Valier Galy
email: vgaly@whoi.edu

Christian France-Lanord

Bruno Lartiges

Loading and fate of particulate organic carbon from the Himalaya to the Ganga-Brahmaputra delta

We use the evolution of river sediment characteristics and sedimentary C org from the Himalayan range to the delta to study the transport of C org in the Ganga-Brahmaputra system and especially its fate during floodplain transit.

A detailed characterisation of both mineral and organic particles for a sampling set of river sediments allows taking into account the sediment heterogeneity characteristic of such large rivers. We study the relationships between sediment characteristics (mineralogy, grain size, specific area) and C org content in order to evaluate the controls on C org loading. Contributions 20 of C3 and C4 plants are estimated from C org stable isotopic composition ( 13 C org ). We use the evolution of 13 C org values from the Himalayan range to the delta in order to study the fate of C org during floodplain transit.

Ganga and Brahmaputra sediments define two distinct linear relations with specific area. In spite of 4 to 5 times higher specific area, Ganga sediments have similar C org content, grain size and mineralogy as Brahmaputra sediments, indicating that specific area does not exert a primary control on C org loading. The general correlation between the total C org content and Al/Si ratio indicates that C org loading is mainly related to: (1) segregation of organic particles under hydrodynamic forces in the river and, (2) the ability of mineral particles to form organo-mineral aggregates. 30

Bed and suspended sediments have distinct 13 C org values. In bed sediments, 13 C org values are compatible with a dominant proportion of fossil C org derived from Himalayan rocks erosion. Suspended sediments from Himalayan tributaries at the outflow of the range have low 13 C org values (-24.8 ‰ average) indicating a dominant proportion of C3 plant inputs. In the Brahmaputra basin, 13 C org values of suspended sediments are constant along the river course in the plain. On the contrary, suspended sediments of the Ganga in Bangladesh have higher

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13 C org values (-22.4 to -20.0 ‰), consistent with a significant contribution of C4 plant derived from the floodplain. Our data indicate that, during the plain transit, more than 50 % of the recent biogenic C org coming from the Himalaya is oxidised and replaced by floodplain C org . This renewal process likely occurs during successive deposition-erosion cycles and river 40 course avulsions in the plain.

INTRODUCTION

Interactions between atmosphere, ocean and continent determine both the shape and climate of the Earth's surface through a sequence of complex processes. Rivers play an important role in this interplay since they are the main conveyors of elements from the continents to the ocean, carrying both mineral and organic species as dissolved and particulate phases. Their role in the long-term climate regulation has long been highlighted and debated, especially through the transport of dissolved cations derived from silicate weathering (GAILLARDET et 50 al., 1999;RUDDIMAN, 1997 and ref. therein). More recently, organic carbon (C org ) transport by rivers has also been receiving more and more attention. Indeed, rivers transport particulate C org to the ocean that if buried represents a net sink of atmospheric CO 2 , and participates in the long-term climate regulation (e.g. [START_REF] Lasaga | An improved geochemical model of atmospheric CO2 fluctuations over the past 100 million years[END_REF]SUNDQUIST, 1985). Nevertheless, rivers appear to export a minor proportion of the net primary production since ca. 99% is oxidised to CO 2 in soils and returns to the atmosphere [START_REF] Mackenzie | Surface area control of organic carbon accumulation in continental shelf sediments[END_REF]. The fate of riverine C org in the oceanic system was also extensively studied as the proportion of riverine C org that is preserved determines the extent of the CO 2 sequestration (e.g. [START_REF] Goni | Distribution and sources of particulate organic matter in the water column and sediments of the Fly River Delta, Gulf of Papua (Papua New Guinea)[END_REF][START_REF] Hedges | Comparative organic geochemistries of soils ans marine sediments[END_REF]. Actually, C org mineralization in the ocean considerably reduces the C org burial flux and, at the global scale, ca. 70% of riverine C org is oxidised prior to being buried in 60 sediments [START_REF] Burdige | Burial of terrestrial organic matter in marine sediments: A reassessment[END_REF][START_REF] Hedges | Comparative organic geochemistries of soils ans marine sediments[END_REF][START_REF] Ludwig | Predicting the oceanic input of organic carbon by continental erosion[END_REF][START_REF] Schlünz | Transport of terrestrial organic carbon to the oceans by rivers: re-estimating flux and burial rates[END_REF]. The role of rivers in terrestrial C org export and burial appears to be more complex than a simple conveyor as it also has a great impact on both the flux and the composition of terrestrial C org and thus on its behaviour. This is highlighted by the contrast between different river systems in terms of terrestrial C org flux, composition and preservation in the ocean. For instance, a large river system with well-developed floodplain such as the Amazon appears to have a C org transport dynamic that is completely different from that of

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small mountainous rivers such as New Zealand rivers, Taiwanese rivers and the Eel river where the transport is very direct from the continent to the ocean (e.g. [START_REF] Aufdenkampe | Organic matter in the Peruvian headwaters of the Amazon: Compositional evolution from the Andes to the lowland Amazon mainstem[END_REF][START_REF] Blair | From bedrock to burial: the evolution of particulate organic carbon across coupled watershed-continental margin systems[END_REF]HILTON et al., in press;[START_REF] Scott | Localized erosion affects national carbon budget[END_REF]. Understanding the controls of C org loading, composition and fate during the fluvial transport is therefore crucial to address the role of continental erosion in the global carbon cycle.

Himalayan erosion generates the largest sediment flux from a single continental drainage basin to the ocean. Each year 1 to 2 billion tons of particles are transported by the Ganga-Brahmaputra (G-B) fluvial system from the Himalayan range to the Bay of Bengal and deposited in the Bengal Fan turbiditic system. The global importance of C org flux associated with sediment transport in the G-B fluvial system has been highlighted in previous studies on the basis of the modern river or the sedimentary record characterisations [START_REF] Aucour | Fluxes and sources of particulate organic carbon in the Ganga-Brahmaputra river system[END_REF][START_REF] France-Lanord | Organic carbon burial forcing of the carbon cycle from Himalayan erosion[END_REF][START_REF] Subramanian | Carbon Transport by the Himalayan Rivers[END_REF]. Recently, we realised a comprehensive budget of C org from Himalayan rocks to the Bengal Fan showing that modern burial flux of recent C org generated by Himalayan erosion is 3.1±0.3 10 11 mol/yr and represents ca. 15 % of the global flux (GALY et al., 2007b). In addition, we discovered that the Himalayan system is characterised by an extreme C org burial efficiency, since almost 100 % of C org exported by G-B fluvial system is effectively buried in Bengal Fan sediments.

This gives the G-B fluvial system a determinant role in terms of terrestrial C org exportation and burial, and therefore in terms of atmospheric CO 2 sequestration.

In this paper we present a detailed characterisation of both C org and mineral particles transported by rivers from the base of the Himalayan range to the G-B delta. We developed and used a depth profile sampling procedure which allowed the large sediment heterogeneity occurring in such rivers to be taken into account (GALY et al., 2007b; SINGH and FRANCE-

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LANORD , 2002). Total C org content (TOC + ) and stable isotopic composition ( 13 C org ) as well as major element compositions (Al and Si), grain size and specific area are reported for the set of river sediments. Thanks to the wide range of sediment properties, the comparison between C org content and bulk sediment physical properties allows study of their respective control on C org loading. The role of specific area, mineralogy and grain size, three significant parameters (e.g. [START_REF] Sollins | Sabilization and destabilization of soil organic matter: mechanisms and controls[END_REF], is especially discussed. To define average C org loading in these sediments, we use the normalisation to a chemical parameter (Al/Si) integrating several sorting processes such as grain size and mineralogy. 13 C of bulk organic matter is used to 100 evaluate the source and nature of C org , especially the relative contributions of C3 and C4 plants. Following the evolution of both C org loading and composition from the base of the range to the delta allows study of the fate of C org during its transport throughout the fluvial system and especially highlights the role of the floodplain. Detailed study of the Himalayan system therefore provides insights on two critical issues: (1) what controls C org loading in river sediments ? and, (2) what is the fate of particulate C org during fluvial transport, i.e. does a river act as a simple conveyor or as a reactor?

MATERIAL AND METHODS 110

Sampling strategy

The Ganga-Brahmaputra (G-B) basin can be divided in two distinct geomorphic parts: (1) the Himalayan range characterised by steep slopes and high incision, and (2) the floodplain characterised by flat topography and drained by very large rivers. The transition between the two sub-units is abrupt as the slope of the rivers decrease by several orders of magnitude , 1976). In the floodplain, the vegetation is composed of a mixture of crops and tropical grasslands. The main crops are rice, wheat, millet, maize and sugar cane. The contribution of C4 crops to the total production is variable but significant, reaching 80 % in the Uttar Pradesh state [START_REF] Aucour | Fluxes and sources of particulate organic carbon in the Ganga-Brahmaputra river system[END_REF].

To describe the G-B fluvial system, we sampled both Himalayan rivers at or near the outflow of the range and rivers in the floodplain (fig. 1). Most sampling was performed during the peak monsoon period (July-August, see Electronic Annex fig. 1). While there is seasonal variation in the sediment composition (e.g. [START_REF] Aucour | Fluxes and sources of particulate organic carbon in the Ganga-Brahmaputra river system[END_REF], monsoon sampling is 150 representative as 95% of the sediment transport occurs during this period (ISLAM and JAMAN, 2006). Suspended sediments were sampled at different depths in the river, from surface to bottom, in order to take into account sediment sorting. Bed sediments were dredged at the bottom of the rivers. This procedure was coupled with current velocity measurements with an Acoustic Doppler Current Profiler (ADCP) allowing the integration of the sediment variability over the whole river section. A few suspended and bank sediments were also collected either before or after the monsoon season.

In the Ganga basin, we sampled three of the major Trans-Himalayan tributaries of the Ganga at their outlet of the Himalaya in Nepal: the Karnali, the Kosi and the Narayani. The Kosi and the Narayani have also been thoroughly sampled before their confluence with the mainstream 160 of the Ganga. In Nepal, we sampled large mountainous rivers of the Narayani basin (Kali Gandaki, Trisuli, Seti Kola) as well as secondary tributaries (Karnala, Rapti). The Gomati river, a pure plain river isolated from direct Himalayan supply (SINGH et al., 2005a), was used as an approach of the floodplain input. The mainstream of the Ganga was sampled in India at several stations along its course in the floodplain and finally sampling has been carried out in triplicate at Harding Bridge (Bangladesh) just before its confluence with the Brahmaputra. In

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2005, the Narayani and Kosi in Nepal were also sampled using a depth profile but were not combined with ADCP.

A similar approach was applied for the Brahmaputra basin. We sampled major

Trans-Himalayan tributaries (Siang, Subansiri, Manas and Tista) at the outlet of the Himalayan range or in the floodplain before their confluence with the Brahmaputra and the mainstream along its course in the floodplain [START_REF] Singh | Tracing the distribution of erosion in the Brahmaputra watershed from isotopic compositions of stream sediments[END_REF]. Finally, the sampling has been repeated over three monsoon seasons at Sirajganj (Bangladesh) before its confluence with the Ganga.

In order to estimate the contribution of fossil C org derived from bedrock erosion, we analysed gravels extracted from bed sediments of several mountainous Himalayan rivers collected in Nepal and Arunachal Pradesh. These coarse sediments were sieved to eliminate the < 2mm and > 4mm fractions and the remaining gravels were rinsed with H 2 O 2 (30% v) to eliminate any trace of C org adsorbed to the surface of the gravels. Special care was also taken to eliminate any large debris of C org . For each sample approximately 500 gravel particles corresponding to small fragments of bedrocks (see Electronic Annex fig. 2) are mixed together. Each gravel sample therefore represents an average sampling of the bedrock of the basin. The average TOC and Al/Si ratio obtained from the gravel samples are comparable to that calculated using a data base of individual rock samples (GALY et al., 2007b), showing that gravel samples are representative of source rock composition.

