Articles | Volume 23, issue 5
https://doi.org/10.5194/hess-23-2379-2019
https://doi.org/10.5194/hess-23-2379-2019
Research article
 | 
16 May 2019
Research article |  | 16 May 2019

Contribution of low-frequency climatic–oceanic oscillations to streamflow variability in small, coastal rivers of the Sierra Nevada de Santa Marta (Colombia)

Juan Camilo Restrepo, Aldemar Higgins, Jaime Escobar, Silvio Ospino, and Natalia Hoyos

Related authors

Tsunami hazard assessment in the southern Colombian Pacific basin and a proposal to regenerate a previous barrier island as protection
L. J. Otero, J. C. Restrepo, and M. Gonzalez
Nat. Hazards Earth Syst. Sci., 14, 1155–1168, https://doi.org/10.5194/nhess-14-1155-2014,https://doi.org/10.5194/nhess-14-1155-2014, 2014
Cold fronts in the Colombian Caribbean Sea and their relationship to extreme wave events
J. C. Ortiz-Royero, L. J. Otero, J. C. Restrepo, J. Ruiz, and M. Cadena
Nat. Hazards Earth Syst. Sci., 13, 2797–2804, https://doi.org/10.5194/nhess-13-2797-2013,https://doi.org/10.5194/nhess-13-2797-2013, 2013

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Stochastic approaches
Towards a conceptualization of the hydrological processes behind changes of young water fraction with elevation: a focus on mountainous alpine catchments
Alessio Gentile, Davide Canone, Natalie Ceperley, Davide Gisolo, Maurizio Previati, Giulia Zuecco, Bettina Schaefli, and Stefano Ferraris
Hydrol. Earth Syst. Sci., 27, 2301–2323, https://doi.org/10.5194/hess-27-2301-2023,https://doi.org/10.5194/hess-27-2301-2023, 2023
Short summary
A mixed distribution approach for low-flow frequency analysis – Part 2: Comparative assessment of a mixed probability vs. copula-based dependence framework
Gregor Laaha
Hydrol. Earth Syst. Sci., 27, 2019–2034, https://doi.org/10.5194/hess-27-2019-2023,https://doi.org/10.5194/hess-27-2019-2023, 2023
Short summary
A mixed distribution approach for low-flow frequency analysis – Part 1: Concept, performance, and effect of seasonality
Gregor Laaha
Hydrol. Earth Syst. Sci., 27, 689–701, https://doi.org/10.5194/hess-27-689-2023,https://doi.org/10.5194/hess-27-689-2023, 2023
Short summary
Significant regime shifts in historical water yield in the Upper Brahmaputra River basin
Hao Li, Baoying Shan, Liu Liu, Lei Wang, Akash Koppa, Feng Zhong, Dongfeng Li, Xuanxuan Wang, Wenfeng Liu, Xiuping Li, and Zongxue Xu
Hydrol. Earth Syst. Sci., 26, 6399–6412, https://doi.org/10.5194/hess-26-6399-2022,https://doi.org/10.5194/hess-26-6399-2022, 2022
Short summary
A geostatistical spatially varying coefficient model for mean annual runoff that incorporates process-based simulations and short records
Thea Roksvåg, Ingelin Steinsland, and Kolbjørn Engeland
Hydrol. Earth Syst. Sci., 26, 5391–5410, https://doi.org/10.5194/hess-26-5391-2022,https://doi.org/10.5194/hess-26-5391-2022, 2022
Short summary

Cited articles

Amarasekera, K., Lee, R., Williams, E., and Elthair, E.: ENSO and the natural variability in the flow of tropical rivers, J. Hydrol., 200, 24–39, https://doi.org/10.1016/S0022-1694(96)03340-9, 1997. 
Arias, P., Martínez, A., and Vieira, S.: Moisture sources to the 2010–2012 anomalous wet season in northern South America, Clim. Dynam., 45, 2861–2884, https://doi.org/10.1007/s00382-015-2511-7, 2015. 
Barnhart, B. L.: The Hilbert-Huang transform: theory, applications, development, PhD Thesis Dissertation, IOWA University, Iowa, p. 102, 2011. 
Battisti, D. and Sarachick, B.: Understanding and predicting ENSO, Rev. Geophys., 33, 1367–1376, https://doi.org/10.1029/95RG00933, 1995. 
Bernal, G., Poveda, G., Roldan, P., and Andrade, C.: Patrones de variabilidad de las temperaturas superficiales del mar en la costa Caribe colombiana, Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 30, 195–208, 2006. 
Download
Short summary
This study evaluated the influence of low-frequency oscillations that are linked to large-scale oceanographic–atmospheric processes, on streamflow variability in small mountain rivers of the Sierra Nevada de Santa Marta, Colombia, aiming to explore streamflow variability, estimate the net contribution to the energy of low-frequency oscillations to streamflow anomalies, and analyze the linkages between streamflow anomalies and large-scale, low-frequency oceanographic–atmospheric processes.