Читать книгу Congo Basin Hydrology, Climate, and Biogeochemistry - Группа авторов - Страница 80

The response of surface water hydrology to climate variability was evaluated by comparing the leading SPEI temporal series (Figure 5.1a and c) with normalized discharge time series (Congo River discharge). The temporal patterns of standardized runoff index (SRI) and SPEI tend to be consistent except during the drought periods between 1995 and 1999 (Figure 5.6a). SRI indicated positive values (except 1998) contrary to SPEI, which showed drought conditions. The SPEI temporal pattern is poorly correlated with SRI during the 1980–2010 period (r = 0.22 at α = 0.05). But as shown in Figure 5.6a, the temporal relationship between SRI and SPEI are relatively better in some periods. For example, SPEI is better correlated with SRI between 1980 and 1987 (r = 0.46; α = 0.05) and the post‐2000 period (r = 0.46; α = 0.05). A recent assessment of global multi‐scale climate influence on historical drought events over the Congo Basin (Ndehedehe et al., 2019) showed that SRI and SPEI were largely correlated during the 1931–1990 and 1961–1990 (r = 0.69 and 0.64, respectively, at α = 0.05) periods unlike the 1991–2010 period (r = 0.38). While this suggests rainfall was the main driver of hydrological conditions of the basin between 1903 and 1990, that appears to have changed as droughts and human activities can impact on the rainfall‐discharge relationship in ways that further complicates our understanding of natural climate processes in the region.

Figure 5.6 Assessing climate influence on surface water hydrology over the Congo Basin. (a) Relationship between river discharge and SPEI, and (b) relationship of Congo River discharge with TWS and surface water storage. TWS here is the GRACE‐hydrological signal in the second orthogonal mode (TWS‐2, Figure 5.5).

Temporal variability in discharge is expected to be driven by changes in precipitation patterns and other land surface conditions, including land cover change. Considerable variability in the Congo River’s discharge between 1960 and 1995 was reported by Alsdorf et al. (2016), consistent with a 21% increase in the Congo River discharge during the same period. Ultimately, this would imply that increased rainfall led to a rise in the Congo River discharge. But the time series of SPEI and SRI were largely inconsistent during most parts of the 1990s when extreme drought was observed (Figure 5.6a). For instance, SRI indicated wet episodes for most of the period after 1995 until 2000 (except 1998) and even during the post‐2000 period, while SPEI was largely characterized by drought episodes in between these periods (Figure 5.6b). Further, it is shown here that the surface water of the Congo Basin is a key component of the GRACE water column, indicating significant association with river discharge and SWS (Figure 5.6b). The multi‐annual variations of TWS (Figure 5.5a,b) observed around the Congo Cuvette centrale is dominated by the Congo River discharge (r = 0.88 at α = 0.05) (Figure 5.6b). The response of the Congo River discharge to climate variations was predicted using the leading modes of SST anomalies of the surrounding oceans (Atlantic, Indian, and Pacific) as predictands in an SVR scheme. The output of the linear SVMR show that global climate through SST anomalies of the three oceans are associated with fluctuations in the Congo river discharge (Figure 5.7a–c). Given the moderately strong correlation (r = 0.79, p = 0.0000) between the observed and predicted (Figure 5.7a,b), SST of the Atlantic and Pacific are relatively stronger predictors of river discharge compared to SST of the Indian ocean, which indicated a moderately strong correlation (r = 0.74, p = 0.0000) (Figure 5.7c). From the SVMR model, the first SST mode (annual) from the Pacific and Indian oceans had the strongest coefficients (second mode of Atlantic SST had the highest coefficients out of the five predictors). However, while the first and second SST modes of the Indian ocean showed strong coefficients, the fifth mode of the Pacific SST showed the second highest coefficients. Overall, the weight of coefficients of the predictands in the SVMR model confirm the importance of slow oceanic and climate signals (e.g., ENSO) from global SST anomaly on hydrological changes and surface water hydrology in the Congo Basin. Furthermore, there is significant difference in the spatial distribution of SWS during extreme drought (2004) and wet (2007) periods in the basin (Figure 5.8a–h, cf. Figure 5.1). Generally, strong spatial patterns of SWS and total inundation are restricted to the Congo River channel with values reaching 200 mm in the September–October period (Figure 5.8a–h). With a gradual rise in rainfall during the November–December period, surface water storage extends to the Cuvette centrale and is perhaps stored as floodplain waters. During the 2004 drought period (Figure 5.8e and g), the floodplain waters around the Cuvette centrale area of the Congo Basin in the November–December period are not as noticeable as the wet period in 2007 (Figure 5.8f and h). There is a significant difference in the SWS spatial and temporal patterns shown for the wet and dry periods (Figure 5.8a–h) and a wider distribution of surface water during the former is observed. This is expected for the Congo Basin, as diminished flow under limited rainfall conditions would be normal. Additional analysis based on observed spatial trends in SWS were also undertaken. These short‐term trends of SWS were estimated for specific drought (e.g., 2005–2005) and wet (e.g., 2006–2007) periods and they are consistent with the aforementioned results.