Organic carbon content and stable isotopic composition

The determination of total C org content and stable isotopic composition in Himalayan river sediments is not straightforward as they contain significant amounts of detrital carbonates, including dolomite grains. Indeed, this requires the use of a liquid acid leaching TOC + indicates that total organic carbon measurements have been corrected for C org loss during carbonate removal through liquid acidification, using the calibration presented in GALY et al. (2007a). EA-IRMS runs were calibrated using 2 lab standards with mineral matrix, C org content and 13 C org comparable to those of the samples. TOC + was expressed in weight per cent of bulk sediment and 13 C bulk was expressed versus V-PDB using the notation [START_REF] Coplen | New guidelines for reporting stable hydrogen, carbon, and oxygen isotope-ratio data[END_REF]. On the basis of repeated internal standards analysis and samples replicates, estimated overall reproducibility for TOC + and 13 C org is 0.03 % and 0.25 ‰, respectively.

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Sediment analyses 210

Major and trace element concentrations were measured by ICP-AES and ICP-MS at Service d'Analyse des Roches et des Minéraux (CRPG-Nancy) on bulk sediment after lithium metaborate fusion. The typical analytical precision of major element concentration is better than 2%.

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Grain size distributions were determined for selected samples using a laser diffraction analyser Malvern Mastersizer in the 1.2-600 μm size range. Representative aliquots were subsampled after bulk sediment drying at 50°C. Large aggregates formed during drying were gently broken in an agate mortar and further dispersed through controlled ultra-sonication.

For selected sediments, we also directly measured grain size distribution on untreated wet sediments. Grain size distributions determined from dried and wet sediments were highly similar, suggesting that preliminary dispersion treatments of samples do not generate any significant artefacts. Results are volume based and are expressed as particle volume versus sphere diameter of equivalent volume. Although the size distributions may be slightly biased by sample treatment, they are reproducible by different methods (wet, dry), appear to be representative, and provide a consistent basis for comparison.

Nitrogen adsorption-desorption isotherms at 77 K were recorded with a step-by-step automatic lab-made setup. Samples were initially degassed at 50°C and 10 -5 Pa for 18 hours.

Adsorption-desorption isotherms were then determined by subjecting samples to various partial pressures of N 2 at 77 K. The specific area (SA) was calculated following the Brunauer Emmet Teller (BET) method [START_REF] Brunauer | Adsorption of gases in multimolecular layes[END_REF]. The proportion of micropores (diameter lower than 2 nm) was estimated following the t-plot method [START_REF] De Boer | The t-curve of multimolecular N 2 adsorption[END_REF].

Organic matter was not removed prior to N 2 sorption analyses since limited amounts of C org in studied sediments must have resulted in negligible artefacts (MAYER, 1994). Maximum 2 s.d.

uncertainty on specific area measurements is ± 0.25 m 2 g -1 .

RESULTS

In large rivers of the G-B fluvial system sediment characteristics are highly variable with water depth (GALY et al., 2007b). This variation results from mineral and grain size sorting under hydrodynamic forces during transport. At the base of the range and in the floodplain 1) we sampled suspended sediments along depth profiles in order to describe the whole sediment heterogeneity. The depth profile data are presented in Table 1.

A C C E P T E D M A N U S C R I P T (fig.
The general G-B sediment characteristic is a relatively low C org content [START_REF] Aucour | Fluxes and sources of particulate organic carbon in the Ganga-Brahmaputra river system[END_REF]GALY et al., 2007b;[START_REF] Subramanian | Carbon Transport by the Himalayan Rivers[END_REF]. In bulk sediments, C org content is generally lower than 1 % and has an arithmetic average value of ca. 0.35 %. Bed sediments dredged from the bottom of the river have systematically lower C org content than suspended sediments with an average value lower than 0.1 %. Direct observation shows that organic matter is different in bottom and upper suspended sediments (fig. 2). Bottom and coarsegrained sediment, almost systematically contain macroscopic vegetal debris that are more or less decomposed. Such debris is absent in upper (fine-grained) sediments in spite of the 250 presence of plant raft floating at the surface. In upper sediments, transmitted electron microscope (TEM) observations on resin-embedded samples reveal that microscopic C org fragments are present aggregated to mineral particles as well as independent particles.

Relation between C org content and Al/Si

Details of the major relationships described in this study (best fit parameters and statistical relevance) are listed in the Electronic Annex Table 1.

The whole set of sediment samples from large rivers (mountainous and floodplain rivers) defines a clear positive correlation between TOC + and Al/Si (mol:mol), as previously 260 observed for Ganga, Brahmaputra and Lower Meghna sediments in Bangladesh (GALY et al., 2007b). This relationship allows comparison of the C org loading (i.e. the TOC + for a constant Al/Si ratio) of different rivers or sampling sites.

Ganga basin

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Grain size

In the Shepard's diagram (not shown), river sediments from the G-B system can be classified as silt, silty sand, sandy silt and sand. Bed sediments are coarser than suspended sediments and fall in the range of pure sand. Surface suspended sediments are the finest and fall in the range of pure silt. The proportion of clay (< 2 μm) is always limited and reaches a maximum of ca. 10 % in surface suspended sediments. Bed and surface suspended sediments generally have uni-modal grain size distribution whose respective mode is > 100 μm and < 50 μm.

Suspended sediments at intermediate depth have bi-modal distributions realising a continuum

between the surface suspended sediment and the bed sediment (fig. 5). For the whole set of sediment, TOC + is correlated with the proportion of fine particles. The data are best modelled 300 by a power curve, although the deviation from linearity is small. The proportion of < 25 μm particles gives the best correlation between TOC + and grain size (fig. 6). Sediments from the Brahmaputra and the Ganga in Bangladesh define distinct trends. For a given proportion of fine particles, Brahmaputra sediments have slightly higher TOC + than Ganga sediments. In such a diagram, suspended sediments from the Kosi and Narayani river are comparable with suspended sediments from the Ganga in Bangladesh. However, suspended sediment from the Karnali as well as Ganga sediments sampled in the Indian floodplain (Patna) have slightly higher relative C org content and appear to be more comparable with sediments from the Brahmaputra. 310

Sediment load

During the monsoon, G-B rivers have high total suspended sediment concentration (TSS).

There is however a large variability from 0.3 to 10.2 g/l. TSS are generally higher at the base of the range than in the floodplain, mostly related to more turbulent and powerful flow. Depth

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sampling profiles show a quasi-linear increase of TSS with depth ((GALY et al., 2007b), table 1), both at the base of the range and in the floodplain. For instance, in the Narayani at the base of the range, TSS increase from 2.9 g/l at the surface to 10.2 g/l near the bottom. This illustrates the large sorting process affecting the sediments during fluvial transport.

C org content of suspended sediments generally decreases with increasing TSS. In a 1/TOC + versus TSS diagram, sediments from the Ganga and Brahmaputra basins define similar positive trends characterized by higher scatter for high TSS values (Electronic Annex fig. 3).

The intercept of these trends when TSS tends to 0 is greater than 0.01, indicating that these relationships are not attributable to pure dilution effects (see EA).

Specific area

BET specific area has been measured for selected samples of the Ganga and Brahmaputra in Bangladesh. Specific areas range between 1.3 and 34.8 m 2 g -1 . Bed sediments from the Ganga and the Brahmaputra have very low values, respectively 1.3 and 1.8 m 2 g -1 . Suspended sediments have higher specific area, ranging between 3.6 and 8.9 m 2 g -1 for Brahmaputra suspended sediments and between 17.4 and 34.3 m 2 g -1 for Ganga suspended sediments. This is consistent with the mineralogy of the clay fraction in these rivers since Ganga sediments carry more than 50 % of smectite whereas Brahmaputra sediments have clays dominated by illite with negligible proportion of smectite [START_REF] Heroy | Mineralogy of the Ganges and Brahmaputra Rivers: implications for river switching and Late Quaternary climate change[END_REF]. Ganga and Brahmaputra sediments present very different N 2 adsorption-desorption isotherms revealing contrasting pore size distributions (fig. 7). We determined the proportions of micropores (< 2 nm) using the t-plot method. Brahmaputra sediments have a negligible proportion of micropores, whereas they represent 19 to 25 % of the total surface area in Ganga sediments. Specific area

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corrected for the surface associated to micropores represents the external specific area. Ganga suspended sediments have external specific areas ranging from 13.7 to 26.0 m 2 g -1 , i.e. still significantly higher than that of Brahmaputra suspended sediments. TOC + and specific area are well correlated but Ganga and Brahmaputra sediments define very distinct trends (fig. 8).

Brahmaputra and Ganga suspended sediments have respective TOC + /SA ratios of 0.73 ± 0.02 and 0.20 ± 0.01 mgCg -1 . For Ganga suspended sediments this ratio increases to 0.23 ± 0.02 mgCg -1 when calculated using external specific area.

Stable

Brahmaputra basin

In every river of the Brahmaputra basin, bed sediments have higher 13 C org values than suspended sediments. The 13 C org of suspended sediments tends to decrease with increasing C org content and surface suspended sediments generally have the lowest 13 C org value (fig. 10).

Bed sediments from Trans-Himalayan rivers have variable 13 C org values between -19.9 ‰ and -23.7 ‰ with an average value of -22.1 ‰. Suspended sediments from the same rivers also have variable 13 C org values between -23.7 ‰ and -26.3 ‰ with an average value of -24.8 ‰. Sediments from secondary Himalayan tributaries tend to have slightly higher 13 C org , with an average value of -24.0 ‰ for suspended sediments. Suspended sediments from the shows that the composition of suspended sediments may be subject to rapid temporal variations within a week. Suspended sediments from the Brahmaputra at Guwahati (India) sampled at the end of October, i.e. after the monsoon season, have significantly lower 13 C org than suspended sediments sampled during the monsoon, with an average value of -24.9 ‰.

This likely derives from a greater contribution of autochthonous organic matter, as 400 documented for the Ganga during the dry season before the monsoon.

13 C org of source rock fossil C org

The gravel sampling allows integration of a considerable number of lithologies over large sub-basins, and provides a good estimate of the average fossil C org eroded from the source rocks and transferred to the river sediments. Gavels from the bed of Himalayan mountainous rivers have highly variable 13 C org between -28.0 and -14.6 ‰ (table 2). There is no systematic difference between gravels from rivers draining the two main lithologic units, the High Himalaya Crystalline (HHC) and the Lesser Himalaya (LH), as both have variable 13 C org . The average 13 C org value calculated for the whole set of gravel samples is -22.6 ‰ but the 410 dispersion of the data is quite high (-28.0 to -14.6 ‰).

DISCUSSION

Sedimentological control of C org loading

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The amount of C org exported by rivers results from a complex interaction between organic matter produced and decomposed within the basin and mineral particles derived from rock erosion. Physical and chemical properties of sediment must therefore exert a control on the C org loading of sediments. Three sediment properties have been identified as the main factors 420 that determine C org loading in detrital sediments (e.g. Mayer, 1994;[START_REF] Sollins | Sabilization and destabilization of soil organic matter: mechanisms and controls[END_REF]Ransom et al., 1998): (1) the specific area of mineral particles (2) the particle size, especially the proportion of fine particles and (3) the mineralogy. However, in spite of several studies, the respective part of each parameter in the control of C org loading remains unclear. In addition, each river system is characterised by different source rocks, physical and chemical erosion rates or transport dynamics that must result in different C org loading mechanisms.

Earlier studies have proposed that specific area exerts a dominant control on C org loading in river sediments by C org adsorbtion to mineral surfaces (e.g. [START_REF] Hedges | Sedimentary organic matter preservation: an assessment and speculative synthesis[END_REF]MAYER, 1994). This hypothesis has mainly been inspired and supported by the single positive correlation between TOC + and specific area found for different river systems (e.g. KEIL et al., 430 1997). It assumes that a single layer of C org covers the entire mineral surface. This monolayer equivalent model was initially used to explain the control of C org loading by specific area as it yields a TOC + /SA ratio compatible with that observed by the authors (0.6 to 1.5 mgC/m 2 ).

