E Zehani

S Hassani

A Lusson

J Vigneron

A Etcheberry

P Galtier

V Sallet

Reconstruction of perfect ZnO nanowires facets with high optical quality

Keywords: ZnO nanowires, annealing, photoluminescence, surface exciton, XPS

ZnO nanowires were grown on sapphire substrates using metalorganic chemical vapor deposition. The samples were subsequently annealed under zinc pressure in a vacuum-sealed ampoule, at temperature ranging from 500 to 800°C. The originality and the main motivation to provide a zinc-rich atmosphere were to prevent the out-diffusion of zinc from the nanowires.

In doing so, the perfect structural properties and the morphology of the nanowires are kept.

Interestingly, photoluminescence experiments performed on nanowires annealed in a narrow window of temperature [580-620°C] show a spectacular improvement of the optical quality, as transitions commonly observable in high quality bulk samples are found. In addition, the intensity of the so-called "surface excitons" (SX) is strongly decreased. To accurately investigate the chemical modifications of the surface, XPS experiments were carried out and show that zinc hydroxide species and/or Zn(OH)2 sublayer were partially removed from the surface. These results suggest that the annealing process in zinc vapor helps to properly reconstruct the surface of ZnO nanowires, and improves the optical quality of their core. Such a thermal treatment at moderate temperature should be beneficial to nanodevices involving surface reaction, e.g. gas sensors.

I. Introduction

Semiconductor nanowires (NWs) are attractive building blocks for a new generation of electronic and opto-electronic devices, as well as gas sensors and nanogenerators. The last decades have shown the accurate control of the electrical properties of bulk materials and thin films, and more recently the evolution of the research towards nanotechnologies made possible both p-type and n-type conductions in 1D nanostructures (nanowires) based on silicon and III-V semiconductors [1]. In addition to these materials, ZnO is a II-VI compound which has demonstrated a great potential due a unique combination of physical properties, as well as an ability to be grown at the nanometer scale by using a variety of techniques [2,3] such as chemical vapor deposition (CVD) [4], metalorganic-CVD [5], molecular beam epitaxy [6], pulse laser deposition [7]. High quality material can also be achieved using low-cost techniques, e.g. electrodeposition [8] and hydrothermal synthesis [9], thus making ZnO a potential candidate for the future development of semiconductor-based nanodevices [10]. In particular, ZnO takes benefit of a direct wide band gap (3.37 eV) and a high exciton binding energy (60 meV). In order to introduce donors or acceptors, ZnO NWs have been doped with various impurities such as Al, Ga, In [11] (towards n-type) and N [12], P [13], Sb [14], As [15] (towards p-type). Nevertheless, for light-emitting applications, the achievement of stable and reproducible p-type conduction is still a bottleneck, due to high activation energies and selfcompensation effect of intrinsic defects [START_REF] Look | Doping and Defects in ZnO[END_REF]. Importantly, a main feature of ZnO material concerns its very reactive surface, highly sensitive to gases such as NOx, CO and NH3. The sensing mechanism is a surface reaction that leads to the modification of the conductance of the nanostructure, relying on the interaction between reactive species on the ZnO surface (such as O2 -) and the detected gas [START_REF] Gupta | [END_REF].

Within this context, it is important to understand the influence of the surface on the electrical and optical properties of ZnO nanowires which exhibit high surface-to-volume ratio. Using photoluminescence (PL), it has been reported that an emission band between 3.365 and 3.367 eV, denoted SX, takes its origin from the surface region of ZnO [18][19][20][21], i.e. the exciton is localized on the potential of a surface defect and/or adsorbed impurity. However the nature of the surface defects responsible for the SX band is not easy to understand. Among the very few reported works, Biswas and al emphasized the role of zinc hydroxides on the SX emission [22].

SX intensity is also shown to increase by covering ZnO surface with organic monolayer [23] or Al2O3 shell [24].

Besides, in an attempt to modify the surface properties of ZnO, a huge variety of annealing experiments can be found in the literature. Thermal treatments were performed after growth under oxygen, air, nitrogen and argon atmosphere at relatively high temperatures up to 1200 °C [25][26][27]. Surprisingly, there are very few works dealing with annealing treatments in Zn vapor.

Actually, one must not only care for oxygen out-diffusion during thermal treatment, but also zinc out-diffusion [28]. Studies related to the thermal treatment of ZnO in zinc vapor were mainly interested in the characterization of intrinsic defects in ZnO crystals. Weber et al [29] and Halliburton et al [30] have observed a red coloration of ZnO crystals after annealing in Zn vapor at 1100°C, and several origins have been proposed : complexes involving hydrogen and oxygen vacancy [29] or zinc interstitials [30]. Furthermore, there are very few reports giving near band edge emission (NBE) details and focusing on SX transition after thermal treatment, whatever the annealing atmosphere. Rather, the deep level emission (DLE) has been investigated in relation with zinc and oxygen vacancies [31]. As a result, the motivation of this work has been to investigate the structural and the optical properties of ZnO nanowires grown by MOCVD and post-annealed in the presence of Zn vapor, focusing on the surface related phenomena.

II. Experiments

Non-intentionally doped ZnO nanowires were grown on (11)(12)(13)(14)(15)[START_REF] Look | Doping and Defects in ZnO[END_REF][START_REF] Gupta | [END_REF](18)(19)(20) a-plane sapphire substrates using an atmospheric MOCVD system including a vertical quartz reactor. Diethylzinc (DEZn) and nitrous oxide (N2O) have been used as zinc and oxygen precursors, respectively. The carrier gas was helium. Partial pressures of DEZn and N2O in the gas phase were set at 92 and 37000 Pa, respectively. The growth temperature was 850 °C, and growth time was 15 min.

After growth, the ZnO nanowires samples were inserted in quartz tubes together with ~30 mg of 5N pure Zn powder. The ampoules were subsequently sealed under vacuum, below 2 × 10 -7 torr. Figure 1 shows the schematic view of an ampoule prepared for the thermal treatment. The samples were then annealed for 5h at a temperature ranging from 500 to 800 °C. Before and after experiments, the morphology of the nanowires was assessed using a JEOL 7001F scanning electron microscope (SEM). Photoluminescence measurements were also carried out at 5K using the 351 nm UV line of an argon ion laser. The chemical evolution of the surface was examined by X-ray Photoelectron Spectroscopy (XPS) using a Thermo Scientific K-Alpha system.

III. Results and discussion

Figure 2 shows the SEM images of as-grown and annealed ZnO nanowires, and for this latter case with and without Zn atmosphere during 5 h at 700 °C. The average length of the nanowires is around 13 µm and their diameter is in the range of 500 to 1000 nm. The NWs are grown along the (0001) c-direction with clear facets on their sides. When processed in zinc vapor, the annealed samples show no macroscopic degradation of their surface and morphology up to 800°C, but may exhibit different contents of point defects. This will be discussed in the next part. The degradation occurs if the annealing is performed without zinc source, as figure 2c reveals a drastic damage of the nanowires above 700°C. This could be due to a strong zinc outdiffusion from ZnO at high temperature, as reported by Wang et al [28], and, to a much lower extent, oxygen diffusion that was shown to create high concentrations of oxygen vacancies [31]. [32]. These peaks are followed by the Y-line at 3.333 eV which is related to excitons bound to extended defects [32], and an electron-acceptor band at 3.31 eV also related to defects [33]. The free exciton FX is hardly seen at 3.375 eV.

