Contribution of low-frequency climatic–oceanic oscillations to streamflow variability in small, coastal rivers of the Sierra Nevada de Santa Marta (Colombia)
TL;DR: In this article, the influence of low-frequency oscillations on streamflow variability in small tropical coastal mountain rivers of the Sierra Nevada de Santa Marta, Colombia, was evaluated.
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.
Citations
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TL;DR: In this paper, the authors evaluated the performance of the combination of three Artificial Neural Networks (ANN) approaches in the forecasting of the monthly rainfall anomalies for Southwestern Colombia, respectively.
Abstract: Improving the accuracy of rainfall forecasting is relevant for adequate water resources planning and management. This research project evaluated the performance of the combination of three Artificial Neural Networks (ANN) approaches in the forecasting of the monthly rainfall anomalies for Southwestern Colombia. For this purpose, we applied the Non-linear Principal Component Analysis (NLPCA) approach to get the main modes, a Neural Network Autoregressive Moving Average with eXogenous variables (NNARMAX) as a model, and an Inverse NLPCA approach for reconstructing the monthly rainfall anomalies forecasting in the Andean Region (AR) and the Pacific Region (PR) of Southwestern Colombia, respectively. For the model, we used monthly rainfall lagged values of the eight large-scale climate indices linked to the El Nino Southern Oscillation (ENSO) phenomenon as exogenous variables. They were cross-correlated with the main modes of the rainfall variability of AR and PR obtained using NLPCA. Subsequently, both NNARMAX models were trained from 1983 to 2014 and tested for two years (2015–2016). Finally, the reconstructed outputs from the NNARMAX models were used as inputs for the Inverse NLPCA approach. The performance of the ANN approaches was measured using three different performance metrics: Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Pearson’s correlation (r). The results showed suitable forecasting performance for AR and PR, and the combination of these ANN approaches demonstrated the possibility of rainfall forecasting in these sub-regions five months in advance and provided useful information for the decision-makers in Southwestern Colombia.
16 citations
TL;DR: In this article, the authors take a social-ecological system perspective to identify examples and pathways towards resilient ecosystems and social development, and identify four tenets for decision-making based on water-security-focused global-change science in the Americas: 1) Decision makers should focus on protecting ecosystems because water security (along with food and energy security) depend on them; 2) Water-use and allocation decisions ought to be made considering future environmental and societal vulnerabilities, especially climate projections; 3) Holistic approaches (at basin or other appropriate levels) are best suited to ensure social
Abstract: Achieving water security for humans and ecosystems is a pervasive challenge globally. Extensive areas of the Americas are at significant risk of water insecurity, resulting from global-change processes coupled with regional and local impacts. Drought, flooding, and water quality challenges pose significant threats, while at the same time, rapid urban expansion, competing water demands, river modifications, and expanding global markets for water-intensive agricultural products drive water insecurity. This paper takes a social-ecological systems perspective, aiming to identify examples and pathways towards resilient ecosystems and social development. It draws on lessons from two science-policy network projects, one focusing on water scarcity in arid and semi-arid regions of Argentina, Chile, Brazil, Peru, Mexico and the United States; and the second addressing river and lake basins as sentinels of climate variability and human effects on water quantity and quality in Canada, the United States, Argentina, Colombia, Uruguay and Chile. Together, these ‘complementary contrasts’ provide an analytical basis to empirically examine stakeholder engagement, knowledge co-production and science-policy interaction supporting decision-making to achieve water security. The paper identifies four tenets for decision-making based on water-security-focused global-change science in the Americas: 1) Decision makers should focus on protecting ecosystems because water security (along with food and energy security) depend on them; 2) Water-use and allocation decisions ought to be made considering future environmental and societal vulnerabilities, especially climate projections; 3) Holistic approaches (at basin or other appropriate levels) are best suited to ensure social-ecological system resilience and reduce vulnerability; and 4) It is essential to support local/traditional livelihoods, and underserved populations to achieve equitable water security and ecosystem resilience.
