geosciences

Article Temporal Variability of Sediments, Dissolved Solids and Dissolved Organic Matter Fluxes in the at /

Guy Dieudonne Moukandi N’kaya 1,* , Didier Orange 2,* , Sandra Murielle Bayonne Padou 1, Pankyes Datok 3 and Alain Laraque 4 1 LMEI/CUSI/ENSP/Marien N’gouabi University, BP 69 Brazzaville, Congo; [email protected] 2 Eco&Sols-UMR IRD/INRA/CIRAD/SupAgro—U. Montpellier—Place Viala, 34060 Montpellier, France 3 Laboratoire écologie Fonctionnelle et Environment, Université de Toulouse, CNRS, INPT, UPS, 31326 Castanet-Tolosan, Toulouse, France; [email protected] 4 UMR 5562 du CNRS, UR 234 de l’IRD—14, av. E. Belin, 31400 Toulouse, France; [email protected] * Correspondence: [email protected] (G.D.M.N.); [email protected] (D.O.); Tel.: +242-0665-996-14 (G.D.M.N. & D.O.)  Received: 12 August 2020; Accepted: 20 August 2020; Published: 28 August 2020 

Abstract: For three decades, the solid and dissolved fluxes of the Congo River have been regularly monitored on a monthly basis, despite 12 years of deficiencies (1994–2005). Two programs successively carried out these follow-ups: PEGI/GBF (1987–1993) and SO HYBAM (2006–2017), upstream and downstream, respectively, of the Malebo Pool near Brazzaville, the main hydrometric station of the Congo River. The objective of this study is to examine the temporal dynamic of TSS, TDS and DOC, to explore how these descriptors change over time. Comparison with the two time programs will shed more light on how these descriptors are related to discharge. Afterward, we then find a relationship between total TSS in the water column and that measured in surface for eventual estimation of TSS by remote sensing. In the last decade, compared to the PEGI/GBF period, the discharge of the Congo River was mainly marked by a 4% increase, leading to a significant change 2 1 on TDS and DOC behaviors. The TSS was quite stable (from 8.2 and 9.3 t km− yr− ) due to the low physical erosion well known in this . The TDS concentrations decreased slightly, by a simple dilution effect. However, the mineral dissolved fluxes (from 11.6 and 10.1 t km-2 yr-1) due to the chemical weathering and atmospheric inputs still predominate over the solid fluxes. Therefore, there was no radical change in the monthly geochemical regime of Congo River Basin (CRB) during these last 30 years. Contrariwise, the DOC concentration marking the biogeochemical processes significantly increased, from 9.0+/ 3.0 mg L 1 to 12.7+/ 5.0 mg L 1, due to more flooding events in − − − − the central part of the CRB. The change for the DOC fluxes is more relevant, with an increase of 45% between the two studied periods, from 11.1 106 to 16.2 106 t yr 1. This highlights the continuous × × − and actual importance of the “Cuvette Centrale” in the heart of the CRB for dissolved organic matter transport by the Congo River.

Keywords: discharge; TSS; TDS; DOC; matter fluxes; Congo River

1. Introduction Large tropical rivers have the largest matter transport capacity, due to having the largest greater volumes of water carried in their major bed [1,2]. Hence, they play a vital role in the global balance between terrestrial and marine ecosystems. Nevertheless, the processes that control the transport of sediment fluxes into the ocean are poorly understood and, because of the big size of the basins, it is often difficult to quantify these processes accurately over time [3].

Geosciences 2020, 10, 341; doi:10.3390/geosciences10090341 www.mdpi.com/journal/geosciences Geosciences 2020, 10, 341 2 of 19

For the , its sustainable socio-ecological management is an important concern related to global change. This is important because of its large size, and due to its position straddling the equator in a zone of fluctuating atmospheric exchanges along the Intertropical Convergence Zone (ITCZ). A better understanding of the evolution of its water flows, solids, and dissolved matter fluxes is still on the international scientific agenda. The current quantification of solid and dissolved fluxes in the large Congo River basin (3.7 106 km2), which covers the main part of the central African rainforest, remains poorly understood × due to the insufficiency of contemporary in situ measurements. The first measurements of Total Suspended Sediment (TSS) and Total Dissolved Solid (TDS) were carried out during the first half of the 20th century at the main hydrological station of Brazzaville/Kinshsa (BZV/KIN). A majority of 1 authors [4–15] presented TSS values with a relatively good convergence, between 20 and 40 mg L− . 1 For TDS it is similar, with values presented between 30 and 40 mg L− [5,11,12,14–21]. For Dissolved 1 Organic Carbon (DOC), all the authors [13,14] found values between 8 and 10 mg L− for analysis carried out from 1982. For TSS and TDS, pre-1968 data is the result of less accurate sampling protocols and laboratory analyses, with samples that do not regularly cover the entire hydrological cycle. In the late 1980s and early 1990s, the French research institute ORSTOM (Office de Recherche Scientifique et Technique d’Outre-Mer) (now Institut de Recherche pour le Développement, IRD) with the Congolese DGRST (Direction Générale de la Recherche Scientifique) conducted two consecutive international research programs in the northern part of the Congo River Basin between Brazzaville (Congo) and (Central African Republic). These are part of the Fluvial research operation (GBF) funded by PIRAT (Programme Interdisciplinaire de Recherche de biogéodynamique intertropicale périatlantique) and PEGI (Program for the Study of the Intertropical Geosphere) programs. The results obtained during these programs made it possible to specify the fluxes of particulate and dissolved solid and organic matters transported by the Congo River and to know precisely the seasonal and interannual variations [22–28]. After this period, and until the early 2000s, very few studies were done on this topic [26,27,29]. It is only since 2005 that the solid and dissolved fluxes of the Congo River at its main hydrometric station, Brazzaville/Kinshasa, have regularly been monitored at monthly time steps. This monitoring is done by the SO HYBAM (Observation Service of the geodynamic, hydrological and biogeochemical controls of erosion/alteration of materials in the basins of the Amazon, Orinoco and Congo) program (SOH) with the collaboration of Marien Ngouabi University of Brazzaville [30]. The first results were published by Laraque et al. (2013) [31]. At last, recent works [32–36] have quantified transport fluxes using different methods, underlining the complexity of this large basin. The objective of this study is to examine the temporal dynamic of TSS, TDS and DOC, to explore how these descriptors change over time. Comparison with the two time programs will shed more light on how these descriptors are related to discharge (i.e., hysteresis response). Afterward, we then find a relationship between total TSS in the water column and that measured at the surface for eventual estimation of TSS by remote sensing. Moreover, in this study, taking into account the insignificant surface area of the Malebo Pool compared to that of the Congo Basin, we postulate that the annual flow balances of the Congo River upstream and downstream remain similar. Even if on a seasonal scale, one can expect a low-intensity alternation of roles of sediment sink or source according to the different phases of the hydrological cycle.

2. Materials and Methods

2.1. Study Area and Sampling Stations The Congo River is the longest river in after the , and the largest river in Africa in terms of water discharge and basin size (respectively 40,500 m3 s 1 and 3.7 106 km2), second − × only to the Amazon River at the global level. The Congo River streambed forms a broad curve that crosses the equator twice (Figure 1a). This provides a very regular hydrogram (with a discharge coefficient of seasonal variation of 1.77), where the discharge inputs of the tributaries of the northern Geosciences 2020, 10, 341 3 of 19 hemisphere (e.g., Ubangi, Sangha Rivers) and south (e.g., Kasai River) succeed and complement each other. The hydrological regime of the Congo River is bimodal, typical of equatorial ones, with a main flood from November to January and a secondary flood from April to June. Its basin extends between the parallels 9◦ N and 14◦ S and the meridians 11◦ E and 34◦ E, with an approximately concentric shape around the Congolese Cuvette, as well as in terms of its relief, its geology, its climate and its vegetation cover (Figure 1a–c). The Congo River Basin (CRB) is a central depression already described by Laraque et al. (2009) [28]. Around the equator, the CRB covers an area of 3,659,900 km2 at the hydrological station of BZV/KIN, which control 98% of its total area (3,730,700 km2), with an annual 3 1 river flow of 40,500 m s− (for the period 1903–2017) [37]. In general, as pointed out by Hughes et al. (2001) [32], the CRB is essentially composed of Precambrian magmatic and metamorphic crystalline rocks with rare carbonate and evaporite rocks [33,38–40], while the central basin is composed of Quaternary alluvial deposits and clastic sedimentary rocks (Figure 1b) [41].

(a) (b)

(c) (d)

FigureFigure 1. 1.Introduction Introduction toto the study study site: site: (a ()a Overview) Overview of the of the Congo Congo River River Basin Basin (adapted (adapted from Runge, from Runge, 20072007 [42 [42]),]), ( b(b)) geology, geology, ((cc)) soil,soil, and ( (dd)) Malebo Malebo Pool; Pool; the the 2 dots 2 dots represent represent the sampling the sampling station station of the of the PEGIPEGI/GBF/GBF program program inin thethe upper part, part, and and the the sa samplingmpling station station of the of theSO/HYBAM SO/HYBAM program program in the in the lowerlower part. part.

Geosciences 2019, 9, x; doi: FOR PEER REVIEW www.mdpi.com/journal/geosciences Geosciences 2020, 10, 341 4 of 19

The main branch of the Congo River originates from the borders of Zambia and the DRC, near the basin of the Zambezi River, south of the Katanga Plateau (in the vicinity of the village of Musofi). The upper Congo River is named Lualaba upstream to at the place of the Boyoma Falls (ex. Stanley falls). Downstream Kisangani the Congo River runs across the “Cuvette Centrale” covered with swamps, floating meadows, and equatorial rain forest, which is partially flooded during flood with 1 very rare areas of dry land. Watered by 1600 to 1800 mm year− [43], this central basin consists of fluvial, clayey or sandy quaternary alluviums belonging to the Andosols class (Figure 1c), with watercourses divided in very sinuous ways, sometimes anastomosed, and often linked together by numerous natural or constructed channels favoring the flooding of the plains, as has been described by Laraque et al. (1998) [44]. There are major lakes such as Lake Tumba and Lake Maï Ndombe, which are very shallow (3–8 m), that extend over more than 3000 km2 on the left bank of the Congo River [45], and Lac Télé, which has an elliptical shape, covering 23 km2, located on the right bank of the Congo River [44]. In the northern part of the basin, the Congo River receives the Ubangui River, then downstream the Likouala aux Herbes, the Sangha and the Likouala-Mossaka rivers. The south part of this zone is representative of equatorial forest surrounded in the North by the large woody and grassy savannah from the Ubangui basin, a typical vegetation of the Sudanese climate [46]. Arriving in its last section, the Congo River collects the Batéké Rivers (Alima, Nkéni and Léfini), which drain the sandy-sandstone geological layers of the Batéké Plateau (arenosols), covered with grassy savanna and not forest (Figure 1c). These Batéké Rivers flow in deep valleys, and represent a hydrological paradox in this region, as stressed by Laraque et al. (1998) [47]. Their monthly discharges are very regular and contrast with the aridity of the vegetation cover [48]. In this region, the average annual rainfall is high (1900 mm) and the almost stable hydrological regimes do not reflect a well-marked dry season from June to August, due to the groundwater behavior [47]. Just after the Léfini, the Kasai River flows into the Congo River, where it contributes its share of organic, solid and dissolved matter. Finally, the Congo River reaches the Malebo Pool, a vast depression about 30 km in diameter, where large sand banks emerge in the low water period (Figure 1d). This river section does not receive any important tributaries. The two gauging stations for liquid, solid and dissolved fluxes of this study are located upstream and downstream of this depression. Before reaching the Ocean, the Congo River crosses the succession of Livingstone rapids, which prohibit any sea connection for boat transport, unlike most other major river basins on the planet [28].