As discussed in the introduction part, the observation of surface excitons is consistent with the increased surface-to-volume ratio, and characteristic of the nanowires [34]. After annealing at low temperature, below 550 °C, PL spectra of ZnO nanowires remain unchanged compared with as-grown reference. For treatments between 580 and 620 °C, and only within this narrow range of temperature, we observe a strong improvement of the PL spectrum which is comparable to PL spectra obtained for high quality bulk ZnO crystals (figure 3b). A fine structure of the near band edge emission is revealed, with well-defined narrow lines in the range 3.35-3.37 eV. The peaks related to excitons bound to Al and H donor impurities, as well as the free exciton structures at higher energy, clearly dominate the SX emission. Indeed, the I6 line at 3.360 eV related to aluminum impurities is dominant after annealing whereas the intensity of SX band has strongly decreased. Aluminium contamination may come from sapphire substrates during the MOCVD growth at 850°C. Remaining defect lines could be explained by extended defects still present at the bottom of the nanowires, close to the interface with sapphire substrate. Above 620°C the benefits of the annealing on the PL emission seem to fade, as the fine structure of the NBE emission is no more observable and SX intensity increases (not shown here). Interestingly, for the ZnO NWs which had been treated at 620 °C, the initial PL spectrum is recovered and SX peak dominates again after the sample has been stored for two months, i.e. photoluminescence studies after the annealing of ZnO NWs. The improvement of the optical quality depends on the technique that had been used to grow the NWs [35]. The NBE intensity is shown to increase significantly [36] and/or to lead to a narrowing of the NBE transitions [8].

The benefit of the annealing is often stronger for nanowires grown at low temperature using chemical bath deposition, or electrodeposition. In that case the improvement of the optical quality can be related to a strong improvement of the crystalline quality of the grown material.

The effect on the DLE has also been observed. At reduced temperature (500°C), a decrease was reported by Yang et al [36], thus lowering the concentration of surface and lattice defects.

However at higher temperature, the DLE can increase due to thermal diffusion and creation of point defects. In this work, we observed for as-grown samples that the DLE intensity is very weak, more than three orders of magnitude lower than the NBE intensity, as shown in the figure 3c. This indicates the high quality of our as-grown material. After annealing at 620°C, the level of the DLE slightly increases with a noticeable blue-shift from ~2.25 to ~2.5 eV which can be related to both creation of oxygen vacancies and reduction of zinc vacancies [31]. However the intensity of the DLE remains very low.

Herein, we could identify each recombination path in the NBE region so that we have been able

to focus on the particular SX emission. To rigorously investigate the chemical modifications of the NWs surface due to the annealing process, X-ray Photoelectron Spectroscopy has been carried out. Four samples were measured : i) as-grown ZnO NWs, ii) annealed at 550°C, iii) annealed at 620°C and iv) annealed at 620°C + 2 months aging.

The global XPS responses were very reproducible and did not need any charge compensation during the acquisition. At first, it is important to note that the position and the energy distribution of the Zn2p3/2 peaks are rigorously the same for all the investigated surfaces. The binding energies of the Zn2p3/2 peaks are 1022.33+/-0.02 eV which is however slightly higher than the value obtained for ZnO monocrystalline face (typically 1021.8 eV [37]). The full width at half maximum (FWHM) values of these peaks are nearly identical to the one observed on planar ZnO crystals. In the same way the O1s maximum is centered at 531.07+/-0.02 eV compared to 530.6 eV obtained on ZnO crystals.Therefore, the energy difference between Zn2p3/2 and O1s peaks is the same as the one observed on monocrystal faces, suggesting a high quality of the NWs.

The XPS results are gathered in the figure 4, and quantifications are given in the table 1. The O1s spectra display a significant evolution upon the different treatments of samples, with a clear reduction of the peak shoulder, whereas the Zn2p3/2 spectra do not show any modification (not shown here).

To separate and analyze the different contributions, the O1s spectra were fitted with three peaks, with binding energies at 531, 532.4 and 533.3 eV. All the FWHMs were kept constant, the value being determined by the main O-Zn peak, which is easily determined and almost constant whatever the treatment of the sample. The fit allows the reconstruction of the whole O1s distribution and indicates the presence of particular oxygen-bonding states at the surface. The main peak at 531 eV is attributed to oxygen atoms bound to zinc (Zn-O) in the wurzite ZnO lattice. The binding energy of O 2-ions depends on the ionicity or covalency of the chemical bound, so that adsorbed molecules on the NWs surface such as -OH and -CO groups will cause the appearance of a second peak at 532.4 eVs peak [37]. Also, a contribution is related to nonstoichiometric ZnO surface planes, leading to a weaker Zn-O bond. In particular, an oxygendeficient region has been suggested by Wang et al, after they have annealed ZnO nanoparticules in argon atmosphere and observed a strong increase of this peak [38]. At higher energy (533.3 eV), a third peak was reported to be related to zinc hydroxide chemical bound (Zn(OH)2) and adsorbed water [39]. In figure 5, the intensity ratio between the hydroxide peak at 533.3 eV and the Olattice peak at 531 eV is plotted. We observe that the intensity ratio decreases after annealing, especially at 620°C, and increases again after aging in ambient air, exhibiting the same tendency as SX peak intensity in PL results. For more accuracy, a quantification of the Zn-(OH)2 XPS peak is given in the table 1, and the level is shown to decrease from 4.1 to 2.8% after annealing, and then return to 4.3% after aging. One can notice that no change in the intensity of the 532.4 eV peak related to, -OH, -CO and non-stoechiometric region has been observed. In addition, the quantification of carbon atoms on the surface has been measured between 7 and 15%. These values are typical of ZnO surface and reflect the carbon contamination (C-C, C=O, H-O-C=O…) after air exposure. One can even emphasize that the sticking of carbon molecules on our ZnO NWs arrays is rather low, as compared to the reference ZnO crystal which exhibits 16.6 % of C on its surface. No tendency was found regarding this adsorption of organic molecules upon annealing for the different series of samples.

Therefore, there is a correlation between the decreasing of SX intensity and the amount of hydroxide Zn(OH)2 on the nanowires surface. The origin of SX could be, at least partially, explained by the occurrence of these species on the ZnO surface. This is in agreement with previously reported results from Biswas et al [22]. During the thermal treatment under zinc atmosphere we infer that a decomposition of zinc hydroxide occurs, following the reaction : Zn(OH)2 → ZnO + H2O.

Such a phase transformation from Zn(OH)2 to ZnO has also been reported by Duchoslav et al [40] and Wang et al [41]. At the same time, the thermal process allows the reconstruction of clean perfect ZnO facets with a reduced concentration of defects, thus decreasing SX emission.