Nevertheless, progress in surface analyses as well as new observation techniques showed that the monolayer equivalent theory is not adequate since only a minor proportion (ca. 15%) of the mineral surface is effectively covered by C org [START_REF] Bock | Mesodensity organo-clay associations in a near-shore sediment[END_REF][START_REF] Mayer | Extent of coverage of mineral surfaces by organic matter in marine sediments[END_REF]. In addition, several studies have shown that C org is not linked to mineral surface as a single adsorbed layer but rather forms patchy organo-mineral aggregates similar to those observed in this study (fig. 2) (e.g. [START_REF] Curry | Direct visualization of clay microfabric signatures driving organic matter preservation in fine-grained sediment[END_REF][START_REF] Furukawa | Energy-filtering transmission electron microscopy (EFTEM) and electron energy-loss spectroscopy (EELS) investigation of clay-organic matter aggregates in aquatic sediments[END_REF][START_REF] Wagai | Sorptive stabilization of organic matter in soils by hydrous iron oxides[END_REF].

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The comparison between Ganga and Brahmaputra sediments provides an insightful case study to address the role of specific area on C org loading in river sediments because both rivers have quite comparable physiographic, geologic and vegetation characteristics but contrasted sediment specific areas. As mentioned in section 3.4, this difference in specific surface areas is only due to the clay composition with high proportion of smectite for the Ganga compared to Brahmaputra. This leads to specific areas of Ganga sediments that are 4 to 5 times higher than those of Brahmaputra sediments for comparable TOC + , grain size or Al/Si ratio.

Brahmaputra suspended sediments have OC/SA ratio in the range defined as "typical river sediment OC/SA ratio" whereas Ganga suspended sediments have lower OC/SA that fall in the range defined as "typical deltaic sediment OC/SA ratio" (e.g. [START_REF] Hedges | Comparative organic geochemistries of soils ans marine sediments[END_REF].

This implies that SA does not exerts a first order control on C org loading, i.e. that C org loading of river sediments is primarily determined by other intrinsic or extrinsic parameters, such as mineralogy, grain size or primary productivity in the basin. Rather the clear relationship between TOC + and SA (fig. 8) results from the co-variation of specific area with other sedimentological characteristics (Electronic Annex fig. 4). Moreover, the SA of river sediments appears to be controlled by minor mineral phases that have very high SA, such as smectite. OC/SA ratio is therefore not a good proxy to compare C org loadings in different rivers. This is further supported by the Huanghe river sediments that have low OC/SA ratio, comparable to that of Ganga suspended sediments [START_REF] Keil | Loss of organic matter from riverine particules in deltas[END_REF], mainly because their clay fraction has significant proportion of smectite (PARK and KHIM, 1992).

In river sediments, grain size and mineralogy are generally not independent parameters; e.g.

clays and sand are differentiated by their particle size but also have very different mineral compositions. This makes it difficult to decouple the parameters controlling C org loading.

Correlations between C org content and the proportion of fine particles have classically been reported in river sediments (e.g. [START_REF] Keil | Loss of organic matter from riverine particules in deltas[END_REF]. Positive co-variation between C org content

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and the proportion of fine particles may result from at least two factors depending on how C org is transported: (1) if C org is mainly independent of minerals particles, its low density would tend to concentrate C org in fine-grained sediments through hydrodynamic sorting, (2) if C org is mainly linked with minerals, both particle size and mineral composition must control the C org loading in detrital sediments. In this case, C org is associated with particles as organo-mineral complexes [START_REF] Wagai | Sorptive stabilization of organic matter in soils by hydrous iron oxides[END_REF], or can be encapsulated within particle microfabrics 470 [START_REF] Curry | Direct visualization of clay microfabric signatures driving organic matter preservation in fine-grained sediment[END_REF], and are preferentially associated with particle edges [START_REF] Furukawa | Energy-filtering transmission electron microscopy (EFTEM) and electron energy-loss spectroscopy (EELS) investigation of clay-organic matter aggregates in aquatic sediments[END_REF][START_REF] Mayer | Organic matter in small mesopores in sediments and soils[END_REF]. Therefore, multiple physical parameters such as particle charge density, chemical composition (nature of exchangeable cation), crystalline structure, size and shape must all determine the ability of C org to be bonded with particles [START_REF] Sollins | Sabilization and destabilization of soil organic matter: mechanisms and controls[END_REF].

In the G-B river system, the chemical composition of bed and suspended sediments can be explained by mineralogical mixing. In an Fe/Si versus Al/Si diagram, river sediments define a mixing line between a quartz rich end-member and a phyllosilicate rich end-member [START_REF] Galy | Higher Erosion rates in the Himalaya: geochemical constraints on riverine fluxes[END_REF][START_REF] Singh | Tracing the distribution of erosion in the Brahmaputra watershed from isotopic compositions of stream sediments[END_REF]. Bed and suspended sediments are differentiated by the combined effect of shape, density and grain size segregation that control the flotation properties of particles. This tends to concentrate coarse 480 and rounded minerals (quartz, feldspars) towards the bottom and fine grained and flaky particles (micas, clays) towards the surface. Since quartz and phyllosilicates represent more than 80% of the silicates, the Al/Si ratio is a function of the relative proportions of quartz and micas+clays and allows representation and quantification of this hydrodynamic differentiation process. For the whole set of river sediment, there is a general co-variation between Al/Si ratio and grain size parameters such as the proportion of <25 μm particles (Electronic Annex fig. 5). The general positive correlation between TOC + and Al/Si therefore indicates that C org content also responds to hydrodynamic segregation processes: (1) organic particles tend to concentrate in surface waters because of their low density and fibrous shapes, and (2) organo- In the Brahmaputra basin, the Trans-Himalayan tributaries which represent the large majority 520 of the sediment influx to the floodplain have higher or lower C org loading than the Brahmaputra in Bangladesh and different samplings along the Brahmaputra course do not show any simple evolution of the C org loading. As a consequence, we can reasonably estimate that average C org loading at the outlflow of the Himalayan range must be quite comparable to that in Bangladesh.

The Ganga sampled in the Indian floodplain at Varanasi and Patna has higher C org loading than further downstream in Bangladesh. The influx of sediments to the Ganga from the Narayani-Gandak and Kosi which have lower C org loading explains this evolution. For the Kosi and the Narayani-Gandak, there is no evolution of the C org loading from Himalaya to their confluence with the Ganga (Electronic Annex fig. 6). The contrast of loading between 530 western and eastern Ganga floodplain is difficult to interpret in the absence of data for the upper Ganga and Yamuna. It may derive from a higher loading of western Himalayan tributaries as suggested by data of the Karnali-Gahgara; alternatively it may be due to organic matter addition in the floodplain. In any case, the higher loading of the western Ganga could result from an overall lower sediment yield of the west compared to the east (e.g. [START_REF] Sinha | Geomorphic characterization and diversity of the fluvial systems of the Gangetic Plains[END_REF] as lower physical erosion should favour higher fixation of organic matter.

13 C org of G-B river system: implication for the source and fate of C org

A C C E P T E D

M A N U S C R I P T

Sources of C org

In river sediments, 13 C org is determined by the relative contribution of different types of C org such as higher plants, fossil C org and phytoplankton. There is a strong isotopic contrast between the 2 major photosynthetic pathways that allows differentiation of C3 and C4 plant inputs in river sediments; C3 plants 13 C org ranges between -35 and -20 ‰ with an average value of -26 ‰ while C4 plants 13 C org ranges between -16 and -10 ‰ with an average value of -13 ‰ (DEINES, 1980). The freshwater phytoplanktonic matter usually has low 13 C org . The isotopic fractionation between phytoplankton and dissolved inorganic carbon (DIC) has been estimated to be ca. -23‰ [START_REF] Mook | Origin and dispersal of recent clay minerals in the Yellow Sea[END_REF]. In the G-B rivers at the outflow of the range and in the floodplain, the 13 C of DIC is between -8 and -12 ‰ during the monsoon [START_REF] Gajurel | C and O isotope compositions of modern fresh-water mollusc shells and river waters from the Himalaya and Ganga plain[END_REF][START_REF] Galy | Weathering processes in the Ganges-Brahmaputra basin and the riverine alkalinity budget[END_REF]SINGH et al., 2005b).

Phytoplanktonic organic matter must therefore have 13 C org values between -31 and -35 ‰. This is further supported by the 13 C org value (-32.1‰) measured by [START_REF] Aucour | Fluxes and sources of particulate organic carbon in the Ganga-Brahmaputra river system[END_REF] in a low stage sediment of the Brahmaputra presenting a strong C org enrichment (7.6%) and an obvious contribution of phytoplankton.

Fossil C org contained in Himalayan source rocks has variable 13 C org between -31 and -18 ‰ [START_REF] Aucour | Fluxes and sources of particulate organic carbon in the Ganga-Brahmaputra river system[END_REF]. Our data from gravel samples are consistent with individual source rock analyses, however, the average value calculated using source rock individual analyses (-25.5 ‰) is lower than that of gravels (-22.5 ‰). Because 13 C org values in source rocks are variable and overlap with recent C org isotopic signatures, 13 C org values in river sediments are not diagnostic to estimate fossil C org proportions. Using 14 C values of river sediments and the mean C org content of Himalayan source rocks (0.05 to 0.08%), the proportion of fossil C org has been estimated in Ganga, Brahmaputra and Lower Meghna sediments in Bangladesh (GALY et al., 2007b). The average proportion of fossil C org has been conservatively estimated between

A C C E P T E D M A N U S C R I P T

For each river, suspended sediments have either higher or lower 13 C org values than bed sediments. In a TOC + vs. 13 C org diagram, they define mixing trends between a bed sediment endmember with low TOC + and 13 C org -23‰ and surface suspended sediment with higher TOC + and 13 C org around -20 to -22‰ for the Ganga or -24 to -26‰ for other rivers (figs. 9 and 10). We interpret these trends as a mixing between bed sediment dominated by fossil C org and surface suspended sediment dominated by recent biogenic C org such as soil organic mater 570 or fresh plant debris. The recent organic matter is however markedly different for the Ganga than for other rivers either in Himalaya or on the Brahmaputra side. In Trans-Himalayan and secondary Himalayan tributaries of the Ganga and Brahmaputra basins, the 13 C org values of suspended sediments around -25 ‰ indicate a contribution of recent C org dominated by C3 plants. This is consistent with Himalayan vegetation that is largely dominated by C3 species [START_REF] Blasco | A vegetation map of tropical continental Asia at scale 1.5 million[END_REF][START_REF] A C C E P T E D M A N U S C R I P T Dobremez | Constraints on the origin of sedimentary organic carbon in the Beaufort Sea from coupled molecular 13C and 14C measurements[END_REF]GALY et al., Submitted). The contribution of phytoplanktonic organic mater appears to be limited since its 13 C is very low (-31 to -35 ‰) i.e. significantly lower than that of C3 plants. This minimal contribution is consistent with the high turbidity and current velocity of such mountainous rivers during the monsoon season.

