the k-means clustering algorithm based on the elbow method. Accounting, Auditing and Finance, 1(1), 5-8. https://www.clausiuspress.com/article/592.html

D’Silva, J. y Sharma, U. (2020). Unsupervised automatic text summarization of Konkani texts using K-means with Elbow method. International Journal of Engineering Research and Technolog, 13(9), 2380-2384. https://dx.doi.org/10.37624/IJERT/13.9.2020.2380-2384

da Silva, C. L. F., da Silva, D. D., Moreira, M. C., Rodrigues, J. M., de Sousa Rocha, I. S., Lima, R. P. C., y Calegario, A. T. (2023). Trend analysis and identification of possible periods of change in the occurrence of extreme streamflow events in a tropical basin. Journal of South American Earth Sciences, 128(104485). https://doi.org/10.1016/j.jsames.2023.104485

Deka, P. y Saha, U. (2023). Introduction of k-means clustering into random cascade model for disaggregation of rainfall from daily to 1-hour resolution with improved preservation of extreme rainfall. Journal of Hydrology, 620(129478). https://doi.org/10.1016/j.jhydrol.2023.129478

Dethier, E., Sartain, S., Renshaw, C. y Magilligan, F. (2020). Spatially coherent regional changes in seasonal extreme streamflow events in the United States and Canada since 1950. Science advances, 6(49). https://doi.org/10.1126/sciadv.aba5939

Díaz, E., García, M., Rodríguez, A., Dölling, O., Ochoa, S. y Bertoni, J. (2018). Temporal evolution of hydrological drought in Argentina and its relationship with macroclimatic indicators. Tecnología y ciencias del agua, 9(5), 1-32. https://revistatyca.org.mx/index.php/tyca/article/view/1973/1413

Fabre, M., Ojeda, A. y Tena, M. (2008). El río Guadalaviar: su comportamiento hidrológico. REHALDA, (7), 37-52. https://dialnet.unirioja.es/servlet/articulo?codigo=2602973

Far, S. S. y Wahab, A. K. A. (2016). Evaluation of peaks-over-threshold method. Ocean Science Discussions, 47, 1-25. https://doi.org/10.5194/os-2016-47

Gao, L., Tao, B., Miao, Y., Zhang, L., Song, X., Ren, W., He, L. y Xu, X. (2019). A global data set for economic losses of extreme hydrological events during 1960‐2014. Water Resources Research, 55(6), 5165-5175. https://doi.org/10.1029/2019WR025135

Guimberteau, M., Ronchail, J., Espinoza, J., Lengaigne, M., Sultan, B., Polcher, J., Drapeau, G., Guyot, J. L., Ducharne, A. y Ciais, P. (2013). Future changes in precipitation and impacts on extreme streamflow over Amazonian sub-basins. Environmental Research Letters, 8(1), 1-13. https://doi.org/10.1088/1748-9326/8/1/014035

Gomes, M., de Albuquerque Cavalcanti, I. F., y Müller, G. V. (2021). 2019/2020 drought impacts on South America and atmospheric and oceanic influences. Weather and Climate Extremes, 34(100404). https://doi.org/10.1016/j.wace.2021.100404

Gómez, C. (2020). Las represas internacionales y su influencia en la dinámica temporal del curso medio del Río Paraná. Párrafos Geográficos, 19(1), 89-99. https://www.revistas.unp.edu.ar/index.php/parrafosgeograficos/issue/view/54

Intergovernmental Panel on Climate Change [IPCC]. (2021). Summary for Policymakers. En: V. Masson-Delmotte, P. Zhai, A. Pirani, S. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. Matthews, T. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (Eds.), Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 3-32). Cambridge, Reino Unido y New York, Estados Unidos: Cambridge University Press. https://doi.org/10.1017/9781009157896.001

Liu, M., Ma, X., Yin, Y., Zhang, Z., Yin, J., Ullah, I. y Arshad, M. (2021). Non‐stationary frequency analysis of extreme streamflow disturbance in a typical ecological function reserve of China under a changing climate. Ecohydrology, 14(7). https://doi.org/10.1002/eco.2323

Lozada, J., García, C., Herrero, H., Barchiesi, G., Romagnoli, M., Portapila, M., López, F., Castelló, E., Cossavella, A. y Brarda, J. P. (2015). Cuantificación del escurrimiento superficial de la cuenca del Río Carcarañá. Revista de la Facultad de Ciencias Exactas, Físicas y Naturales, 2(1), 59-72. https://revistas.unc.edu.ar/index.php/FCEFyN/article/view/9232

Mahto, S. S. y Mishra, V. (2019). Does ERA‐5 outperform other reanalysis products for hydrologic applications in India? Journal of Geophysical Research: Atmospheres, 124(16), 9423-9441. https://doi.org/10.1029/2019JD031155

Marengo, J. A., Menéndez, A., Guetter, A., Hogue, T. y Mechoso, C. R. (2006). Eventos Hidrometeorológicos Extremos. Caracterización y Evaluación de Métodos de Predicción de Eventos Extremos de Clima y de la Hidrología en la Cuenca del Plata. Revista de Gestão de Água da América Latina, 3(2), 83-95. https://abrh.s3-sa-east-1.amazonaws.com/Sumarios/68/2fec10c7c34f3142d88dcb5f4a0e178d_4ff96015c3b2b75e379f7f904c05f159.pdf

Marianetti, G., Hinrichs, S. y Rivera, J. (2018). Cuando el río suena: análisis de los períodos de caudales extremos en los ríos de los Andes centrales de Argentina. Investigación, Ciencia y Universidad, 2(3), 195-197. https://ri.conicet.gov.ar/handle/11336/94881

