Abstract
Despite the absence of tectonic activity, cratonic environments are characterized by strongly variable, and in places significant, rock weathering rates. This is shown here through an exploration of the weathering rates in two inter-tropical river basins from the Atlantic Central Africa: the Ogooué and Mbei River basins, Gabon. We analyzed the elemental and strontium isotope composition of 24 water samples collected throughout these basins. Based on the determination of the major element sources we estimate that the Ogooué and Mbei rivers total dissolved solids (TDS) mainly derive from silicate chemical weathering. The chemical composition of the dissolved load and the area-normalized solute fluxes at the outlet of the Ogooué are similar to those of other West African rivers (e.g., Niger, Nyong, or Congo). However, chemical weathering rates ( rate expressed as the release rate of the sum of cations by silicate chemical weathering) span the entire range of chemical weathering intensities hitherto recorded in worldwide cratonic environments. In the Ogooué-Mbei systems, three regions can be distinguished: (i) the Eastern sub-basins draining the Plateaux Batéké underlain by quartz-rich sandstones exhibit the lowest rates, (ii) the Northern sub-basins and the Mbei sub-basins, which drain the southern edge of the tectonically quiescent South Cameroon Plateau, show intermediate rates and (iii) the Southern sub-basins characterized by steeper slopes record the highest rates. In region (ii), higher DOC concentrations are associated with enrichment of elements expected to form insoluble hydrolysates in natural waters (e.g., Fe, Al, Th, REEs) suggesting enhanced transport of these elements in the colloidal phase. In region (iii), we suggest that a combination of mantle-induced dynamic uplift and lithospheric destabilization affecting the rim of the Congo Cuvette induces slow base level lowering thereby enhancing soil erosion, exhumation of fresh primary minerals, and thus weathering rates. The study points out that erosion of lateritic covers in cratonic areas can significantly enhance chemical weathering rates by bringing fresh minerals in contact with meteoric water. The heterogeneity of weathering rates amongst cratonic regions thus need to be considered for reconstructing the global, long-term carbon cycle and its control on Earth climate.
Introduction
Over geological time scales, chemical weathering acts as a major player of the global biogeochemical cycles of elements in the Earth's Critical Zone. In particular, silicate weathering is known to consume CO2 through mineral hydrolysis and neutralization of base cations hosted by silicate minerals, and therefore can contribute to regulating the global climate (Berner et al., ). Tectonic activity is thought to be a primary driver of chemical weathering (Raymo and Ruddiman, 1992; Herman et al., ). Orogenic uplift associated with collision between tectonic plates forms the major world mountain chains, favoring mechanical erosion, and the exposure of fresh primary mineral surfaces to meteoric water and subsequent chemical weathering. This phenomenon has long been suggested to be responsible for the gradual cooling of the Earth over the Cenozoic under the effect of global mountain uplift (Herman et al., ; Becker et al., ), although this hypothesis is strongly debated (e.g., Godderis, ; Willenbring and Von Blanckenburg, 2010; Von Blanckenburg et al., 2015; Norton and Schlunegger, ; Caves Rugenstein et al., ; Hilton and West, ; Penman et al., ). By contrast, tectonically quiescent cratonic areas, which represent almost 70% of the continents surface (Artyushkov et al., ), have long been considered to be relatively inefficient in terms of chemical weathering compared to erosive, mountainous regions (e.g., Carson and Kirkby, ; Stallard, 1985). Indeed, especially in the humid tropics, these low-relief settings favor the formation of deep regolith covers, chemically depleted in base cations and limiting water-bedrock interactions due to slow water percolation from the surface to the bedrock (e.g., Stallard and Edmond, 1987; Braun et al., , ; West, 2012; Riebe et al., 2017). While these hot and humid cratonic areas commonly exhibit low silicate weathering rates by comparison with orogenic areas (e.g., Gaillardet et al., ; Moon et al., ) they dominate the intertropical regions surface area and, therefore, represent a significant proportion of the global delivery of dissolved matter to the oceans (Milliman and Farnsworth, ; Von Blanckenburg et al., 2015). In particular, according to modeling results (Goddéris et al., ) the net weathering budget of the intertropical cratonic areas and their role on the long term CO2 budget may have been underestimated and need to be investigated in more detail to characterize their potential role in the Cenozoic global climate evolution.
River hydrochemical analyses are essential tools for estimating catchment-scale silicate weathering fluxes, through the quantification of the export of silicate-derived dissolved cations (Gaillardet et al., ). River basins draining cratonic areas exhibit contrasted weathering rates (expressed as the drainage-area normalized flux of the sum of cations released by silicate chemical weathering, rate) from those recorded under boreal conditions ( rate < 1 t km−2 yr−1; Millot et al., ; Zakharova et al., 2005, 2007; Pokrovsky et al., ) to those measured in India in the Kavery (Pattanaik et al., ) and Nethravati (Gurumurthy et al., ) basins ( rate > 15 t km−2 yr−1). Various drivers can be invoked to explain this spatial variability. For example, the Nsimi experimental watershed is located in a tectonically quiescent area of the Nyong river basin (South Cameroon Plateau) where swamp environments are widespread. There, organic-rich waters increase the mobilization and transfer of some elements generally considered as immobile (e.g., Al, Fe, Th, Zr) through colloidal transport (Oliva et al., ; Viers et al., 2000; Braun et al., , ). Such enhancement of weathering in the presence of organic matter has also been reported for boreal Siberian rivers rich in dissolved organic matter and poor in suspended matter (Zakharova et al., 2005, 2007; Pokrovsky et al., , 2016). Indeed, in this type of environment such environments, organo-metal complexes form, leading to the solubilization of Al, Fe, Th, and Zr and thus to the breakdown of silicate minerals (e.g., Oliva et al., ; Tamrat et al., 2019). The Kaveri and Nethravati basins drain the Indian craton and exhibit low annual runoff (<220 mm yr−1) by comparison with other tropical cratonic areas. In this region, intense monsoons can enhance weathering through strong erosional processes, exposing of felsic granulites and gneissic rocks (Pattanaik et al., ; Meunier et al., ). In this case, climate and erosion act as dominant drivers of weathering rates. Finally, in the small monolithologic basins of the Mule Hole-India tropical watershed, the presence of minor/accessory minerals (Ca-bearing minerals like epidote and apatite), the dissolution of smectite and calcite, as well as the drainage characteristics of weathering profiles have all been shown to play a key role on weathering budget (Braun et al., ; Violette et al., 2010). However, most of the aforementioned work has focused on a local scale (i.e., soil profiles or small watersheds) or, when dealing with weathering fluxes measured at a larger scale, the variability of weathering rates amongst cratonic environments was not considered to be part of the scope of the study.
The existence of sustained uplift due to mantle dynamics or lithospheric destabilization (Cottrell et al., ; Jaupart et al., ; Hu et al., ) in cratonic areas has not been considered yet as a potential driver of Earth denudation. Although much slower and occurring over larger spatial scales than mountain uplift mediated by faulting in collisional tectonic settings (Lamb and Watts, ; Flament et al., ), mantle-induced dynamic uplift or lithospheric destabilization can lead to lowering of the geomorphological base level that in turn can trigger physical erosion processes (Kusky et al., ) as observed for the Southern African Craton (Braun et al., ), North China Craton (Zhu et al., 2017) or Brazilian Shield (Rodríguez Tribaldos et al., 2017). Such slow, large-scale mantle and lithospheric dynamics, in conjunction to eustatic changes, have also been shown to control relief as well as erosion and sedimentary processes (Conrad and Husson, ; Guillocheau et al., ). Presumably, physical erosion processes sustained by mantle induced dynamic uplift or lithospheric destabilization in cratonic settings could lead to significant rock weathering through soil erosion and subsequent increased exposure of “fresh” mineral surfaces—a phenomenon we set out to address in the present study.
The Ogooué River Basin, western Central Africa, is located between the western border of the Congo cuvette and the south of the Cameroun Plateau. This intra-cratonic basin experiences a homogeneous tropical humid climate (Bogning et al., , ) and has undergone successive and contrasted uplift phases over the Cenozoic (Guillocheau et al., ). The present study provides the opportunity to explore the variability in weathering fluxes and rates in the large Ogooué River Basin (drainage area of ~ 215,000 km2) as well in the neighboring, smaller Mbei River Basin (drainage area of ~ 1,800 km2) with respect to geomorphology, tectonics, and lithology. Based on discrete hydrochemical analyses of the main Ogooué River tributaries, we assess, for the first time, the Ogooué weathering fluxes and their variability throughout the basin. These new constraints allow us to explore the main potential drivers controlling the variability in weathering rates in cratonic areas and to discuss the implications for the long-term evolution of the Earth's climate.
Study Area
The equatorial Ogooué River basin covers ~215,000 km2 (location: between 3°9'S and 2°4'N and between 8°5'E and 14°3E; Figure 1). Around 85% of the basin lies within Gabon, 12% in the Republic of Congo and the remaining area in Cameroon and Equatorial Guinea. With an annual discharge of 4,750 m3 s−1 (Bogning et al., ), the Ogooué is the third largest river in terms of annual discharge along the African West Coast after the Congo (~41,000 m3 s−1; Laraque et al., ) and the Niger (~6,000 m3 s−1) rivers (Dai and Trenberth, ). In addition to the Ogooué Basin, this study reports on the hydrochemistry of the smaller Mbei River (location: between 0°1'N and 1°1'N and between 10°7'E and 10°4E; Figure 1), which is a northern tributary of the Komo River discharging to the Atlantic Ocean around 150 km north of the Ogooué River outlet. The Mbei River is characterized by an annual discharge of ~60 m3 s−1 (ORSTOM, ; Njutapvoui Fokouop, ; data only available for the period 1964–1973) and a drainage area of ~ 1,800 km2. According to the Köppen-Geiger classification, the Ogooué and Mbei basins experience a tropical savanna climate. The Ogooué Basin receives around 2,000 mm yr−1 in annual precipitation, which leads to a runoff of around 700 mm yr−1 (Mahe et al., ; Bogning et al., ; Kittel et al., ). The basin exhibits a bi-modal precipitation regime with wet periods from March to May and from October to December with a maximal monthly rainfall of ~200 and ~300 mm month−1, respectively. The dry period extends from June to August with a minimum monthly rainfall <15 mm month−1 in July. The mean annual temperature is around 24°C and is relatively invariant across the year. In the present work, the study area corresponds to the Ogooué Basin upstream from the Lambaréné station (Figure 2F) and covers 206,000 km2, representing 96% of the entire Ogooué Basin (Figure 1), combined to four Mbei tributaries each covering basin areas <500 km2. At the Lambaréné station, the Ogooué River discharge variation follows the rainfall regime of the basin (Mahe et al., ). Overall, the seasonal variability in discharge (SV as quantified by the ratio between maximum and minimum monthly discharge; SV = 3.7; Figure 3) is relatively low by comparison with other intertropical rivers experiencing a monsoonal regime (e.g., Pacific Peruvian rivers: SV = 6–21; Moquet et al., ; Nethravati River: SV = 600–1,100; Gurumurthy et al., ). The elevation of the Ogooué basin, as considered in the present study, extends from 914 m.a.s.l (Lolo River sub-basin upstream) to 20 m.a.s.l. (Lambaréné station).