Suspended sediments of the Ganga and Brahmaputra in the plain define opposite mixing 580 trends as surface suspended sediments have respectively higher and lower 13 C org than bed sediments. This reveals different recent C org sources. While suspended sediments of the Brahmaputra have similar 13 C org values to that of its Trans-Himalayan tributaries, suspended sediments of the Ganga in the plain have 13 C org values that are on average 2 to 4 ‰ higher than that of its Himalayan tributaries.

fate of C org in the Ganga basin

The evolution of 13 C org from Himalaya to the Ganga shows that organic matter with a significant proportion of C4 plant is incorporated into the river sediment during the floodplain

A C C E P T E D

M A N U S C R I P T transit (fig. 11). This is consistent with the presence of natural C4 grasses and cultivated C4 crops in the floodplain (AUCOUR et al., 2006 and ref. therein). Such evolution implies either an addition of C org during transit or a replacement. In the Kosi and Narayani rivers, the 13 C org values of the suspended sediments increase of ca. 2 ‰ from the Himalayan range to the confluence with the Ganga (fig. 11) without increase of their C org loading (Electronic Annex fig. 6). The Gomati river, which is a pure plain river isolated from direct Himalayan supply for several thousand years (SINGH et al., 2005a), can be used as an analogue of the plain C org input. While it was sampled only once and may not be representative of the whole Gangetic plain, its 13 C org value (-21.9‰) suggests that floodplain C org input is composed of mixed C4 and C3 plants. This suggests that average floodplain organic matter is not significantly different from that of the Ganga suspended sediment and it rules out the hypothesis of a simple addition of pure C4 organic matter during the plain transit.

The alternative is therefore that part of the C org derived from mountainous vegetation is fossil C org . This is consistent with its highly refractory character that makes it very resistant to oxidation (e.g. [START_REF] Blair | The persistence of memory: the fate of ancient sedimentary organic carbon in a modern sedimentary system[END_REF].

fate of C org in the Brahmaputra basin

In the Brahmaputra basin, in contrast to the Ganga basin, there is no clear 13 C org change from the outlet of the Himalaya to the delta (fig. 13). This may indicate that there is no C org renewal 620 during the fluvial transport from the outflow of the Himalayan range to the delta or that there is no C3/C4 contrast between the Brahmaputra floodplain and the Himalaya. The Brahmaputra plain is almost exclusively cultivated with C3 crops [START_REF] Aucour | Fluxes and sources of particulate organic carbon in the Ganga-Brahmaputra river system[END_REF] and the proportion of C4 plants in its natural vegetation should be lower than in the Gangetic plain due to more humid conditions. The average 13 C org of Brahmaputra plain vegetation may thus be very close to that of its Himalayan tributaries. This is further supported by vegetation simulations obtained using the Dynamic Vegetation Model CARAIB (GALY et al., Submitted). Consequently, any renewal of C org during the Brahmaputra transit would have only minor effect on 13 C org of river sediments. Consequently, more specific tracers are required to precise the fate of C org in the Brahmaputra basin. However, the characteristics of 630 the two rivers and their respective floodplains are different: the Ganga is a meandering river with a large floodplain whereas the Brahmaputra is a braided river with a narrow floodplain.

The residence time of river sediments is a key parameter controlling the extent of C org oxidation during fluvial transport (e.g. [START_REF] Aufdenkampe | Organic matter in the Peruvian headwaters of the Amazon: Compositional evolution from the Andes to the lowland Amazon mainstem[END_REF][START_REF] Blair | From bedrock to burial: the evolution of particulate organic carbon across coupled watershed-continental margin systems[END_REF]. The morphological and hydrodynamic differences between Ganga and Brahmaputra rivers could therefore favour a longer transit, hence a more efficient renewal in the Ganga than in the Brahmaputra.

A C C E P T E D

M A N U S C R I P T

CONCLUSIONS

The comparison between Ganga and Brahmaputra sediments that have comparable C org content but highly different specific area clearly indicates that specific area is not the key parameter that determines C org content in such sediments. In G-B fluvial sediments, C org is both present as independent particles and intimately linked to mineral particles. The control of C org loading in these sediments appears to be related to: ( 1 C org renewal rate for the Brahmaputra than for the Ganga. More focused tracers such as molecular level 13 C, D and 14 C (e.g. [START_REF] A C C E P T E D M A N U S C R I P T Dobremez | Constraints on the origin of sedimentary organic carbon in the Beaufort Sea from coupled molecular 13C and 14C measurements[END_REF][START_REF] Eglinton | Gas chromatographic isolation of individual compounds from complex matrices for radiocarbon dating[END_REF][START_REF] Sauer | Compound-specific D/H ratios of lipid biomarkers from sediments as a proxy for environmental and climatic conditions[END_REF] must have a great potential to track and quantify C org renewal during fluvial transport. The study of the G-B fluvial system shows that processes associated with physical erosion and sediment transport exert a primary control on both loading and fate of riverine C org . In addition, floodplains appear to play a determinant role in the terrestrial C org dynamic acting as a "reactor" promoting both C org oxidation and loading. Our study also indicates that large rivers may preferentially export terrestrial C org produced in particular zones of the basin, such as floodplains. This process must be carefully addressed in the scope of paleo-vegetation and paleo-climate reconstructions based on riverine C org buried in oceanic sediments. Finally, 680 precise characterisation at the basin scale of both the terrestrial C org dynamic and the relationships between physical erosion and C org export should significantly improve models of the global C cycle.

A C C E P T E D

M A N U S C R I P T collaboration and help on the field. Angelina Razafitianamaharavo performed Nitrogen 690 adsorption-desorption experiments and is greatly thanked for her help in data treatment.

Caroline Guilmette is also acknowledged for her valuable help in the stable isotope laboratory. Finally we thank Shuh-Ji Kao, two anonymous reviewers as well as Robert Aller for their constructive remarks. This is CRPG contribution # XXXX.

A C C E P T E D

M A N U S C R I P T

A C C E P T E D

M A N U S C R I P T Al/Si indicating similar control of the C org loading in the basin. The slope of these trends characterises the C org loading which is defined as TOC + /(Al/Si) (see Electronic Annex Table 1). The Ganga in the Western floodplain (Varanasi and Patna), the Karnali river as well as secondary tributaries have the highest C org loading.

A C C E P T E D

M A N U S C R I P T ratio, the slope of these trends represents the C org loading (see Electronic Annex Table 1).

Brahmaputra and Trans-Himalayan rivers have comparable C org loading while secondary tributaries clearly have higher C org loading.

  kilometres. The Himalayan range is drained southward by a dozen Trans-Himalayan rivers originating in southern Tibet, which collects most of the Himalayan runoff and supply G-B in the East-West Indo-Gangetic floodplain. The G-B basin is composed of two sub-basins: the Ganga basin to the West and the Brahmaputra basin to the East. The Himalayan part of these two sub-basins are quite comparable but their floodplains are very different. The Ganga floodplain is 200 to 300 km wide and very flat with the Ganga meandering far south of the Himalayan front. On the other hand, the Brahmaputra floodplain is only 50 to 100 km wide due to the presence of the Shillong plateau and Burmese range to the South. The Brahmaputra is steeper, more channelled and remains a braided river until its confluence with the Ganga. Ganga and Brahmaputra merge in Bangladesh to form the Lower Meghna that finally supplies the Indian Ocean in the Bay of Bengal. Geologically, the Himalayan range is divided in four superimposed units (e.g. LE FORT, 1989). From North to South: the Tethyan Sedimentary Series consists of variably metamorphosed clastic sediments and carbonates, the High Himalaya Crystalline formations (HHC) are composed of orthogneisses, highly metamorphosed paragneisses and some marbles, the Lesser Himalaya (LH) is composed of metamorphosed metasediments, including minor black shales and limestones, finally, the Siwaliks forms the frontal range and is composed of sandstones and conglomerate that are uplifted Mio-Pliocene sediments deposited in the paleo-floodplain. To the south of the range, the floodplain is entirely composed of Quaternary fluvial sediment. Fluvial migration being intense most deposits are Holocene. The G-B basin is one of the most densely populated of the world and the vegetation is consequently largely controlled by human activities (i.e. deforestation and farming). In the Himalayan range, the forest is still dominant although it has been severely affected by deforestation during the last decades. The vegetation distribution is however largely controlled by altitude and alpine scrub grassland dominate above 3000 to 3500 m A C C E P T E D M A N U S C R I P T (DOBREMEZ

  Reported in a TOC + versus Al/Si diagram, sediments from Himalayan rivers, floodplain rivers as well as Ganga define positive linear correlations (fig.3). Each sampling site defines an individual trend but the overall variability in their slope is limited and they tend to converge towards similar TOC + value (< 0.05 %) for low Al/Si ratios. Among the Large Trans-Himalayan tributaries, Narayani and Kosi have very comparable C org loading. The Karnali seems to have significantly higher loading (based on a single suspended sediment). Large tributaries of the Narayani sampled in the Himalayan range have comparable C org loading to the Narayani at the outflow of the Himalaya. Detailed depth sampling on the Ganga river at different locations from Varanasi downstream to Harding Bridge also define distinct trends showing that C org loading is not absolutely constant throughout the river course. Nevertheless, samples collected during three different monsoons at Harding Bridge define highly similar trends suggesting a rather constant C org loading at the outflow of the basin. 3.1.2 Brahmaputra basin The Brahmaputra at Sirajganj was sampled in detail four times during the 2002, 2004 and 2005 monsoons. The four sets of samples define a unique trend in the TOC + versus Al/Si diagram indicating constant C org loading (fig. 4). Sediments from the Brahmaputra mainstream sampled along its course in the plain are consistent and have comparable or slightly higher C org loading than the Brahmaputra at Sirajganj. Sediments of the four Trans-Himalayan tributaries of the Brahmaputra define distinct trends in the TOC + versus Al/Si diagram. The Siang and the Tista rivers have comparable C org loading, slightly lower than that of the mainstream. Sediments from the Subansiri and the Manas have higher C org loading than mainstream sediments. Secondary Himalayan tributaries are all very distinct from the Transhimalayan tributaries and the mainstream with C org loading 4 to 5 times higher.

  Kosi, Narayani and Karnali rivers at the outlet of the Himalaya have13 C org values between -23.6 and -25.6 ‰.13 C org of bed sediments is higher than that of suspended sediments which are comparatively enriched in C org . In suspended sediments,13 C org value decreases with C org content and for the Kosi and the Narayani the surface suspended sediment is the most 13 C depleted (fig.9). Suspended sediments of the Kosi and Karnali rivers have 13 C org values ca. 1 ‰ lower than suspended sediments of the Narayani river. Suspended sediments of large mountainous rivers of the Narayani basin have variable13 C org value from -25.0 to -22.4 ‰. However, their average 13 C org value (-24.3 ‰) is comparable to that of the Narayani at the outflow of the Himalaya. Suspended sediments from 360 the Kosi and the Gandak (name of the Narayani in India) sampled before their confluence with the mainstream of the Ganga have higher 13 C org values (ca. 2 ‰) than at the outlet of the Himalaya. Secondary Himalayan tributaries have 13 C org values from -24.4 to -25.6 ‰, comparable to that of Trans-Himalayan rivers. Suspended sediments from Ganga mainstream have higher 13 C org than bed sediments. On the contrary to Himalayan tributaries,13 C org of A C C E P T E D M A N U S C R I P T suspended sediments increases with TOC + . Suspended sediments from different locations along the mainstream of the Ganga in the Indian floodplain have variable 13 C org with average values ranging from -21.2 ‰ at Varanasi to -22.3 ‰ at Manihari. The three detailed depth samplings realised at Harding Bridge during the 2002, 2004 and 2005 monsoons show noticeable 13 C org differences from one monsoon to another. The average 13 C org of suspended sediments varies from -22.2 ‰ in 2002 to -20.7 ‰ in 2005. Suspended sediments sampled at Harding Bridge therefore have systematically higher 13 C org values than suspended sediments sampled at the outlet of the Himalaya. Bed sediments dredged at the bottom of the river at Harding Bridge have lower 13 C org than their corresponding suspended sediments with an average value of -22.5 ‰. Two suspended sediments sampled at Patna during the dry season (May) have very low 13 C org value compared to Ganga suspended sediments sampled during the monsoon; their average value is -26.3 ‰. The total sediment concentration that was 5 to 10 times lower than during the monsoon, as well as the presence of abundant algae in the surface water, indicate that these low 13 C org values derive from a greater contribution of autochthonous organic matter.

