3.2. Rainfall vs river discharge
Similar to rainfall, observed river discharge was also statistically
decomposed using the singular spectral analysis. This approach is
warranted because unlike rainfall, the discharge time series is a one
column vector unit and decomposing it similar to rainfall allows
comparison between their leading modes. The temporal patterns of the
leading modes of rainfall and discharge were compared with one another
(Figs. 8a-b). The relationship between leading modes (PC-1) of rainfall
and river discharge show marked fluctuations during the entire period
(1901-2010). The strongest linear correlation (r = 0. 71)
was observed during 1991-2010 period while the lowest (r =
0. 59) was observed at the start of the century
(1903- 1930). The other two climatological periods show moderately
strong correlations (r = 0. 68 and 0. 64 for the
1930-1960 and 1961-1990 periods, respectively). Maximum correlation
between the second modes of rainfall and discharge is also linear and
strong but with a one-month phase lag. For example, the second modes of
rainfall and discharge during the 1903- 1930 (r =
0. 71)
and 1991-2010 (r = 0. 66) were found to be well associated
at one-month lag. The total variability accounted for by the two leading
modes of rainfall and discharge are summarised in Table 1. The annual
signal in GPCC explains an average of 42.7% of variability in discharge
while the multi-annual signal accounts for about 50% at 1-month lag.
During all climatological periods, temporal relationships between the
first modes of rainfall and discharge are moderately strong and
significant (r = 0. 05). At the start of the century, more
of the variability in rainfall were rather consistent with those of
discharge (92% and 96.7% total variability for rainfall and discharge,
respectively) as opposed to the 1990- 2010 period (91% and 98.3%
total variability for rainfall and discharge, respectively) when there
was increased variability in discharge (Figs. 8a-b). Similar to rainfall
(Figs. 5a-b and 6a-b), the variability in leading modes of discharge
fluctuated during the century (between 69% and 76%). This suggests
that apart from rainfall, Congo river discharge is driven by other
factors, which may include the influence of human activities through
deforestation and sand mining. While the interaction and exchange of
fluxes within wetlands could disturb the variability of the Congo river,
Conway et al. (2009) confirmed the dominant control of inter-annual and
decadal rainfall variability in river flows whilst acknowledging the key
roles of human interventions. Notably, a significant proportion of
changes in the dominant discharge patterns is still not explained by
those of rainfall. This information signals the threshold of complex
hydrological processes in the region, and perhaps suggest the influence
of anthropogenic contributions and strong multi-scale ocean-atmosphere
phenomena as key secondary drivers of hydrologic variability.