Meis, M. y Llano, M. P. (2019). Hydrostatistical study of the Paraná and Uruguay Rivers. International Journal of River Basin Management, 17(1), 1-12. http://doi.org/10.1080/15715124.2018.1446962

Meresa, H., Tischbein, B., Mendela, J., Demoz, R., Abreha, T., Weldemichael, M. y Ogbu, K. (2022). The role of input and hydrological parameters uncertainties in extreme hydrological simulations. Natural Resource Modeling, 35(1). https://doi.org/10.1111/nrm.12320

Merz, B., Blöschl, G., Vorogushyn, S., Dottori, F., Aerts, J. C., Bates, P., Bertola, M., Kemter, M., Kreibich, H., Lall, U. y Macdonald, E. (2021). Causes, impacts and patterns of disastrous river floods. Nature Reviews Earth & Environment, 2(9), 592-609. https://doi.org/10.1038/s43017-021-00195-3

Naumann, G., Podestá, G., Marengo, J., Luterbacher, J., Bavera, D., Arias Muñoz, C., Barbosa, P., Cammalleri, C., Chamorro, L., Cuartas, L., De Jager, A., Escobar, C., Hidalgo, C., Leal De Moraes, O., Mccormick, N., Maetens, W., Magni, D., Masante, D., Mazzeschi, M., ... Toreti, A. (2022). The 2019-2021 extreme drought episode in La Plata Basin. Publications Office of the European Union. https://doi.org/10.2760/773

Oliveira, D. H. M. C., Lima, K. C. y Spyrides, M. H. C. (2021). Rainfall and streamflow extreme events in the São Francisco hydrographic region. International Journal of Climatology, 41(2), 1279-1291. https://doi.org/10.1002/joc.6807

Permadi, V., Tahalea, S. y Agusdin, R. (2023). K-Means and Elbow Method for Cluster Analysis of Elementary School Data. Progres Pendidikan, 4(1), 50-57. https://doi.org/10.29303/prospek.v4i1.328

Pike, M. y Lintner, B. R. (2020). Application of clustering algorithms to TRMM precipitation over the tropical and South Pacific Ocean. Journal of Climate, 33(13), 5767-5785. https://doi.org/10.1175/JCLI-D-19-0537.1

Pyszczek, O. L. (2016). Condiciones atmosféricas y clasificación climática del espacio geográfico correntino. En F. I. Contreras y M. P. Odriozola (Comps.), III Libro de la Junta de Geografía de la Provincia de Corrientes (pp. 6-17). Junta de Geografía de la Provincia de Corrientes.

Reshmidevi, T., Kumar, D., Mehrotra, R. y Sharma, A. (2018). Estimation of the climate change impact on a catchment water balance using an ensemble of GCMs. Journal of Hydrology, 556, 1192-1204. https://doi.org/10.1016/j.jhydrol.2017.02.016

Rivera, J. y Penalba, O. (2018). Spatio-temporal assessment of streamflow droughts over Southern South America: 1961-2006. Theoretical and applied climatology, 133(3), 1021-1033. http://dx.doi.org/10.1007/s00704-017-2243-1

Sistema Nacional de Información Hídrica [SNIH]. (2023). Sistema Nacional de Información Hídrica [Base de datos]. Secretaría de Infraestructura y Políticas Hídricas, Ministerio de Obras Públicas de la Nación. http://snih.hidricosargentina.gob.ar/

van Kempen, G., van der Wiel, K. y Melsen, L. (2021). The impact of hydrological model structure on the simulation of extreme runoff events. Natural Hazards and Earth System Sciences, 21(3), 961-976. https://doi.org/10.5194/nhess-21-961-2021

Vincenti, R. D. (2004). La incidencia de los factores litológicos en el escurrimiento fluvial. Revista Geográfica, 63-78. https://www.jstor.org/stable/40996679

Vincenti, R. D. (2015). Simetrías y asimetrías en el escurrimiento fluvial superficial encauzado en las provincias de Chaco y Corrientes, según sus características fisiográficas. Investigaciones y ensayos geográficos, (12), 40-55. http://repositorio.unne.edu.ar/handle/123456789/51144

Vich, A., Norte, F. y Lauro, C. (2014). Análisis regional de frecuencias de caudales de ríos pertenecientes a cuencas con nacientes en la Cordillera de los Andes. Meteorológica, 39(1), 3-26. http://www.scielo.org.ar/scielo.php? script=sci_arttext&pid=S1850-468X2014000100001

Wang, W., Chen, X., Shi, P. y Van Gelder, P. (2008). Detecting changes in extreme precipitation and extreme streamflow in the Dongjiang River Basin in southern China. Hydrology and Earth System Sciences, 12(1), 207-221. https://doi.org/10.5194/hess-12-207-2008

Zhang, L., Liu, Y., Zhan, H., Jin, M. y Liang, X. (2021). Influence of solar activity and EI Niño-Southern Oscillation on precipitation extremes, streamflow variability and flooding events in an arid-semiarid region of China. Journal of Hydrology, 601, 126630. https://doi.org/10.1016/j.jhydrol.2021.126630

Zucarelli, G. (2013). Identificación de eventos hídricos extremos en la cuenca del río Paraná. Tecnología y ciencias del agua, 4(5), 181-187. https://www.scielo.org.mx/scielo.php? script=sci_arttext&pid=S2007-24222013000500012

Published

2024-12-30

How to Cite

Blanco, P. (2024). Precipitation Patterns Associated with Monthly Mean Discharge Extremes in Corrientes Province (Argentina). Geográfica Digital, 21(42), 133–156. https://doi.org/10.30972/geo.21427655