2.2. Sampling and Analytical Measurements Before describing the methodology, we should discuss the representativeness of the two sampling stations. Indeed, the monthly samples were taken at the Maluku Trechot station for the PEGI/GBF period and at the Brazzaville/Kinshasa station (BZV/KIN) for the SOH period. These two stations, separated by less than 30 km (Figure 1d), have the same climatic characteristics. This anastomosed river section, called the Malebo Pool, has no tributaries to impact the discharge. The morphology of the riverbed with sand islands have not changed during the last 40 years (no extension of islands and no reduction of anastomosed channels). Moreover, taking into account the insignificant surface area of the Malebo Pool compared to that of the Congo Basin, we assumed that this local geomorphological shape does not impact the Congo River annual fluxes. The sampling time step for the two studied periods is monthly. The descriptive parameters of water quality (temperature T ◦C, electrical conductivity EC, pH) were measured in situ using pre-calibrated electrodes. The TDS mineral concentrations have been measured according to the protocols described in Sondag et al. (1995) [23], Laraque et al. (2013) [31], http://www.so-hybam.org/ index.php/fre/Techniques/Analyses-de-laboratoire[30], and summarized in Figure 2. During the PEGI/GBF program (1987–1993), TSS concentration was measured through a water sampling of 20 liters taken at five points along a central vertical line of the Congo River cross section at the Maluku Trechot station (upper part of the ), then sieved with a porosity of 62 µm to Geosciences 2020, 10, 341 5 of 19 Geosciences 2019, 9, x FOR PEER REVIEW 5 of 19 getto get the the sand sand particles. particles. Next, Next, one one aliquot aliquot of 1 literof 1 wasliter filteredwas filtered through through 0.45 µ 0.45m cellulose μm cellulose acetate acetate filter paperfilter paper previously previously weighed weighed in dry condition.in dry condition. After filtration, After filtration, the filter the paper filter was paper placed was in placed an oven in atan aoven temperature at a temperature of 105 ◦C of for 105 24 hours.°C for 24 After hours. leaving After the leaving oven, thethe filteroven, paper the filter is kept paper in a is desiccator kept in a beforedesiccator being before weighed being again. weighed The weight again. in The excess weight of that in excess which wasof that initially which weighed was initially before weighed heating 1 representsbefore heating the total represents suspended the total sediment suspended (TSS) insediment mg L− .(TSS) in mg L−1. ForFor the the SOH SOH program program (2006–2017), (2006–2017), each each water water sample sample was takenwas taken once at once 30–50 at cm30–50 below cm the below surface the ofsurface the central of the vertical central line vertical of the Congoline of Riverthe Congo cross section River atcross the Brazzavillesection at the/Kinshasa Brazzaville/Kinshasa station. Water samplesstation. wereWater collected samples and were filtered collected the same and day infiltered the laboratory the same using day pre-measured in the laboratory 0.45 cellulose using acetatepre‐measured filter paper 0.45 previouslycellulose acetate weighed filter in paper dry condition. previously To weighed determine in dry the condition. Total Suspended To determine Solid (TSS),the Total 500 millilitersSuspended were Solid filtered (TSS), onto 500 pre-weighedmilliliters were 0.45 filteredµm cellulose onto pre acetate‐weighed filter 0.45 paper μm under cellulose the sameacetate conditions filter paper as forunder the PEGIthe same/GBF conditions program. as for the PEGI/GBF program.

FigureFigure 2. 2. ProtocolsProtocols forfor the chemical analyses of descriptive descriptive water water quality quality parameters parameters (temperature (temperature T T°C,◦C, electrical electrical conductivity conductivity EC, EC, pH pH and and TDS). TDS).

DOCDOC waswas analyzedanalyzed withwith thethe samesame protocolprotocol forfor PEGIPEGI/GBF/GBF andand SOHSOH programs,programs, suchsuch asas thatthat describeddescribed byby SeylerSeyler etet al. al. (2006)(2006) [[27].27]. A waterwater samplesample ofof 11 literliter waswas takentaken inin thethe centercenter ofof thethe river river crosscross section section in in sterilized sterilized containers. containers. AfterAfter homogenization,homogenization, preciseprecise volumesvolumes ofof waterwater werewere filtered filtered throughthrough pre-heated pre‐heated and and pre-weighed pre‐weighed 0.70 0.70µm μ Whatmanm Whatman GFF fiberglass GFF fiberglass filters under filters reduced under pressurereduced topressure separate to dissolvedseparate dissolved and particulate and particulate matter. Thematter. water The fractions water fractions passing passing through through the filter the were filter acidifiedwere acidified on a boardon a board with with ultrapure ultrapure H3PO H34POand4 and analyzed analyzed in in the the laboratory laboratory by by high-temperature high‐temperature catalyticcatalytic oxidationoxidation methodmethod (HTCO)(HTCO) usingusing aa Shimadzu Shimadzu TOC-5OOOTOC‐5OOO InstrumentInstrument toto determine determine DOCDOC concentrationsconcentrations (Figure (Figure2 2).).

2.3.2.3.Statistical Statistical Analysis DiDifferentfferent statistical statistical analyses analyses (means, (means, standard standard deviation deviation and and coe coefficientfficient of of variation) variation) were were done done inin the the Minitab Minitab software software [ [49]49] and and calculations calculations of of the the monthly monthly fluxes fluxes of of dissolved dissolved and and solid solid elements elements usingusing the the freewarefreeware softwaresoftware HYDRACCESS [30]. [30]. The The sample sample concentration concentration of of the the day day is is estimated estimated to 1 1 to be the monthly concentration (Cm mg L ). Then, the monthly fluxes (kg s ) were calculated be the monthly concentration (Cm mg L−1).− Then, the monthly fluxes (kg s−1) −were calculated by 3 1 by multiplying the monthly concentration with the monthly discharge (Qm m 3 s −1), according to multiplying the monthly concentration with the monthly discharge (Qm m s− ), according to 1 EquationEquation (1). (1). AnnualAnnual fluxesfluxes (t (t yr yr−−1) were calculated as the sum of monthly fluxesfluxes [[50].50].

X1212 FluxFlux=K KC Cm Q Qm (1)(1)  mm× m=m11 wherewhereK Kis theis the unit unit conversion conversion factor factor taking taking into account into account the period the of period interpolation of interpolation between measured between datameasured and the data units and in the which units the in fluxes which will the befluxes expressed. will be expressed. To control the relative behavior of the TSS, TDS and DOC in relationship with the two studied periods, we propose to examine the hysteresis curves in relation to the monthly discharge. A study

Geosciences 2020, 10, 341 6 of 19

To control the relative behavior of the TSS, TDS and DOC in relationship with the two studied periods, we propose to examine the hysteresis curves in relation to the monthly discharge. A study on the distribution of TSS along the central vertical line of sampling has been carried out since 2013 at the BZV/KIN measurement section. Geosciences 2019, 9, x FOR PEER REVIEW 6 of 19 3. Results 3. Results 3.1. Temporal Dynamic of Discharges, TSS, TDS and DOC Concentrations 3.1. Temporal Dynamic of Discharges, TSS, TDS and DOC Concentrations The evolution of the monthly discharge between the two studied periods is quite similar (Figure 3a). The twoThe curves evolution are quite of the parallel, monthly with discharge a slight increase between of the 4% fortwo the studied recent period.periods Theis quite interannual similar 3 1 3 1 average(Figure is3a). 38,080 The m twos− curvesand 39,660 are quite m s −parallel,respectively with a for slight PEGI increase/GBF period of 4% and for SOH the periodrecent period. (Figure 3Theb), withinterannual a similar average standard is 38,080 deviation m3 (Tables−1 and1 ).39,660 The PEGIm3 s−/1GBF respectively period belong for PEGI/GBF to the driest period interannual and SOH hydroclimaticperiod (Figure period. 3b), with a similar standard deviation (Table 1). The PEGI/GBF period belong to the driest interannual hydroclimatic period.

60,000 60,000 48,000 55,000 PEGI/GBF (1987-1993) )

-1 50,000 50,000 39,710 SO HYBAM (2006 - 2017) .s 40,500 3 )

-1 45,000 Mean(1903-2017) s

3 40,000 40,000 (m Qm Q (m

35,000 30,000 38,080 39,660

30,000

25,000 20,000 JFMAMJJASOND 1903 1922 1941 1960 1979 1998 2017 (a) (b)