13 citations
TL;DR: The analysis of past monthly rainfall variability is highly relevant for the adequate management of water resources, the relationship between the climate-oceanographic indices, and the variability of monthly rainfall in Southwestern Colombia at different time scales was chosen as the research topic as discussed by the authors.
Abstract: Given that the analysis of past monthly rainfall variability is highly relevant for the adequate management of water resources, the relationship between the climate-oceanographic indices, and the variability of monthly rainfall in Southwestern Colombia at different time scales was chosen as the research topic It should also be noted that little-to-no research has been carried out on this topic before For the purpose of conducting this research, we identified homogeneous rainfall regions while using Non-Linear Principal Component Analysis (NLPCA) and Self-Organizing Maps (SOM) The rainfall variability modes were obtained from the NLPCA, while their teleconnection in relation to the climate indices was obtained from Pearson’s Correlations and Wavelet Transform The regionalization process clarified that Narino has two regions: the Andean Region (AR) and the Pacific Region (PR) The NLPCA showed two modes for the AR, and one for the PR, with an explained variance of 75% and 48%, respectively The correlation analyses between the first nonlinear components of AR and PR regarding climate indices showed AR high significant positive correlations with Southern Oscillation Index (SOI) index and negative correlations with El Nino/Southern Oscillation (ENSO) indices PR showed positive ones with Nino1 + 2, and Nino3, and negative correlations with Nino34 and Nino4, although their synchronous relationships were not statistically significant The Wavelet Coherence analysis showed that the variability of the AR rainfall was influenced principally by the Nino34 index on the 3–7-year inter-annual scale, while PR rainfall were influenced by the Nino3 index on the 15–3-year inter-annual scale The El Nino (EN) events lead to a decrease and increase in the monthly rainfall on AR and PR, respectively, while, in the La Nina (LN) events, the opposite occurred These results that are not documented in previous studies are useful for the forecasting of monthly rainfall and the planning of water resources in the area of study
12 citations
TL;DR: In this paper, different filtering parameters were applied to separate the baseflow of the Heihe River Basin (HRB) in Northwest China using digital filtering methods. And multivariate relationships between baseflow and meteorological factors/large scale circulation indices were identified for several factors, which explained most of the variations.
8 citations
TL;DR: In this paper, wave energy flux in the Colombian Caribbean Sea is assessed using a 60 years wave reanalysis from 1958 to 2017 using virtual buoys allocated in the central Caribbean, at the continental shelf and around insular territories revealing a long-term decrease in magnitude with an annual rate between 0.01 and 0.2%.
8 citations
References
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TL;DR: In this article, a step-by-step guide to wavelet analysis is given, with examples taken from time series of the El Nino-Southern Oscillation (ENSO).
Abstract: A practical step-by-step guide to wavelet analysis is given, with examples taken from time series of the El Nino–Southern Oscillation (ENSO). The guide includes a comparison to the windowed Fourier transform, the choice of an appropriate wavelet basis function, edge effects due to finite-length time series, and the relationship between wavelet scale and Fourier frequency. New statistical significance tests for wavelet power spectra are developed by deriving theoretical wavelet spectra for white and red noise processes and using these to establish significance levels and confidence intervals. It is shown that smoothing in time or scale can be used to increase the confidence of the wavelet spectrum. Empirical formulas are given for the effect of smoothing on significance levels and confidence intervals. Extensions to wavelet analysis such as filtering, the power Hovmoller, cross-wavelet spectra, and coherence are described. The statistical significance tests are used to give a quantitative measure of change...
12,803 citations
"Contribution of low-frequency clima..." refers background or methods in this paper
...The global wavelet spectrum provides an ad-15 equate estimation of the long-term processes’ characteristics (Torrence and Compo, 1998; Labat, 2005)....
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...Analysis of monthly streamflow data was performed using generalized local base functions with CWT. Mother wavelets were translated and stretched in time resolution and frequency (Torrence and Compo, 1998)....