  A C C E P T E D M A N U S C R I P TBrahmaputra mainstream sampled during the monsoon at different locations in the Indian plain have quite comparable 13 C org with an average value of -23.7 ‰. The four detailed depth sampling realised at Sirajganj during the 2002, 2004 and 2005 monsoons show minor 13 C org differences. The average 13 C org value of suspended sediments varies between -22.9 ‰ and -23.8 ‰. The 0.9 ‰ difference between the two detailed samplings performed in July 2004

A

  C C E P T E D M A N U S C R I P Tmineral aggregates are preferentially formed from clays and to a minor extent from micas and therefore tend also to concentrate in surface regions.4.2 C org loading evolution along the G-B river systemSince sediment characteristics exert a primary control on C org content, comparing C org loading at different locations in the basin requires a common reference. Al/Si ratios are probably the best reference as they clearly allow taking into account the combined sedimentological effects. At the basin scale, this ratio is not necessarily conservative with respect to weathering, however in the Himalayan case the chemical erosion of Si represents less than 1% of its solid flux[START_REF] Galy | Weathering processes in the Ganges-Brahmaputra basin and the riverine alkalinity budget[END_REF] and Al/Si ratios are essentially insensitive to weathering processes. Therefore we use the slope defined by sediments from a given location in the Al/Si ratio vs. TOC + diagram to compare the C org loading of sediments independently of mineralogy, specific area or grain size distribution.C org loading of suspended sediments from the Ganga and Brahmaputra in Bangladesh are highly comparable and stable over the three monsoon samplings studied. This likely derives from the relative stability of sediment composition throughout time and reflects the buffering effect of such a large river system. The different Trans-Himalayan tributaries have either slightly higher or slightly lower C org loading than Ganga and Brahmaputra in Bangladesh. Our sampling may not be fully representative, as most of these large rivers have been sampled only once. However, the Narayani and the Kosi have been sampled twice and detailed depth sampling has been performed on these rivers. Our results indicate similar C org loading for the two samplings, supporting the representativeness of our data. Secondary Himalayan tributaries of the Brahmaputra have systematically higher C org loading than Trans-Himalayan tributaries. C org loading differences between Himalayan rivers may be related to differences in A C C E P T E D M A N U S C R I P T physical erosion characteristics such as the respective proportions of sediment generated by glacier and landslides or overall physical erosion rates. More data within the mountain basins would be required to support this inference as precise comparison of contrasting Himalayan basins would certainly provide insightful constraints on the control of C org loading in river sediments.

  oxidised and replaced by C org derived from the plain vegetation. This C org renewal process likely occurs during the repeated deposition-erosion cycles affecting the sediments from one monsoon to the other as well as during river course avulsion. Estimating the proportion of renewed C org is not straightforward as we do not precisely know the composition of the plain C org . Nevertheless, taking into account estimates of the cultivated areas covered by C3 and C4 plants in the plain (AUCOUR et al., 2006), and the composition of the Gomati river we can propose that a minimum of 50 % of the C org is renewed. The 13 C org variability between suspended sediments of the Ganga in Bangladesh sampled in 2002, 2004 and 2005 may either reflect a variation of the proportion of C org that is renewed or a variation of the composition of the plain input. The relative stability of the bed sediments 13 C org value as well as the fact that mixing trends defined by Ganga suspended sediments are opposed to that defined by Himalayan rivers suspended sediments indicate a selective preservation of the rock derived A C C E P T E D M A N U S C R I P T

  ) organic particles segregation under hydrodynamic forces in the river and, (2) the ability of mineral particles to form aggregates in which C org can be encapsulated. As a consequence, sorting processes generated by fluvial transport, which mainly determine sediment characteristics, exert a first order control on C org loading in G-B river sediments. Estimation of C org loading in river sediments is therefore highly sensitive to the representativeness of the sample set that is used. The depth profile sampling procedure applied to G-B rivers allows the sediment heterogeneity in the river to be taken into account. This sampling provides a range of sediment compositions naturally generated by sorting processes during the fluvial transport. The comparison of TOC + to a conservative parameter describing the bulk sediment characteristics, such as Al/Si, therefore allows the actual C org loading in sediments exported by the river to be characterised. During the monsoon, C org loading appear to be rather constant from large trans-Himalayan rivers sampled at the base of the range to Ganga and Brahmaputra sampled in the Bangladeshi delta.At the base of the Himalayan range, 13 C of bulk organic matter reveals a mixing between C3 plant inputs and fossil C org derived from source rock erosion. In the delta, organic matter transported by the Brahmaputra results from similar mixing while organic matter transported by the Ganga clearly results from the mixing between fossil C org and a C4 plant rich endmember mainly originating from the floodplain. During the Gangetic floodplain transit, recent C org derived from the Himalaya is oxidised and is replaced by C org derived from the A C C E P T E D M A N U S C R I P T floodplain. This process is likely related to channel avulsion, generating re-erosion of sediments previously deposited in the plain. Determining the extent of such a renewal process would require knowing the exact 13 C of the floodplain C org . However, conservative hypotheses indicate that at least 50 % of the C org is renewed. The case of the Brahmaputra is ambiguous due to the lack of marked C3/C4 difference between Himalayan and plain vegetation. Differences in the floodplain width and rivers morphology however suggest lower 670

( a )Figure 1 :

 a1 FIGURE CAPTIONS

Figure 2 :Figure 3 :

 23 Figure 2: Typical Transmitted Electron Microscope (a,b), binocular (c) and natural (d,e) 900

Figure 4 :

 4 Figure 4: Total C org content of river sediments from the Brahmaputra basin as a function of their Al/Si ratio. Different samplings define positive linear relation between TOC + and Al/Si

Figure 5 :

 5 Figure 5: Evolution of grain size distribution with sampling depth for suspended (SL) and bed

Figure 6 :

 6 Figure 6: Total C org content of river sediments from the G-B system as a function of the

Figure 7 :Figure 8 :

 78 Figure 7: N 2 adsorption-desorption isotherms for surface suspended sediment of the Ganga

Figure 9 :Figure 10 :

 910 Figure 9: Organic carbon stable isotopic composition ( 13 C org ) of river sediments from the Ganga basin as a function of their TOC + . Trans-Himalayan rivers at the outflow of the

Figure 11 :

 11 Figure 11: Simplified map of the G-B fluvial system showing the evolution of 13 C org values from the Himalayan range to the delta. Bold numbers represent 13 C org values of surface suspended sediments; italic numbers represent 13 C org values of fine-grained bank sediments used as analogous of suspended sediments. 960

  Figure 1

  decarbonation that solubilizes significant amounts of C org . Detailed description of this method as well as calibration data allowing the taking into account C org solubilization during decarbonation are described inGALY et al. (2007a). Samples were crushed in an agate mortar

		and leached with 4 % HCl at 85 °C during 1 hour to remove any carbonate particles
		(including detrital dolomite). After careful rinsing and drying at 50 °C, samples were
		homogenised in an agate mortar. Elemental and isotopic compositions were then determined
		using a modified EuroEA3028-HT elemental analyser coupled to a GV Instruments IsoPrime
		continuous-flow isotope mass spectrometer. Total C org concentrations (TOC + ) were then
	200	calculated from the C org content determined on decarbonated sediments. The abbreviation

Table 1 : Chemical composition, organic carbon composition, specific area and grain size of river sediments from the Ganga- Brahmaputra basin.