FigureFigure 3. 3.(a )(a Evolution) Evolution of monthly of monthly river river discharge discharge related related to the two to studiedthe two periods studied and periods the interannual and the periodinterannual (1903–2017). period ((1903–2017).b) Interannual (b) variation Interannual of annual variation Congo of annual River dischargesCongo River (period discharges 1903–2017). (period 1903–2017). Table 1. Interannual yearly discharge (Qy) and surface water quality parameters (temperature, pH, electrical conductivity, SiO , total dissolved solid (TDS) concentrations, dissolved organic carbon (DOC) Figure 4 shows the monthly2 variation of discharge Qm and concentrations of TSS, TDS and concentrations, total suspended solid (TSS) concentrations, and total matter (TOTAL = TDS + DOC + DOC from 1987 to 2017. The descriptive parameters of the water quality are quite similar, only that TSS) for the Congo River Outlet, calculated for the two studied periods (1987–1993 and 2006–2017). we notice more acidic waters (from 6.7 to 6.0) with a weaker conductivity (from 36.6 μS cm−1 to 28.4 μS cm−1) and a higher annual concentrationPEGI/GBF (1987–1993) in DOC for the recent period.SOH DOC (2006–2017) increased from 9.9 mgParameters L−1 to 12.7& Unitsmg L−1, a MeansignificantStd increase Max of Min 28%. Max/Min Mean Std Max Min Max/Min ± ± Qy (m3 s 1) 38,080 8.46 61,400 24,000 3.5 39,660 8.70 61,330 22,710 2.7 − ± ± TemperatureTable 1. Interannual (T ◦C) yearly- discharge- (Qy) and - surface - water quality 27.7 1.6parameters 31.7 (temperature, 20.0 pH, 1.6 pH 6.7 0.5 8.4 5.7 1.5 6.0 ±0.7 8.9 5.1 1.8 ± 2 ± ECelectrical (µs cm 1 at conductivity, 25 C) 36.6 SiO6.7, total dissolved 48.4 22.0 solid (TDS) 2.2 concentrations, 28.4 4.98 dissolved 36.0 organic 20.0 carbon 1.8 − ◦ ± ± (DOC)SiO concentrations,9.6 total1.1 suspended 15.0 solid 7.2(TSS) concentrations, 2.1 10.5 and1.1 total matter 14.4 (TOTAL 5.7 = TDS 2.5 + 2 ± ± TSS (mg L 1) 25.3 4.6 41.2 11.9 3.5 27.2 7.9 53.2 10.6 5.0 DOC + TSS)− for the Congo± River Outlet, calculated for the two studied± periods (1987–1993 and TDS (mg L 1) 36.5 5.4 48.9 23.0 2.1 31.1 3.8 39.5 18.2 2.2 − ± ± 2006–2017).DOC (mg L 1 ) * 9.9 3.0 * 17.6 * 6.2 2.8 12.7 5.0 29.3 5.2 5.6 − ± ± TOTAL (mg L 1) 71.7 --- 71.0 --- − PEGI/GBF (1987–1993) SOH (2006–2017) Std: Standard deviation. * These are the values of Seyler et al. (2006) [27] and Coynel et al. (2006) [26] for the Parametersperiod 1990–1993. & Units Mean ± Std Max Min Max/Min Mean ± Std Max Min Max/Min Qy (m3 s−1) 38,080 ± 8.46 61,400 24,000 3.5 39,660 ± 8.70 61,330 22,710 2.7 Temperature (T °C) ‐ ‐ ‐ ‐ 27.7 ± 1.6 31.7 20.0 1.6 Figure 4pHshows the monthly6.7 ± 0.5 variation 8.4 of discharge5.7 1.5 Qm and concentrations6.0 ± 0.7 8.9 of TSS,5.1 TDS and1.8 DOC fromEC 1987 (μs tocm 2017.−1 at 25 The °C) descriptive 36.6 ± 6.7 parameters 48.4 22.0 of the water2.2 quality28.4 are ± 4.98 quite similar,36.0 only20.0 that we1.8 notice 1 1 more acidicSiO waters2 (from 6.79.6 to± 1.1 6.0) with15.0 a weaker7.2 conductivity2.1 10.5 (from ± 1.1 36.6 µ14.4S cm − 5.7to 28.4 µ2.5S cm − ) 1 and a higherTSS (mg.L annual−1) concentration25.3 ± 4.6 in DOC41.2 for11.9 the recent3.5 period.27.2 DOC ± 7.9 increased 53.2 from10.6 9.9 mg5.0 L − to 1 −1 12.7 mgTDS L− ,(mg.L a significant) increase36.5 ± 5.4 of 28%.48.9 23.0 2.1 31.1 ± 3.8 39.5 18.2 2.2 TheDOC total (mg.L matter−1) transported*9.9 ± 3.0 (TOTAL*17.6 =*6.2TSS + TDS2.8 + DOC)12.7 did± 5.0 not change29.3 between5.2 5.6 the two TOTAL (mg.L−1) 71.7 1 ‐ ‐ ‐ 1 71.0 ‐ ‐ ‐ studied periods, around 71.3 mg L− , with 37% TSS (26.3 mg L− ) and 63% of total dissolved matter Std: Standard deviation. * These are1 the values of Seyler et al. (2006) [27] and Coynel et al. (2006) [26] for the (TDM = TDS + DOC) (45 mg L− ) (Table 1). However, the dissolved balance between mineral and period 1990–1993.

The total matter transported (TOTAL = TSS + TDS + DOC) did not change between the two studied periods, around 71.3 mg L−1, with 37% TSS (26.3 mg L−1) and 63% of total dissolved matter (TDM = TDS + DOC) (45 mg L−1) (Table 1). However, the dissolved balance between mineral and organic matter changed. For the more recent SOH period, DOC concentrations represent 30% of dissolved concentrations, while it was only 21% during the last PEGI period.

Geosciences 2020, 10, 341 7 of 19

Geosciences 2019, 9, x FOR PEER REVIEW 7 of 19 organic matter changed. For the more recent SOH period, DOC concentrations represent 30% of dissolvedThe measured concentrations, TSS concentrations while it was only between 21% during the two the periods last PEGI are period. quite similar, with a slight increase from 25.3 to 27.2 mg L−1. The variability during the recent period is more important.

60 70,000

60,000 50 50,000 ) 1 ‐ 40 40,000 L

) (mg

1 30,000 ‐ s

30 3 (m

20,000 Qm

20 10,000 Concentrations

,000 10 DOC TDS -10,000 TSS Qm 0 -20,0000 januaryjanvier‐‐8787 january janvier‐‐91 january janvier‐‐9595 january janvier‐99‐99 january janvier‐03‐03 january janvier‐‐0707 january janvier‐11‐11 january janvier‐15‐15 Janvier 1987 à Décembre 2017 january 1987 at december 2017

Figure 4.4.The The interannual interannual variation variation of monthly of monthly discharge discharge (Qm) and (Qm) concentrations and concentrations of total suspended of total suspendedsediment (TSS), sediment total dissolved(TSS), total solids dissolved (TDS) solids and dissolved (TDS) and organic dissolved carbon organic (DOC) carbon of the (DOC) Congo of River the Congoat Maluku River Trechot at Maluku for 1987–1993 Trechot for (PEGI 1987–1993/GBF program) (PEGI/GBF and program) at Brazzaville and /atKinshasa Brazzaville/Kinshasa for the 2006–2017 for theperiod 2006–2017 (SOH program). period (SOH Monthly program). DOC Monthly values are DOC from values December are from 1990 December to October 1990 1993 to and October during 1993 the and2006–2017 during period). the 2006–2017 period).

ThenThe measured we conclude TSS that concentrations only the dissolved between concentrations the two periods significantly are quite similar, changed with between a slight increasethe two 1 studiedfrom 25.3 periods, to 27.2 with mg L a− decrease. The variability of TDS and during an increase the recent of periodDOC. is more important. Then we conclude that only the dissolved concentrations significantly changed between the two 3.2.studied Monthly periods, Concentrations with a decrease and Fluxes of TDS and an increase of DOC.

3.2. MonthlyThe main Concentrations well‐known and characteristic Fluxes of the Congo River at its outlet is the regular monthly variation of its discharge, with a variation coefficient of 1.8 for the two studied periods (Table 2). TSS and TDSThe mainconcentrations well-known have characteristic a lower variation of the Congo coefficient River (< at its1.5); outlet only is DOC the regular concentration monthly showed variation a variationof its discharge, of 2.4 during with a variationthe period coe 1987–1993,fficient of but 1.8 forits thevariation two studied during periods the recent (Table period2). TSS is similar and TDS to thatconcentrations of TDS, at around have a lower 1.4 (Table variation 2). coefficient (< 1.5); only DOC concentration showed a variation of 2.4Monthly during the TSS period concentrations 1987–1993, are but linked its variation to the monthly during the discharge, recent period with two is similar small to peaks that ofduring TDS, theat around year, one 1.4 (Table in March,2). just before the first rise in water of the Congo River, and a second in August–September,Monthly TSS concentrations just at the beginning are linked of to the the main monthly water discharge, rise of withthe Congo two small River peaks (Figure during 5). However,the year, oneTDS inand March, DOC concentrations just before the do first not risefollow in this water pattern. of the During Congo the River, earlier and studied a second period in (1987–1993),August–September, the monthly just at TDS the beginning concentrations of the described main water a riseone‐ ofpeak the curve Congo along River the (Figure year:5 ).the However, peak of TDS andload DOC is in concentrations August (with do 42.2 not mg follow L−1) thisduring pattern. the base During flow the period. earlier studiedThe monthly period DOC (1987–1993), curve followsthe monthly a delay, TDS describing concentrations also a described one‐peak a curve one-peak with curve the maximum along the year:in November the peak (with of TDS 34.1 load mg is 1 Lin−1 August), just one (with month 42.2 before mg L −the) during discharge the peak base flowflow period.(Figure 5). The monthly DOC curve follows a delay, 1 describingDuring also the a recent one-peak period curve (2006–2017), with the maximum the monthly in November TDS concentrations (with 34.1 mg are L− lower,), just onewhile month the monthlybefore the DOC discharge concentrations peak flow are (Figure higher5). and quite similar throughout the year, in a range of 10 to 15 mg L−1. The monthly increase of DOC is more significant during the first part of the year, from January to July, which corresponds to the discharge recession period of the Congo River. Consequently, the ratio between DOC and TDM (= DOC + TDS) has significant seasonal changes, from 14% to 31% in 1987–1993, and from 24% to 37% in 2006–2017. On average, the DOC represents 29% of the total dissolved concentration during the recent period, against 21% during the previous studied period (Table 2).

Geosciences 2020, 10, 341 8 of 19

Table 2. Interannual monthly discharges (Qm) and interannual monthly concentrations of total suspended sediment (TSS), total dissolved solid (TDS), dissolved organic carbon, total dissolved matter (TDM = TDS + DOC) and DOC/TDM percentage, at the Congo River Outlet, respectively, calculated for the two studied periods (1987–1993 and 2006–2017).

PEGI/GBF Program (1987–1993) SO HYBAM Program (2006–2017) Parameters Qm TSS TDS DOC TDM DOC/TDM Qm TSS TDS DOC TDM DOC/TDM 3 1 1 1 1 1 3 1 1 1 1 1 Unit m s− mg L− mg L− mg L− mg L− % m s− mg L− mg L− mg L− mg L− % Jan. 46,979 24.95 29.53 9.40 38.93 24 48,597 21.24 24.92 14.60 39.52 37 Febr. 35,841 25.94 33.37 8.65 42.02 21 38,696 28.78 29.54 14.01 43.55 32 March 32,566 27.87 35.55 7.23 42.77 17 35,580 31.17 29.89 11.10 40.99 27 April 35,073 26.78 37.57 6.20 43.77 14 36,942 31.78 31.69 11.28 42.97 26 May 35,557 26.12 39.07 7.60 46.67 16 37,447 28.08 33.19 11.17 44.37 25 June 33,606 24.02 39.31 7.50 46.81 16 34,868 23.34 33.06 13.58 46.65 29 July 29,137 22.36 41.56 7.63 49.18 16 30,778 28.39 32.95 12.99 45.94 28 Aug. 28,663 23.17 42.22 9.25 51.47 18 30,478 27.10 34.35 10.92 45.27 24 Sept. 34,383 26.66 39.84 11.13 50.96 22 35,198 26.97 33.05 11.74 44.79 26 Oct. 39,854 26.07 36.26 14.55 50.81 29 41,592 27.23 32.18 12.73 44.92 28 Nov. 48,014 25.18 34.06 15.00 49.06 31 49,743 27.33 29.66 13.48 43.15 31 Dec. 52,774 25.22 32.15 13.30 45.45 29 55,855 24.15 26.57 15.72 42.28 37 Mean Std 37,704 7.678 25.36 1.57 36.71 3.92 9.79 3.01 46.49 4.01 21 6 39,648 7.883 27.13 3.03 30.92 2.89 12.78 1.56 43.70 2.07 29 4 Max.± 52 774± 27.87± 42.22± 15.00± 51.47± 31± 55,855± 31.78± 34.35± 15.72± 46.65± 37± Min. 28 663 22.36 29.53 6.20 38.93 14 30,478 21.24 24.92 10.92 39.52 24 Max./Min. 1.84 1.25 1.43 2.42 1.32 2.21 1.83 1.50 1.38 1.44 1.18 1.54 Geosciences 2019, 9, x FOR PEER REVIEW 8 of 19

Table 2. Interannual monthly discharges (Qm) and interannual monthly concentrations of total suspended sediment (TSS), total dissolved solid (TDS), dissolved organic carbon, total dissolved matter (TDM = TDS + DOC) and DOC/TDM percentage, at the Congo River Outlet, respectively, calculated for the two studied periods (1987–1993 and 2006–2017).