In this process the limitation of zinc exo-diffusion from ZnO nanowires could help. Zn vapor may be also beneficial to the optical properties of the NWs body, as sharp excitonic emissions are seen in the PL spectra. Interestingly, in this range of temperature, no oxygen supply is required to achieve high optical quality ZnO nanowires. Although oxygen vacancies are created, the DLE intensity is kept very low, as compared with the NBE intensity. Hence, we emphasize the role of surface physical-chemistry in the optical properties of ZnO nanowires. Such surface reconstruction could be helpful before integrating ZnO nanowires into nanodevices based on surface reactions, like gas sensors.

Figure captions

Tables

Table 1 Quantification of XPS Zn2p3/2, O1s, and C1s peak (atm.%)

Figure 1

 1 Figure 1 Schematic view of a sealed ampoule, prepared for the annealing in zinc vapor

Figure 2

 2 Figure 2 SEM images of ZnO nanowires (a) as-grown, (b) post-annealed with Zn at 700 °C, (c) post-annealed without Zn at 700 °C.

Figure 3

 3 Figure 3 presents the evolution of photoluminescence spectra recorded on as-grown and annealed NWs. The PL emission of the as-grown nanowires is dominated by the surface recombination (SX) at 3.367 eV. Additional transitions can be distinguished involving excitons bound to Al and H impurities at 3.372 eV (D + X(Al)), 3.362 eV (D°X(H)), and 3.360 eV

Figure 3

 3 Figure 3 PL spectra measured at 5K for ZnO nanowires samples: a) as grown, b) treatment at 580 °C under Zn source (insert : ZnO crystal), c) near band edge emission of as-grown (black), and deep level emissions of as-grown (red) and annealed at 620°C (blue). For DLE bands, the integration time has been increased and filters changed to enhance the PL signals

Figure 4

 4 Figure 4 Peak fitted XPS O1s spectra for different treatments: (a) as grown (b) post-annealed at 550 °C (c) post-annealed at 620 °C (d) exposed to air for 2 month after treatment at 620 °C.

Figure 5

 5 Figure 5 Intensity ratio between (533.3 eV)-and (531 eV)-O1s peaks for the different treated samples

Figure 1 :Figure 2 :

 12 Figure 1 : Schematic view of a sealed ampoule, prepared for the annealing under zinc vapor

Figure 3 Figure 4 :

 34 Figure3PL spectra measured at 5K for ZnO nanowires samples: a) as grown, b) treatment at 580 °C under Zn source (insert : ZnO crystal), c) near band edge emission of as-grown (black), and deep level emissions of as-grown (red) and annealed at 620°C (blue). For DLE bands, the PL integration time has been increased and filters changed to enhance the signals

Figure 5 :

 5 Figure 5 : Intensity ratio between (533.3 eV)-and (531 eV)-O1s peaks for the different treated samples

Table 1

 1 Quantification of XPS Zn2p3/2, O1s, and C1s peak (atm.%)IV. ConclusionA strong improvement of the optical quality is observed for ZnO nanowires samples after thermal treatment in zinc vapor carried out between 580 and 620 °C, thus at moderate temperature compared with the usual temperature reported in the literature. The PL emission due to surface excitons is decreased in the favor of a fine NBE structure similarly observed in high quality ZnO bulk crystals. This improvement of the surface chemistry is associated with the reduction of hydroxide species and/or Zn(OH)2 sublayer present on the surface after the growth of nanowires. The results suggest that the annealing process of ZnO nanowires enables to reconstruct clean M-plane facets and further increases the optical quality of the body, as sharp excitonic emission lines are observed. A moderate increase of the concentration of oxygen vacancies is nevertheless induced and the weakly intense DLE band shifts from 2.25 to 2.5 eV.

	2.6	16.6
	4.1	6.9

Acknowledgements : this work was supported by the French "Agence Nationale de la Recherche", project n° ANR-11-NANO-013


Access to Optically-Pure Benzosultams by Superelectrophilic Activation

Bastien Michelet, a * Ugo Castelli, a Emeline Appert, a Maude Boucher, a Kassandra Vitse, a Jérôme Marrot, b Jérôme Guillard, a Agnès Martin-Mingot, a Sébastien Thibaudeau a * a Université de Poitiers, UMR-CNRS 7285, IC2MP, Equipe Synthèse Organique, 4 rue Michel Brunet, TSA 51106, 86073 Poitiers Cedex 9 (France) b Institut Lavoisier de Versailles, UMR CNRS 8180, 45 avenue des Etats-Unis, Versailles 78035 Cedex (France) Supporting Information Placeholder ABSTRACT: Through superacid activation, N-(arenesulfonyl)-aminoalcohols derived from readily-available ephedrines or amino acids undergo an intramolecular Friedel-Crafts reaction to afford enantiopure benzosultams bearing two adjacent stereocenters in high yields with a fully-controlled diastereoselectivity. Low-temperature NMR spectroscopy demonstrated the crucial role played by the conformationally-restricted chiral dicationic intermediates.