Figure 1
Figure 2

Photos of (A) Mbei river tributary 1, (B) Ivindo river at Loaloa (a Northern basin), (C) Lékoni river at Lakeni (Plateaux Batéké basin), (D) Lopé river at Lopé (a Southern basin), (E) Ogooué River at Ndjolé, and (F) Ogooué River at Lambaréné.
Figure 3

Daily discharge (07/2001 to 08/2017) and mean monthly discharge of the Ogooué River at the Lambaréné station (Bogning et al.,
The Ogooué Basin can be separated into three geomorphological domains (Figure 1; Table 1). The Plateaux Batéké region (Eastern sub-basins) located close to the Congo border is composed of Cenozoic sandstone (pure quartz; Seranne et al., 2008) and is active in terms of dynamic uplift (Guillocheau et al.,
Table 1
| Group | Sampling date | Sample number | River | Location | Sampling site characteristics | Basin characteristics | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Latitude | Longitude | Sampled site elevation | Annual mean discharge | Basin area | Basin elevation | Mean basin slope | Rainfall | Specific discharge | |||||
| Decimal degree | m.a.s.l. | m3 s−1 | km2 | m.a.s.l. | % | mm yr−1 | mm yr−1 | ||||||
| Mbei tributaries | 05/09/2017 | 1 | Mbei tributary 1 | 0.5332 | 10.2148 | 139 ± 3 | 0.36 ± 0.06 | 13 | 448 | 7.9 | 2,244 | 890 | |
| 05/09/2017 | 2 | Mbei tributary 2 | Akelayong | 0.5874 | 10.2541 | 160 ± 9 | 0.14 ± 0.02 | 5 | 387 | 7.5 | 2,244 | 890 | |
| 05/09/2017 | 3 | Mwengue | Akoga | 0.8709 | 10.4961 | 534 ± 3 | 2.4 ± 0.68 | 135 | 639 | 1.0 | 1,957 | 567 | |
| 05/09/2017 | 4 | Binguili | Assok | 0.7110 | 10.3570 | 526 ± 3 | 0.36 ± 0.06 | 13 | 613 | 0.8 | 2,244 | 890 | |
| Ogooué R. main | 10/09/2017 | 18 | Ogooué | Dam Poubara 2 | −1.7728 | 13.5499 | 420 ± 3 | 454 ± 45 | 8,778 | 582 | 0.7 | 2,663 | 1,631 |
| channel | 10/09/2017 | 17 | Ogooué | Franceville | −1.6355 | 13.5314 | 285 ± 5 | 781 ± 76 | 14,944 | 555 | 1.0 | 2,672 | 1,650 |
| 12/09/2017 | 20 | Ogooué | Lastourville | −0.8096 | 12.7285 | 228 ± 3 | 1,928 ± 233 | 45,823 | 493 | 1.1 | 2,512 | 1,328 | |
| 13/09/2017 | 26 | Ogooué | Ayem | −0.1037 | 11.4153 | 88 ± 3 | 3,674 ± 726 | 142,373 | 502 | 0.9 | 2,186 | 814 | |
| 07/09/2017 | 8 | Ogooué | Ndjolé | −0.1827 | 10.7701 | 16 ± 3 | 3,933 ± 818 | 160,312 | 497 | 1.0 | 2,155 | 774 | |
| 06/09/2017 | 6 | Ogooué | Lambaréné (SEEG) | −0.7139 | 10.2221 | 3 ± 3 | 4,341* | 205,585 | 467 | 1.2 | 2,159 | 666* | |
| Northern Ogooué tributaries | 07/09/2017 | 7 | Abanga | Bel_Abanga | −0.2726 | 10.4847 | 16 ± 3 | 139 ± 42 | 8,265 | 448 | 1.3 | 1,915 | 531 |
| 07/09/2017 | 9 | Missanga | Ndjolé | −0.1800 | 10.7687 | 13 ± 3 | 8.3 ± 2.4 | 483 | 281 | 3.0 | 1,933 | 546 | |
| 07/09/2017 | 10 | Okano | Alembé | −0.0591 | 10.9782 | 46 ± 3 | 183 ± 56 | 11,135 | 494 | 1.1 | 1,902 | 521 | |
| 07/09/2017 | 11 | Lara | Mindzi | 0.6034 | 11.4966 | 313 ± 5 | 35 ± 10.4 | 2,049 | 590 | 0.8 | 1,935 | 547 | |
| 08/09/2017 | 12 | Mvoung | Ovan | 0.3136 | 12.1879 | 404 ± 3 | 160 ± 44 | 8,803 | 523 | 0.5 | 1,967 | 575 | |
| 08/09/2017 | 13 | Ivindo | Loaloa | 0.5215 | 12.8245 | 462 ± 3 | 892 ± 252 | 49,503 | 549 | 0.6 | 1,960 | 569 | |
| Southern Ogooué tributaries | 12/09/2017 | 19 | Leyou | Ndoubi | −1.3313 | 13.0989 | 293 ± 3 | 53 ± 5 | 1,161 | 592 | 1.5 | 2,579 | 1458 |
| 12/09/2017 | 21 | Lolo | Lolo | −0.6685 | 12.4929 | 213 ± 3 | 258 ± 38 | 7,582 | 531 | 1.6 | 2,368 | 1,077 | |
| 12/09/2017 | 22 | Ouagna | Wagny | −0.5988 | 12.3150 | 201 ± 4 | 56 ± 10 | 2,020 | 394 | 1.3 | 2,236 | 880 | |
| 12/09/2017 | 23 | Offoué | Entrance Lopé park | −0.3510 | 11.7627 | 183 ± 3 | 159 ± 36 | 7,057 | 493 | 1.8 | 2,103 | 713 | |
| 13/09/2017 | 25 | Lopé | Lopé | −0.1102 | 11.6019 | 118 ± 3 | 6.1 ± 1.9 | 379 | 322 | 2.0 | 1,890 | 512 | |
| Plateaux Batéké | 09/09/2017 | 14 | Sébé | Okandja | −0.6176 | 13.6812 | 295 ± 3 | 136 ± 23 | 4,513 | 458 | 0.8 | 2,287 | 952 |
| 09/09/2017 | 15 | Lékoni | Akieni | −1.1852 | 13.8773 | 387 ± 3 | 263 ± 25 | 4,911 | 537 | 1.4 | 2,692 | 1694 | |
| 10/09/2017 | 16 | Passa | Franceville | −1.6294 | 13.6103 | 287 ± 3 | 312 ± 30 | 5,892 | 524 | 1.6 | 2,682 | 1,672 | |
Main characteristics of the Mbei and Ogooué rivers and their tributaries.
Drainage area and mean slope are based on the SRTM 90 digital elevation model (NASA). For annual discharge values,
represent the measured discharge at Lambaréné station (Bogning et al.,
The study area is essentially covered by rainforest with patchy savanna grassland and is home to a high biodiversity (e.g., Koffi et al.,
Materials and Methods
Sampling and in-situ Analyses
Surface water samples were collected at 24 locations in the Ogooué main channel (six samples), Ogooué's tributaries (14 samples), and in the Mbei River tributaries (four samples) in September 2017 (Figures 1, 2; Table 1).
Electrical conductivity (normalized to a temperature of 25°C), pH and water temperature were measured in situ. We followed the protocol of Bouchez et al. (
Analytical Methods
All laboratory procedures and measurements were performed at the PARI (Plateau d'Analyse Haute Résolution) analytical platform of the IPGP (Institut Physique du Globe de Paris). Major cations (Ca2+, Na+, Mg2+, K+) and major anions (Cl−, , and ) concentration were determined using ion chromatography (CS16 cationic colomn and AS9HC anionic column—IC5000+DIONEX THERMO). Trace elements were analyzed by Quadrupole-ICP-MS (ICP-QMS 7900 Agilent). For major element concentration, the analytical uncertainty is around 5% (95% confidence interval), and for most trace elements, the analytical uncertainty is <5%. Accuracy was checked using repeated measurements of the river water reference material SLRS-6 (St-Lawrence River water, National Research Council of Canada), with concentration measurements being mostly <10% away from the certified concentrations. DOC concentrations was quantified using a Shimadzu TOC-V CSH with a relative analytical uncertainty <5%. Major element and DOC concentrations are reported in Table 2 and trace element concentration are reported in Table 3.