 1

	Sample #	River	Locality	Latitude	Longitude	Type	Date	TSS	Al/Si	TOC +	13 Corg	SA	External SA < 25 m
				°N	min	°E	min	depth (m)		g/l	mol:mol	%	‰	m 2 /g	m 2 /g	% v
	PB 76	Rapti	Bahlubang	27	50.2	82	32.4	SL surf	14/07/05	2.6	0.22	0.27	-24.4
	MO 315	Kali		27	54.2	83	89.2	SL surf	08/07/98		0.24	0.27	-25.0
	PB 61	Kali	confluence	27	44.5	84	25.3	SL surf	11/07/05	4.4	0.24	0.33	-24.9
	MO 305	Seti		28	3.0	84	4.5	SL surf			0.29	0.20	-22.4
	MO 301	Trisuli	Benighat	27	48.6	84	46.8	SL surf			0.30	0.31	-24.7
	PB 82	Trisuli		27	48.6	84	50.2	SL surf	14/07/05	0.5	0.36	0.52	-24.4
	PB 72	Karnala Nadi	Highway bg.	26	52.7	86	8.5	SL surf	13/07/05	1.1	0.34	0.83	-25.5
	PB 73	Karnala Nadi	Highway bg.	26	52.7	86	8.3	SL surf	13/07/05	5.3	0.10	0.20	-25.6
	BR 133	Gomati		25	34.6	82	59.8	Bank	09/08/01		0.28	0.63	-21.9
	Trans-Himalayan rivers
	PB 79	Karnali	Chisapani	28	38.5	81	17.0	SL surf	15/07/05	1.3	0.21	0.41	-25.6			45.1
	PB 80	Karnali	Chisapani	28	40.7	81	17.1	Bank	15/07/05		0.10	0.02	-23.6
	BR 356	Ghaghara	Ayodia	26	48.8	82	12.2	Bank	15/05/04		0.30	0.29	-23.0
	BR 372	Ghaghara	Dohrighat	26	16.5	83	30.8	Bank	16/05/04		0.24	0.24	-23.2
	BR 344	Ghaghara	Revelganj	25	49.2	84	35.1	Bank	12/05/04		0.27	0.26	-23.0
	MO 331	Narayani	Narayanghat	27	41.4	84	23.7	SL surf			0.24	0.22	-24.4
	MO 217	Narayani	Narayanghat	27	41.4	84	23.7	BL	20/05/97		0.15	0.08	-23.8
	NAG 48 †	Narayani	Narayanghat	27	41.4	84	23.7	Bank			0.15	0.11	-24.0
	PB 60	Narayani	Narayanghat	27	42.2	84	25.6	SL surf*	11/07/05		0.27	0.34	-24.5
	PB 58	Narayani	Narayanghat	27	42.2	84	25.6	SL surf	11/07/05	2.9	0.27	0.33	-24.7			53.9
	PB 57	Narayani	Narayanghat	27	42.2	84	25.6	SL 2 m	11/07/05	4.8	0.23	0.24	-24.3			37.2
	PB 56	Narayani	Narayanghat	27	42.2	84	25.6	SL 4 m	11/07/05	5.6	0.22	0.21	-24.3			25.1
	PB 55	Narayani	Narayanghat	27	42.2	84	25.6	SL 6 m	11/07/05	9.1	0.21	0.20	-24.3			26.1
	PB 54	Narayani	Narayanghat	27	42.2	84	25.6	SL 8 m	11/07/05	10.2	0.19	0.18	-24.2			19.4
	BR 335	Gandak	Barauli	26	21.6	84	44.7	Bank	11/05/04		0.22	0.26	-23.3
	BR 113	Gandak	Hajipur	25	41.3	85	11.3	SL surf	05/08/01	1.2	0.31	0.59	-23.9
	BR 114	Gandak	Hajipur	25	41.3	85	11.3	SL 1.5 m	05/08/01		0.27	0.32	-23.8
	BR 117	Gandak	Hajipur	25	41.3	85	11.3	Bank	05/08/01		0.16	0.11	-22.6
	PB 65	Kosi	Chatra	26	50.8	87	9.1	SL 3.8 m	13/07/05	5.7	0.30	0.32	-25.2			36.3
	PB 66	Kosi	Chatra	26	50.8	87	9.1	SL 2.8 m	13/07/05	3.4	0.30	0.35	-25.4			44.3
	PB 67	Kosi	Chatra	26	50.8	87	9.1	SL 1 m	13/07/05	2.8	0.33	0.40	-25.4			48.2
	PB 68	Kosi	Chatra	26	50.8	87	9.1	SL surf	13/07/05	2.6	0.32	0.42	-25.5			48.7
	PB 70	Kosi	Chatra	26	50.8	87	9.1	Bank	13/07/05		0.14	0.05	-23.6
	BR 331	Kosi	Dumarighat	25	32.4	86	43.3	Bank	10/05/04		0.31	0.33	-21.8
	BR 102	Kosi	confluence	25	25.1	87	13.7	SL 6.5 m	05/08/01		0.22	0.14	-23.5
	BR 103	Kosi	confluence	25	25.1	87	13.7	BL	05/08/01		0.16	0.04	-23.3
	Mainstream
	BR 351	Ganga	Allahabad	25	26.0	81	53.0	Bank	14/05/04		0.29	0.32	-21.6
	BR 140	Ganga	Varanasi	25	18.4	83	0.6	SL 1.5 m	10/08/01	0.4	0.32	0.73	-21.2
	BR 139	Ganga	Varanasi	25	18.1	83	0.5	SL 3 m	10/08/01	0.7	0.31	0.72	-21.2
	BR 138	Ganga	Varanasi	25	18.3	83	0.6	SL 6 m	10/08/01	1.1	0.25	0.54	-21.3
	BR 137	Ganga	Varanasi	25	18.1	83	0.5	SL 8 m	10/08/01	1.5	0.19	0.36	-21.3
	BR 136	Ganga	Varanasi	25	17.9	83	0.6	BL 4.5 m	10/08/01		0.09	0.02	-25.0
	BR 144	Ganga	Varanasi	25	19.1	83	1.5	BL 15 m	10/08/01		0.15	0.05	-23.9
	BR 122	Ganga	Patna	25	37.4	85	9.2	SL 1.5 m	08/08/01	1.0	0.28	0.56	-22.1			64.9
	BR 120	Ganga	Patna	25	37.5	85	9.1	SL 3.5 m	08/08/01	1.2	0.25	0.56	-22.2			55.9
	BR 119	Ganga	Patna	25	37.5	85	9.0	SL 5.2 m	08/08/01	1.1	0.27	0.53	-21.9			59.1
	BR 121	Ganga	Patna	25	37.4	85	9.1	SL 6.1 m	08/08/01	1.1	0.27	0.54	-22.0			62.5
	BR 125	Ganga	Patna	25	37.4	85	8.8	SL 6.2 m	08/08/01	0.5	0.40	0.96	-22.0			80.9
	BR 118	Ganga	Patna	25	37.5	85	9.1	SL 7.8 m	08/08/01	3.1	0.15	0.21	-22.6			14.6
	BR 124	Ganga	Patna	25	37.4	85	8.8	BL 7 m	08/08/01		0.11	0.03	-24.3			1.4
	BR 303	Ganga	Patna	25	37.4	85	9.1	SL 6.7 m	07/05/04	0.2	0.12	0.20	-26.4
	BR 304	Ganga	Patna	25	37.4	85	9.1	SL 3.4 m	07/05/04	0.2	0.12	0.21	-26.2
	BR 306	Ganga	Patna	25	37.4	85	9.1	Bank	07/05/04		0.10	0.03	-24.3
	BR 314	Ganga	Barauni	25	22.8	85	59.9	Bank	08/05/04		0.29	0.42	-22.5
	BR 109	Ganga	Manihari	25	18.5	87	36.0	SL 1.5 m	06/08/01	1.1	0.30	0.57	-21.8
	BR 108	Ganga	Manihari	25	18.5	87	36.0	SL 5.2 m	06/08/01	1.2	0.29	0.61	-22.4
	BR 107	Ganga	Manihari	25	18.2	87	36.2 SL 10.8 m	06/08/01	2.3	0.25	0.53	-22.7
	BR 106	Ganga	Manihari	25	18.1	87	36.3	Bank	06/08/01		0.13	0.07	-23.3
	BR 104	Ganga	Manihari	25	19.0	87	36.2	SL 4.3 m	06/08/01	3.1	0.22	0.42	-22.3
	BR 105	Ganga	Manihari					SL 5.6 m	06/08/01		0.17	0.26	-22.7
	BGP 7 †	Ganga	R a jshahi	24	21.5	88	36.5	SL surf	02/08/93	1.1	0.37	0.71	-21.7
	BGP 5 †	Ganga	R a jshahi	24	21.5	88	36.5	BL	02/08/93		0.21	0.19	-22.3
	BGP 6 †	Ganga	R a jshahi	24	21.5	88	36.5	BL	02/08/93		0.12	0.05	-24.5
	BGP 68	Ganga	R a jshahi	24	21.5	88	36.5	BL	02/08/93		0.11	0.05	-23.5
	BR 212	Ganga	Harding bridge	24	3.7	89	1.6	SL 1 m	16/07/02	0.6	0.38	0.66	-22.0			81.9
	BR 211	Ganga	Harding bridge	24	3.6	89	1.7	SL 3.5 m	16/07/02	0.8	0.34	0.62	-22.4			74.9
	BR 209	Ganga	Harding bridge	24	3.8	89	1.6	SL 5 m	16/07/02	0.7	0.35	0.67	-22.3			75.5
	BR 208	Ganga	Harding bridge	24	3.8	89	1.6	SL 10 m	16/07/02	0.7	0.34	0.62	-22.1			71.9
	BR 210	Ganga	Harding bridge	24	3.8	89	1.6	SL 17 m	16/07/02	1.2	0.28	0.47	-22.4			52.8
	BR 214	Ganga	Harding bridge	24	3.6	89	1.7	BL 22 m	16/07/02		0.14	0.10	-22.8			12.4
	BR 417	Ganga	Harding bridge	24	1.4	89	2.0	SL surf*	13/07/04		0.38	0.53	-21.0			80.5
	BR 415	Ganga	Harding bridge	24	1.4	89	2.0	SL surf	13/07/04	0.8	0.38	0.53	-21.1			77.8
	BR 414	Ganga	Harding bridge	24	1.3	89	2.1	SL 2 m	13/07/04	1.0	0.33	0.46	-20.9			69.4
	BR 413	Ganga	Harding bridge	24	1.3	89	2.3	SL 4 m	13/07/04	1.3	0.29	0.42	-20.6			62.0
	BR 412	Ganga	Harding bridge	24	1.4	89	2.4	SL 6.5 m	13/07/04	1.5	0.28	0.38	-21.2			55.1
	BR 411	Ganga	Harding bridge	24	1.5	89	2.3	SL 9 m	13/07/04	2.9	0.21	0.22	-21.4			31.8
	BR 418	Ganga	Harding bridge	24	1.4	89	2.0	BL 10 m	13/07/04		0.13	0.03	-22.7			1.2
	BR 515	Ganga	Harding bridge	24	2.3	89	2.0	SL surf	23/07/05	0.9	0.37	0.71	-20.7	34.8	26.0	86.5
	BR 514	Ganga	Harding bridge	24	2.3	89	2.0	SL 2.5 m	23/07/05	1.4	0.32	0.57	-20.6
	BR 513	Ganga	Harding bridge	24	2.3	89	2.0	SL 5 m	23/07/05	1.7	0.28	0.45	-21.0	21.3	16.7	65.8
	BR 512	Ganga	Harding bridge	24	2.3	89	2.0	SL 7 m	23/07/05	1.8	0.27	0.42	-21.0
	BR 511	Ganga	Harding bridge	24	2.3	89	2.0	SL 10 m	23/07/05	2.4	0.24	0.32	-21.4	17.4	13.7	46.3
	BR 516	Ganga	Harding bridge	24	2.3	89	2.0	BL 11 m	23/07/05		0.13	0.05	-22.4	1.3	1.0	3.7
	BR 519	Ganga	Harding bridge	24	2.5	89	2.2	SL surf	23/07/05	0.7	0.41	0.82	-20.8
	BR 518	Ganga	Harding bridge	24	2.5	89	2.2	SL 5 m	23/07/05	1.5	0.31	0.53	-20.9			69.6
	BR 517	Ganga	Harding bridge	24	2.5	89	2.2	SL 9.8 m	23/07/05	1.8	0.28	0.47	-20.8
	BR 520	Ganga	Harding bridge	24	2.5	89	2.2	BL 10 m	23/07/05		0.17	0.14	-22.3
	BR 522	Ganga	Harding bridge	24	2.5	89	2.2	SL surf*	23/07/05		0.40	0.70	-20.0

Table 1

 1 (continued)