Benzosultams are prominent scaffolds in organic synthesis and have found many applications, especially in medicinal chemistry (Figure 1). 1 In light of the growing demand for enantioenriched benzosultam-based therapeutics, versatile methodologies for their synthesis have been developed, including metalcatalyzed asymmetric cyclization, enantioselective addition to N-sulfonyl imines, reductive amination or C-H bond amination. 2 Although demonstrated to be efficient approaches to generate enantioenriched benzosultams exhibiting one sterocenter, expeditious methods to control multiple continuous stereocenters of enantiopure benzosultams are still on demand. One of the simplest route to nitrogen-containing heterocycles is probably the intramolecular Friedel-Crafts alkylation of alkenes or alcohols. 4 We previously demonstrated that under superacid conditions, N-allyl-arenesulfonamides cyclize to benzolsutams. 5 This process is promoted by the in situ formation of superelectrophilic ammonium-carbenium dications that can react with very poor aromatic nucleophiles such as arenesulfonamides despite the strong deactivating character of the sulfamoyl group (Figure 2A). Interestingly, starting from a N-aroyl derivative of (-)-ephedrine, Trepanier demonstrated the formation of an enantiopure dihydroisoquinolinone derivative after reaction in concentrated sulfuric acid (Figure 2B). 6 This reaction suggested the implication of a strong electrophilic benzylic carbocation and motivated this work. By taking advantage of the stability of benzylic carbocations and of benzylic strain, Bach 7 and others 8 developed highly diastereoselective inter-and intramolecular reactions that can be considered as guides for further developments (Figure 2C). We envisioned that starting from simple N-(arenesulfonyl)-ephedrine derivatives 1, conformationally-restricted dicationic key intermediate A could be generated in superacidic conditions. It would react diastereoselectively to furnish enantiopure benzosultams (Figure 2D). This strategy would also be amenable to a higher level of complexity starting from amino acids in very few steps, making this method one of the rare examples of enantiopure benzosultams synthesis from the chiral pool. 9-12 First, our initial hypothesis was evaluated by testing the reactivity of ephedrine derivative 1a, bearing a relatively electronrich tosyl group, to various acidic conditions (Table 1). Using neat HF/SbF5 superacid, 5 we could obtained the desired cyclized product 2a after only 30 min at -40 °C in a good 70% yield with a fully-controlled diastereoselectivity (Table 1, entry 1). Delightfully, switching HF/SbF5 to the safer trifluoromethanesulfonic acid allowed to afford 2a in similar yield and again, as a single diastereomer (Table 1, entry 2). However, any attempts of using lower amounts of trifluoromethanesulfonic acid in CH2Cl2 led to poor yields or formation of the regioisomer 2b when the reaction was carried out at higher temperature (Table 1, entries 3-5). Such isomerization is a well-known drawback of Friedel-Crafts alkylations and can be explained by intramolecular rearrangement within the arenium ion generated by subsequent protonation of the kinetic product 2a to the most stable product 2b. 13 Nevertheless, the formation of byproduct 2b can be prevented by keeping the reaction mixture at -40 °C allowing the isolation of 2a as a single regio-and stereoisomer. [START_REF]Partial isomerization was observed with TfOH or FeCl3 even at -20 °C[END_REF] We next evaluated the reactivity of 1a with excess of Lewis acids. FeCl3 was found inactive at -40 °C and carrying out the transformation at higher temperature afforded again the undesired regioisomer 2b (Table 1, entries 6-10). The use of other Lewis acids from the main group, transition metal or lanthanide series led to poor yields or no conversion at all (Table 1, entries 11-16). Decreasing the protonating ability of the system by running the reaction in sulfuric acid or trifluoroacetic acid was shown to be detrimental to the reaction, a result which supports our initial hypothesis and the necessity to use superelectrophilic activation to perform this transformation (Table 1, entries 17-18). In order to avoid the formation of any regioisomeric byproducts and for better reproducibility, we selected the use of neat trifluoromethanesulfonic acid at -40 °C as the optimal conditions (Table 1, entry 2). The scope and functional group tolerance of this diastereoselective intramolecular Friedel-Crafts cyclization was next evaluated (Figure 3). Ephedrine derivatives 1a-e, exhibiting alkyl electron-donating groups on the aromatic ring, were smoothly converted to the corresponding enantiopure benzosultams in good to excellent yields. The presence of electron-donating group on the arenesulfonamide is not essential for the cyclization, as shown by the clean conversion of substrate 1f to its cyclic analogue 2f. Naphthalene and indane derivatives 2g and 2h were also generated in very good yields by exploiting this reaction. The reaction proceeded equally well with electron-rich methoxy-substituted arenesulfonamides affording compounds 2i and 2j in excellent yields. Noteworthy, the two regiosiomers 2jp and 2jo could be isolated separately after flash column chromatography. While products 2k-m were generated in generally lower yields, their formationwhich must involve the nucleophilic addition of the halogenated deactivated aromatic ringsfurther reinforces the hypothesis of the transient formation of a highly reactive cationic intermediate. However, strongly-deactivating substituents such as CF3, C(O)Me or NO2 completely inhibited the cyclization (Figure 3, bottom). Heteroarene could also be used as nucleophile as exemplified by the preparation of benzosultam 2n, an analogue of the antiglaucoma agent brinzolamide. Norephedrine derivative 1o, bearing no methyl group on the nitrogen atom, reacted in the optimized conditions to afford benzosultams 2o, albeit in moderate yield, opening new synthetic perspectives through further N-functionalizations.

The structure and stereochemistry of these chiral compounds were confirmed by X-ray analysis of the collected crystals of 2a generated after reaction of substrate 1a. [START_REF]CCDC 1994486[END_REF] To highlight the versatility of the method and verify the enantiopurity of every products, the reaction was carried out with each enantiomer of starting material. With success, the corresponding cyclic products were generated in enantiopure form in similar yields.

One step further in complexity, substrates bearing more hindered alkyl substituents at the stereogenic center as well as substitutents on the phenyl ring were selected (substrates 1p-s, Figure 4). Using the corresponding aminoacids as chiral platform, successive tosylation / reductive amination / reduction / aryl Grignard addition led to the clean formation of enantiomers 1pr. A slightly modified procedure from proline derivatives led to the formation of product 1s. The Grignard addition was fairly diastereoselective (dr from 4.7:1 to > 20:1) and the major syn diastereomers 1p-s could be isolated cleanly by flash chromatography on silica gel. 16 The superacid-promoted cyclization applied to 1p and 1q gratifyingly demonstrated the compatibility of the method with halogenated ephedrine derivatives (Figure 5). However, substrates exhibiting vinyl or electronically-enriched p-methoxyphenyl substituents led only to complex mixture of compounds. In the latter case, the enhanced stability of the postulated benzylic cation seems detrimental to the process, leading to the formation of degradation byproducts upon hydrolysis. Performing this reaction with FeCl3 (conditions from Table 1, entry 8) afforded only N-(methyl)tosylamine in 97% yield which confirms the lower reactivity of the cationic intermediate towards Friedel-Crafts alkylation. As illustrated by the transformation of 1r and 1s, respectively synthesized from leucine and proline, the diastereoselectivity of the reaction is maintained with bulkier αsubstituted amines. Furthermore, the formation of enantiomers 2s proves the efficiency of this strategy to generate enantiopure conformationally-rigid sultams of interest. 17 From a mechanistic point of view, this reaction most-likely proceed through the formation of a benzylic carbocation. 7d The stereochemical information borne by the hydroxy-substituted benzylic carbon should therefore play only a minor role in the outcome of the transformation. When the tosyl-pseudoephedrine 1a' (diastereomer of 1a) was reacted in the optimized conditions, benzosultam 2a was isolated in a similar yield (83% vs. 70-77%) as starting from 1a, thus confirming our hypothesis (Figure 6A). Then, we explore the hypothetical formation of any dicationic intermediate in superacid solutions. To this end, preventing the substrate from any cyclization by substituting the arenesulfonyl moiety with a trifluoromethyl group, we initiated our investigation by exploring the behavior of N-(arenesulfonyl)ephedrine 1t in TfOH by low-temperature in situ NMR analysis. Unfortunately, in TfOH, no clean 1 H or 13 C NMR spectra could be collected from this experiment. Considering that the lifetime of the generated cations in these conditions disallow any observation at the NMR time scale, the same experiment was conducted in weaker nucleophilic conditions 18 by submitting the same substrate to HF/SbF5 superacid solution. In these conditions, 1 H, 13 C and HSQC NMR analysis of the crude reaction mixture provided strong evidences for the formation of the key dicationic species At (Figure 6B). 19 1 H NMR spectrum displays a doublet (J = 9.7 Hz) at 8.10 ppm characteristic of a carbocationic benzylic C-H bond 7d as well as a broad signal at 6.37 ppm attributed to the protonation of the sulfonamide moiety. 20 The signal of the N-methyl substituent is now a doublet (J = 4.6 Hz) slightly shielded to 1.79 ppm (compared to a singlet at 2.79 ppm for 1t in CDCl3). This species is also characterized by a benzylic carbenium ion at 198.4 ppm in the 13 C NMR spectrum. 7d, 8d Interestingly, both 1 H and 13 C NMR spectra show non-equivalent signals for the phenyl substituent indicating a restriction of rotation around the phenyl-carbocation bond. 7b Luckily, the 1 H NMR spectrum was sufficiently well-resolved to allow a NOESY experiment which showed a correlation between the benzylic proton and an aromatic ortho proton as well as a correlation between the proton at the stereogenic center and another aromatic ortho proton. Altogether, these NMR observations supported our initial hypothesis on the generation of conformationally-restricted superelectrophiles in superacid. The carbon atom in para position displays a strong downfield shift to 168.1 ppm (compared to 128.1 ppm for 1t in CDCl3) indicating a strong delocalization of the positive charge to this carbon atom. This observation might be explained by the propensity of the aryl group to tackle the destabilization of the benzylic carbocation induced by the proximity of the second cationic charge located on the nitrogen atom. 8d Collectively, these data suggest that a right balance between conformational stabilization and sufficient electrophilic character must exist to favor the intramolecular diasteroselective nucleophilic substitution. To conclude, taking advantage of the chiral pool, a series of optically-active N-(arenesulfonyl)-aminoalcohols were efficiently converted to enantiopure benzosultams exhibiting a wide array of functions and substitution patterns. Demonstrated by lowtemperature NMR spectroscopy, this process exploits the superelectrophilic character and the privileged conformation of chiral benzylic dications in superacidic solution.