PEGI/GBF Program (1987–1993) SO HYBAM Program (2006–2017) Parame DO TD DOC/T DOC/T Qm TSS TDS Qm TSS TDS DOC TDM ters C M DM DM mg. mg Unit m3 s−1 mg L−1 mg L−1 % m3 s−1 mg L−1 mg.L−1 mg L−1 mg L−1 % L−1 L−1 38.9 Jan. 46,979 24.95 29.53 9.40 24 48,597 21.24 24.92 14.60 39.52 37 3 42.0 Febr. 35,841 25.94 33.37 8.65 21 38,696 28.78 29.54 14.01 43.55 32 2 42.7 March 32,566 27.87 35.55 7.23 17 35,580 31.17 29.89 11.10 40.99 27 7 43.7 April 35,073 26.78 37.57 6.20 14 36,942 31.78 31.69 11.28 42.97 26 7 46.6 May 35,557 26.12 39.07 7.60 16 37,447 28.08 33.19 11.17 44.37 25 7 46.8 June 33,606 24.02 39.31 7.50 16 34,868 23.34 33.06 13.58 46.65 29 1 49.1 July 29,137 22.36 41.56 7.63 16 30,778 28.39 32.95 12.99 45.94 28 8 51.4 Aug. 28,663 23.17 42.22 9.25 18 30,478 27.10 34.35 10.92 45.27 24 7 11.1 50.9 Sept. 34,383 26.66 39.84 22 35,198 26.97 33.05 11.74 44.79 26 3 6 14.5 50.8 Oct. 39,854 26.07 36.26 29 41,592 27.23 32.18 12.73 44.92 28 5 1 15.0 49.0 Nov. 48,014 25.18 34.06 31 49,743 27.33 29.66 13.48 43.15 31 0 6 13.3 45.4 Dec. 52,774 25.22 32.15 29 55,855 24.15 26.57 15.72 42.28 37 0 5 9.79 46.4 Mean ± 37,704 ± 25.36 ± 36.71 ± 39,648 ± 27.13 ± 30.92 ± 12.78 ± 43.70 ± ± 9 ± 21 ± 6 29 ± 4 Std 7.678 1.57 3.92 7.883 3.03 2.89 1.56 2.07 3.01 4.01 15.0 51.4 Max. 52 774 27.87 42.22 31 55,855 31.78 34.35 15.72 46.65 37 0 7 38.9 Min. 28 663 22.36 29.53 6.20 14 30,478 21.24 24.92 10.92 39.52 24 3 Max./M Geosciences 20201.84, 10 , 341 1.25 1.43 2.42 1.32 2.21 1.83 1.50 1.38 1.44 1.18 1.549 of 19 in.

TSS TDS TSS TDS Interannual mean (1987 ‐ 1993) Interannual mean (2006 ‐ 2017) 45 DOC Qm 60,000 45 DOC Qm 60,000 40 55,000 40 55,000 ) ) 1 ) ) ‐ 1 1 1 ‐ ‐ s ‐ 35 35 s l l

3 50,000 50,000 3

30 (m 30 (m

(mg

(mg

45,000 45,000

25 Qm 25 Qm

40,000 40,000 20 20 35,000 35,000 15 15 Discharge 30,000 30,000 Discharge

10 Concentrations 10 Concentrations 5 25,000 5 25,000 0 20,000 0 20,000 JFMAMJJASOND JFMAMJJASOND

(a) (b)

FigureFigure 5. 5.The The annual annual variation variation ofof interannualinterannual monthly concentrations concentrations of of total total suspended suspended sediment sediment (TSS),(TSS), total total dissolved dissolved solid solid (TDS)(TDS) andand dissolved organic organic carbon carbon (DOC) (DOC) (on (on left left axis) axis) at at the the Congo Congo RiverRiver Outlet Outlet related related to to the the interannual interannual monthly discharge (Q) (Q) (on (on right right axis), axis), for for (a ()a the) the PEGI PEGI period period (1987–1993)(1987–1993) and and ( b(b)) the the SOH SOH period period (2006–2017).(2006–2017).

During the recent period (2006–2017), the monthly TDS concentrations are lower, while the monthly DOC concentrations are higher and quite similar throughout the year, in a range of 10 to 15 1 mg L− . The monthly increase of DOC is more significant during the first part of the year, from January to July, which corresponds to the discharge recession period of the Congo River. Consequently, the ratio between DOC and TDM (= DOC + TDS) has significant seasonal changes, from 14% to 31% in 1987–1993, and from 24% to 37% in 2006–2017. On average, the DOC represents 29% of the total dissolved concentration during the recent period, against 21% during the previous studied period (TableGeosciences2). 2019, 9, x FOR PEER REVIEW 9 of 19 The monthly evolution of TSS, TDS and DOC fluxes follow exactly what was observed for their concentrationsThe monthly (Figure evolution6). The of TSS, seasonal TDS variationsand DOC fluxes in suspended follow exactly and dissolved what was matter observed fluxes for (TSS,their TDSconcentrations and DOC) (Figure are similar 6). The to the seasonal discharge variations for the in two suspended studied periods. and dissolved The maxima matter are fluxes observed (TSS, duringTDS and the DOC) peak are flow similar of the Congoto the discharge River; the for minima the two correspond studied periods. to the low-water The maxima period. are observed during the peak flow of the Congo River; the minima correspond to the low‐water period.

kg s‐1 3 ‐1 kg s‐1 TSS m s TSS m3 s‐1 2000 TDS 60,000 2000 TDS 60,000 1800 DOC 1800 DOC Qm 50,000 Qm 50,000 1600 1600 1400 1400 40,000 40,000 1200 1200 1000 30,000 1000 30,000 800 800 20,000 20,000 600 600 400 400 10,000 10,000 200 200

0 ,0000 0 ,0000 JFMAMJJASOND JFMAMJJASOND (a) (b)

Figure 6. The annual variation of interannual monthly fluxesfluxes of total suspended sediment (TSS), total dissolved solid (TDS) and dissolved organic carbon (DOC) at the Congo River outlet, related to thethe interannualinterannual monthly dischargedischarge (Qm),(Qm), fromfrom ((aa)) 1987–1993,1987–1993, andand ((bb)) 2006–2017.2006–2017.

3.3. Annual Fluxes The interannualinterannual total total matter matter fluxes fluxes (dissolved (dissolved and and particulate) particulate) at the at Congothe Congo River River Outlet Outlet are quite are similarquite similar between between the two the studied two studied periods, periods, 1987–1993 1987–1993 and 2006–2017. and 2006–2017. During During the PEGI the/GBF PEGI/GBF period, the interannual total matter flux was 84.0 106 t yr 1 versus 87.9 106 t yr 1 during the recent period period, the interannual total matter flux was× 84.0 ×− 106 t yr−1 versus× 87.9 × −106 t yr−1 during the recent (Table 3). TSS fluxes have increased by 11%, respectively 30.2 106 to 33.6 106 t yr 1 between old period (Table 3). TSS fluxes have increased by 11%, respectively× 30.2 × 106 to× 33.6 × 10−6 t yr−1 between and recent periods. TDS fluxes have decreased by 11% (from 42.7 106 to 38.1 106 t yr 1); at the old and recent periods. TDS fluxes have decreased by 11% (from 42.7× × 106 to 38.1× × 106 t yr−−1); at the opposite the DOC fluxes have increased by 46% (from 11.1 106 to 15.1 106 t yr 1). opposite the DOC fluxes have increased by 46% (from 11.1 ×× 106 to 15.1 × 106 t yr−1−). Of course, this change has significantly impacted the water quality of the Congo River at its mouth outlet (Figure 7). In the 1990s, DOC flux represented 13% of the total matter transported with 51% of TDS and 36% of TSS. In addition, today, DOC part has increased to close to 19%, with a TDS flux decrease and quite similar with TSS flux, representing respectively 43% in TDS and 38% in TSS (Table 3 and Figure 7). Finally, the measured change between the two studied periods is very important if we consider the specific temporal flux of DOC. Indeed, the DOC flux changed from 3.1 to 4.5 t km−2 yr−1; a strong increase of around 45%.

Table 3. Interannual mean fluxes and specific fluxes of water (Qs), total suspended sediment (TSS), total dissolved solid (TDS), dissolved organic carbon, total dissolved matter (TDM = TDS + DOC) and total transported matter (TOTAL = TSS + TDM), for the two studied periods, 1987–1993 and 2006–2017.

Basin Total Qm Area at Basin TSS TDS DOC TDM TOTAL Mean Inter‐Annual Fluxes 109 m3 Station Area 106 t yr−1 106 t yr−1 106 t yr−1 106 t yr−1 106 t yr−1 yr−1 106 km2 106 km2 1987–1993 3.6 3.7 1189 30.2 42.7 11.1 53.8 84.0 ± 15.9 2006–2017 3.6 3.7 1250 33.6 38.1 16.2 54.3 87.9 ± 11.6 Qs TSS TDS DOC TDM TOTAL Specific Fluxes l s−1 km−2 t km−2 yr−1 t km−2 yr−1 t km−2 yr−1 t km−2 yr−1 t km−2 yr−1 1987–1993 10.3 8.4 11.9 3.1 14.9 23.3 ± 4.4 2006–2017 10.8 9.3 10.6 4.5 15.1 24.4 ± 3.2

Geosciences 2020, 10, 341 10 of 19

Table 3. Interannual mean fluxes and specific fluxes of water (Qs), total suspended sediment (TSS), total dissolved solid (TDS), dissolved organic carbon, total dissolved matter (TDM = TDS + DOC) and total transported matter (TOTAL = TSS + TDM), for the two studied periods, 1987–1993 and 2006–2017.

Mean Basin Area Total Basin Qm TSS TDS DOC TDM TOTAL Inter-Annual at Station Area 109 m3 yr 1 106 t yr 1 106 t yr 1 106 t yr 1 106 t yr 1 106 t yr 1 Fluxes 106 km2 106 km2 − − − − − − 1987–1993 3.6 3.7 1189 30.2 42.7 11.1 53.8 84.0 15.9 2006–2017 3.6 3.7 1250 33.6 38.1 16.2 54.3 87.9 ± 11.6 ± Specific Qs TSS TDS DOC TDM TOTAL 1 2 2 1 2 1 2 1 2 1 2 1 Fluxes l s− km− t km− yr− t km− yr− t km− yr− t km− yr− t km− yr− 1987–1993 10.3 8.4 11.9 3.1 14.9 23.3 4.4 2006–2017 10.8 9.3 10.6 4.5 15.1 24.4 ± 3.2 ±

Of course, this change has significantly impacted the water quality of the Congo River at its mouth outlet (Figure 7). In the 1990s, DOC flux represented 13% of the total matter transported with 51%

Geosciencesof TDS and2019, 36%9, x FOR of TSS.PEER InREVIEW addition, today, DOC part has increased to close to 19%, with a TDS10 of flux 19 decrease and quite similar with TSS flux, representing respectively 43% in TDS and 38% in TSS (Table 3 and Figure2006–20177). 10.8 9.3 10.6 4.5 15.1 24.4 ± 3.2

DOC DOC 13% TSS 19% TSS 36% 38%

TDS TDS 51% 43%

(a) (b)

FigureFigure 7. 7. PercentagePercentage contribution contribution in in fluxes fluxes of of total total suspended suspended sediment sediment (TSS), (TSS), total total dissolved dissolved solid solid (TDS),(TDS), and and dissolved dissolved organic organic carbon carbon (DOC) (DOC) of of the the total total matter matter fluxes fluxes transported byby thethe CongoCongo River River at atits its mouth mouth outlet outlet for: for: ( (aa)) the the 1987–1993 1987–1993 period, period, and and ( (bb)) the the 2006–2017 2006–2017 period. period.