Table 2
| Group | sample number | temperature | pH | conductivity | TSS | DOC | Na+ | K+ | Mg2+ | Ca2+ | Sr2+ | F− | Cl− | Si | TDS | TZ+ | TZ− | NICB | 87Sr/86Sr | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ± | |||||||||||||||||||||||
| °C | μS cm−1 | mg l−1 | μmol l−1 | mg l−1 | meq l−1 | 10−5 | |||||||||||||||||
| Mbei tributaries | 1 | 22.4 | 7.22 | 26 | 6 | 1.7 | 95.9 | 15.7 | 28.1 | 32.6 | 0.21 | 6.1 | 28.3 | 8.0 | 8.4 | 172 | 210 | 30.2 | 233 | 232 | 0% | 0.72161 | 1.8 |
| 2 | 22.2 | 6.90 | 20 | 9 | 1.1 | 66.6 | 12.9 | 20.4 | 27.4 | 0.15 | 5.3 | 9.4 | 8.4 | 4.1 | 144 | 212 | 26.4 | 175 | 176 | 0% | 0.71440 | 2.3 | |
| 3 | 22.9 | 6.58 | 16 | 21 | 1.1 | 63.2 | 13.8 | 16.2 | 24.6 | 0.13 | 4.3 | 12.0 | 9.4 | 3.9 | 122 | 209 | 24.7 | 158 | 155 | 1% | 0.71709 | 2.4 | |
| 4 | 21.6 | 6.75 | 20 | 8 | 1.4 | 68.6 | 14.5 | 19.6 | 27.1 | 0.13 | 8.5 | 16.3 | 10.9 | 4.9 | 133 | 195 | 25.3 | 177 | 179 | −1% | 0.71783 | 2.3 | |
| Ogooué R. main channel | 18 | 27.4 | 6.93 | 17 | 9 | 2.1 | 66.1 | 17.3 | 16.7 | 26.0 | 0.25 | 7.1 | 7.9 | 0.0 | 3.7 | 108 | 205 | 23.3 | 169 | 131 | 13% | 0.71880 | 1.2 |
| 17 | 24.8 | 6.62 | 18 | 10 | 2.3 | 63.3 | 15.3 | 17.4 | 23.7 | 0.17 | 6.6 | 7.7 | 0.0 | 4.2 | 107 | 218 | 23.7 | 161 | 129 | 11% | 0.71837 | 2.6 | |
| 20 | 26.9 | 6.76 | 16 | 30 | 1.6 | 44.8 | 11.2 | 15.8 | 20.0 | 0.11 | 15.5 | 8.6 | 0.0 | 6.0 | 88 | 206 | 21.5 | 128 | 124 | 1% | 0.71752 | 0.9 | |
| 26 | 27.2 | 7.10 | 26 | 21 | 2.7 | 77.0 | 19.3 | 28.8 | 32.6 | 0.22 | 7.7 | 8.3 | 0.0 | 9.0 | 158 | 255 | 30.6 | 219 | 192 | 7% | 0.71658 | 4.0 | |
| 8 | 26.5 | 7.08 | 26 | 18 | 2.7 | 77.5 | 20.2 | 29.2 | 34.3 | 0.18 | 9.0 | 9.5 | 0.0 | 8.5 | 151 | 252 | 30.2 | 225 | 187 | 9% | 0.71730 | 0.5 | |
| 6 | 27.1 | 7.10 | 27 | 9 | 2.5 | 80.1 | 21.7 | 31.0 | 35.0 | 0.21 | 9.6 | 10.2 | 0.0 | 9.2 | 175 | 250 | 31.8 | 234 | 213 | 5% | 0.71765 | 1.2 | |
| Northern Ogooué tributaries | 7 | 24.9 | 6.82 | 34 | 70 | 2.5 | 111 | 24.2 | 39.6 | 46.0 | 0.28 | 11.8 | 19.5 | 0.0 | 7.2 | 252 | 273 | 39.4 | 306 | 298 | 1% | 0.71532 | 1.5 |
| 9 | 24.9 | 6.84 | 39 | 29 | 1.8 | 88.5 | 16.8 | 62.1 | 56.7 | 0.33 | 11.8 | 25.0 | 5.4 | 20.0 | 248 | 229 | 38.5 | 343 | 330 | 2% | 0.72012 | 2.5 | |
| 10 | 25.4 | 7.18 | 30 | 23 | 4.6 | 94.3 | 28.2 | 35.8 | 41.8 | 0.26 | 10.8 | 17.6 | 1.1 | 12.8 | 193 | 240 | 34.0 | 278 | 248 | 6% | 0.71712 | 0.6 | |
| 11 | 23.9 | 6.85 | 20 | 21 | 5.0 | 69.4 | 15.8 | 21.6 | 28.0 | 0.16 | 8.2 | 9.5 | 1.0 | 4.7 | 126 | 190 | 23.8 | 185 | 154 | 9% | 0.71502 | 2.7 | |
| 12 | 24.3 | 6.68 | 27 | 19 | 4.3 | 91.9 | 25.7 | 29.8 | 39.5 | 0.21 | 10.2 | 12.7 | 0.0 | 4.5 | 193 | 275 | 34.6 | 256 | 225 | 6% | 0.71691 | 3.4 | |
| 13 | 26.7 | 6.32 | 23 | 14 | 11.1 | 65.1 | 22.4 | 27.7 | 34.4 | 0.17 | 7.8 | 14.2 | 1.2 | 21.2 | 67 | 188 | 22.5 | 212 | 132 | 23% | 0.71801 | 1.7 | |
| Southern Ogooué tributaries | 19 | 24.2 | 7.32 | 48 | 48 | 2.0 | 191 | 34.0 | 41.8 | 63.8 | 0.48 | 23.8 | 11.7 | 0.0 | 6.3 | 362 | 442 | 59.1 | 436 | 410 | 3% | 0.71347 | 1.6 |
| 21 | 27.7 | 7.52 | 60 | 15 | 1.7 | 216 | 40.8 | 56.9 | 85.2 | 0.75 | 5.1 | 5.7 | 0.0 | 8.0 | 535 | 484 | 73.6 | 541 | 561 | −2% | 0.71250 | 1.8 | |
| 22 | 28.1 | 7.62 | 78 | 19 | 2.0 | 168 | 40.6 | 117 | 137 | 0.45 | 26.1 | 15.3 | 0.0 | 15.2 | 589 | 390 | 75.1 | 715 | 660 | 4% | 0.71479 | 2.4 | |
| 23 | 27.2 | 7.29 | 47 | 16 | 1.7 | 161 | 37.4 | 50.1 | 57.4 | 0.38 | 17.8 | 12.1 | 0.0 | 8.0 | 343 | 398 | 54.7 | 413 | 388 | 3% | 0.71970 | 2.5 | |
| 25 | 25.6 | 7.23 | 51 | 6 | 2.5 | 174 | 44.1 | 62.3 | 57.6 | 0.52 | 22.5 | 21.5 | 0.0 | 10.5 | 389 | 372 | 57.5 | 458 | 454 | 0% | 0.72257 | 4.3 | |
| Plateaux Batéké | 14 | 26.3 | 6.30 | 11 | 19 | 1.7 | 32.7 | 6.37 | 11.2 | 15.8 | 0.00 | 4.43 | 5.37 | <D.L. | 10.2 | 44 | 213 | 18.6 | 93.2 | 74.1 | 11% | - | |
| 15 | 26.4 | 4.63 | 8 | 15 | 0.9 | 2.13 | 2.12 | 2.93 | 6.26 | 0.00 | 1.31 | 3.02 | <D.L. | 10.0 | 0.0 | 162 | 11.3 | 22.6 | 24.4 | −4% | - | ||
| 16 | 25.6 | 5.20 | 5 | 22 | 1.2 | 5.97 | 3.86 | 4.24 | 6.77 | 0.00 | 1.27 | 4.32 | 2.0 | 7.0 | 0.89 | 155 | 11.0 | 31.8 | 22.5 | 17% | - | ||
Physico-chemical parameters, major elements concentrations, DOC concentrations, and strontium isotopic ratios (87Sr/86Sr) measured in the river dissolved phase (i.e., <0.22 μm) of the Ogooué and Mbei and basins.
TSS, DOC, TDS, and NICB stand for “total suspended solid”, “dissolved organic carbon,” “total dissolved solid,” and “normalized inorganic charge balance,” respectively. Uncertainty on major elements is <5%.
Table 3
| Group | Sample number | Li | Be | Al | Ti | V | Cr | Mn | Fe | Co | Ni | Cu | As | Rb | Sr | Y | Nb | Cd | Sn | Cs | Ba |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ppb (μg.l−1) | |||||||||||||||||||||
| Mbei tributaries | 1 | 0.580 | 0.0059 | 32.2 | 0.751 | 0.216 | 0.160 | 1.54 | 40.3 | 0.031 | 0.339 | 0.556 | 0.017 | 1.62 | 14.6 | 0.060 | 0.011 | 0.0008 | 0.001 | 0.010 | 17.7 |
| 2 | 0.302 | 0.0041 | 5.76 | 0.199 | 0.144 | 0.135 | 3.25 | 14.9 | 0.041 | 7.14 | 0.313 | 0.018 | 1.61 | 16.5 | 0.016 | 0.0003 | 0.0016 | 0.000 | 0.011 | 25.3 | |
| 3 | 0.289 | 0.0054 | 8.53 | <blk | 0.165 | 0.104 | 4.44 | 22.7 | 0.051 | 0.912 | 0.320 | 0.007 | 1.74 | 12.4 | 0.020 | <blk | 0.0024 | <blk | 0.010 | 20.4 | |
| 4 | 0.376 | 0.0058 | 11.1 | <blk | 0.128 | 0.151 | 3.12 | 39.3 | 0.033 | 0.198 | 0.286 | 0.016 | 1.75 | 12.0 | 0.030 | <blk | 0.0011 | 0.001 | 0.012 | 17.6 | |
| Ogooué R. main channel | 18 | 0.517 | 0.0029 | 10.1 | <blk | 0.162 | 0.125 | 1.28 | 27.9 | 0.021 | 0.188 | 0.182 | 0.081 | 2.18 | 15.0 | 0.0085 | 0.0049 | 0.0009 | 0.001 | 0.044 | 10.1 |
| 17 | 0.521 | 0.0033 | 7.39 | <blk | 0.153 | 0.133 | 0.88 | 13.9 | 0.017 | 0.267 | 0.285 | 0.046 | 2.12 | 16.8 | 0.0076 | 0.0018 | 0.0008 | 0.001 | 0.046 | 13.2 | |
| 20 | 0.450 | 0.0023 | 16.8 | 0.085 | 0.240 | 0.190 | 3.05 | 15.4 | 0.019 | 0.243 | 0.287 | 0.049 | 1.37 | 11.3 | 0.0072 | <blk | 0.0012 | 0.001 | 0.015 | 8.81 | |
| 26 | 0.634 | 0.0029 | 14.2 | 0.277 | 0.456 | 0.185 | 2.06 | 26.5 | 0.021 | 0.401 | 0.543 | 0.081 | 2.25 | 20.4 | 0.022 | 0.0107 | 0.0064 | 0.001 | 0.019 | 17.1 | |
| 8 | 0.625 | 0.0051 | 14.8 | 0.076 | 0.432 | 0.206 | 1.80 | 50.8 | 0.024 | 0.472 | 0.440 | 0.070 | 2.46 | 19.5 | 0.022 | <blk | 0.0011 | 0.002 | 0.020 | 16.4 | |
| 6 | 0.602 | 0.0056 | 10.6 | <blk | 0.411 | 0.205 | 3.13 | 22.5 | 0.029 | 1.71 | 0.570 | 0.065 | 2.66 | 20.2 | 0.020 | 0.0000 | 0.0007 | <blk | 0.017 | 17.6 | |
