The success of many projects linked to the management and planning of water resources depends mainly on the quality of the climatic and hydrological data that is provided. Nevertheless, the missing data are frequently found in hydroclimatic variables due to measuring instrument failures, observation recording errors, meteorological extremes, and the challenges associated with accessing measurement areas. Hence, it is necessary to apply an appropriate fill of missing data before any analysis. This paper is intended to present the filling of missing data of monthly rainfall of 45 gauge stations located in southwestern Colombia. The series analyzed covers 34 years of observations between 1983 and 2016, available from the Instituto de Hidrología, Meteorología y Estudios Ambientales (IDEAM). The estimation of missing data was done using Non-linear Principal Component Analysis (NLPCA); a non-linear generalization of the standard Principal Component Analysis Method via an Artificial Neural Networks (ANN) approach. The best result was obtained using a network with a [45-44-45] architecture. The estimated mean squared error in the imputation of missing data was approximately 9.8 mm. month-1, showing that the NLPCA approach constitutes a powerful methodology in the imputation of missing rainfall data. The estimated rainfall dataset helps reduce uncertainty for further studies related to homogeneity analyses, conglomerates, trends, multivariate statistics and meteorological forecasts in regions with information deficits such as southwestern Colombia.

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.

This study examines the influence of the Atlantic Multidecadal Oscillation (AMO) on the Choco Low-level Jet (CJ) variations during the 1983–2016 period. Considering the September–November (SON) 925 hPa zonal wind index in the CJ core, a significant breakpoint occurs in 1997 with larger values after 1997. The changes in the CJ and Caribbean Low-Level Jet (CLLJ), and their related ocean-atmospheric patterns and impacts on precipitation over Colombia were analyzed considering separately the 1983–1996 and 1998–2016 periods, which overlap the cold and warm AMO phases, respectively. During the 1998–2016 period, the negative sea surface temperature (SST) anomalies in the tropical Pacific Ocean and the positive ones in the Caribbean Sea and Tropical North Atlantic (TNA) strengthen the CJ and weaken the CLLJ, and moisture is transported into Central and Western Colombia increasing the rainfall there. Our results indicate that part of the CJ strengthening after 1997 was due to a higher percentage of intense CJ events coinciding with La Niña events during the warm AMO and cold Pacific Decadal Oscillation (PDO) background. However, the AMO-related SST and sea level pressure (SLP) variations in the TNA seem to be more crucial in modulating the CJ and CLLJ intensities, such that CJ is weakened (intensified) and CLLJ is intensified (weakened) before (after) 1997. As far as we know, the relations of the CJ and CLLJ intensities to the AMO phases were not examined before and might be useful for modeling studies.