3.4. ConcentrationsFinally, the measured of Matter Versus change Water between Discharges the two studied periods is very important if we consider 2 1 the specific temporal flux of DOC. Indeed, the DOC flux changed from 3.1 to 4.5 t km− yr− ; a strong increaseThe concentrations of around 45%. versus discharges at a monthly time step described a classical C–Q hysteresis; this could be used as a descriptor of biogeochemical behavior of the river basin [51–53]. For3.4. the Concentrations two periods, of TSS, Matter TDS versus and DOC Water monthly Discharges concentrations at the Congo River Outlet show a classic double hysteresis, linked to its bimodal river regime related to the hydrological cycle of the The concentrations versus discharges at a monthly time step described a classical C–Q hysteresis; river which begins at the end of August (Figure 8). For all the variables, the main hysteresis takes this could be used as a descriptor of biogeochemical behavior of the river basin [51–53]. For the two place from November to January, during the main flood of the river, and the second from March to periods, TSS, TDS and DOC monthly concentrations at the Congo River Outlet show a classic double June during the second small peak flow in the spring period. hysteresis, linked to its bimodal river regime related to the hydrological cycle of the river which begins at the end of August (Figure 8). For all the variables, the main hysteresis takes place from November to January, duringTSS: the PEGI/GBF main (1987 flood‐1993) of the river, and the second fromTSS :SO March HYBAM to(2006 June‐2017) during the second Ap 30 32 M ) ) small1 peak flow in the spring period. ‐ 1 ‐ L

M L 30 28 S F Jl (mg

N (mg May Ap O 28 May S O N 26 D A mean

F mean 26

24 D J 24

monthly A Ju Ju

monthly 22 Jl 22 J TSS TSS 20 20 25000 30000 35000 40000 45000 50000 55000 25000 30000 35000 40000 45000 50000 55000 60000 Q monthly mean (m3 s‐1) Q monthly mean (m3 s‐1)

TDS: PEGI/GBF 1987‐1993 TDS: SO HYBAM 2006‐2017

45 35 )

) A 1 1 ‐

A ‐ S May L L

Jl Ju O 40 May Jl

(mg S Ap (mg

Ju 30 N Ap O M F mean

mean 35 M N D

F 25 J D monthly 30

monthly

J TDS TDS 25 20 25000 30000 35000 40000 45000 50000 55000 25000 30000 35000 40000 45000 50000 55000 60000 Q monthly mean (m3 s‐1) Q monthly mean (m3 s‐1)

Geosciences 2019, 9, x FOR PEER REVIEW 11 of 19

Geosciences 2020, 10, 341 11 of 19

TSS: PEGI/GBF (1987-1993) TSS : SO HYBAM (2006-2017) Ap 30 32 M ) ) 1 - 1 M - 30 28 S F Jl Ap O N 28 May May S O N 26 D A F 26 24 D J 24 A Ju Ju 22 Jl 22 J TSS monthly mean (mg mean (mg monthly TSSL TSS monthly mean (mg mean (mg monthly TSSL 20 20 25,000 30,000 35,000 40,000 45,000 50,000 55,000 25,000 30,000 35,000 40,000 45,000 50,000 55,000 60,000 Q monthly mean (m3 s-1) Q monthly mean (m3 s-1)

TDS: PEGI/GBF 1987-1993 TDS: SO HYBAM 2006-2017

45 35 )

) A 1 1 -

A - S May Jl Ju O 40 May Jl S Ap Ju 30 N Ap O M F 35 M N D

F 25 J D 30 J TDS monthly mean (mg L TDS mean (mg monthly TDS monthly mean (mg L TDS mean (mg monthly 25 20 25,000 30,000 35,000 40,000 45,000 50,000 55,000 25,000 30,000 35,000 40,000 45,000 50,000 55,000 60,000 Q monthly mean (m3 s-1) Q monthly mean (m3 s-1)

DOC: PEGI/GBF (1990 -1993) DOC: SO HYBAM (2006-2017)

16 ) 16 D 1

N -

) O 1 - 15 D J 12 F S 14 Ju Jl N J 13 A F O 8 Jl Ju 12 M May S May

Ap mean (mg monthly DOC L 11 A M Ap DOC monthly mean (mg mean (mg monthly DOC L 4 10 25,000 30,000 35,000 40,000 45,000 50,000 25,000 30,000 35,000 40,000 45,000 50,000 55,000 60,000 3 -1 Q monthly mean (m s ) Q monthly mean (m3 s-1)

(a) (b) Figure 8. Hysteresis curves between monthly mean TSS, TDS and DOC concentrations versus mean Figure 8. Hysteresis curves between monthly mean TSS, TDS and DOC concentrations versus mean monthly discharges at the Congo River Outlet: (a) 1987–1993 period, and (b) 2006–2017 period. monthly discharges at the Congo River Outlet: (a) 1987–1993 period, and (b) 2006–2017 period. TSS and TDS C-Q curves describe a clockwise loop for both studied periods. It describes a TSS and TDS C-Q curves describe a clockwise loop for both studied periods. It describes a classic classic dilution pattern of concentration by the discharge. Relatively stable, the TSS concentrations dilution pattern of concentration by the discharge. Relatively stable, the TSS concentrations show −1 show a slight decrease in January for both studied periods (between 24 to 26 mg1 L for 1987–1993 a slight decrease in January for both studied periods (between 24 to 26 mg L− for 1987–1993 and −1 and between 22 to 26 mg1 L for 2006–2017). The TDS concentrations show a dilution effect during between 22 to 26 mg L− for 2006–2017). The TDS concentrations show a dilution effect during the the flood, underlined by the inclination of the loop for the two studied periods (between 30 to 38 mg1 flood, underlined by the inclination of the loop for the two studied periods (between 30 to 38 mg L− −1 −1 L for the 1987–1993 and between 25 to 32 mg1 L for 2006–2017). for the 1987–1993 and between 25 to 32 mg L− for 2006–2017). However, the DOC C-Q hysteresis behavior seems to have changed between the two studied However, the DOC C-Q hysteresis behavior seems to have changed between the two studied periods: from a classic dilution pattern in 1987–1993, it seems to take on a flushing pattern during the periods: from a classic dilution pattern in 1987–1993, it seems to take on a flushing pattern during recent period. Indeed, the rotation pattern of the DOC-Q hysteresis for the current period is the recent period. Indeed, the rotation pattern of the DOC-Q hysteresis for the current period is counterclockwise, while that of the PEGI period was clockwise. counterclockwise, while that of the PEGI period was clockwise.

3.5. Spatio Spatio-Temporal-Temporal DistributionDistribution of TSS CentralCentral Sampling Vertical LineLine The distribution distribution of of TSS TSS along along a vertical a vertical line inline the in middle the midd of thele river of the cross river section cross was section measured was measuredmonthly from monthly 2013 from to 2017 2013 at to the 2017 BZV at/KIN the BZV/KIN station (Figure station9 ).(Figure During 9). theDuring recent the period, recent theperiod, TSS theconcentration TSS concentration at the water at the surface water issurface always is higher always except higher in except May and in May June. and Based June. on Based three pointson three of pointsmeasurement of measurement along the verticalalong the (from vertical 0 to 11(from m depth), 0 to 11m a significant depth), a significant positive regression positive wasregression established was Geosciences 2020, 10, 341 12 of 19

Geosciences 2019, 9, x FOR PEER REVIEW 2 of 2 between the mean TSS vertical and the surface TSS concentration, with a regression coefficient of Geosciences 2019, 9, x FOR PEER REVIEW 2 of 2 R2 = 0.62 (Figure 10). [TSS: mg.l-1] 10 20 30 10 15 20 25 30 10 15 20 25 10 20 30 40 1 1 1 1 3 3 [TSS: mg.l-13] 10 20 30 10 15 20 25 30 10 15 20 25 3 10 20 30 40 5 5 15 1 1 15 7 7 37 3 3 37 59 59 59 59 117 117 117 117 139 139 139 139 Depth (m) Depth 1115 1115 1115 1115 1317 1317 1317 1317 Depth (m) Depth 1519 January 1519 1519 1519 February March April 17 17 17 17 19 January 19 19 19 February March April 10 30 50 10 15 20 25 30 10 20 30 40 10 20 30 40 1 1 1 1

3 10 30 50 3 10 15 20 25 30 3 10 20 30 40 3 10 20 30 40 15 15 15 15 37 37 37 37 59 59 59 59 117 117 117 117 139 139 139 139 1115 1115 1115 1115 1317 1317 1317 1317 1519 May 1519 1519 1519 June July August 17 17 17 17 19 May 19 19 19 June July August 10 30 50 10 15 20 25 30 10 15 20 25 10 15 20 25 30 1 1 1 1

3 10 30 50 3 10 15 20 25 30 3 10 15 20 25 3 10 15 20 25 30 15 15 15 15 37 37 37 37 59 59 59 59 117 117 117 117 139 139 139 139 1115 1115 1115 1115 1317 1317 1317 1317 1519 September 1519 1519 1519 October November December 17 17 17 17 19 September 19 19 19 October November December Figure 9. Spatial and temporal distribution of mean monthly TSS concentration (during the period JanuaryFigure 9. 2013–DecemberSpatial and temporal 2017) at distribution three point ofof meanthe water monthly column TSS (Surface, concentration Middle, (during Bottom). the On period the Figure 9. Spatial and temporal distribution of mean monthly TSS concentration (during the period Januaryx-axis are 2013–December the TSS concentrations 2017) at (mg three L point−1) and of on the the water y-axis column the depth (Surface, (m). Middle, Bottom). On the January 2013–December 2017) at three point1 of the water column (Surface, Middle, Bottom). On the x-axis are the TSS concentrations (mg L− ) and on the y-axis the depth (m). x-axis are the TSS concentrations (mg L−1) and on the y-axis the depth (m). 50

) 50

-1 40 )

-1 40 30 30 20 y = 0.652x + 8.638 20 R² = 0.617 10 y = 0.652x + 8.638 [TSS]Section (mgL R² = 0.617 10 [TSS]Section (mgL 0 0 1020304050 0 [TSS] surface (mg L-1) 0 1020304050 -1 Figure 10. Average vertical TSS concentration[TSS] versus surface surface (mg L TSS) concentration for Congo River at Figure 10. Average vertical TSS concentration versus surface TSS concentration for Congo River at BZV/KIN during SOH program. BZV/KIN during SOH program. Figure 10. Average vertical TSS concentration versus surface TSS concentration for Congo River at 4. DiscussionBZV/KIN during SOH program. Based on the longest serial data records of the Congo River discharge at its outlet, from 1903 3 1 to 2017, the yearly module of the Congo River at its main station is 40,500 m s− . On this long temporal chronicle, the evolution of the flows during the two studied periods presents a hydroclimatic