| Northern Ogooué tributaries | 7 | 0.492 | 0.0030 | 22.6 | 0.289 | 0.375 | 0.306 | 1.93 | 43.1 | 0.033 | 0.854 | 0.507 | 0.035 | 3.06 | 27.8 | 0.022 | <blk | 0.0012 | <blk | 0.014 | 23.2 |
| 9 | 1.183 | 0.0020 | 5.76 | 0.026 | 0.143 | 0.080 | 49.9 | 46.4 | 0.108 | 0.568 | 0.829 | 0.100 | 2.49 | 19.0 | 0.032 | <blk | 0.0020 | 0.000 | 0.031 | 9.84 | |
| 10 | 0.616 | 0.0075 | 15.8 | 0.066 | 0.344 | 0.255 | 7.85 | 58.6 | 0.077 | 0.623 | 0.715 | 0.046 | 3.71 | 26.8 | 0.037 | 0.0003 | 0.0025 | 0.001 | 0.024 | 21.3 | |
| 11 | 0.242 | 0.0087 | 31.6 | 0.053 | 0.360 | 0.365 | 3.83 | 54.8 | 0.088 | 2.82 | 0.572 | 0.040 | 1.93 | 16.1 | 0.034 | <blk | 0.0010 | 0.000 | 0.009 | 16.7 | |
| 12 | 0.442 | 0.0063 | 12.5 | 0.031 | 0.439 | 0.335 | 7.34 | 55.3 | 0.077 | 0.570 | 0.489 | 0.033 | 3.44 | 23.8 | 0.023 | 0.0038 | 0.0012 | <blk | 0.038 | 24.1 | |
| 13 | 0.597 | 0.0161 | 110 | 0.187 | 0.559 | 0.851 | 14.0 | 125 | 0.169 | 1.20 | 0.773 | 0.070 | 2.94 | 15.0 | 0.074 | 0.0081 | 0.0068 | 0.001 | 0.040 | 16.5 | |
| Southern Ogooué tributaries | 19 | 1.688 | 0.0027 | 9.85 | 0.023 | 0.779 | 0.11 | 1.03 | 24.5 | 0.022 | 0.339 | 0.377 | 0.019 | 3.50 | 47.3 | 0.013 | 0.0002 | 0.0015 | 0.000 | 0.020 | 30.2 |
| 21 | 0.870 | 0.0017 | 4.54 | 0.004 | 0.866 | 0.08 | 0.41 | 12.7 | 0.017 | 0.245 | 0.335 | 0.029 | 3.74 | 64.8 | 0.008 | <blk | 0.0003 | 0.000 | 0.008 | 49.2 | |
| 22 | 2.501 | 0.0045 | 18.2 | 0.104 | 0.471 | 0.13 | 7.71 | 51.4 | 0.042 | 0.704 | 0.719 | 0.255 | 3.46 | 54.2 | 0.009 | 0.0012 | 0.0018 | <blk | 0.018 | 52.2 | |
| 23 | 1.872 | 0.0023 | 14.2 | 0.0183 | 0.432 | 0.11 | 5.64 | 23.2 | 0.030 | 0.271 | 0.498 | 0.093 | 4.22 | 40.1 | 0.011 | <blk | 0.0009 | 0.002 | 0.030 | 41.5 | |
| 25 | 1.876 | 0.0018 | 10.3 | 0.0467 | 0.232 | 0.06 | 16.7 | 40.5 | 0.070 | 0.425 | 0.512 | 0.064 | 6.30 | 53.3 | 0.011 | <blk | 0.0005 | <blk | 0.023 | 29.7 | |
| Plateaux Batéké | 14 | 0.629 | 0.0033 | 11.6 | <blk | 0.224 | 0.09 | 4.85 | 17.8 | 0.039 | 0.292 | 0.313 | 0.079 | 0.800 | 5.81 | 0.013 | <blk | 0.0011 | 0.001 | 0.007 | 5.33 |
| 15 | 0.140 | 0.0082 | 29.0 | <blk | 0.118 | 0.06 | 5.48 | 16.3 | 0.037 | 0.420 | 0.149 | 0.018 | 0.271 | 0.889 | 0.007 | <blk | 0.0095 | <blk | 0.007 | 2.18 | |
| 16 | 0.174 | 0.0051 | 19.1 | <blk | 0.135 | 0.06 | 7.95 | 6.6 | 0.040 | 0.218 | 0.119 | 0.028 | 0.491 | 1.93 | 0.007 | <blk | 0.0047 | <blk | 0.009 | 3.69 | |
| Group | Sample number | La | Ce | Pr | Nd | Sm | Eu | Gd | Tb | Dy | Ho | Er | Tm | Yb | Lu | Th | U | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ppb (μg.l−1) | ||||||||||||||||||||
| Mbei tributaries | 1 | 0.101 | 0.113 | 0.0187 | 0.0719 | 0.0126 | 0.0061 | 0.0128 | 0.0018 | 0.0101 | 0.0021 | 0.0062 | 0.0011 | 0.0055 | 0.0006 | 0.0063 | 0.0036 | |||
| 2 | 0.0183 | 0.0352 | 0.0039 | 0.0168 | 0.0036 | 0.0049 | 0.0030 | 0.0004 | 0.0024 | 0.0005 | 0.0014 | 0.0002 | 0.0014 | 0.0002 | 0.0018 | 0.0019 | ||||
| 3 | 0.0221 | 0.0467 | 0.0050 | 0.0221 | 0.0039 | 0.0048 | 0.0041 | 0.0004 | 0.0031 | 0.0006 | 0.0019 | 0.0002 | 0.0021 | 0.0001 | 0.0048 | 0.0027 | ||||
| 4 | 0.0351 | 0.0692 | 0.0083 | 0.0342 | 0.0066 | 0.0046 | 0.0064 | 0.0008 | 0.0049 | 0.0010 | 0.0036 | 0.0004 | 0.0032 | 0.0003 | 0.0059 | 0.0035 | ||||
| Ogooué R. main channel | 18 | 0.0124 | 0.0222 | 0.0025 | 0.0100 | 0.0019 | 0.0023 | 0.0018 | 0.0002 | 0.0012 | 0.0002 | 0.0007 | 0.0001 | 0.0003 | 0.0001 | 0.0012 | 0.0026 | |||
| 17 | 0.00925 | 0.0191 | 0.0021 | 0.0092 | 0.0018 | 0.0026 | 0.0016 | 0.0002 | 0.0012 | 0.0002 | 0.0008 | 0.0001 | 0.0005 | 0.0001 | 0.0021 | 0.0036 | ||||
| 20 | 0.0127 | 0.0224 | 0.0023 | 0.0098 | 0.0018 | 0.0020 | 0.0013 | 0.0002 | 0.0010 | 0.0002 | 0.0005 | 0.0000 | 0.0006 | 0.0000 | <blk | 0.0041 | ||||
| 26 | 0.0263 | 0.0582 | 0.0070 | 0.0271 | 0.0054 | 0.0045 | 0.0053 | 0.0007 | 0.0036 | 0.0008 | 0.0022 | 0.0004 | 0.0025 | 0.0003 | 0.0169 | 0.0074 | ||||
| 8 | 0.0366 | 0.0742 | 0.0086 | 0.0354 | 0.0071 | 0.0043 | 0.0060 | 0.0007 | 0.0033 | 0.0006 | 0.0021 | 0.0003 | 0.0019 | 0.0003 | 0.0044 | 0.0100 | ||||
| 6 | 0.0277 | 0.0496 | 0.0063 | 0.0269 | 0.0055 | 0.0045 | 0.0044 | 0.0005 | 0.0032 | 0.0005 | 0.0016 | 0.0001 | 0.0019 | 0.0001 | 0.0033 | 0.0104 | ||||
| Northern Ogooué tributaries | 7 | 0.0318 | 0.0714 | 0.0070 | 0.0298 | 0.0057 | 0.0054 | 0.0054 | 0.0006 | 0.0029 | 0.0007 | 0.0021 | 0.0003 | 0.0016 | 0.0003 | 0.0032 | 0.0036 | |||
| 9 | 0.0488 | 0.0968 | 0.0117 | 0.0488 | 0.0084 | 0.0033 | 0.0085 | 0.0009 | 0.0049 | 0.0010 | 0.0032 | 0.0003 | 0.0025 | 0.0005 | 0.0033 | 0.0142 | ||||
| 10 | 0.0527 | 0.112 | 0.0121 | 0.0518 | 0.0095 | 0.0061 | 0.0094 | 0.0011 | 0.0066 | 0.0013 | 0.0037 | 0.0004 | 0.0033 | 0.0006 | 0.0198 | 0.0114 | ||||
| 11 | 0.0392 | 0.0802 | 0.0095 | 0.0382 | 0.0071 | 0.0049 | 0.0073 | 0.0009 | 0.0051 | 0.0011 | 0.0033 | 0.0005 | 0.0032 | 0.0004 | 0.0132 | 0.0045 | ||||
| 12 | 0.0275 | 0.0551 | 0.0068 | 0.0264 | 0.0049 | 0.0050 | 0.0051 | 0.0007 | 0.0042 | 0.0007 | 0.0024 | 0.0003 | 0.0023 | 0.0004 | 0.0097 | 0.0080 | ||||
| 13 | 0.0856 | 0.183 | 0.0235 | 0.0972 | 0.0208 | 0.0073 | 0.0171 | 0.0023 | 0.0132 | 0.0025 | 0.0078 | 0.0010 | 0.0070 | 0.0010 | 0.0304 | 0.0149 | ||||
| Southern Ogooué tributaries | 19 | 0.0245 | 0.0355 | 0.0045 | 0.0191 | 0.0041 | 0.0059 | 0.0032 | 0.0004 | 0.0017 | 0.0004 | 0.0010 | 0.0001 | 0.0013 | 0.0002 | 0.0023 | 0.0026 | |||
| 21 | 0.0156 | 0.0223 | 0.0031 | 0.0134 | 0.0029 | 0.0096 | 0.0025 | 0.0002 | 0.0011 | 0.0003 | 0.0008 | 0.0001 | 0.0006 | 0.0001 | 0.0014 | 0.0032 | ||||
| 22 | 0.0209 | 0.0335 | 0.0038 | 0.0158 | 0.0026 | 0.0109 | 0.0026 | 0.0003 | 0.0011 | 0.0003 | 0.0008 | 0.0001 | 0.0007 | 0.0001 | <blk | 0.0040 | ||||
| 23 | 0.0221 | 0.0416 | 0.0046 | 0.0183 | 0.0026 | 0.0088 | 0.0036 | 0.0002 | 0.0016 | 0.0003 | 0.0008 | 0.0001 | 0.0008 | 0.0001 | <blk | 0.0026 | ||||
| 25 | 0.0244 | 0.0476 | 0.0050 | 0.0201 | 0.0038 | 0.0058 | 0.0038 | 0.0002 | 0.0017 | 0.0003 | 0.0010 | 0.0001 | 0.0007 | 0.0001 | 0.0044 | 0.0071 | ||||
| Plateaux Batéké | 14 | 0.0176 | 0.0347 | 0.0037 | 0.0151 | 0.0026 | 0.0015 | 0.0027 | 0.0004 | 0.0019 | 0.0005 | 0.0012 | 0.0001 | 0.0012 | 0.0001 | <blk | 0.0036 | |||
| 15 | 0.00740 | 0.0106 | 0.0012 | 0.0053 | 0.0013 | 0.0007 | 0.0011 | 0.0001 | 0.0012 | 0.0001 | 0.0008 | <blk | 0.0004 | 0.0001 | <blk | 0.0023 | ||||
| 16 | 0.00338 | 0.0080 | 0.0011 | 0.0049 | 0.0009 | 0.0010 | 0.0010 | 0.0001 | 0.0008 | 0.0002 | 0.0010 | 0.0000 | 0.0008 | 0.0000 | 0.0002 | 0.0025 | ||||
Concentration (in ppb or μg.l−1) of trace elements in the dissolved phase (i.e., <0.22 μm) of the Ogooué and Mbei basins.