	Sample #	River	Locality					Type	Date	TSS	Al/Si	TOC +	13 Corg	SA	External SA < 25 μm
				°N	min	°E	min	depth (m)		g/l	mol:mol	%	‰	m 2 /g	m 2 /g	% v
	Secondary tributaries
	BR 25	Ranga Nadi		27	12.2	94	3.5	Bank	29/10/99		0.12	0.31	-24.1
	BR 58	Ranga Nadi		27	12.3	94	3.6	Bank	27/07/01		0.10	0.15	-23.6
	BR 35	Puthimari		26	22.0	91	39.2	Bank	30/10/99		0.15	1.26	-22.8
	BR 69	Puthimari		26	22.0	91	39.2	SL surf	30/07/01		0.28	1.50	-23.6
	BR 70	Puthimari		26	22.0	91	39.2	Bank	30/07/01		0.15	0.88	-23.3
	BR 76	Tipkai		26	13.1	90	8.3	Bank	30/07/01		0.09	0.02	-21.1
	BR 27	Jia Bhareli		26	48.6	92	52.6	Bank	29/10/99		0.15	0.34	-22.5
	BR 63	Jia Bhareli		26	48.6	92	52.8	SL surf	29/07/01		0.22	1.16	-24.5
	BR 64	Jia Bhareli		26	48.6	92	52.8	Bank	29/07/01		0.12	0.60	-23.2
	Trans-Himalayan rivers
	BR 59	Siang		28	4.7	95	20.2	SL surf	28/07/01		0.26	0.33	-23.7
	BR 60	Siang		28	4.7	95	20.2	Bank	28/07/02		0.18	0.05	-19.9
	BR 21	Subansiri		27	26.9	94	15.1	Bank	28/10/99		0.12	0.15	-22.5
	BR 61	Subansiri		27	26.7	94	15.4	SL surf	28/07/01		0.28	0.77	-26.3
	BR 62	Subansiri		27	26.7	94	15.4	Bank	28/07/01		0.14	0.17	-22.6
	BR 33	Manas		26	29.7	90	55.0	Bank	30/10/99		0.14	0.15	-23.8
	BR 71	Manas		26	29.7	90	55.2	SL surf	30/07/01		0.25	0.45	-24.5
	BR 72	Manas		26	29.7	90	55.2	Bank	30/07/01		0.13	0.09	-22.6
	BGP 11 †	Tista	Kaunia	25	47.5	89	26.2	Bank	04/08/93		0.20	0.10	-23.7
	BGP 76	Tista	Kaunia	25	47.5	89	26.2	Bank	07/03/94		0.24	0.15	-23.7
	Mainstream
	BR 29	Brahmaputra	Tezpur bg.	26	36.7	92	51.2	Bank	29/10/03		0.16	0.13	-22.9
	BR 65	Brahmaputra	Tezpur bg.	26	36.7	92	51.2	SL surf	29/07/01		0.30	0.82	-24.3
	BR 66	Brahmaputra	Tezpur bg.	26	36.7	92	51.2	BL	29/07/01		0.18	0.13	-22.4
	BR 8	Brahmaputra	Guwahati	26	11.2	91	44.3	SL 5 m	25/10/99	1.2	0.26	0.46	-25.5
	BR 7	Brahmaputra	Guwahati	26	11.2	91	44.3	SL 5 m	25/10/99	2.5	0.22	0.21	-25.3
	BR 6	Brahmaputra	Guwahati	26	11.6	91	44.2	SL surf	25/10/99	0.8	0.32	0.74	-24.7
	BR 2	Brahmaputra	Guwahati	26	11.5	91	44.4	SL 5 m	25/10/99		0.25	0.46	-24.9
	BR 4	Brahmaputra	Guwahati	26	11.6	91	44.2	SL 10.5 m	25/10/99	1.8	0.24	0.30	-24.7
	BR 3	Brahmaputra	Guwahati	26	11.5	91	44.4	SL 11 m	25/10/99	0.8	0.28	0.49	-24.5
	BR 9	Brahmaputra	Guwahati	26	11.6	91	45.0	Bank	25/10/99		0.18	0.08	-23.1
	BR 55	Brahmaputra	Guwahati	26	11.6	91	44.2	SL surf	26/07/01		0.32	0.62	-23.9
	BR 54	Brahmaputra	Guwahati	26	11.6	91	44.2	SL 5 m	26/07/01		0.32	0.67	-23.9
	BR 53	Brahmaputra	Guwahati	26	11.6	91	44.2	SL 10 m	26/07/01		0.22	0.37	-23.8
	BR 52	Brahmaputra	Guwahati	26	11.6	91	44.2	SL 15 m	26/07/01		0.22	0.29	-23.7
	BR 56	Brahmaputra	Guwahati	26	11.6	91	44.2	BL	26/07/01		0.19	0.09	-23.4
	BR 73	Brahmaputra	Dhubri	26	1.1	89	59.8	SL surf	30/07/01		0.33	0.68	-23.5
	BR 74	Brahmaputra	Dhubri	26	1.1	89	59.8	BL	30/07/01		0.16	0.05	-22.3
	BGP 18 † Brahmaputra	Chilmari	25	33.0	89	43.2	SL surf	05/08/96	0.4	0.33	0.59	-23.0
	BGP 82 † Brahmaputra	Chilmari	25	33.0	89	43.2	BL	07/03/94		0.16	0.05	-22.2
	BGP 14 † Brahmaputra	Chilmari	25	33.0	89	43.2	BL	05/08/93		0.19	0.22	-22.9
	BR	Brahmaputra	Sirajganj	24	28.4	89	43.6	SL 6.5 m	11/07/04	4.3	0.23	0.26	-23.3			25.2
	BR	Brahmaputra	Sirajganj	24	27.5	89	43.7	SL 5 m	12/07/04	6.0	0.22	0.22	-23.2			17.8
	BR	Brahmaputra	Sirajganj	24	27.6	89	43.7	SL 3 m	12/07/04	3.1	0.24	0.32	-22.0			36.1
	BR	Brahmaputra	Sirajganj	24	28.0	89	43.5	11 m	12/07/04	6.4	0.22	0.26	-23.0	3.6	3.6	19.0
	BR	Brahmaputra	Sirajganj	24	28.1	89	43.5	SL 1.5 m	12/07/04	1.8	0.29	0.44	-23.0			51.8
	BR	Brahmaputra	Sirajganj	24	28.1	89	43.5	SL surf	12/07/04	1.3	0.32	0.54	-23.1	7.6	7.6	65.8
	BR	Brahmaputra	Sirajganj	24	28.4	89	43.6	SL surf*	11/07/04		0.32	0.50	-22.5			65.4
	BR	Brahmaputra	Sirajganj	24	28.2	89	43.9	SL surf*	23/07/04		0.37	0.64	-23.9			87.2
	BR	Brahmaputra	Sirajganj	24	28.5	89	43.7	SL surf	23/07/04	1.3	0.36	0.69	-23.9			81.4
	BR	Brahmaputra	Sirajganj	24	28.4	89	43.6	SL 3 m	23/07/04	2.9	0.28	0.45	-23.5			50.6
	BR	Brahmaputra	Sirajganj	24	28.0	89	43.8	SL 6 m	23/07/04	2.4	0.29	0.50	-23.9			54.7
	BR	Brahmaputra	Sirajganj	24	28.3	89	43.5	SL 9 m	23/07/04	6.2	0.22	0.29	-23.6			23.6
	BR	Brahmaputra	Sirajganj	24	28.4	89	43.7	BL 10 m	23/07/04		0.17	0.04	-22.1			1.7
	BR	Brahmaputra	Sirajganj	24	30.9	89	44.1	BL	23/07/04		0.31	0.68	-24.1			66.2
	BR	Brahmaputra	Sirajganj	24	27.4	89	43.7	BL	23/07/04		0.22	0.19	-23.1
	BR	Brahmaputra	Sirajganj	89	44.6	24	28.6	SL surf*	21/07/05		0.31	0.58	-23.5
	BR	Brahmaputra	Sirajganj	89	44.6	24	28.6	SL 6.5 m	22/07/05	2.0	0.29	0.51	-23.7			44.2
	BR	Brahmaputra	Sirajganj	89	44.6	24	28.6	SL 2.5 m	22/07/05	0.8	0.33	0.59	-23.9
	BR	Brahmaputra	Sirajganj	89	44.6	24	28.7	BL 7.5 m	22/07/05		0.18	0.11	-23.2	1.8	1.3
	BR	Brahmaputra	Sirajganj	89	43.9	24	28.4	SL 9.8 m	22/07/05	2.3	0.25	0.37	-24.3	5.2	5.2	39.8
	BR	Brahmaputra	Sirajganj	89	43.7	24	28.4	SL 7 m	22/07/05	2.1	0.27	0.40	-23.9			55.4
	BR	Brahmaputra	Sirajganj	89	43.8	24	28.4	SL 5 m	22/07/05	1.6	0.29	0.49	-23.4	6.5	6.5
	BR	Brahmaputra	Sirajganj	89	43.8	24	28.4	SL 2.8 m	22/07/05	1.4	0.32	0.53	-23.6
	BR	Brahmaputra	Sirajganj	89	43.8	24	28.4	SL surf	22/07/05	0.8	0.36	0.64	-24.1	8.9	8.9	78.1
	BR	Brahmaputra	Sirajganj	89	43.8	24	28.4	BL 10 m	22/07/05		0.15	0.05	-21.8			1.4
	BR	Brahmaputra	Sirajganj	24	23.9	89	47.8	SL surf	15/07/02	1.2	0.31	0.57	-23.0			64.3
	BR	Brahmaputra	Sirajganj	24	24.2	89	47.8	SL 2 m	15/07/02		0.27	0.53	-23.4			50.0
	BR	Brahmaputra	Sirajganj	24	23.4	89	47.8	SL 6 m	15/07/02		0.26	0.52	-23.6			44.3
	BR	Brahmaputra	Sirajganj	24	23.1	89	47.9	SL 9.5 m	15/07/02	1.4	0.21	0.29	-23.0			16.4
	BR	Brahmaputra	Sirajganj	24	23.0	89	47.9	SL 11.5 m	15/07/02	5.9	0.19	0.14	-23.3
	BR	Brahmaputra	Sirajganj	24	23.1	89	47.8	BL 12 m	15/07/02		0.20	0.06	-22.7			2.5
	BR	Brahmaputra	Sirajganj					SL 1 m	15/07/02		0.23	0.25	-23.6
	BGP 3 †	Brahmaputra	Aricha Ghat	23	50.0	89	46.1	SL surf	01/08/96	0.3	0.37	0.72	-22.9
	TOC

+

and Al/Si of Bangladesh river sediments presented in this study are from

Galy et al. (2007)

. Samples marked with a † are from

[START_REF] Aucour | Fluxes and sources of particulate organic carbon in the Ganga-Brahmaputra river system[END_REF]

. Latitude Longitude SA = specific area, External SA = specific area corrected for the microporosity (see text) Brahmaputra basin SL = suspended sediment with depth of sampling, surf = surface sediment, * = sediment obtained by settling + filtration, BL = bed sediment.

Table 2 : Organic carbon content and sable isotopic composition of gravel samples from Himalayan rivers.

 2 (b) Average value was calculated as the arithmetic mean of the 11 samples.

	Latitude	Longitude
		gravel 2-4mm

Table 1 .

 1 The Himalayan range, Tibetan plateau, Indian shield and Indo-Gangetic floodplain (white) are also shown.

Ganga basin

Acknowledgements

This study was funded by CNRS-INSU programs "Eclipse" and "Relief de la Terre". We thank Prof. Mustafizur Rahman from Dhaka University, Dr Sunil K. Singh from PRL Amadabad, and Dr. Ananta Gajurel from Tribhuvan University for their constant


Guillaume Le Roux

of urban and regional studies. Residential Mobility

Keywords: housing, migration, residential mobility, spatiotemporal data, urban geography

Residential mobility has been the subject of much research in various disciplines such as demography, economics, geography, history, and sociology. The meaning of this concept changes depending on the discipline, the date, and the national academic context. In its broadest sense, residential mobility can be defined as residence relocation regardless of the distance between the dwellings. The focus on the topic shifted from the measure of interregional migration to the study of individual behaviors in urban areas. In the meantime, the approaches diversified from a transversal perspective to a life course perspective, offering promising prospects of research.

Residential mobility has been the subject of much research in various disciplines such as demography, economics, geography, history, and sociology. The meaning of the concept changes depending on the discipline, the date, and the national academic context. In its broadest sense, residential mobility can be defined as residence relocation regardless of the distance between the dwellings. A dwelling unit can also be broadly defined as any living quarter used to shelter a household, whether it is built in precarious materials or not, mobile or static. The concept of residential mobility encompasses under this definition internal and international migration, and changes of residence within the same urban area. However, the introduction of this concept in academic research has primarily responded to the need for measuring residence relocation within the same urban unit.

Changes of focus on residential mobility and diversification of approaches

Interest in the theme of residential mobility, and the angle from which the subject is treated, has evolved according to changes in societies and of the social demand. In the USA, at the end of the 1970s, most of the empirical and theoretical work was centered on interregional and interurban mobility: the concern was mainly to understand the mobility of labor. Research on intraurban residential mobility has mostly been developed since the 1970s. However, urban ecology works on the city of Chicago early started highlighting the relationship between intraurban residential mobility and urban change in a context of growth of the city by migration. In France, research on residential mobility was initially focused on migration due to the magnitude of the rural exodus in the middle of the twentieth century. Then, in the 1980s, the focus shifted to intraurban mobility due to the "urban crisis" and the highlighting of inequalities in access to urban resources. In Latin America, while the theme of internal migration is the subject of wide scientific interest, research on residential mobility within cities is rare and relatively new. In most of the national contexts, the focus shifted from the observation of migration in a context of rural exodus to intraurban residential mobility: as countries progress in demographic transition and urbanization, the relative weight of intraurban residential mobility is becoming more important than migration (Zelinsky 1971). In France, the idea of residential mobility started spreading widely in the social sciences in the 1990s. According to Jacques [START_REF] Brun | La mobilité résidentielle et les sciences sociales[END_REF], the lexical shift from migration to residential mobility Version auteur au 08/01/2019 Le Roux G. ( 2019), « Residential Mobility », The Wiley-Blackwell Encyclopedia of urban and regional studies.

is not neutral and cannot merely be explained by the growing interest on intraurban mobility: it implicitly relates the geographical move and other forms of mobility -including social mobilityand integrates a more comprehensive vision of mobility.

In parallel with the change of point of view on residential mobility, approaches have diversified from those establishing laws at a macroscopic level to those focused on individual behavior.