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...…of 6 was defined for the frequency localization of the Morlet wavelet (ωo) to fulfill the admissibility condition (localization in time and frequency, zero mean, and to acquire a proper balance be- 50 tween frequency and time) (Torrence and Compo, 1998; Grinsted et al., 2004; Nalley et al., 2016)....
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...…with a non-normal distribution were transformed prior to applying the XWT and WTC analyses, using a widely used standardization procedure (zero mean, unit standard deviation) (e.g., Torrence and Compo, 1998; Grin- 25 sted et al., 2004; Labat, 2005). www.hydrol-earth-syst-sci.net/23/1/2019/ Hydrol....
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...The 95 % confidence level was calculated for contours and edge effects’ area following the method of Torrence and Compo (1998)....
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TL;DR: It is demonstrated how phase angle statistics can be used to gain confidence in causal relation- ships and test mechanistic models of physical relationships between the time series and Monte Carlo methods are used to assess the statistical significance against red noise backgrounds.
Abstract: Many scientists have made use of the wavelet method in analyzing time series, often using popular free software. However, at present there are no similar easy to use wavelet packages for analyzing two time series together. We discuss the cross wavelet transform and wavelet coher- ence for examining relationships in time frequency space be- tween two time series. We demonstrate how phase angle statistics can be used to gain confidence in causal relation- ships and test mechanistic models of physical relationships between the time series. As an example of typical data where such analyses have proven useful, we apply the methods to the Arctic Oscillation index and the Baltic maximum sea ice extent record. Monte Carlo methods are used to assess the statistical significance against red noise backgrounds. A software package has been developed that allows users to perform the cross wavelet transform and wavelet coherence (http://www.pol.ac.uk/home/research/waveletcoherence/). As we are interested in extracting low s/n ratio signals in time series we discuss only CWT in this paper. While CWT is a common tool for analyzing localized intermittent os- cillations in a time series, it is very often desirable to ex- amine two time series together that may be expected to be linked in some way. In particular, to examine whether re- gions in time frequency space with large common power have a consistent phase relationship and therefore are sug- gestive of causality between the time series. Many geophys- ical time series are not Normally distributed and we suggest methods of applying the CWT to such time series. From two CWTs we construct the Cross Wavelet Transform (XWT) which will expose their common power and relative phase in time-frequency space. We will further define a measure of Wavelet Coherence (WTC) between two CWT, which can find significant coherence even though the common power is low, and show how confidence levels against red noise back- grounds are calculated. We will present the basic CWT theory before we move on to XWT and WTC. New developments such as quanti- fying the phase relationship and calculating the WTC sig- nificance level will be treated more fully. When using the methods on time series it is important to have solid mecha- nistic foundations on which to base any relationships found, and we caution against using the methods in a "scatter-gun" approach (particularly if the time series probability density functions are modified). To illustrate how the various meth- ods are used we apply them to two data sets from meteo- rology and glaciology. Finally, we will provide links to a MatLab software package.
4,586 citations
"Contribution of low-frequency clima..." refers background or methods or result in this paper
...Such a consistent varying phase lag implies a phase-locked relationship and suggests a physical link (i.e., not a casual relationship) between the streamflow25 variability and each of the climatic–oceanographic indices (Grinsted et al., 2004; Labat, 2005)....
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...Spectral analyses such as wavelet transform (WT) and the Hilbert–Huang transform (HHT) (Grinsted et al., 2004; Labat et al., 2005; Tor- 90 rence and Compo, 1998; Massei and Fournier, 2012; Schulte et al., 2016) have proven useful for identifying the timing of important features of non-stationary…...
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...…high common powers and relative phases in a time–frequency space, whereas the WTC finds significant coherence even with a low common power and shows confidence levels against red noise, highlighting locally phase-locked patterns 15 (Shumway and Stoffer, 2004; Grinsted et al., 2004; Labat, 2005)....
