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

Abstract

Abstract. This study evaluated the influence of low-frequency oscillations, that are linked to large-scale oceanographic–atmospheric processes, on streamflow variability in small tropical coastal mountain rivers of the Sierra Nevada de Santa Marta, Colombia. We used data from six rivers that had > 32 years of complete, continuous monthly streamflow records. This investigation employed spectral analyses to (1) explore temporal characteristics of streamflow variability, (2) estimate the net contribution to the energy spectrum of low-frequency oscillations to streamflow anomalies, and (3) analyze the linkages between streamflow anomalies and large-scale, low-frequency oceanographic–atmospheric processes. Wavelet analyses indicate that the 8–12-year component exhibited a quasi-stationary state, with a peak of maximum power between 1985 and 2005. These oscillations were nearly in phase in all rivers. Maximum power peaks occurred for the Palomino and Rancheria rivers in 1985 and 1995, respectively. The wavelet spectrum highlights a change in river variability patterns between 1995 and 2015, characterized by a shift towards the low-frequency oscillations' domain (8–12 years). The net contribution of these oscillations to the energy spectrum was as high as 51 %, a value much larger than previously thought for rivers in northwestern South America. The simultaneous occurrence of hydrologic oscillations, as well as the increase in the amplitude of the 8–12-year band, defined periods of extremely anomalous wet seasons during 1989–1990, 1998–2002 and 2010–2011, reflecting the role of low-frequency oscillations in modulating streamflow variability in these rivers. Cross-wavelet transform and wavelet coherence revealed high common powers and significant coherences in low-frequency bands (>96 months) between streamflow anomalies and Atlantic Meridional Oscillation (AMO), Pacific Decadal Oscillation (PDO) and the Tropical North Atlantic Index (TNA). These results show the role of large-scale, low-frequency oceanographic–climate processes in modulating the long-term hydrological variability of these rivers.

Wavelet coherence between ENSO indices and two precipitation database for the Andes region of Colombia

“…Continuous wavelet transform (WT) is a method to analyze the frequency and phase variations across time in a signal at several scales simultaneously (Torrence and Compo, 2011;Massei and Fournier, 2012;Schulte et al, 2016;Restrepo et al, 2019). The transform is defined as the convolution of the time series x t with a set of "daughter" wavelets Ψ (t -τ/s) which are generated by the "mother" wavelet Ψ(t) by translation in time by τ and scaling by s:…”

“…Carmona and Poveda (2012 and explored FT, WC, and HHT to detect principal modes of hydroclimatic variability in Colombia; they also identified links between ENSO and precipitation, temperature, and river discharge. More recently, Restrepo et al (2019) implemented HHT and WT to identify the contribution of low-frequency climatic-oceanic oscillations to streamflow variability in coastal rivers of the Sierra Nevada de Santa Marta (Colombia). All these studies have detected evidence of the ENSO-precipitation relation; however, they have also established that ENSO teleconnections have substantial heterogeneity at different spatio-temporal scales over Colombia.…”

“…All of them co-occur and mutually influence one another, generating moisture advection anomalies during ENSO phases that are different for each region of the country (Poveda et al, 1997, Salas et al, 2020. Therefore, there is still a need to carry out studies to determine local ENSO influences in more detail (Sun et al, 2017;Restrepo et al, 2019).…”

“…Another method used to assess links between large-scale climate oscillations and local climate variability is coherence analysis (CA). CA applied the idea of time-varying coherence using time-frequency analysis methods like FT, HHT, or WT (Torrence and Compo, 2011;Massei and Fournier, 2012;Schulte et al, 2016;Restrepo et al, 2019). The Wavelet-based coherence (WC) and the HHT coherence (HHTC) are the most widely used time-varying coherence methods (Restrepo et al, 2019).…”

“…CA applied the idea of time-varying coherence using time-frequency analysis methods like FT, HHT, or WT (Torrence and Compo, 2011;Massei and Fournier, 2012;Schulte et al, 2016;Restrepo et al, 2019). The Wavelet-based coherence (WC) and the HHT coherence (HHTC) are the most widely used time-varying coherence methods (Restrepo et al, 2019). WC was selected because previous results have shown that even though HHTC has higher time resolution and frequency resolution than WC under ideal conditions, the WC is more stable; further, it has been implemented and explored for climate teleconnection analysis with a proven performance (Zhang et al, 2004;Ouachani et al, 2013;Araghi et al, 2016;Nalley et al, 2016;Schulte et al, 2016, Restrepo et al, 2019.…”