One type of approach focuses on factors of residential mobility at a macroscopic level. The first models to analyze interregional mobility were based on the macroeconomic theories of "pushpull": push factors impel people to leave their areas of origin and pull factors attract them to certain regions, according to the greater or lower presence of resources (jobs, housing, equipment). The Zipf model is a simplistic translation of this theory but more complex models have been developed. Moving to a microlevel of analysis, a second type of approach is based on microeconomic theories. In these theories, individuals make rational choices: as consumers they maximize utility -under the constraint of their incomes -and intentionally decide to relocate (De Jong and Gardner 1981). Despite the fact that these models take more and more factors into account (cost of relocation, duration of residence, household context, local social ties, etc.) and explain human behaviors in a simple way, they are criticized because of the assumptions that underlie them: for example, the fact that individuals are fully informed of the offer and of the consequences of their relocation, or that the aspirations are defined as common to the entire population. These approaches that give primacy to market forces and economic modeling are much more developed in the USA, whereas European researchers place more stress on the complexity of the mobility process, supposedly due to greater government intervention in the housing market (Strassman 2001).

A third type of approach can be called the "behavioral approach." This focuses on actual individual behaviors and on the decision-making process. These works show how residential choices can diverge from rational behaviors and be made under uncertainty. This type of research gathers studies from the relocation decision to the choice process. European and North American research highlights the role of the life cycle on the decision to move: relocation decisions are broadly related to the stages of the family constitution (leaving home, union, birth of children, child departures, etc.) and to the adaptation of housing to the new family situation. Other elements motivate individuals to change residence: the degradation of the residential environment, the desire for homeownership, looking for comfort, the affirmation of a new social status, or the choice of a new lifestyle. Anglo-Saxon works introduced the notion of residential stress to describe the mismatch between the household needs or preferences and the characteristics of the actual housing and neighborhood [START_REF] Brown | The Intra-Urban Migration Process: A Perspective[END_REF]. A household will relocate at a certain level of stress. The emergence in France in the late 1980s of the terms "residential strategies" and "residential choices," in a context of diversification of housing supply, highlights the flexibility that individuals and households have in the selection process. Residential choices result in the choice of a type of dwelling (house, apartment, size, comfort, architectural criteria), a tenure (ownership, rental), a location, and an urban context (on objective and subjective criteria). Households with different economic capital and social capital do not have the same flexibility: some have no or little choice and others have free choice and can express a particular logic of social, professional, or familial mobility [START_REF] Authier | Elire domicile. La construction sociale des choix résidentiels[END_REF].

The behavioral approach show the relations between life cycle and residential mobility and the role of long term experiences on the decision-making process. This led to the fourth type of approach: the life course approach. This approach focuses, through a lifetime perspective, on the link between different life domains of individuals (residential, family, professional) and on the Version auteur au 08/01/2019 Le Roux G. ( 2019), « Residential Mobility », The Wiley-Blackwell Encyclopedia of urban and regional studies.

interactions with other individuals' trajectories. It spread in the northern countries at the end of the 1980s but has much anteriority in Latin America and Africa.

In France, the introduction of the life course perspective in the discipline of demography expresses more generally the renewed interest in the individual actor in the social sciences. The shift in the study of residential mobility, from a transversal to a life course perspective, has been driven by numerous exchanges between disciplines and areas of empirical research. The transversal perspective, based on statistics on aggregated population at a given time, was the dominant approach in the mid-twentieth century in France. This was also the case in Anglo-Saxon literature until the pioneering work of Peter [START_REF] Rossi | Why Families Move: A Study in the Social Psychology of Urban Residential Mobility[END_REF], which centered the analysis of residential mobility at the household level. The statistics on aggregated populations described social facts but remained limited in interpreting phenomena by the ecological error -the error interpreting the correlation between two aggregated measures at an individual level. Then the longitudinal approach was developed by introducing time into the analysis. This approach consists in the retrospective or prospective follow-up of homogeneous cohorts to study the occurrence of demographic processes, independently of each other. However, this approach does not encompass two overarching phenomena: the analysis of the heterogeneity of populations and the analysis of interdependencies between demographic phenomena. Putting away the hypothesis of independence of the various demographic phenomena, the life course approach highlights the interactions between the residential, familial, and professional trajectories. The focus on residential mobility thus altered in order to better understand individual behaviors, to study to which extent an event can influence the individual life course, and how distinct characteristics can push an individual to behave differently from another.

A survey set up in the 1960s in the city of Monterrey in Mexico, a pioneering study in Latin America, is a model in terms of observation of spatial mobility with a biographical approach. It collected the migratory, professional, educational, and familial trajectories of over 1,500 men living in the city. The biographical approach to residential mobility was then gradually developed through theoretical and methodological exchanges between disciplines. Biographies and life stories are tools widely used today. Now, data collection and analysis tools are broadly diversified and improved, contributing to a better understanding of the phenomenon of residential mobility. Abundant research focuses on the links between residential mobility and life cycle, and between residential mobility and occupational mobility.

Achievements, difficulties, and new directions

The measure of residential mobility is based on different sources: population registers, census data, and specific surveys. In the late 1990s, many studies of the factors of residential mobility showed recurrences of phenomena observed in various geographical contexts. Changes in the intensity of residential mobility during the life cycle are fairly well known: high at young ages, it falls back after 40 years and recovers, more or less, after retirement. The intensity and distance of residence relocations vary by income levels and socio-rofessional categories. Mobility is lower for owners and those who live in large homes. Finally, mobility is correlated to important life events: partnerships, divorce, births, changes in education, and work opportunities stimulate changes in residence. However, these events do not affect the distance of relocations in the same way. Changes in work are not decisive in residential mobility within the same city: they concern mainly long distance mobility. Several reasons are cited in the French literature but can be generalized to a large number of contexts: the modernization of intraurban transport means people move less for reasons linked to space, and, in a context of job instability, the dwelling has become the major social security. On the contrary, reasons for moving over short distances are more related to the adaptation of the dwelling to the size of the family.

General trends are now fairly well known. Nevertheless, improvements of data collection and analysis tools revealed the complexity of transitions in the life cycle of individuals or of behaviors of certain groups. For example, works have focused on the study of young adults leaving the parental home, of elderly people retiring, or on the behaviors of ethnic groups. Most of the works show how complex or "fuzzy" certain transitions are [START_REF] Grab | Fuzzy states and complex trajectories. Observation, modelization and interpretation of life histories[END_REF] or highlight the diversity of life cycles. In many national contexts, growing family instability and job insecurity impact lifecycles and residential mobility. Studies in Western countries describe, for example, the phenomenon of return of young adults to the parental home after having an independent dwelling, because of economic difficulties or job loss. More recently, the conceptualization of the second demographic transition has encouraged new fields of research about solo living, recomposed families, and couples who do not share a dwelling (Coulter, van Ham, and Findlay 2015).

One of the contributions of the life course approach is to link lives through time and space and to take into account the interactions between individuals and structures. It is on these two points that innovations in collection and analysis of biographies have more recently been focused, but many challenges remain.

Despite the methodological innovations, measurement and interpretation of residential mobility phenomena remain difficult given the diversity of elements to take into consideration, the complexity of the facts, and the limitations imposed by the measure. First, residential mobility is often analyzed at the individual or household level. However, the use of the concept of household -that is to say the coresidents in a dwelling at a given time -is under discussion. This group is an entity that changes over time depending on people leaving, births, deaths, arrivals, and so on. Also, the residential stability of a household may, as shown in some works in West Africa, hide a high residential mobility of individuals attached to it. Conversely, studies on residential mobility have shown that the mobility of individuals is rarely isolated and must be analyzed with respect to their collective or family unit. In Africa, the detection of circulations of people through all the dwellings of the extended family, described under the concept of the family residential system, revealed the multilocal character of family strategies. The concept of residential system was then used more broadly by considering all the places of residence of individuals and their families. In Latin America, the multiresidence of individuals and families was taken into account very early in surveys in Mexico, Ecuador, and Colombia. The complexity of these flows encounter measurement problems, particularly because of the shortness of the time scales on which these movements are held. In response to these challenges, surveys in India, Latin America, and West Africa have gradually introduced innovations in the collection of spatial mobility, feeding one another or inspired from other experiments, driven by the will to take into consideration the movements of individuals between different dwellings or different places of life, and to include people in their relation networks. In France, the survey Biographie et Entourage conducted by the French Institute for Demographic Research (INED) in 2001 is one of the most thorough biographical survey in aiming at liking lifes. Through the development of the concept of "entourage," the survey featured a retrospective collection of information on family members, members of the different households to which the individual belonged, and key individuals in the life of the respondent. However, this approach faces practical difficulties: the restitution of life courses by a third person endangers the quality of the information and the amount of information needed leads to large time requirements.

In addition, the life course approach guides us to analyze the interaction between residential mobility and wider structures, and to study how individual behaviors contribute to the production or the reproduction of sociospatial structures (Coulter, van Ham, and Findlay 2015).

The introduction of the notion of residential trajectory invites a renewed interest in the study of the relationships between social mobility and spatial mobility. In demography, this relationship is usually studied according to dwelling characteristics (tenure, comfort). Moving from a rental unit to homeownership is often associated with the idea of an upward trajectory and the opposite as a downward trajectory. The qualitative work of sociologists also shows that, for households, the choice of the place of residence corresponds to a choice of a lifestyle, indicating more or less consciously their social position. Then, characterizing the successive places of residence of an individual describes their social trajectory from residential choices -made according to the social labeling of spaces and habitat types -and considers their social position according to the resources offered by proximity -social, environmental, equipment [START_REF] Lévy | Population patterns and household trajectories milieu: The example of the Seine-Saint-Denis[END_REF]. Thus, the residential trajectories, in an economically and socially selective space, are partly a reflection of social trajectories. This angle of analysis, which has been the subject of a significant literature on "spatial assimilation" in the case of ethnic minorities in the USA, has been more scarcely developed from a wider sociodemographic perspective.

In return individuals socially requalify the spaces in which they settle. Urban change results, then, from the interaction of residential trajectories and spatial dynamics. For example, some research has highlighted the interactions between residential mobility and the dynamics of the housing stock through the study of household succession mechanisms [START_REF] Bourne | The Geography of Housing[END_REF]. This method aims at following the mobility of a household, usually in a new home -but also by the death or the departure of the agglomeration, the release chain and reallocation of housing that it entails: a household moving to a new home releases its dwelling which will be occupied by another household which leaves its own, and so forth. This chain of released dwellings initiated by the move of a household -called a vacancy chain -stops when a property is destroyed or when children leave home -no housing release in this case. Following vacancy chains, which evolve in the inverse way to households' residential mobility, is an investigation method initiated in the 1950s. Empirical work in major cities in Canada, England, and France showed that vacancy chains are relatively compartmentalized channels which generally reproduce social hierarchies. Households of different social levels can see their living conditions improve during their residential trajectory but in separate channels. The channels are influenced by the local context and, in return, the mobilities associated with the vacancy chains alter the context for future mobility chains. These mobility channels thus maintain social divisions of space but can also evolve over the long term through their impacts on the local contexts and the housing supply. The release and reassignment of housing, which constitutes the pulse of the process, depends not only on demographic phenomena (children leaving home, deaths, arrivals, and departures from the urban area), but also on housing production and transformation (construction, demolition, renovation, or modification of dwellings). These illustrations show how the spatial context influences mobility and in return how residential mobility impacts the local context.

The spatial contextualization of the residential trajectory depends on the accurate measurement of places during data collection. In connection with changing issues -from the measure of migrations to the study of residential behaviors -the reduction of the geographical scope of biographical surveys favored a more accurate collection of locations, allowing the characterization of successive places of the trajectories through secondary sources. It remains necessary to consider on the one hand context evolution, in order not to make the mistake of retrospectively characterizing places according to their current situation, and, on the other hand, that places are changing even when individuals are immobile. One difficulty remains in choosing the levels of context that characterize or influence the trajectories. In addition, studying interactions between intraurban dynamics and residential trajectories requires establishing a particularly complex observation system.

  Version auteur au 08/01/2019 Le Roux G. (2019), « Residential Mobility », The Wiley-Blackwell Encyclopedia of urban and regional studies.

	SEE ALSO: EURS0142; EURS0203; EURS0206; EURS0268; EURS0307; EURS0379; EURS0381