“<blk” refer to values below the blank values concentration.
The TDS (Total Dissolved Solids) concentration corresponds to the sum of the cations (Ca2+, Mg2+, Na+, and K+), the anions (, , and Cl−) and SiO2 concentrations, all expressed in mg l−1 (Table 2).
Isotopic Measurements
The chemical purification of Sr (~200 ng) was performed using extraction chromatography (Sr-SPEC resin; Eichrom) before isotope analysis according to Hajj et al. (
Discrimination of Solute Sources
To discriminate between the different river solutes sources we use a “forward method” (Garrels and MacKenzie,
Atmospheric Inputs
In the studied basins, the primary source of Cl− is precipitation as evaporite rocks are virtually absent from the Ogooué and Mbei basins (Thiéblemont et al., 2009) and because anthropogenic inputs can be considered as negligible (see section Study Area). Therefore, for all water samples, we can apply the following formula to estimate the atmospheric contribution of each solute (X) concentration ([Xrain] in μmoles l−1):
with X= , Na+, Ca2+, Mg2+, K+, and Sr2+, [] the total Cl− concentration in the river, and the X/Cl− molar ratio of seawater, considered here as the sole source of ions to the rain (Berner and Berner,
Thereafter, the “*” symbol stands for concentrations corrected from atmospheric inputs.
Contribution of Silicate and Carbonate Weathering
After correction from rainfall inputs, the dissolved load of the rivers is considered to be the result of weathering of silicate and carbonate minerals. The quantitative estimation of the sum of the cations concentrations delivered by silicate weathering ([] in mg l−1) is:
with [Xsil] the concentration of the cation X (with X = Na+, Ca2+, Mg2+ and K+) derived from silicate weathering (here in μmoles l−1) and MC the molar mass of the corresponding cation C (in g mol−1).
We consider that all the K+ and the Na+ remaining after correction from atmospheric inputs is derived from silicate weathering only:
The concentrations of Ca2+ and Mg2+ derived from silicate weathering can then be calculated as:
As the Ogooué Basin drains silicate rocks similar to those of the Congo basin (cratonic plutonic and metamorphic lithology) to estimate [Casil] and [Mgsil] and thus [] we used the value of (Ca/Na)sil = 0.35 ± 0.15 and (Mg/Na)sil = 0.24 ± 0.12 (mol/mol) determined by Négrel et al. (
Without alternative proton sources such as pyrite oxidation (e.g., Calmels et al.,
After estimating the contribution of silicate weathering to the river dissolved load, the remaining dissolved Ca2+ and Mg2+ is attributed to carbonate weathering, the result in terms of total concentration ([] in mg l−1) being therefore:
From the metrics mentioned above, we can finally calculate the three components of TDS concentration (mg l−1; Figure 5):
Where [SiO2] is the SiO2 concentration express in mg l−1, MHCO3− is the molar mass and
Note that [] is entirely derived from CO2 consumption during silicate weathering while half of the [] derives from CO2 consumption and the other half from the carbonate mineral itself. Also, note that here all SiO2 is assumed to derive from silicate weathering in these calculations. This set of [TDSi] and [] (equations 11-13) parameters indicates the concentration of TDS and TZ+ apportioned to each specific source process i (atmospheric inputs, silicate weathering, and carbonate weathering).
The fluxes (F) and area-normalized fluxes (Fspe) were calculated by multiplying the concentrations of TDS, , and CO2 sil by the discharge (Q) and the drainage area-normalized discharge (Qspe also named specific discharge), respectively (see the section Hydrological and Climate Data about the calculation of Q and Qspe). For silicate weathering we also calculated the chemical denudation (Dchem sil) expressed in m Ma−1 using the concentration of solutes (Casil, Mgsil, Ksil, Nasil, and SiO2 in mg l−1), expressed as equivalent oxides (CaO, MgO, K2O, Na2O, SiO2 in mg l−1) and using a rock density (d) of 2.7 g cm−3 (West et al., 2005; Bouchez and Gaillardet,
with MO the molar mass of O. This Dchem sil parameter expresses the rate at which silicate weathering processes result in a lowering of the Earth surface.
Hydrological and Climate Data
Drainage areas and mean slopes upstream of the sampling points were extracted from the digital elevation model SRTM 90 (Shuttle Radar Topography Mission; NASA) using ArgGis 10.3 (Esri) and QGis 2.18. The lithological composition for each sub-basin was also extracted from the lithological map of Gabon using ArcGis 10.3 (Esri) (Thiéblemont et al., 2009; see Supplementary Table 1).
The daily water discharge of the Ogooué River is available only for the Lambaréné station from Bogning et al. (
To calculate the annual discharge of other sampled sites we apply a statistical approach based on a regional polynomial relationship between specific discharge (Qspe) and rainfall (P) as performed by Scherler et al. (2017) to estimate Qspe in ungauged Himalayan rivers. We first calculated the annual mean rainfall received by each studied sub-basin from the TRMM dataset (extracted for the Ogooué Basin over the period 1998–2015 according to the TRMM data–https://gpm.nasa.gov/). The calculated rainfall for these basins ranges from 1,890 to 2,692 mm.yr−1. At the Lambaréné station, P = 2,159 mm yr−1 and Qspe is calculated according to:
with Q the discharge (136 109 m3 yr−1) and S the basin area (205.9 103 km2). At Lambaréné, Qspe is therefore equal to 666 mm yr−1 (Table 1).
Second, we compiled a new database (Supplementary Figure 2; Supplementary Table 3) for both specific discharge (Qspe) and rainfall (P) for rivers of western Central Africa (Congo: Becker et al.,
We then applied this relationship to the P-values estimated for each sub-basin of the Ogooué and Mbei basins. We used the RMSE of the fit (161 mm yr−1) as a measure of the uncertainty on these Qspe estimates (see Supplementary Figure 2), and propagated this uncertainty in the solute flux calculations (see section Solute Flux Calculation). Note that for the Ogooué River at Lambaréné station, for a rainfall of 2,159 mm yr−1, the simulated Qspe is 780 mm yr−1 while the measured Qspe was 666 mm yr−1. The difference between simulated and measured value is therefore 113 mm yr−1 (12%) and is lower than the Qspe uncertainty considered (161 mm yr−1).
Solute Flux Calculation
The area-normalized fluxes (hereafter called Fspe and “rates” when referring to weathering variables) of each solute was estimated by multiplying the concentration of each solute parameters values by the Qspe value estimated at each sampling sites. To compute the area-normalized fluxes for each sub-region of the study area, we substracted the upstream fluxes (F) where necessary (i.e., samples number 17, 20, 26, 8, 6 along the Ogooué River and sample number 10 on the Okano River).
Our river hydrochemistry dataset features only one sampling date. Therefore, the computed solute fluxes might be affected by significant uncertainty if solute concentrations were to vary along the year. We first note that in other West African rivers like the Nyong (Viers et al., 2000), the Niger (Picouet et al.,
We calculated the fluxes (F, in 103 t y−1 or 106 mol y−1) for the total dissolved solids (TDS), the total dissolved solids corrected from atmospheric inputs (TDS*), dissolved silica (express as SiO2), the cations derived from silicate weathering () and for CO2 consumption associated to silicate weathering (CO2 sil). The corresponding fluxes are called F TDS, F TDS*, F SiO2, F, and F CO2 sil, respectively. The corresponding area-normalized fluxes (also called “specific fluxes” or “rates,” equation 16, in t km−2 y−1 or 103 mol km−2 y−1) are called FspeTDS, FspeTDS*, FspeSiO2, Fspe, and Fspe CO2 sil, respectively (Table 4).