Geosciences 2020, 10, 341 13 of 19

3 1 3 1 deficit for the PEGI period (38,080 m s− ) and a hydroclimatic normal stage for SOH (39,660 m s− ). The Congo River discharge slightly increased by 4% for each month throughout the year (Figure 3a). 1 The interannual mean TSS concentrations appear to be similar, from 25.3 mg L− in 1987–1993 to 1 27.2 mg L− in 2006–2017 (Table 1). By consequence, the total suspended flux transported by the Congo 6 6 1 River at its mouth is very stable between the two studied periods, from 30.2 10 to 33.6 10 t yr− , × × 2 which demonstrates no significant change on the specific erosion of the CRB, from 8.4 to 9.3 t km− 1 yr− (Table 3). This small increase of 1 unit could be attributed to the small increase of the discharge and not at all from any anthropogenic impact on the forest cover. These TSS values are similar to those obtained by Laraque et al. (2013) [31], who studied a shorter chronicle (2006–2010), and correspond to the same order of magnitude of erosion rates previously published and determined by different independent methods [25,29,35,36,54,55]. We note that a TSS flux of 31.2 106 t yr 1 was calculated by Gibbs (1967) [8]. × − Therefore, the Congo River Basin is particularly characterized by a very stable mechanical erosion along the last 30 years (from 1987 to 2017). In addition, based on the calculation of Gibbs (1967) [8], we might conclude that the erosion did not change from the 1960s. Compared to the major rivers of 2 the planet, we confirm that the erosion on the CRB is very low. For instance, Amazon (1509.3 t km− 1 2 1 2 1 yr− )[56] and Orinoco (88.5 t km− yr− )[31] in , or Mekong (625 t km− yr− )[55] 2 1 and Red River in (600 t km− yr− )[57] have much higher values of specific erosion. Within the African , the Congo River is only ahead of the Senegal River, which has a specific degradation 2 1 calculated over 9 years of 16.7 t km− yr− [51]. In contrast, the total dissolved solid TDS transported by the Congo River at its mouth significantly changed in terms of concentrations (from 36.7+/ 3.9 mg L 1 to 30.9+/ 2.9 mg L 1) and fluxes (from − − − − 42.7 106 to 38.1 106 t yr 1) between the two studied periods. Throughout the year, the TDS × × − concentrations are the lowest during the peak flow due to the classic dilution effect. The maximum occurs during the low flow in August. This scheme was observed from the fluxogram of the two studied periods. The decrease of 11% of TDS fluxes might be attributed partially to the increase of the discharge. On the other hand, the weak predominance in TDS could come from low cation concentrations in the lixiviation waters, as the soils appear to have already leached from most of their dissolved elements over time as underlined by Laraque et al. (1998b) [47]. If there were some specific point source of pollution due to the recent human land-use, the large amount of water volume transported by the Congo River is always efficient to dilute these human disruptions. 2 1 The specific chemical weathering decreased slightly on these last 30 years, from 11.9 t km− yr− 2 1 to 10.6 t km− yr− (Table 3). These values of geochemical erosion range the CRB in thirtieth position worldwide and first position for Africa just before the Zambezi River [22]. These comparisons are indicative and deserve to be re-evaluated. Indeed, on the one hand, the methods of operation and calculation vary according to the authors and the periods of study, and do not always concern interannual averages, which moreover were not established at the same periods. On the other hand, the specific dissolved fluxes calculated here are not corrected by atmospheric inputs, whose relative influence is all the more important as the water is not very polluted. Thus, for dissolved matter of Congo River, Nkounkou and Probst (1987) [21] estimate the atmospheric inputs at 34% of the TDS fluxes. The change for the DOC fluxes is more relevant, with an increase of 45% between the two 1 1 6 studied periods, from 9.0+/ 3.0 mg L− to 12.7+/ 5.0 mg L− in concentrations and from 11.1 10 to 6 1 − − × 16.2 10 t yr− in fluxes. These DOC concentrations are a little bit more important than the values × 1 published in early 1980s, with 8 to 10 mg L− [13,14]. The dissolved organic carbon comes essentially from the Congolese basin, covered with a tropical forest flooded to semi-flooded depending on the hydrological cycle [25,26,58,59]: the DOC concentration increases with the increase of the discharge. It is exactly the pathway observed during the period 1987–1993 (Figure 4). The DOC concentration increases in relation to the production of humic and fulvic acids from the central forest and swamps, which also causes a drop in pH [28,59], as shown in Table 1. In the same way, a first previous study Geosciences 2020, 10, 341 14 of 19 of DOC variations in the 1950s [60] suggested that the left bank tributaries strongly contribute to the supply of dissolved organic matter. This therefore confirms the scenario according to which during the period of high flow, the forest of the Congolese basin is flooded and brings large amounts of DOC through the tributaries of the left and right banks [44,47]. This natural framework of the Congolese basin functioning implies a decrease in the monthly DOC concentrations during the low flow, which we observed for the two periods studied, although with different amplitudes. During the recent period, 1 the monthly DOC concentrations were more stable throughout the whole year, from 11 to 16 mg L− (Figure4, Table2). The hysteresis features between concentrations and discharges describe a consistent bimodal pattern across the last 30 years for TSS and TDS, and not for DOC. In this study, we showed that there is remarkable stability in the forms and patterns of C-Q hysteresis for TSS and TDS concentrations versus the Congo River discharges, describing a bimodal clockwise loop. The hysteresis loop is double because of the bimodal regime of the river. DOC-Q hysteresis does not have this recurring characteristic, with either clockwise or counterclockwise bimodal shapes, respectively, in 1986–1993 and 2006–2017. This prevents their classification in a general model [52,53]. If we consider a still slow evolution of human activities inside the CRB [61], we may assume that the recent DOC change in the Congo River’s fluxes should be attributed to the slight increase of the Congo River. This change may be due to the higher discharges in the SOH period compared to the PEGI/GBF period, leading to greater flooding of the Cuvette Centrale, which will therefore release more DOC. Finally, the Total Dissolved Matter TDM (= TDS + DOC) is notably stable between the two studied periods, despite the 4% increase in flows. Interannual TDM fluxes remain relatively stable due to the reverse compensating effect of TDS and DOC, around 54 106 t yr 1 (i.e., 15 t km 2 yr 1). × − − − During a hydrological year, the Congo River in Brazzaville/Kinshasa benefits from hydro-sedimentary inputs from its various tributaries, which complement each other at its different phases; this may provide the small differences (from the single to only the double of the concentrations of TSS, TDS and DOC, similar to its monthly discharges). Because of some recent results obtained in the Amazon and Orinoco basins [62–65]—two other large intertropical rivers—evaluating the river TSS fluxes based on remote sensing by river water colorimetry, we analyzed the TSS concentrations from January 2013 at three points of the central vertical line of the river cross section (Figure 9). In general, for large rivers, the velocity gradients are reversed along the water column with respect to TSS concentrations (the discharge acting as a dilutant of the TSS concentration). In fact, near the riverbed, the water velocity is lower due to the friction effect, and the TSS concentrations are higher due to Stokes law. For the Congo River at BZV/KIN, we observed the opposite (Figure 9). The slightly higher concentrations of surface TSS are an unusual feature, and can be explained by two factors. On the one hand, (i) a narrowing of the river at the outlet of the Stanley Pool can favor the mixing of the TSS by funnel effect, and/or on the other hand, (ii) those TSS already not very concentrated 1 (between 10 and 50 mg L− ) are probably mainly composed of low-density particles, which would facilitate their return to the surface. As the TSS concentrations of the three sampling depths vary concomitantly (Figure 11), it is now possible, thanks to satellite remote sensing (Landsat 8 OLI and MODIS sensors), to evaluate the TSS concentration of the Congo waters, as was successfully carried out on the Orinoco, Amazon and Guyanese rivers [62–65]. The colorimetry of waters makes it possible to link their reflectance to their surface TSS concentration. In addition, the regression of Figure 10 makes it possible to estimate the average TSS concentration in the measuring section of the Congo River. Then, using the daily flows of the day of sampling, a TSS flow is obtained. Geosciences 2020, 10, 341 15 of 19 Geosciences 2019, 9, x FOR PEER REVIEW 15 of 19

Qm (m3 s‐1) 60 60,000

50,000 50 40,000

30,000 40 ) 1 ‐ L 20,000 (mg

30 10,000 TSS

,0 20 ‐10,000

‐20,000 10

TSS Surface TSS Middle TSS Bottom Qm ‐30,000

0 ‐40,000

Figure 11. Temporal evolution of TSS sampled at different depths versus the hydrological cycle on Figure 11. Temporal evolution of TSS sampled at different depths versus the hydrological cycle on Congo River at BZV/KIN section. Congo River at BZV/KIN section. 5. Conclusions 5. Conclusion A comparison of TSS, TDS, DOC concentrations and fluxes of the Congo River at its mouth was madeA comparison from two of sets TSS, of TDS, in situ DOC data concentrations (PEGI/BGF, period: and fluxes 1987–1993 of the Congo vs. SOH, River period: at its 2006–2017).mouth was Themade results from providetwo sets a of general in situ hydrologicaldata (PEGI/BGF, and biogeochemicalperiod: 1987–1993 explanation vs. SOH, period: of the dynamics 2006–2017). of TSS,The TDSresults and provide DOC in a thegeneral Congo hydrological River during and the biogeochemical last 30 years. explanation of the dynamics of TSS, TDS and DOCBetween in the these Congo two River studied during periods, the last the Congo30 years. River discharge slightly increased by 4% and the interannualBetween mean these TSS two concentrations studied periods, appears the Congo to be River similar. discharge This confirms slightly increased that the Congo by 4% Riverand the is showinginterannual little mean degradation TSS concentrations compared to appears other of to the be world’s similar. major This rivers.confirms Contrariwise, that the Congo the dissolved River is mattershowing (mineral little degradation and organic) compared transported to by other the Congoof the River world atʹs its major mouth rivers. significantly Contrariwise, changed the in concentrationsdissolved matter and (mineral fluxes betweenand organic) the two transported studied periods. by the Congo There is River a decrease at its mouth in TDS significantly for the SOH periodchanged compared in concentrations to the PEGI and/GBF fluxes period. between Throughout the two the studied hydrological periods. cycle, There TDS is a concentrations decrease in TDS are lowestfor the during SOH period peak flow, compared due to the to classicalthe PEGI/GBF dilution period. effect. TheThroughout most observed the hydrological change is the cycle, increase TDS in DOCconcentrations concentrations are lowest between during the two peak study flow, periods, due to because the classical the higher dilution discharge effect. allowsThe most more observed intense floodingchange is of the the increase Cuvette in Centrale, DOC concentrations the main producer between of organic the two matter study in periods, this vast because basin. The the increase higher indischarge flooded allows area and more in time intense of water flooding residence of the Cuvette in the flooded Centrale, forest the at main the confluenceproducer of between organic Congomatter andin this the vast tributaries basin. The of theincrease Ubangui, in flooded Sangha, area Likouala and in time aux of Herbes, water Likoualaresidence Mossaka,in the flooded Lake forest Tumba, at Rukithe confluence may explain between the increase Congo in and DOC the contents tributaries (+31%). of the Then Ubangui, the variations Sangha, in flowLikouala rates aux between Herbes, the twoLikouala periods Mossaka, appear Lake to be Tumba, the predominant Ruki may factors explain of the the increase changes in in DOC concentrations contents (+31%). and fluxes Then of the mineralvariations and in organicflow rates dissolved between water the two components periods appear (TDS and to be DOC) the predominant of the Congo factors River atof itsthe mouth. changes in concentrationsThe monthly and pattern fluxes of the of the classical mineral C-Q and hysteresis organic annualdissolved loop water confirms components this behavior. (TDS and Due DOC) to the bimodalof the Congo annual River hydrological at its mouth. cycle of the Congo River at BZN/KIN, the bimodal pattern of hysteresis loopThe is recurrent, monthly with pattern a general of the clockwiseclassical C rotation.‐Q hysteresis However, annual during loop theconfirms current this period, behavior. the DOC-Q Due to hysteresisthe bimodal has annual changed hydrological to counterclockwise, cycle of the highlighting Congo River the flooding at BZN/KIN, impact the of the bimodal Cuvette pattern Centrale of leachinghysteresis more loop DOC. is recurrent, with a general clockwise rotation. However, during the current period, the DOCAnother‐Q hysteresis highlight has of this changed study isto the counterclockwise, relative homogeneity highlighting of the TSS the along flooding a vertical impact gradient of the studiedCuvette inCentrale the middle leaching of the more BZV DOC./KIN river cross-section. This relative homogeneity can be explained by theAnother hydrodynamic highlight characteristics of this study ofis the sectionrelative and homogeneity by the composition of the TSS and along the a density vertical of gradient the TSS. studied in the middle of the BZV/KIN river cross‐section. This relative homogeneity can be explained by the hydrodynamic characteristics of the section and by the composition and the density