ASSOCIATED CONTENT Supporting Information

The Supporting Information is available free of charge on the ACS Publications website. General experimental procedures, reaction setup, characterization data, low-temperature NMR spectra and spectra for all key compounds (PDF).

3

 3

Figure 1 .

 1 Figure 1. Selected examples of biologically-active benzosultams.

Figure 2 .

 2 Figure 2. A. Previous work on superacid-mediated synthesis of racemic benzosultams. B. Dihydroisoquinolinone derivative synthesis in concentrated sulfuric acid. C. Highly diastereoselective intramolecular Friedel-Crafts alkylation induced by benzylic strain. D. Strategy envisioned for the diastereoselective synthesis of optically-pure benzosultams by superelectrophilic activation (this work). Interestingly, starting from a N-aroyl derivative of (-)-ephedrine, Trepanier demonstrated the formation of an enantiopure

Figure 3 .

 3 Figure 3. Reaction scope for the synthesis of enantiopure benzosultams derived from ephedrines. a A 63% yield was obtained on 1 g scale (see SI for full details). b Major regioisomer depicted with solid bonds; minor regioisomer depicted with dashed bonds. c Ellipsoids are drawn at 50% probability level and hydrogen atoms are represented as fixed-size spheres of radius 0.30 Å.

Figure 4 .

 4 Figure 4. Synthesis of benzosultam precursors 1p-s from amino acids.

Figure 5 .

 5 Figure 5. Reaction scope for the synthesis of enantiopure benzosultams derived from aminoacids.

Figure 6 .

 6 Figure 6. A. Synthesis of benzosultam 2a from tosyl-pseudoephedrine 1a'. B. Low-temperature 1 H NMR (top) and 13 C NMR (bottom) analysis of ephedrine derivative 1t in HF/SbF5 (1/1) at -40 °C. Acetone-d6 is used as external standard.

Table 1 .

 1 Optimization of the acid-promoted diastereoselective synthesis of benzosultam 2a.

	Entry	Acid	Conditions	[2a] a [2b] a
	1	HF/SbF5 (7/1) b	-40 °C, 0.5 h	70%	-
	2	TfOH b	-40 °C, 0.5 h 70%	-
	3	TfOH (2 equiv.)	-40 °C, 16 h	10%	-
	4	TfOH (2 equiv.)	20 °C, 0.5 h	-c	32% d
	5	TfOH (2 equiv.)	20 °C, 16 h	-	45% d
	6	FeCl3 (2 equiv.)	-40 °C, 16 h	-	-
	7	FeCl3 (2 equiv.)	20 °C, 0.5 h	-	48% d
	8	FeCl3 (2 equiv.)	20 °C, 16 h	-	89%
	9	FeCl3 (1 equiv.)	20 °C, 16 h	-	38%
	10	FeCl3 (0.1 equiv.)	20 °C, 16 h	-	-
	11	AlCl3 (2 equiv.)	20 °C, 16 h	-	18%
	12	BF3OEt2 (2 equiv.)	20 °C, 16 h	-	-
	13	CeCl3 (2 equiv.)	20 °C, 16 h	-	-
	14	Ce(OTf)3 (2 equiv.)	20 °C, 16 h	-	-
	15	Bi(OTf)3 (2 equiv.)	20 °C, 16 h	-	-
	16	Sc(OTf)3 (2 equiv.)	20 °C, 16 h	-	-
	17	H2SO4 (95%) b	10 °C, 16 h	14%	14%
	18	CF3CO2H b	-14 °C, 16 h	-	-

a Yield of isolated product unless stated otherwise. b Used as solvent. c Traces. d Determined by 1 H-NMR analysis using p-anisaldehyde as internal standard.

ACKNOWLEDGMENT

We great fully acknowledge the French Ministry of research and education for PhD grant (for U.C.). We also acknowledge the University of Poitiers, the Centre National de la Recherche Scientifique, the European Union (ERDF), the Région Nouvelle-Aquitaine and the French Fluorine Network.

AUTHOR INFORMATION Corresponding Author

Sébastien Thibaudeau -Université de Poitiers, IC2MP UMR CNRS 7285 / Superacid Group Organic Synthesis Team / 4 rue Michel Brunet 86073 Poitiers cedex 9, France ; orcid.org/0000-0002-6246-5829; E-mail: sebastien.thibaudeau@univ-poitiers.fr Bastien Michelet -Université de Poitiers, IC2MP UMR CNRS 7285 / Superacid Group -Organic Synthesis Team / 4 rue Michel Brunet 86073 Poitiers cedex 9, France ; orcid.org/0000-0002-3248-5781; E-mail: bastien.michelet@univ-poitiers.fr

Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.


Clément Fabre
email: clement.fabre21@gmail.com

S Sauvage

J Guilhen

R Cakir

M Gerino

J M Sánchez-Pérez

Daily denitrification rates in floodplains under contrasting pedoclimatic and anthropogenic contexts: modelling at the watershed scale

Keywords: denitrification, nitrate, floodplains, watershed, daily time step, organic carbon

Floodplains play a crucial role in water quality regulation via denitrification. This biogeochemical process reduces nitrate (NO3 -), with aquifer saturation, organic carbon (OC) and N availability as the main drivers. To accurately describe the denitrification in the floodplain, it is necessary to better understand nitrate fluxes that reach these natural bioreactors and the transformation that occurs in these surface areas at the watershed scale.

At this scale, several approaches tried to simulate denitrification contribution to nitrogen dynamics in study sites. However, these studies did not consider OC fluxes influences, hydrological dynamics and temperature variations at a daily time step. This paper focuses on a new model that allows insights on nitrate, OC, discharge and temperature influences on daily denitrification for each water body. We used a process-based deterministic model to estimate daily alluvial denitrification in different watersheds showing various pedo-climatic conditions.