Table 4
| Group | Sample number | Qspe | basin area | Fluxes (F) | area-normalized fluxes (Fspe)) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| TDS | TDS* | SiO2 | CO2sil | TDS | TDS* | SiO2 | Dchem sil | CO2sil | ||||||
| mm yr−1 | km2 | 103 t yr−1 | 106mol yr−1 | t km−2yr−1 | m Ma−1 | 103 mol km−2 yr−1 | ||||||||
| Mbei tributaries | 1 | 890 | 13 | 0.35 ± 0.08 | 0.3 ± 0.07 | 0.15 ± 0.06 | 26.9 ± 11.3 | 23.2 ± 9.8 | 11.2 ± 4.7 | |||||
| 2 | 890 | 5 | 0.12 ± 0.03 | 0.11 ± 0.02 | 0.057 ± 0.024 | 23.5 ± 9.9 | 22.2 ± 9.3 | 11.4 ± 4.8 | ||||||
| 3 | 567 | 135 | 1.89 ± 0.64 | 1.75 ± 0.59 | 0.96 ± 0.5 | 14 ± 7.3 | 13 ± 6.7 | 7.1 ± 3.7 | ||||||
| 4 | 890 | 13 | 0.3 ± 0.06 | 0.27 ± 0.06 | 0.14 ± 0.06 | 22.5 ± 9.5 | 20.4 ± 8.6 | 10.4 ± 4.4 | ||||||
| Ogooué main | 18 | 1,631 | 8,778 | 333 ± 39 | 314 ± 37 | 176 ± 61 | 37.9 ± 13 | 35.8 ± 12.3 | 20.1 ± 6.9 | |||||
| channel | 17 | 1,650 | 14,944 | 585 ± 68 | 553 ± 64 | 323 ± 111 | 39.2 ± 13.4 | 37 ± 12.7 | 21.6 ± 7.4 | |||||
| 20 | 1,328 | 45,823 | 1,306 ± 188 | 1,209 ± 174 | 752 ± 275 | 28.5 ± 10.4 | 26.4 ± 9.6 | 16.4 ± 6 | ||||||
| 26 | 814 | 142,373 | 3,551 ± 834 | 3,337 ± 784 | 1,777 ± 778 | 24.9 ± 10.9 | 23.4 ± 10.3 | 12.5 ± 5.5 | ||||||
| 8 | 774 | 160,312 | 3,744 ± 925 | 3,502 ± 866 | 1,876 ± 840 | 23.4 ± 10.5 | 21.8 ± 9.8 | 11.7 ± 5.2 | ||||||
| 6 | 666 | 205,585 | 4,358 ± 1,090 | 4,071 ± 1,018 | 2,061 ± 515 | 21.2 ± 5.3 | 19.8 ± 5.0 | 10 ± 2.5 | ||||||
| Northern | 7 | 531 | 8,265 | 173 ± 62 | 160 ± 58 | 72 ± 39 | 20.9 ± 11.3 | 19.3 ± 10.4 | 8.7 ± 4.7 | |||||
| Ogooué | 9 | 546 | 483 | 10.2 ± 3.6 | 8.9 ± 3.1 | 3.6 ± 1.9 | 21 ± 11.2 | 18.4 ± 9.7 | 7.5 ± 4 | |||||
| tributaries | 10 | 521 | 11,135 | 197 ± 72 | 178 ± 65 | 84 ± 45 | 17.7 ± 9.6 | 16 ± 8.7 | 7.5 ± 4.1 | |||||
| 11 | 547 | 2,049 | 26.7 ± 9.3 | 24.9 ± 8.7 | 13 ± 7 | 13 ± 6.9 | 12.2 ± 6.4 | 6.2 ± 3.3 | ||||||
| 12 | 575 | 8,803 | 175 ± 58 | 165 ± 55 | 84 ± 43 | 19.9 ± 10.3 | 18.8 ± 9.7 | 9.5 ± 4.9 | ||||||
| 13 | 569 | 49,503 | 633 ± 213 | 528 ± 177 | 317 ± 165 | 12.8 ± 6.6 | 10.7 ± 5.5 | 6.4 ± 3.3 | ||||||
| Southern | 19 | 1,458 | 1,161 | 100 ± 13.1 | 96.6 ± 12.7 | 45 ± 16 | 86.1 ± 30.6 | 83.2 ± 29.5 | 38.7 ± 13.7 | |||||
| Ogooué | 21 | 1,077 | 7,582 | 601 ± 107 | 589 ± 105 | 237 ± 93 | 79.3 ± 31.1 | 77.7 ± 30.5 | 31.3 ± 12.3 | |||||
| tributaries | 22 | 880 | 2,020 | 133 ± 29 | 128 ± 28 | 42 ± 18 | 66 ± 28 | 63.1 ± 26.8 | 20.6 ± 8.7 | |||||
| 23 | 713 | 7,057 | 275 ± 74 | 264 ± 71 | 120 ± 56 | 39 ± 18.1 | 37.4 ± 17.4 | 17 ± 7.9 | ||||||
| 25 | 512 | 379 | 11.2 ± 4.2 | 10.5 ± 3.9 | 4.3 ± 2.4 | 29.4 ± 16.1 | 27.6 ± 15.1 | 11.4 ± 6.3 | ||||||
| Plateaux Batéké | 14 | 952 | 4,513 | 79.9 ± 16 | 73.7 ± 14.8 | 55 ± 23 | 17.7 ± 7.3 | 16.3 ± 6.7 | 12.2 ± 5 | |||||
| 15 | 1,694 | 4,911 | 94.1 ± 10.6 | 87.4 ± 9.9 | 81 ± 28 | 19.2 ± 6.5 | 17.8 ± 6.1 | 16.5 ± 5.6 | ||||||
| 16 | 1,672 | 5,892 | 108.5 ± 12.4 | 97.1 ± 11.1 | 92 ± 31 | 18.4 ± 6.3 | 16.5 ± 5.6 | 15.6 ± 5.3 | ||||||
| Group | Qspe | basin area | Fluxes (F) | area-normalized fluxes (Fspe)) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| TDS | TDS* | SiO2 | CO2sil | TDS | TDS* | SiO2 | Dchem sil | CO2sil | |||||
| mm yr−1 | km2 | 103 t yr−1 | 106mol yr−1 | t km−2yr−1 | m Ma−1 | 103 mol km−2 yr−1 | |||||||
| Ogooué R. (at Lambaréné station) | 666 | 205,585 | 4,358 ± 1090 | 4,071 ± 1018 | 2,061 ± 515 | 21.2 ± 5.3 | 19.8 ± 5 | 10 ± 3 | |||||
| Northern Tributaries | 558 | 80,239 | 1214 ± 637 | 1,064 ± 558 | 572 ± 300 | 15 ± 8 | 13 ± 7 | 7 ± 4 | |||||
| Southern Tributaries | 468 | 63,471 | 1,734 ± 1,001 | 1,656 ± 956 | 633 ± 365 | 27 ± 16 | 26 ± 15 | 9 ± 6 | |||||
| Plateaux Batéké | 1,467 | 15,317 | 282 ± 100 | 258 ± 91 | 227 ± 81 | 18 ± 7 | 16 ± 6 | 14 ± 5 | |||||
| Remaining area | 858 | 46,558 | 1,126 ± 482 | 1,091 ± 468 | 626 ± 268 | 24 ± 10 | 23 ± 10 | 13 ± 6 | |||||
River fluxes and area-normalized fluxes of TDS (Total dissolved solids), TDS*(Total dissolved solids corrected from atmospheric inputs), (cations derived from silicate weathering), SiO2, and CO2 sil (CO2 consumption associated to silicate weathering) in the Ogooué and Mbei Basin, and for the main domains of the Ogooué Basin.
Uncertainty calculation is described in section Uncertainty Calculation.
Uncertainty Calculation
The uncertainties associated to the calculated flux values (Tables 1, 4 and related figures) take into account the propagation of the uncertainty on the major element concentration measurements (5%), a sensitivity test performed on the Ca/Nasil and Mg/Nasil ratios used in the Equations 6 and 7, the uncertainty on the discharge estimate at each sampling location (RMSE = 161 mm yr−1), and the uncertainty associated to our relatively loose sampling time resolution (20%). Note that the propagation of the uncertainty of Ca/Nasil and Mg/Nasil produces asymmetric values and only affects F TDSsil, FF CO2 sil, and Dchemsil. In the text (sections Results and Discussion) and in the Table 4, we thus report these fluxes values as “” where F is the central estimate, and F+x and F−y the upper and lower bound of the range of estimates, respectively. According to this method, the relative uncertainties on F TDS, F TDS*, F TDSsil, F, F CO2 sil, and Dchemsil range between 11 and 84% (Table 4).
Results
In order to ease the presentation of results and the discussion thereof, we divided the samples into five groups which correspond to individual basins, as well as geomorphological and lithological units (Table 1; Figures 1, 2): The Mbei tributaries, the Northern Ogooué tributaries, the Plateaux Batéké Ogooué tributaries, the Southern Ogooué tributaries and the Ogooué River main channel. Note that the Ogooué River main channel exhibit intermediate values for all parameters (pH, conductivity, solutes concentration) indicating that its composition simply results from the mixing between the composition of the upstream tributaries inputs.
Physico-Chemical Parameters
The pH of the river water samples range between 4.63 and 7.62 and the conductivity range between 5 and 78 μS cm−1 (Table 2). Intermediate values of pH (6.62–7.10) and conductivity (16–27 μS cm−1) were recorded in the Ogooué mainstream. The two lowest values of pH (<5.5) and conductivity (<10 μS cm−1) were recorded in two tributaries draining the Plateaux Batéké (Lékoni and Passa rivers). The highest values (pH > 7.2 and conductivity > 45 μS cm−1) were recorded in the Southern Ogooué tributaries. The other rivers exhibit intermediate values (6.30 < pH < 7.18; 11 < conductivity < 34 μS cm−1). Water temperature range between 21.6 and 28.1°C. The lowest temperature values were recorded in the Mbei tributaries (21.6–22.9°C) whereas the Ogooué Basin samples exhibit a narrow temperature range (23.9–28.1°C). No direct relationship between temperature and elevation is observed. The instantaneous SPM (Suspended Particulate Matter) concentration range between 6 and 70 mg l−1 (Table 2) and its distribution does not display any clear spatial distribution.
Major Elements and Dissolved Organic Carbon
The TDS concentration (and conductivity) are variable throughout the basin and range between 11 and 75 mg l−1 (Table 2). The highest values (55–75 mg l−1) were recorded in the Southern basins, the lowest values (11–23 mg l−1) are observed in the rivers draining the sandstone region of the Plateaux Batéké, while the other groups (Northern basins, Mbei tributaries, and Ogooué main channel) exhibit intermediate values (21–39 mg l−1).
The total cationic charge (TZ+, in meq l−1) is generally dominated by Ca2+, Mg2+, and Na+ in almost equivalent proportion, while the contribution of K+ to TZ+ is systematically lower (7 to 12% of TZ+). The anionic charge (TZ−, in meq l−1) is generally dominated by (> 80% of TZ−). Concentrations of Ca2+, Mg2+, Na+, K+, , and SiO2 are significantly correlated to the conductivity and to TDS concentration and thus followed the same spatial distribution (Table 2). The SiO2 contribution to TDS concentration range from 86% (Plateaux Batéké) to 31% (Southern basins) and decrease in importance as the TDS concentration increases. Interestingly, dissolved Si concentration is correlated to concentration (R = 0.91; n = 24; p < 0.01; Figure 4B), showing that the alkalinity and, therefore, CO2 consumption associated with water-rock interactions were likely due to silicate weathering in the Ogooué and Mbei basins. The concentrations of Cl− and do not follow the same spatial distribution. We did not identify any parameter controlling the concentration distribution; however, range from 3.7 to 21 μmoles l−1 which is small by comparison with the global riverine discharge-weighted average ( 108 μmoles l−1; Burke et al.,
Figure 4

Main characteristics of the dissolved load of the tributaries of the Ogooué and Mbei basins (A) Cl− concentration as function of the centroid basin location. The dotted line represents the decreasing Cl− concentration from the coast (B) SiO2 vs. . (C)87Sr/86Sr ratio vs. Ca/Na (rock weathering end members defined by Négrel et al.,
The normalized inorganic charge balance (; note that charges borne by organic matter are not taken into account in this definition of NICB) is smaller than ±10% for most samples. For 5 samples the NICB was within 11% to 23%, which reflected an excess of cationic charge relatively to the anions (Table 2). As suggested by the weak but statistically significant correlation between DOC (see below) and NICB (R= 0.63; N = 24; p < 0.01), as previously reported for Guyana rivers (Sondag et al., 2010), and by the fact that the NICB decreased to 0% when the concentration of “inorganic” solutes increases, the on-average positive NICB is most likely due to the presence of negatively charged dissolved organic matter. Assuming a negative charge of 6 ± 0.5 μeq mg−1 of DOC (Dupré et al.,
Dissolved organic carbon concentration ranged between 0.9 and 11 mg l−1. The highest values were recorded in the Northern basins with values ranging from 4.3 to 11 mg l−1, while the other samples exhibited values ranging between 0.9 and 2.7 mg l−1.