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...The WTC spectrum highlights the intensity of the covariance of these signals, regardless of the highpower display (Grinsted et al., 2004; Nalley et al., 2016)....
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...The Morlet wavelet also allows us to describe the hydrological 45 data structure as well as to have better frequency resolution (Grinsted et al., 2004; Labat, 2005)....
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TL;DR: In this paper, data from 280 rivers discharging to the ocean indicates that sediment loads/yields are a log-linear function of basin area and maximum elevation of the river basin.
Abstract: Analysis of data from 280 rivers discharging to the ocean indicates that sediment loads/yields are a log-linear function of basin area and maximum elevation of the river basin. Other factors controlling sediment discharge (e.g., climate, runoff) appear to have secondary importance. A notable exception is the influence of human activity, climate, and geology on the rivers draining southern Asia and Oceania. Sediment fluxes from small mountainous rivers, many of which discharge directly onto active margins (e.g., western South and North America and most high-standing oceanic islands), have been greatly underestimated in previous global sediment budgets, perhaps by as much as a factor of three. In contrast, sediment fluxes to the ocean from large rivers (nearly all of which discharge onto passive margins or marginal seas) have been overestimated, as some of the sediment load is subaerially sequestered in subsiding deltas. Before the proliferation of dam construction in the latter half of this century, rivers...
3,227 citations
"Contribution of low-frequency clima..." refers background in this paper
...These fluvial systems possess low streamflow buffering capacity because of their topographic setting (Milliman and Syvitski, 1992), and they are exposed to regional-scale atmospheric– oceanographic processes (Hastenrath, 1990; Enfield and Al- 75 faro, 1999)....
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TL;DR: In this paper, the authors review the current state of science regarding historical trends in hydrologic variables, including precipitation, runoff, tropospheric water vapor, soil moisture, glacier mass balance, evaporation and growing season length.
2,025 citations
"Contribution of low-frequency clima..." refers background in this paper
...In the past several decades, streamflow variability has in- 40 creased (Milliman et al., 2008; Dai et al., 2009), causing frequent and pronounced flood–drought cycles (Huntington, 2006)....
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TL;DR: In this paper, Hilbert spectral analysis is proposed as an alternative to wavelet analysis, which provides not only a more precise definition of particular events in time-frequency space, but also more physically meaningful interpretations of the underlying dynamic processes.
Abstract: We survey the newly developed Hilbert spectral analysis method and its applications to Stokes waves, nonlinear wave evolution processes, the spectral form of the random wave field, and turbulence. Our emphasis is on the inadequacy of presently available methods in nonlinear and nonstationary data analysis. Hilbert spectral analysis is here proposed as an alternative. This new method provides not only a more precise definition of particular events in time-frequency space than wavelet analysis, but also more physically meaningful interpretations of the underlying dynamic processes.
1,945 citations
"Contribution of low-frequency clima..." refers background or methods in this paper
...In order to determine the frequency25 and energy of each of the signal modes, we define the average frequency (f (n)) and average energy (En) of each mode (Huang et al., 1999, 2009): f (n)= ∞∫ 0 fEn(f )df ∞∫ 0 En(f )df , (7) En = T∫ 0 C2n(t)dt, (8)30 where En is the Fourier power density spectrum....
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...The HHT is an adaptive empirical method used to obtain 65 modes of variability with nonlinear and non-stationary data (Huang et al., 1999)....
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...6), which represents the sum of all ampli-20 tudes (energy) over all data (Barnhart, 2011): h(w)= T∫ 0 H(w,t)dt. (6) The Hilbert marginal spectrum corresponds to the energy associated with each of the frequencies that make up the signal (Huang et al., 1999)....
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...A combination of the algorithm to obtain the functions of intrinsic modes, together with the Hilbert spectral analysis, is called the Hilbert–Huang transform (Huang et al., 1999; Barnhart, 2011).35...
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