Geosciences 2020, 10, 341 16 of 19

It should be interesting to assess the solid matter fluxes of the Congo River at its mouth through remote sensing techniques. The relative stability of the hydro-sediments and bio-geochemical descriptors of the Congo River at BZV/KIN underlines the inertia of this large hydrographic basin straddling the equator, which remains dominated by its pristine character. Finally, since the SO HYBAM period (2006–2017) presents an average inter-annual flow similar to that of the entire period of available flows since 1903 (1250 109 m3 yr 1), one could consider that its × − material flows are representative of the average flow from Congo to BZV/KIN over the past 115 years, 6 1 i.e., 33.6; 38.1; 16.2 and 87.9 10 t yr− , respectively, for TSS, TDS, DOC and for its total exports of × 1 2 suspended and dissolved materials to the Atlantic Ocean. Its specific flows (10.8 l s− km− , 9.3 and 2 1 15.1 t km− yr− ), respectively for Q, TSS, and TDM make it possible to compare this large intertropical 1 2 2 1 watershed with its counterparts (e.g., Orinoco River: 37.9 l s− km− , 88.5 and 41.1 t km− yr− [31]).

Author Contributions: Conceptualization, G.D.M.N. and A.L.; methodology, G.D.M.N., D.O. and P.D.; software, G.D.M.N. and S.M.B.P.; validation, D.O. and A.L.; formal analysis, G.D.M.N. and D.O.; data curation, A.L. and S.M.B.P.; writing—original draft preparation, G.D.M.N.; writing—review and editing, G.D.M.N., D.O., P.D. and A.L.; visualization, P.D., A.L. and D.O.; supervision, A.L.; project administration, G.D.M.N. and A.L.; funding acquisition, G.D.M.N. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by AUF; grant number DRACGL-2019-4100” and “The APC” did not receive any funding. Acknowledgments: Thanks go to the IRD through the SO HYBAM program and the GET Toulouse laboratory and team with the support of Marien Ngouabi University (UNMG) and Groupement d’Intérêt Economique- Service Commun d’Entretien des Voies Navigable (GIE-SCEVN). Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

1. Zhu, Y.M.; Lu, X.X.; Zhou, Y. Suspended sediment flux modeling with artificial neural network: An example of the Longchuanjiang River in the upper Yangtze catchment, China. Geomorphology 2007, 84, 111–125. [CrossRef] 2. Syvitski, J.P.M.; Kettner, A.J.; Overeem, I.; Brakenridge, G.R. Latitudinal Controls on Siliciclastic Sediment Production and Transport. In Latitudinal Controls on Stratigraphic Models and Sedimentary Concepts; SEPM Special Publication: Tulsa, OK, USA, 2017; pp. 1–15. [CrossRef] 3. Molliex, S.; Kettner, A.J.; Laurent, D.; Droz, L.; Marsset, T.; Laraque, A.; Rabineau, M.; Moukandi N’Kaya, G.D. Simulating sediment supply from the Congo watershed over the last 155 ka. Quarter. Sci. Rev. 2019, 203, 38–55. [CrossRef] 4. Van Mierlo, J.G. Le mécanisme des alluvions du Congo. Annls Ass Ingrs Éc Gand 1926, 5, 349–354. 5. Spronck, R. Mesures hydrographiques dans la région divagante de bief maritime du fleuve Congo. Mém. Inst. Roy. Colon, Sect. Sci. Technol. 1941, 3, 56. 6. Devroey, E. Le Bassin Hydrographique Congolais, Spécialement Celui du Bief Maritime; Institut Royal Colonial Belge: Brussels, Belgium, 1941; p. 172. 7. Nedeco (Netherlands Engineering Company). River Studies, Niger and Benué; North Holland Publ. Co.: Amsterdam, The Netherlands, 1959. 8. Gibbs, R.J. Amazon river - environmental factors that control Iits dissolved and suspended load. Science 1967, 156, 1203–1232. [CrossRef] 9. Van der Linden, M.J.H. Reactions between Acids and Leaf Liter. Premier Colloque Int. Biodegradation et Humification. Ph.D. Thesis, University of Nancy, Pont-à-Mousson, France, 1975. 10. Eisma, D.; Kalf, J.; Vandergaast, S.J. Suspended Matter in the Zaire Estuary and the Adjacent Atlantic Ocean. Neth. J. Sea Res. 1978, 12, 382–406. [CrossRef] 11. Meybeck, M. Note on e1ementa1 contents of the Zaïre River. Neth. J. Sea Res. 1978, 12, 293–295. [CrossRef] 12. Molinier, M. Note sur les débits et la qualité des eaux du Congo à Brazzaville. Cah. ORSTOM Sér. Hydrol. 1979, 16, 55–66. Geosciences 2020, 10, 341 17 of 19

13. Eisma, D. Suspended matter as a carrier for pollutants in estuaries and the sea. In Marine Environmental pollution, 2. Mining and Dumping; Geyer, R.A., Ed.; Elsevier: Amsterdam, The Netherlands, 1981; Volume 27, pp. 281–295. 14. Mouzeo, K. Transport Particulaire Actuel du Fleuve Congo et de Quelques Affluents; Enregistrement Quaternaire Dans L’éventail Détritique Profond (Sédimentologie, Mineralogie et Géochimie). Ph.D. Thesis, Université de Perpignan, Perpignan, France, 1986. 15. Olivry, J.C.; Bricquet, J.P.; Thiébaux, J.P.; Sigha-Nkamdjou, L. Transport de matière sur les grands fleuves des régions intertropicales: Les premiers résultats des mesures de flux particulaires sur le bassin du fleuve Congo. In Sediment Budgets; AISH: Porto-Alegre, Brazil, 1988; pp. 509–521. 16. Symoens, J.J. La minéralisation des eaux naturelles. Résultats scientifiques. Explo. hydrobiol. Bassin du Lac Bangwelo et du Luapula 1968, 2, 1–199. 17. Meybeck, M. Concentrations des eaux fluviales en éléments majeurs et apports en solution aux océans. Rev. Géol. Dyn. Géogr. Phys. 1979, 21, 215–246. 18. Deronde, L.; Symoens, J.J. L’exportation des éléments dominants du bassin du fleuve Zaïre: Une réévaluation. Ann. Limnol-Int. J. Limnol. 1980, 16, 183–188. [CrossRef] 19. Moukolo, N.; Laraque, A.; Olivry, J.-C.; Bricquet, J.P. Transport en solution et en suspension par le fleuve Congo (Zaïre) et ses principaux affluents de la rive droite. Hydrol. Sci. J. 1993, 38, 133–145. [CrossRef] 20. Meybeck, M. Carbon, nitrogen and phosphorus transport by world rivers. Am. J. Sci. 1982, 282, 401–450. [CrossRef] 21. Nkounkou, R.; Probst, J.L. Hydrology and geochemistry of the Congo River system. In Transport of Carbon and Minerals in Major World Rivers; Degens, E.T., Ed.; SCOPE/UNEP Sond, Part 4; Mitt. Geol-palaont. Insti. Univ.: Hambourg, Germany, 1987; Volume 64, pp. 483–508. 22. Laraque, A.; Briquet, J.P.; Olivry, J.C.; Berthelot, M. Transport solides et dissous du fleuve Congo (bilan de six années d’observation. In Grands Bassins Fluviaux Périatlantiques: Congo, Niger, Amazone; Olivry, J.C., Boulegue, J., Eds.; IRD: Marseille, France, 1995; pp. 133–145. 23. Sondag, F.; Laraque, A.; Riandey, C. Chimie des eaux du fleuve Congo à Brazzaville et de l’Oubangui à Bangui (années 1988 à 1992). In Grands Bassins Fluviaux Périatlantiques: Congo, Niger, Amazone; Olivry, J.C., Boulegue, J., Eds.; IRD: Marseille, France, 1995; pp. 121–131. 24. Olivry, J.C.; Briquet, J.P.; Laraque, A.; Guyot, J.L.; Bourges, J.; Roche, M.A. Flux liquides, dissous et particulaires de deux grands bassins intertropicaux: Le Congo à Brazzaville et le Rio Madeira à Villabella. In Grands Bassins Fluviaux Périatlantiques: Congo, Niger, Amazone; Olivry, J.C., Boulegue, J., Eds.; IRD: Marseille, France, 1995; pp. 345–355. 25. Gaillardet, J.; Dupré, B.; Allègre, C.J. A global chemical budget applied to the Congo Basin Rivers: Erosion rates and continental crust composition. Geochem. Cosmochim. Acta 1995, 59, 3469–3485. [CrossRef] 26. Coynel, A.; Seyler, P.; Etcheber, H.; Meybeck, M.; Orange, D. Spatial and seasonal dynamics of total suspended sediment and organic carbon species in the Congo River. Glob. Biogeochem. Cycles 2006, 19, GB4019. [CrossRef] 27. Seyler, P.; Coynel, A.; Moreira-Turcq, P.; Etcheber, H.; Colas, C.; Orange, D.; Bricquet, J.P.; Laraque, A.; Guyot, J.L.; Meybeck, M. Organic carbon transported by the equatorial rivers: Example of Zaire-Congo and Amazon Rivers. In Soil Erosion and Carbon Dynamics; Roose, E.J., Lal, R., Feller, C., Barthes, B., Stewart, B.A., Eds.; CRC Press: Boca Raton, FL, USA, 2006; Volume 15, pp. 255–274. 28. Laraque, A.; Bricquet, J.P.; Pandi, A.; Olivry, J.C. A review of material transport by the Congo River and its tributaries. Hydrol. Process. 2009, 23, 3216–3224. [CrossRef] 29. Leturmy, P.; Lucazeau, F.; Brigaud, F. Dynamic interactions between the Gulf of passive margin and the Congo River drainage basin: 1. Morphology and mass balance. J. Geophys. Res. 2003, 108, 2383. [CrossRef] 30. Hybam. So-Hybam Water Resources Observation Serve. Available online: http://www.so- hybam.org (accessed on 27 September 2019). 31. Laraque, A.; Castellanos, B.; Steiger, J.; Lopez, J.L.; Pandi, A.; Rodriguez, M.; Rosales, J.; Adèle, G.; Perez, J.; Lagane, C. A comparison of the suspended and dissolved matter dynamics of two large inter-tropical rivers draining into the Atlantic Ocean: The Congo and the Orinoco. Hydrol. Process. 2013, 1–18. [CrossRef] Geosciences 2020, 10, 341 18 of 19