Strontium Isotope Ratios
Dissolved 87Sr/86Sr ratios range between 0.7125 and 0.7226 over the studied basins (Table 2). According to the 87Sr/86Sr vs. Ca/Na relationship (Figure 4C) and the end members determined by Négrel et al. (
Discrimination of Solute Sources
According to the results of the source discrimination method explained in section Discrimination of Solute Sources, atmospheric inputs to river chemistry in the Ogooué and Mbei basins are low and contribute to <15% of the TDS for most of the rivers (Figure 5). Interestingly, according to this method, the entirety of river derive from atmospheric inputs. Again, this is consistent with the absence of known evaporite outcrops in the region. The atmospheric contribution to the river budget of other dissolved species is generally lower than 40% with a decreasing impact in the order: Mg2+ (40 ± 21%) > K+ (29 ± 16%) > Ca2+ (27 ± 12%) > Na+ (19 ± 21%) > Sr2+ (5 ± 3%). Given the low relative input of rain to the dissolved Sr budget, no attempt was made to correct dissolved 87Sr/86Sr ratios from the rain contribution.
Figure 5

Absolute (A) and relative (B) contributions of rainfall, carbonate weathering, and silicate weathering to the river TDS for each sampling site of the Ogooué and Mbei basins.
The Mg/Na*, Ca/Na*, and HCO3/Na* molar ratios of the sampled waters are consistent with the silicate end member previously defined for the Congo Basin (Négrel et al.,
Figure 6

Mixing diagrams indicating the source of solutes to the rivers of the Ogooué and Mbei basins (A) Mg/Na* vs. Ca/Na* and (B) HCO3/Na* vs. Ca/Na*. The “*” symbol stands for concentrations corrected from atmospheric inputs (Equation 2). The silicate, carbonate and evaporite end members defined by Gaillardet et al.,
Trace Elements
The concentrations of trace elements in the Ogooué and Mbei basins (Table 3; Figure 7), are generally lower than the global average (Gaillardet et al.,
Figure 7

Global average-normalized patterns for the river dissolved load of the Ogooué and Mbei rivers. Plain lines correspond to individual samples, whereas lines with a symbol correspond to average values for each domain defined in Table 1. Global river averages are from Gaillardet et al. (
Based on correlation analysis with other parameters (physico-chemical parameters and concentration of DOC and of major elements) across the sample set, two groups of trace elements can be distinguished. First, elements such as Be, Al, Cr, Fe, Co, Y, most REEs, Zr, Th, and U correlate positively with DOC concentration (R > 0.5; p < 0.01; Supplementary Figure 4; see for example the Fe-DOC relationship in Figure 8). In particular, the higher DOC concentration measured in the Northern Ogooué basins corresponds to higher concentration for these elements. Second, other elements such as Li, V, Cu, As, Rb, Sr, Ba, and Eu correlate positively (R > 0.5; p < 0.01) with conductivity and the concentration of most major elements, and are therefore reflective of release by rock weathering. These elements thus exhibit high concentration in the Southern basins, low concentration in the Plateaux Batéké and intermediate concentration in the other basins. We note that B concentration is strongly correlated to Cl− concentration (which might point toward a dominantly atmospheric origin of B in the Ogooué–MBei rivers), and that other elements (Ti, Mn, Ni, Nb, Cd, Cs) do not show any significant correlation with the parameters cited above. Interestingly, the elements commonly considered as weakly soluble during weathering (e.g., Al, Fe, REEs+Y) or strongly insoluble (Th, Zr) are correlated to DOC concentration in the Ogooué and Mbei basins, where they exhibit low concentration both in comparison with global rivers (Gaillardet et al.,
Figure 8

Fe vs. DOC relationship in the Ogooué and Mbei basins. The domain corresponding to the Nyong values (monthly sampling from October 1994 to January 1997; Viers et al., 2000) is added for reference.
Silicate Weathering Fluxes and Associated CO2 Consumption
Using estimates of Qspe values (specific discharge; see section Hydrological and Climate Data), the TDS and silicate weathering fluxes (F TDS and F) of the Ogooué and Mbei rivers and their tributaries were calculated. As carbonate weathering is a small contributor to the river dissolved load over the studied area, no attempt was made to estimate the corresponding river dissolved fluxes. At the Lambaréné station, the sampling location closest to the Ogooué outlet, the Ogooué river export a F TDS of 4.4 ± 1.1 Mt yr−1 including 2.1 ± 0.5 Mt yr−1 of F SiO2 and Mt yr−1 of . The corresponding Fspeare 21 ± 5.3, 10 ± 2.5 and t km−2 yr−1, respectively, and the Dchemsil was m Ma−1 (Table 4). Values of the FspeTDS, Fspe, and Dchemsil parameters are particularly variable throughout the basin (Figure 9A). The highest values (FspeTDS = 29 ± 16 to 86 ± 31 t km−2 yr−1; Fspe = to t km−2 yr−1; Dchemsil = to m Ma−1) are recorded in the Southern basins, the lowest ones are observed in the Plateaux Batéké tributaries (FspeTDS = 18 ± 7 to 19 ± 7 t km−2 yr−1; Fspe = to t km−2 yr−1; Dchemsil = to m Ma−1), while the other basins exhibit intermediate values (FspeTDS = 13 ± 7 to 39 ± 13 t km−2 yr−1; Fspe = – t km−2 yr−1; Dchemsil = – m Ma−1) (Table 4; Figure 9A). The CO2 consumption flux associated with silicate weathering (CO2 sil) is 109 mol yr−1 for the Ogooué Basin, range between 103 mol km−2 yr−1 and 103 mol km−2 yr−1, scaling with Fspe (Table 4). Spatially, the Northern basins, the Southern basins and the Plateaux Batéké tributaries contribute to around 28, 40, and 6% of the TDS export from the Ogooué at Lambaréné, respectively (for drainage areas representing 39, 31, and 7% of the total drainage area, respectively). The remaining part of the basin (the Ogooué mainstream and unsampled tributaries; 23% of the Ogooué area) contributes to 26% of the TDS flux (Figure 9B).
Figure 9

Spatial distribution of weathering fluxes in the Ogooué Basin: (A) Color map showing the spatial distribution of specific fluxes (Fspe) of TDS, , SiO2, and associated CO2 sil consumption Fspe distribution throughout the Ogooué Basin (the darkness of the color is proportional to these rates; the extreme values are reported in the caption). Note that at this scale the basins of the Mbei tributaries are too small to be visible. (B) Relative contribution of each region in term of drainage area, discharge and fluxes of TDS, , SiO2, and CO2 sil consumption. The uncertainties are reported in Table 4.
Discussion
Silicate Weathering Rates in the Ogooué and Mbei Basins, and Comparison With Regional and Global Rates
This study presents the first TDS flux estimates for the Ogooué River. With a TDS flux F TDS = 4.4 ± 1.1 106 t yr−1, the Ogooué River contributes to around 4% of the TDS flux for around 7% of the discharge of Western Africa (according to Western Africa TDS flux and discharge estimates of Milliman and Farnsworth,
These flux values estimated at the Ogooué outlet result from the mixing of waters derived from regions characterized by a variety of heterogeneous weathering rates. Indeed, the river TDS, , SiO2, associated CO2 consumption Fspe and the chemical silicate denudation (Dchemsil) estimated throughout the Ogooué Basin are heterogenous. These estimates cover the whole range of values yet measured in cratonic environments under all latitudes (Figure 10). As throughout the Ogooué Basin the area-normalized fluxes of TDS, , SiO2 (and associated CO2 consumption) as well as the Dchem sil are strongly correlated to one another (R > 0.87; p < 0.01), here we discuss only controls on the values of Fspe. At the global scale, cratonic environments exhibit a large variability in silicate weathering rates (Figure 10), ranging from 0.25 t km−2 yr−1 (Slave River, Canada; West et al., 2002) to 16 t km−2 yr−1 (Kaveri River, India; Pattanaik et al.,
Figure 10

Silicate weathering rate (Fspe in t km−2 yr−1) vs. specific discharge (Qspe) for rivers of the Ogooué and Mbei basins, and of other rivers draining cratons at the global scale. The HYBAM database provides major elements fluxes for the Upper Negro, Branco, Xingu, and Tapajos (Moquet et al.,
Among cratonic environments, no direct relationship between specific discharge and silicate weathering intensity is observed, neither at the global scale nor at the scale of the Ogooué Basin (Figure 10). The present study shows that the silicate weathering flux calculated at the outlet of the Ogooué Basin does not reflect an intrinsic property of weathering in cratonic areas (i.e., low physical erosion rates associated to low weathering rates; e.g., West, 2012), but results from the mixing of solute fluxes derived from contrasted environments in terms of weathering. In addition, our observations highlight that cratonic areas can be particularly active in terms of weathering, as in the Southern Ogooué Basin, and that the absence of tectonic activity does not necessarily imply slow weathering.
Controlling Factors of Silicate Weathering in the Ogooué Basin and Implications for the Long-Term Carbon Cycle
At the global scale, silicate weathering is controlled by a range of variables like climate, lithology, geomorphology or the presence of organic matter (e.g., Goudie and Viles,
Climate
With all things considered equal, climate is a key driver in differential weathering reaction rates, which can alter reaction temperature (e.g., Oliva et al.,
Figure 11

Relationship between silicate weathering rate (Fspe in t km−2 yr−1) and (A) specific discharge and (B) mean basin slope in the Ogooué and Mbei basins. * correspond to the basins which exhibit concentration >5 μmoles l−1. (C) Zoom on B only for basins with drainage area >500 km2. In panel A, the regression line is reported for Southern Ogooué tributaries for reference (R = 0.94; significant for p < 0.05). Error bars reflect uncertainties, the calculation of which is detailed in section Uncertainty Calculation.