To better understand global alluvial denitrification variability, we applied the method to three contrasting catchments: The Amazon for tropical zones, the Garonne as representative of the temperate climate and the Yenisei for cold rivers. The Amazon with a high discharge, frequent flooding and warm temperature, leads to aquifers saturation, and stable OC concentrations.

Those conditions favour a significant loss of N by denitrification. In the Garonne River, the low OC delivery limits the denitrification process. While Arctic rivers have high OC exports, the low nitrate concentrations and cold temperature in the Yenisei River hinder denitrification. We found daily alluvial denitrification rates of 119.4 ± 47.5, 7.6 ± 5.4 and 0.1 ± 0.5 kgN.ha -1 .yr -1 during the 2000-2010 period for the Amazon, the Garonne and the Yenisei respectively. This study quantifies the floodplains influence in the water quality regulation service, their contribution to rivers geochemical processes facing global changes and their role on nitrate and OC fluxes to the oceans.

Introduction

Intensive agriculture brings high amounts of nitrates to rivers by leaching of fertilizers. The nitrate concentrations in free river water are significantly lower than the nitrate concentrations in alluvial aquifers for areas under intense agriculture pressures (Sánchez-Pérez et al., 2003). This difference is explained by the dilution effect when the water flows from aquifers to rivers, together with the N retention capacity of floodplains [START_REF] Craig | Localized zones of denitrification in a floodplain aquifer in southern Wisconsin, USA[END_REF]. This retention capacity results from plant uptake and denitrification [START_REF] Pinay | Change in Groundwater Nitrate Concentration in a Large River Floodplain: Denitrification, Uptake, or Mixing?[END_REF][START_REF] Craig | Localized zones of denitrification in a floodplain aquifer in southern Wisconsin, USA[END_REF][START_REF] Ranalli | The importance of the riparian zone and in-stream processes in nitrate attenuation in undisturbed and agricultural watersheds -A review of the scientific literature[END_REF]. Denitrification is the process of nitrate reduction (NO3 -) into nitrous oxide (N2O) or dinitrogen (N2). It is the main process that leads to nitrate loss in watersheds [START_REF] Pinay | Change in Groundwater Nitrate Concentration in a Large River Floodplain: Denitrification, Uptake, or Mixing?[END_REF][START_REF] Pfeiffer | Identification of groundwater flow paths and denitrification zones in a dynamic floodplain aquifer[END_REF][START_REF] Baillieux | Regional water quality patterns in an alluvial aquifer: Direct and indirect influences of rivers[END_REF]. Denitrifying bacteria are generally facultative aerobic heterotrophs [START_REF] Zaman | Emissions of nitrous oxide (N2O) and dinitrogen (N2) from the agricultural landscapes, sources, sinks, and factors affecting N2O and N2 ratios[END_REF]. They can switch to anaerobic respiration under low oxygen conditions by completing the denitrification, i.e. by using the oxygen from nitrate. Thus, denitrification is optimized under specific conditions and is limited by three main factors: the availability of nitrate, the availability of organic carbon (OC; [START_REF] Rivett | Nitrate attenuation in groundwater: A review of biogeochemical controlling processes[END_REF] and the small oxygen availability [START_REF] Zaman | Emissions of nitrous oxide (N2O) and dinitrogen (N2) from the agricultural landscapes, sources, sinks, and factors affecting N2O and N2 ratios[END_REF]. In this way, denitrification is a microbial process consuming OC [START_REF] Zaman | Emissions of nitrous oxide (N2O) and dinitrogen (N2) from the agricultural landscapes, sources, sinks, and factors affecting N2O and N2 ratios[END_REF]. The OC used by denitrifying bacteria is taken from soils leaching and in-situ sediments or comes from the river contributions [START_REF] Gift | Denitrification Potential, Root Biomass, and Organic Matter in Degraded and Restored Urban Riparian Zones[END_REF][START_REF] Peter | Intensified organic carbon dynamics in the groundwater of a restored riparian zone: Organic carbon in riparian aquifers[END_REF]. OC in rivers is separated into two classes: particulate organic carbon (POC) and dissolved organic carbon (DOC; [START_REF] Hope | A review of the export of carbon in river water: Fluxes and processes[END_REF]. These two forms have two different origins. While POC mostly comes from soil erosion, DOC is a result of soil leaching [START_REF] Meybeck | C, N, P and S in Rivers: From Sources to Global Inputs[END_REF][START_REF] Raymond | Use of 14 C and 13 C natural abundances for evaluating riverine, estuarine, and coastal DOC and POC sources and cycling: a review and synthesis[END_REF]. DOC is the most consumed OC form in denitrification [START_REF] Peyrard | Longitudinal transformation of nitrogen and carbon in the hyporheic zone of an N-rich stream: A combined modelling and field study[END_REF][START_REF] Zarnetske | Labile dissolved organic carbon supply limits hyporheic denitrification[END_REF][START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF].

Floodplains are hot spots of denitrification [START_REF] Mcclain | Biogeochemical Hot Spots and Hot Moments at the Interface of Terrestrial and Aquatic Ecosystems[END_REF][START_REF] Billen | The nitrogen cascade from agricultural soils to the sea: modelling nitrogen transfers at regional watershed and global scales[END_REF]. Floodplains are areas connected to the river network and are strongly influenced by the hydrodynamic of the basin, which results in oscillations between aerobic and anaerobic conditions. The location of floodplains intensifies transfers of OC and nitrate by leaching from uplands to the river.

These transfers occur at hot moments with a high temporal resolution [START_REF] Bernard-Jannin | Spatiotemporal analysis of factors controlling nitrate dynamics and potential denitrification hot spots and hot moments in groundwater of an alluvial floodplain[END_REF]. Therefore, daily time step studies should highlight the temporal variability of the denitrification process.