32. Hughes, H.J.; Sondag, F.; Cocquyt, C.; Laraque, A.; Pandi, A.; André, L.; Cardinal, D. Effect of seasonal biogenic silica variations on dissolved silicon fluxes and isotopic signatures in the Congo River. Limnol. Oceanogr. 2011, 56, 551–561. [CrossRef] 33. Mann, P.J.; Spencer, R.G.M.; Dinga, B.J.; Poulsen, J.R.; Hernes, P.J.; Fiske, G.; Salter, M.E.; Wang, Z.A.; Hoering, K.A.; Six, J.; et al. The biogeochemistry of carbon across a gradient of streams and rivers within the Congo Basin. J. Geophys. Res. Biogeosci. 2014, 119, 687–702. [CrossRef] 34. Spencer, R.G.M.; Hernes, P.J.; Dinga, B.; Wabakanghanzi, J.N.; Drake, T.W.; Six, J. Origins, seasonality, and fluxes of organic matter in the Congo River. Glob. Biogeochem. Cycles 2016, 30.[CrossRef] 35. Guillocheau, F.; Galmier, V.; Robin, C. Source to Sink study of the Congo system since 40 Myr: A measurement ratio between mechanical and chemical erosion. In Proceedings of the Source to Sink: A Long Term Perspective of Sediment Budgets and Sources Characterization, Rennes, France, 30 November–2 December 2016. 36. Latrubesse, E.M.; Arima, E.Y.; Dunne, T.; Park, E.; Baker, V.R.; d’Horta, F.M.; Wight, C.; Wittmann, F.; Zuanon, J.; Baker, P.A.; et al. Damming the rivers of the Amazon basin. Nature 2017, 546, 363–369. [CrossRef] [PubMed] 37. Moukandi N’kaya, G.D.; Laraque, A.; Paturel, J.M.; Gulemvuga, G.; Mahé, G.; Tshimanga Muamba, R. A new look at hydrology in the Congo Basin, based on the study of multi-decadal chronicles. In Congo Basin Hydrology, Climate, and Biogeochemistry: A Foundation for the Future; Alsdorf, D., Tshimanga Muamba, R., Moukandi N’kaya, G.D., Eds.; AGU, John Wiley & Sons Inc.: Malden, MA, USA, 2021; Unpublished work. 38. Giresse, P. La succession des sédimentations dans les bassins marins et continentaux du Congo depuis le début du Mésozoïque. Sci. Géol. Bull. Strasbg. 1982, 35, 183–206. 39. Négrel, P.; Allegre, C.J.; Dupre, B.; Lewin, E. Erosion sources determined by inversion of major and trace element ratios and strontium isotopic ratios in river water: The Congo Basin case. Earth Planet. Sci. Lett. 1993, 120, 59–76. [CrossRef] 40. Giresse, P. Mesozoic-Cenozoic history of the Congo basin. J. Afr. Earth Sci. 2005, 43, 301–315. [CrossRef] 41. Dürr, H.H.; Meybeck, M.; Dürr, S.H. Lithologic composition of the Earth’s continental surfaces derived from a new digital map emphasizing riverine material transfer. Glob. Biogeochem. Cycles 2005, 19, GB4S10. [CrossRef] 42. Runge, J. The Congo River, . In Large Rivers: Geomorphology and Management; Gupta, A., Ed.; Wiley and Sons: London, UK, 2007; pp. 293–309. 43. BRLi. Développement et Mise en Place de L’outil de Modélisation et D’allocation des Ressources en eau du Bassin du Congo; Rapport technique de construction et de calage du modèle; CICOS: Kinshasa, , 2016. 44. Laraque, A.; Pouyaud, B.; Rocchia, R.; Robin, R.; Chaffaut, I.; Moutsambote, J.M.; Maziezoula, B.; Censier, C.; Albouy, Y.; Elenga, H.; et al. Origin and function of a closed depression in equatorial humid zones: The lake Tele in north Congo. J. Hydrol. 1998, 207, 236–253. [CrossRef] 45. Wei, X.; Sauvage, S.; Le, T.P.Q.; Ouillon, S.; Orange, D.; Vinh, V.D.; Sanchez-Perez, J.M. A modeling approach to diagnose the impacts of global changes on discharge and suspended sediment concentration within the Red River Basin. Water 2019, 11, 958. [CrossRef] 46. Wesselink, A.; Orange, D.; Feizouré, C.T.; Randriamiarisoa. Les régimes hydroclimatiques et hydrologiques d’un bassin versant de type tropical humide: L’Oubangui (République Centrafricaine). In L’hydrologie Tropicale: Géosciences et Outil Pour le Développement: Mélanges à la Mémoire de Jean Rodier; Chevallier, P., Pouyaud, B., Eds.; IAHS: Wallingford, UK, 1996; Volume 238, pp. 179–194. 47. Laraque, A.; Mietton, M.; Olivry, J.C.; Pandi, A. Impact of lithological and vegetal covers on flow discharge and water quality of Congolese tributaries from the Congo River. Rev. Sci. Eau. 1998, 11, 209–224. 48. Molinier, M.; Barilly, A.; Gathelier, R.; Thébé, B. Note Hydrologique sur Les Rivières Mary et Gamboma; ORSTOM: Brazzaville, Republic of the Congo, 1974. 49. Minitab. Available online: http://www.minitab.com/fr-fr/products/minitab/free-trial/ (accessed on 27 September 2019). 50. Moatar, F.; Birgand, F.; Meybeck, M.; Faucheux, C.; Raymond, S. Incertitudes sur les métriques de qualité des cours d’eau (médianes et quantiles de concentrations, flux, cas des nutriments évaluées à partir de suivis discrets). Houil. Blanc. 2009, 3, 68–76. [CrossRef] 51. Orange, D. Hydroclimatologie du Fouta Djalon et dynamique actuelle d’un vieux paysage latéritique (Afrique de l’Ouest). Sci. Géol. 1992, 93, 206. Geosciences 2020, 10, 341 19 of 19

52. Butturini, A.; Gallart, F.; Latron, J.; Vazquez, E.; Sabater, F. Cross-site comparison of variability of DOC and nitrate c–q hysteresis during the autumn–winter period in three Mediterranean headwater streams: A synthetic approach. Biogeochemistry 2006, 77, 327–349. [CrossRef] 53. Butturini, A.; Alvarez, M.; Bernal, S.; Vazquez, E.; Sabater, F. Diversity and temporal sequences of forms of

DOC and NO3-discharge responses in an intermittent stream: Predictable or random succession? J. Geophys. Res. 2008, 113, 1–10. [CrossRef] 54. Algharib, I. Apport des Isotopes a vie Moyenne de L’uranium et du Thorium, 210Pb et 10Be Dans L’étude de L’érosion Chimique et Physique de Deux Grands Bassins: Amazone et Congo. Ph.D. Thesis, Nice Sophia Antipolis University, Nice, France, 1992. 55. Summerfield, M.A.; Hulton, N.J. Natural controls of fluvial denudation rates in major world drainage basins. J. Geophys. Res. Solid Earth 1994, 99, 13871–13883. [CrossRef] 56. Degens, E.T.; Kempe, S.; Richey, J.E. Biogeochemistry of Major World Rivers, SCOPE Report 42; John Wiley & Sons: Chichester, UK, 1991. 57. Dang, T.H.; Coynel, A.; Orange, D.; Blanc, G.; Etcheber, H.; Le, L.A. Long-term monitoring (1960-2008) of the river-sediment transport in the Red River Watershed (Vietnam): Temporal variability and dam-reservoir impact. Sci. Total Environ. 2010, 408, 4654–4664. [CrossRef][PubMed] 58. Cadée, G.C. Particulate and dissolved organic matter and chlorophyll A in the Zaire River, estuary and plume. Neth. J. Sea Res. 1984, 17, 426–440. [CrossRef] 59. Orange, D. Transports de matières dans un bassin fluvial tropical humide en zone de forêt: L’Uélé au Zaïre. Sci. Géol. Bull. 1996, 49, 71–88. 60. Clerfayt, A. Composition des eaux de rivières du Congo - Influence des Facteurs Géologiques et Climatiques. In Centre Belge d’étude et de Documentation des Eaux; CEBEDEAU: Liège, Belgium, 1956; Volume 31, pp. 26–31. 61. Nguimalet, C.; Orange, D. Hydroclimatic variabilities in Tomi at Sibut, Gribingui at Kaga-Bandoro and Fafa at Bouca basins, Central-north and central-south of Central African Republic. In Proceedings of the 8th Global FRIEND-Water Conference: Hydrological Processes and Water Security in a Changing World, Beijing, China, 6–9 November 2018. 62. Espinoza Villar, R.; Martinez, J.M.; Guyot, J.L.; Fraizy, P.; Armijos, E.; Crave, A.; Bazan, H.; Vauchel, P.; Lavado, W. The integration of field measurements and satellite observations to determine river solid loads in poorly monitored basins. J. Hydrol. 2012, 444, 221–228. [CrossRef] 63. Espinoza Villar, R.; Martinez, J.M.; Le Texier, M.; Guyot, J.L.; Fraizy, P.; Meneses, P.R.; Oliveira de, E. A study of sediment transport in the Madeira River, Brazil, using MODIS remote-sensing images. J. South Am. Earth Sci. 2012, 44, 45–54. [CrossRef] 64. Yepez, S.; Laraque, A.; Martinez, J.M.; De Sa, J.; Carrera, J.M.; Castellanos, B.; Gallay, M.; Lopez, J.L. Retrieval of suspended sediment concentrations using landsat-8 OLI satellite images in the Orinoco River (Venezuela). C. R. Geosci. 2018, 350, 20–30. [CrossRef] 65. Gallay, M.; Martinez, J.M.; Mora, A.; Castellano, B.; Yepez, S.; Cochonneau, G.; Alfonso, J.A.; Carrera, J.M.; Lopez, J.L.; Laraque, A. Assessing Orinoco river sediment discharge trend using MODIS satellite images. J. South Am. Earth Sci. 2019, 91, 320–331. [CrossRef]

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).