Lithology
Lithology is another major factor controlling the Earth surface chemical denudation (e.g., White and Blum, 1995; Hartmann et al.,
The remaining part of the basin drains the Congo craton mainly composed of Archean and Paleoproterozoic granitic and gneissic rocks. Non-calcareous sedimentary formations (Eburnéen foreland—Francevilien D Group composed of greenish pelite with sandstone and tuffaceous intercalations; Thiéblemont et al., 2009) constitute a more important component of the underlying rocks in the Southern basins than in the Northern basins (see Supplementary Table 1). The dissolved Mg/Na* vs. Ca/Na* and HCO3/Na* vs. Ca/Na* ratios of the studied basins are relatively homogenous (Figure 6) and lie within the field of the granitic weathering end member previously defined for the Congo Basin (Négrel et al.,
Dynamics of Organic Matter and Colloids
The Northern tributaries of the Ogooué Basin drain the southern part of the Cameroon plateau and exhibits characteristics similar to those of the neighboring Nyong Basin: tectonic quiescence, low slopes, and subsequent water stagnation in swamp systems (Viers et al., 1997; Oliva et al.,
The Mbei tributaries and the Missanga River (a small Northern Ogooué tributary) exhibit the highest concentration (from 5.4 to 11 μmoles l−1) of the dataset (Table 2; Figure 11B). Some of these basins also feature the highest mean slopes of the study area (from 3.0 to 7.9%) and all drain an area <500 km2. The other Northern basins exhibit low (<1.2 μmoles l−1) concentrations and low slopes <1.3%. The concentration values recorded in the Mbei and Missanga rivers are within the range recorded in the hillslope piezometers of the experimental Nsimi watershed in the neighboring Nyong Basin (Braun et al.,
Altogether, these observations suggest that the presence or absence of flat, swampy areas exert a significant control on the export fluxes of trace elements and nitrate in the Ogooué Basin.
Relief and Erosion
The Southern tributaries of the Ogooué, which exhibit the highest weathering rates of the whole basin, contain DOC concentrations similar to those of rivers draining the Plateaux Batéké, and drain rocks similar to those of the Northern basins. The main characteristic of this region amongst the sub-basins of the Ogooué Basin is the relatively steeper slopes than the Northern sub-basins and the main Ogooué channel (mean slopes = 1.5–2% for the Southern sub-basins; Table 1). It is widely acknowledged that in tectonically active areas mountain uplift triggers mechanical erosion, which in turns favors the exposure of “fresh” mineral surfaces to water and reactive gases, providing a potential explanation for the high weathering rates recorded in orogenic regions (Larsen et al.,
As for mountain uplift in tectonically active areas, the most likely process for a positive influence of mantle- or lithosphere-induced dynamic on weathering in tectonically quiescent areas is the enhancement of erosion rates. However, whereas in mountains a tight coupling between erosion and weathering is required to maintain a finite regolith thickness over significant timescales (>103-104 yrs), in tropical cratonic environments mantle uplift would rather sustain regolith rejuvenation (i.e., exposure of deep regolith horizons hosting relatively unweathered primary minerals to water flowpaths in the critical zone) through long-term thinning of the lateritic cover. Regardless of the exact dynamics at play, in both cases erosion remains the main driver for “fresh” material exposure to the Earth surface. Estimates of erosion rates are not available yet for the Ogooué Basin to test this hypothesis, but the steeper slopes of the Southern basins lends support to the following scenario (Figure 11C). In the Southern Ogooué basins, higher erosion rates driven by mantle-induced dynamics or by uplift due to lithospheric instability would enhance weathering rates through accrued erosion and thinning of lateritic soils, allowing for an increase in the exposure of “fresh” mineral surfaces to reactive fluids, while in the Northern basins, the absence of uplift inhibits soil erosion and leads to the formation and the preservation of deep lateritic soils. Such scenario would imply that weathering in the Ogooué Basin operates with the “supply-limited” regime (Figure 11C), meaning that chemical weathering rates are limited by physical erosion rates (e.g., Riebe et al., 2017).
To our knowledge, this is the first time that an influence of mantle or lithosphere dynamic (also sometimes referred to as “epeirogenic” uplift by geologists) on weathering rates is proposed for cratonic areas. This hypothesis implies that erosion could affect weathering, the global long-term carbon cycle, and climate not only through the formation of the main orogenic belts in collisional contexts (Raymo and Ruddiman, 1992) but also through the slow, large-scale dynamics of the mantle and lithosphere in cratonic areas. Cratonic environments can therefore have a significant role on the continental weathering budgets, and need to be considered carefully when evaluating the global carbon cycle (Goddéris et al.,
Conclusion
Cratonic areas located in humid tropical regions have been reported to exhibit low chemical weathering rates due to a “shielding” effect of deep, mature regolith covers. Nevertheless, thanks to their wide aerial extent on intertropical surfaces, cratonic areas represent at the global scale a significant proportion of the dissolved matter delivery to the oceans. Despite this crucial significance, assessment of chemical weathering fluxes and rates in these environments is seldom conducted, and the variability in the intra-cratonic weathering rates–especially in terms of the diversity of geomorphological setting—has generally not been considered to date.
The present study allows us to quantify the chemical weathering budget of the intertropical cratonic basins of the Mbei and the Ogooué basins, Gabon, and to explore the main drivers of weathering in this context. The chemical composition (major and trace element concentration and 87Sr/86Sr ratios) of 24 river water samples taken in September 2017 was measured. Solute source discrimination shows that atmospheric inputs account for <15% of the TDS, while silicate weathering is the main TDS source. Interestingly, the hydrochemical composition of the Ogooué River at the outlet and the whole-basin silicate weathering rate are similar to those of the world average, and similar to (if not higher than) other basins of Western Africa. The significant weathering flux of the Ogooué results from contrasted weathering regimes across the basin, which cover the range of values yet recorded in cratonic basins at the global scale.
In the Ogooué and Mbei basins, three domains, submitted to similar climate, have been identified:
(i) Low weathering rates were recorded in the Plateaux Batéké (Eastern Ogooué tributaries). These low weathering rates, corresponding to the lowest values recorded in cratonic environments at the global scale, are due to a lithological effect associated with the low abundance of chemically-mobile elements in the minerals (i.e., mostly quartz) which compose the underlying Cenozoic sandstones.
(ii) Intermediate weathering rates, comparable to the Ogooué mainstream values, were recorded in the Mbei tributaries and the Northern Ogooué sub-basins. The higher DOC concentrations recorded in the Northern Ogooué sub-basins are associated with elevated concentrations of classically insoluble elements (e.g., Fe, Al, Th, Zr, REEs) suggesting a prominent control of colloidal transport in these basins. In these rivers, our data also show that active nitrification occurs on hillslopes while denitrification is promoted in swamp areas in the valleys.
(iii) The highest weathering rates were recorded in the Southern Ogooué tributaries basins. The rim of the Congo Cuvette drained by these tributaries is submitted to active mantle uplift, which enhances soil erosion, and leads to the dismantlement of soils and to increased availability of fresh mineral surfaces to reactive fluids, thereby promoting higher weathering rates.
In addition to the lithological effect observed in the Plateaux Batéké and to the role of organic matter in Northern basins, the novelty of the present study is to hypothesize that mantle-induced dynamic uplift or lithospheric destabilization in cratonic areas can significantly enhance chemical weathering rates by leading to soil erosion and bringing fresh rocks in contact with meteoric water. As a corollary, the cratonic zones may also host hot-spots of weathering. These Earth surface movements of long spatial (100–1,000 km) and temporal (tens of millions years) wavelengths should be considered, along with the establishment of major orogenic belts linked to plate collision, in models of the global long-term carbon cycle and climate. The drivers of weathering in shield environments thus need deeper investigation to estimate continental weathering budgets and to constrain global-scale, long-term biogeochemical cycles.
Statements
Data availability statement
The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding author/s.
Author contributions
J-JB, JG, and JB designed the project. J-SM, J-JB, SB, and AM measured in-situ data and collected the samples. J-SM and JB performed and coordinated the chemical analyses. SB contributed to the hydroclimate data calculation. SB and J-PB contributed to the hydrological data production. EM contributed to the GIS data compilation. J-SM and JB interpreted the results with the help of J-JB and JG. J-SM wrote the manuscript with the help of JB and J-JB. JG, SC, and VR contributed to the data interpretation and revised the manuscript. M-CP contributed to the study implementation. All authors contributed to the article and approved the submitted version.
Funding
This study was supported by the project RALTERAC EC2CO INSU, by the International Joint Laboratory DYCOFAC (Dynamics of the forested ecosystems of Central Africa in a context of global change) and by the Programme Emergences of the City of Paris Chemical weathering of sediments in large tropical floodplains (agreement205DDEEES165). Parts of this work were supported by IPGP multidisciplinary programme PARI and by Paris-IdF region SESAME Grant No. 12015903 and by a grant overseen by the French National Research Agency (ANR) as part of the Investments d'Avenir Programme LabEx VOLTAIRE, 10-LABX-0100.
Acknowledgments
We especially thank Dr. Aurélie Flore Koumba Pambo for the research authorizations in Gabon, Jean-Grégoire Kayoum driver and photograph during the sampling field, Pr. Marc Benedetti (IPGP) for Dissolved Organic Carbon analyses, Caroline Gorge (IPGP) for the major element analyses, Dr. Pierre Burckel (IPGP) for trace element analyses, D. Thiéblemont (BRGM) for constructive discussions about the Ogooué river Basin geology, G. Mahé (Hydroscience Montpellier) for providing discharge and precipitation data of west African rivers, F. Guillocheau (Géosciences Rennes) for providing the regional topographic map and C. Farnetani (IPGP) for constructive discussions about mantle and lithosphere dynamics in cratons. We also thank ANPN and CIRMF for their support during the field campaign. We thank Alissa M. White, Bryan G. Moravec and Richard Wanty for their constructive recommendations along the review process.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/frwa.2020.589070/full#supplementary-material
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Summary
Keywords
chemical weathering, river hydrochemistry, Congo craton, Western Central Africa, Ogooué River basin, regolith rejuvenation
Citation
Moquet J-S, Bouchez J, Braun J-J, Bogning S, Mbonda AP, Carretier S, Regard V, Bricquet J-P, Paiz M-C, Mambela E and Gaillardet J (2021) Contrasted Chemical Weathering Rates in Cratonic Basins: The Ogooué and Mbei Rivers, Western Central Africa. Front. Water 2:589070. doi: 10.3389/frwa.2020.589070
Received
30 July 2020
Accepted
10 December 2020
Published
03 February 2021
Volume
2 - 2020
Edited by
Alexis Navarre-Sitchler, Colorado School of Mines, United States
Reviewed by
Alissa M. White, University of Arizona, United States; Bryan G. Moravec, University of Arizona, United States; Richard Wanty, Colorado School of Mines, United States
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Copyright
© 2021 Moquet, Bouchez, Braun, Bogning, Mbonda, Carretier, Regard, Bricquet, Paiz, Mambela and Gaillardet.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Jean-Sébastien Moquet jean-sebastien.moquet@cnrs-orleans.fr
This article was submitted to Water and Critical Zone, a section of the journal Frontiers in Water
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