Past studies used in situ observations to evaluate large-scale denitrification but they revealed high uncertainties [START_REF] Groffman | Methods for measuring denitrification: diverse approaches to a difficult problem[END_REF]. Therefore, modelling appears as an important tool to better assess those processes at large scale [START_REF] Groffman | Terrestrial denitrification: challenges and opportunities[END_REF]. Modelling tools that focus on the exchanges between rivers and floodplains were usually used for hydrology interactions [START_REF] Yamazaki | A physically-based description of floodplain inundation dynamics in a global river routing model: Floodplain inundation dynamics[END_REF][START_REF] Jung | Joint climate-hydrology modelling: an impact study for the data-sparse environment of the Volta Basin in West Africa[END_REF]. Regarding floodplains biogeochemistry, previous models showed their ability to simulate denitrification [START_REF] Hattermann | Integrating wetlands and riparian zones in river basin modelling[END_REF][START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF]. They can be used to identify nitrate sources and sinks [START_REF] Boano | Biogeochemical zonation due to intrameander hyporheic flow: Intrameander biogeochemical zonation[END_REF][START_REF] Peyrard | Longitudinal transformation of nitrogen and carbon in the hyporheic zone of an N-rich stream: A combined modelling and field study[END_REF][START_REF] Zarnetske | Coupled transport and reaction kinetics control the nitrate source-sink function of hyporheic zones: Hyporheic N source-sink controls[END_REF] as well as hot spots and hot moments of nutrients cycling [START_REF] Groffman | Challenges to incorporating spatially and temporally explicit phenomena (hotspots and hot moments) in denitrification models[END_REF][START_REF] Bernard-Jannin | Spatiotemporal analysis of factors controlling nitrate dynamics and potential denitrification hot spots and hot moments in groundwater of an alluvial floodplain[END_REF]. Two options are commonly used to estimate denitrification at large scale: coupling a hydrological with biogeochemical models [START_REF] Peyrard | Longitudinal transformation of nitrogen and carbon in the hyporheic zone of an N-rich stream: A combined modelling and field study[END_REF] or implementing biogeochemical modules in a hydrological model [START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF]. [START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF] was the first study to show models capacity to simulate daily denitrification variations at the scale of a reach by considering the river-aquifers exchanges of water, nitrate and OC. Denitrification is usually modelled as a nitrate retention rate [START_REF] Boyer | Modelling denitrification in terrestrial and aquatic ecosystems at regional scales[END_REF][START_REF] Ruelland | SENEQUE: A multi-scaling GIS interface to the Riverstrahler model of the biogeochemical functioning of river systems[END_REF][START_REF] Peyrard | Longitudinal transformation of nitrogen and carbon in the hyporheic zone of an N-rich stream: A combined modelling and field study[END_REF][START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF]. Although the integration of the OC availability into floodplains denitrification is a recent effort [START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF], the temporal variations of OC fluxes have not been integrated into models yet. We assume that high temporal resolution of this OC delivery is important to consider in models as a control of the denitrification process. Thus, the accurate modelling approach to better simulate the effective biogeochemical processes with the limiting factors should be done at a daily time step.

Past research that uses modelling tools to predict spatial and temporal denitrification variations in floodplains highlighted the potential of these approaches to predict nitrate and OC fluxes at large scale [START_REF] Peyrard | Longitudinal transformation of nitrogen and carbon in the hyporheic zone of an N-rich stream: A combined modelling and field study[END_REF][START_REF] Bernard-Jannin | Spatiotemporal analysis of factors controlling nitrate dynamics and potential denitrification hot spots and hot moments in groundwater of an alluvial floodplain[END_REF][START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF]. Recent research using new methods tried to estimate alluvial wetlands denitrification with remote sensing data [START_REF] Guilhen | Denitrification, carbon and nitrogen emissions over the Amazonianwetlands[END_REF]. With a similar approach, this study is the first that aims to simulate denitrification at the scale of several watersheds with contrasting climatic and soil properties. The main objectives of the study are i) to propose a new and easy-to-use methodology to estimate floodplains denitrification at the watershed scale by taking into account spatial and temporal DOC variability, ii) to apply this methodology at the scale of three contrasting watersheds representative of various climatic and soils conditions and iii) to quantify their daily floodplains denitrification.

Materials and Methods

Study cases

To highlight the global denitrification variabilities, we selected three watersheds for their different ranges of nitrate and OC concentrations in the free waters. These three watersheds are the Amazon River, representative of tropical areas, with low nitrate and low OC content, the Yenisei River in Siberia, representative of cold climate, with low nitrate and high OC contents in the free-water, and the Garonne River in France, as a temperate and anthropogenic watershed, with high nitrate and low OC contents (Figure 1). Nitrate contents of the Amazon and the Yenisei rivers are mostly coming from natural sources while the Garonne basin shelters intensive agriculture activities. The Amazon basin is the largest draining area of the world with 6,500,000 km² and displays three large floodplains located in the Northern (the Branco Floodplain) and the Southern (the Madeira Floodplain) part of the basin as well as alongside the mainstream. Based on the GLOBAL-NEWS model results [START_REF] Mayorga | Global Nutrient Export from WaterSheds 2 (NEWS 2): Model development and implementation[END_REF], the Amazon River has a dissolved inorganic nitrogen (DIN) export of 1.6 kgN.ha -1 .yr -1 and a DOC export of 49.8 kgC.ha -1 .yr -1 . The DIN export consists mainly of nitrate, which is one of the compounds used in denitrification [START_REF] Zaman | Emissions of nitrous oxide (N2O) and dinitrogen (N2) from the agricultural landscapes, sources, sinks, and factors affecting N2O and N2 ratios[END_REF]. The basin also has an average soils OC content of 9 kgC.m -3 [START_REF] Batjes | Harmonized soil profile data for applications at global and continental scales: updates to the WISE database[END_REF]. The Yenisei River is one of the main rivers flowing into the Arctic Ocean with a basin area of 2,500,000 km². The main floodplains of the Yenisei River are in the downstream part of the main channel. The DIN export is around 0.3 kgN.ha - 1 .yr -1 , the DOC export is at 10.6 kgC.ha -1 .yr -1 while the average soils OC content is at 34 kgC.m - 3 [START_REF] Batjes | Harmonized soil profile data for applications at global and continental scales: updates to the WISE database[END_REF]. Finally, the Garonne River is one of the main French basins with a draining area of 55,000 km². Wide floodplains are mainly located alongside the mainstream in the middle course. The DIN export of this river under high anthropogenic pressures is around 5.6 kgN.ha -1 .yr -1 [START_REF] Mayorga | Global Nutrient Export from WaterSheds 2 (NEWS 2): Model development and implementation[END_REF] with a DOC export of 14.3 kgC.ha -1 .yr -1 and average soils OC content in soils of 9 kgC.m -3 .

Delineation of the floodplains

An accurate delineation of these areas (Figure 1) was performed to simulate the contribution of the floodplains at the watershed scale spatially. The Amazon and Yenisei floodplains were delineated based on the tools available in the new GIS-interface developed for the SWAT+ model (https://swat.tamu.edu/software/plus/). This method allows the user to delineate floodplains based on a slope threshold [START_REF] Rathjens | Development of a gridbased version of the SWAT landscape model: Development of a grid-based version of the SWAT landscape model[END_REF] with a digital elevation model (DEM) from [START_REF] De Ferranti | Digital Elevation Model[END_REF]. For the Garonne, this method was not able to return consistent delineation. Thus the Garonne floodplain boundaries were based on alluvial soils area (Fluvisols) as proposed by [START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF].

Floodplains of the three watersheds cover over 660,000 km² (10.2%), 419,000 km² (15.5%), 4,000 km² (7.1%) for the Amazon, the Yenisei and the Garonne basins, respectively. Forests and pastures mainly cover Amazon and Yenisei floodplains with 78% and 13% for the Amazon and 66% and 20% for the Yenisei (Figure 1). Nevertheless, some areas are covered by agriculture, especially in the upstream parts of the watersheds. On the contrary, the Garonne floodplains are mostly covered by agriculture, with over 65% of the total area.

