Streamflow Variability in Colombian Pacific Basins and Their Teleconnections with Climate Indices

Abstract

Oceanic-atmospheric phenomena of different time scales concurrently might affect the streamflow in several basins around the world. The Atrato River Basin (ARB) and Patía River Basin (PRB) of the Colombian Pacific region are examples of such basins. Nevertheless, the relations between the streamflows in the ARB and PRB and the oceanic-atmospheric factors have not been examined considering different temporal scales. Hence, this article studies the relations of the climate indices and the variability of the streamflows in the ARB and PRB at interannual and decadal timescales. To this, the streamflow variability modes were obtained from the principal component analysis (PCA); furthermore, their linear dependence with indices of the El Niño/Southern Oscillation (ENSO), precipitation (PRP), the Choco low-level jet (CJ), and other indices were quantified through (a) Pearson and Kendall’s tau correlations, and (b) wavelet transform. The PCA presented a single significant mode for each basin, with an explained variance of around 80%. The correlation analyses between the PC1s of the ARB and PRB, and the climate indices showed significant positive (negative) high correlations with PRP, CJ, and Southern Oscillation Index (SOI) (ENSO indices). The wavelet coherence analysis showed significant coherencies between ENSO and ARB: at interannual (2–7 years) and decadal scale (8–14), preferably with the sea surface temperature (SST) in the east and west Tropical Pacific Ocean (TPO). For PRB with the SST in the central and western regions of the TPO in the interannual (4–8 years) and decadal (8–14 years) scales, the decreases (increases) in streamflow precede the El Niño (La Niña) events. These results indicate multiscale relations between the basins’ streamflow and climate phenomena not documented in previous works, relevant to forecast the extreme flow events in the Colombian Pacific rivers and for planning and implementing strategies for the sustainable use of water resources in the basins studied.

Monthly Rainfall Anomalies Forecasting for Southwestern Colombia Using Artificial Neural Networks Approaches

“…They showed an increase (decrease) in the rainfall values linked to negative (positive) anomalies of the SST in the central region of the Tropical Pacific Ocean. Regarding the persistence of the influence of the ENSO indices on the rainfall, the results are consistent with those of Navarro et al [65] and Canchala et al [34]. They reported a persistent lagged influence of up 9 and 10 months, mainly with the SST in the central region of the Tropical Pacific Ocean.…”

“…Eight large-scale climate indices linked to the SST in the Tropical Pacific Ocean and ENSO phenomenon were used as exogenous variables (predictor variables). Several studies performed in Western Colombia evidenced that its hydroclimatology has high concurrent or lagged correlations with these large-scale climate indices [24][25][26][27][28]30,31,[33][34][35]41,42]. Therefore, we use regional Sea Surface Temperatures (SSTs): SST1+2 (0°-10° S, 90°-80° W), SST3 (5° S-5° N, 90°-150° W), SST3.4 (5° N-5° S, 170°-120° W), and SST4 (5° N-5° S, 160° E-150° W) provided by the National Oceanic and Atmospheric Administration (NOAA) and available at https://www.esrl.noaa.gov/psd/data/climateindices/list/ [43].…”

Variation in Seasonal Precipitation over Gaza (Palestine) and Its Sensitivity to Teleconnection Patterns

“…No autocorrelation was found in the SP trend at any station. These methods, linear least square, prewhitening, and Mann Kendall, are widely used to analyze rainfall data within time series [6,10,[42][43][44][45][46].…”

“…Spearman correlation is a non-parametric test. Both correlation methods are widely used to detect regional rainfall teleconnection with climate indices [10,43,45,52,54,55].…”

Characterization of comprehensive drought events associated with the ENSO warm phase through satellite images in the Valle del Cauca Colombia

“…Drought is one of the most complex yet least well understood of all the natural threats [1]. For this reason, it has been the subject of several scientific studies [2], however the planet´s climatic variability makes it difficult to use the same rainfall deficit threshold in different places [3]. As a consequence of this diversity, a multitude of outcomes and tools for the quantification of drought have been implemented [4].…”