Model implementation for denitrification

The first model applied by [START_REF] Peyrard | Longitudinal transformation of nitrogen and carbon in the hyporheic zone of an N-rich stream: A combined modelling and field study[END_REF] estimated the denitrification rate in the hyporheic zone. This rate estimation depends on the availability of POC, DOC and NO3 -as well as oxygen (O2) availability and influence of nitrification rate from ammonia (NH4 + ) transformation. [START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF] simplified the equation by removing the ammonia term and used surface water-groundwater exchanges to approach the anaerobic conditions. A focus on the soil water content is necessary to assess when anaerobic conditions are occurring to trigger denitrification [START_REF] Sauvage | Modelling the role of riverbed compartments in the regulation of water quality as an ecological service[END_REF][START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF]. [START_REF] Guilhen | Denitrification, carbon and nitrogen emissions over the Amazonianwetlands[END_REF] used remote sensing data to assess the extent of water bodies as well as the water saturation in soils where denitrification occurs. Indeed, the denitrification rate in this study depends on the Surface Water Fraction (SWAF) product. Although this product possesses a low spatial resolution (25 km x 25 km for one pixel), its high frequency (3 days to map the whole Amazon Basin; [START_REF] Parrens | High-resolution mapping of inundation area in the Amazon basin from a combination of L-band passive microwave, optical and radar datasets[END_REF] makes it possible to record a sudden change in the hydrology. By comparing the brightness temperature of forest and water, a percentage of water cover in a pixel was deduced and used to estimate the anaerobic conditions in the model of [START_REF] Peyrard | Longitudinal transformation of nitrogen and carbon in the hyporheic zone of an N-rich stream: A combined modelling and field study[END_REF]. Nevertheless, the SWAF data determine the surface water extent in a pixel with a coarse resolution of 25 km x 25 km. However, the SWAF methodology had only been used on the Amazon River so far [START_REF] Parrens | Mapping Dynamic Water Fraction under the Tropical Rain Forests of the Amazonian Basin from SMOS Brightness Temperatures[END_REF]2018;2019) and remote sensing data used in this methodology are not available for Arctic zones yet.

In this study, we followed the conceptual schema shown in Figure 2 with denitrification occurring in the floodplain aquifers by using the available nitrate and OC content in aquifers. The denitrification process studied in past research is as followed:

4 𝑁𝑁𝑁𝑁 3 -+ 5 𝐶𝐶𝐶𝐶 2 𝑁𝑁 + 4 𝐶𝐶 + → 2 𝑁𝑁 2 (𝑔𝑔) + 5 𝐶𝐶𝑁𝑁 2 (𝑔𝑔) + 7 𝐶𝐶 2 𝑁𝑁 ( 1 )
Abril and Frankignoulle ( 2001) demonstrated an increase in alkalinity due to wetland denitrification. To take this phenomenon into account, the formation of HCO 3 -from dissolved CO 2 (eq.2) was coupled to the denitrification (eq.1). Overall, in this study, denitrification was modelled using the following equation:

4 𝑁𝑁𝑁𝑁 3 -+ 5 𝐶𝐶𝐶𝐶 2 𝑁𝑁 → 2 𝑁𝑁 2 (𝑔𝑔) + 𝐶𝐶𝑁𝑁 2 (𝑔𝑔) + 4 𝐶𝐶𝐶𝐶𝑁𝑁 3 -+ 3 𝐶𝐶 2 𝑁𝑁 ( 2 )
By using 𝑥𝑥 = 5 in ( 2) to compare the use of organic carbon and the consumption or the production of the other molecules [START_REF] Peyrard | Longitudinal transformation of nitrogen and carbon in the hyporheic zone of an N-rich stream: A combined modelling and field study[END_REF], we obtain:

0.8𝑥𝑥 𝑁𝑁𝑁𝑁 3 -+ 𝑥𝑥 𝐶𝐶𝐶𝐶 2 𝑁𝑁 → 0.5𝑥𝑥 𝑁𝑁 2 (𝑔𝑔) + 0.2𝑥𝑥 𝐶𝐶𝑁𝑁 2 (𝑔𝑔) + 0.8𝑥𝑥 𝐶𝐶𝐶𝐶𝑁𝑁 3 -+ 0.6𝑥𝑥 𝐶𝐶 2 𝑁𝑁
( 3 ) [START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF] showed the capability of [START_REF] Peyrard | Longitudinal transformation of nitrogen and carbon in the hyporheic zone of an N-rich stream: A combined modelling and field study[END_REF] model to describe the denitrification rates in the main floodplains of the Garonne by comparing their simulations with in-situ denitrification measurements. However, applying this model at the watershed scale or in other watersheds was not practicable because of its specific design for the middle course Garonne floodplains. To further estimate denitrification in contrasting basins, we investigated a more straightforward method considering OC dynamics and anaerobic conditions.

Therefore, we applied a new version of the model allowing an estimation of the denitrification rate based on easy-to-obtain variables as followed:

𝑅𝑅 𝑁𝑁𝑁𝑁3,𝑖𝑖 = -0.8𝑥𝑥 �𝜌𝜌. 1 -𝜑𝜑 𝜑𝜑 . 𝑘𝑘 𝑃𝑃𝑁𝑁𝑃𝑃 [𝑃𝑃𝑁𝑁𝐶𝐶 𝑖𝑖 ]. 10 6 𝑀𝑀 𝑐𝑐 + 𝑘𝑘 𝐷𝐷𝑁𝑁𝑃𝑃 [𝐷𝐷𝑁𝑁𝐶𝐶 𝑖𝑖 ]� . �𝑁𝑁𝑁𝑁 3,𝑖𝑖 � 𝐾𝐾 𝑁𝑁𝑁𝑁 3 + �𝑁𝑁𝑁𝑁 3,𝑖𝑖 � . 𝑄𝑄 𝑖𝑖 𝑄𝑄 𝑏𝑏𝑏𝑏𝑏𝑏 . 𝑒𝑒 -(𝑇𝑇 𝑖𝑖 -𝑇𝑇 𝑜𝑜𝑝𝑝𝑝𝑝 )² 100 ( 4 )
where 𝑅𝑅 𝑁𝑁𝑁𝑁3,𝑖𝑖 is the denitrification rate in µmol.L -1 on day i, 0.8𝑥𝑥 is the stoichiometric proportion of nitrate consumed in denitrification compared to the organic matter used with 𝑥𝑥 = 5, 𝜌𝜌 is the dry sediment density in kg.dm -3 , 𝜑𝜑 corresponds to the sediment porosity, 𝑘𝑘 𝑃𝑃𝑁𝑁𝑃𝑃 and 𝑘𝑘 𝐷𝐷𝑁𝑁𝑃𝑃 are the mineralization rate constants of POC and DOC (day -1 ), [𝑃𝑃𝑁𝑁𝐶𝐶 𝑖𝑖 ] and [𝐷𝐷𝑁𝑁𝐶𝐶 𝑖𝑖 ] are the concentrations on day i (µmol.L -1 ) of POC in alluvial soils and DOC in the river, 𝑀𝑀 𝑐𝑐 is the carbon molar mass (g.mol -1 ), �𝑁𝑁𝑁𝑁 3,𝑖𝑖 � is the nitrate concentration in the aquifer on day i (µmol.L -1 ), 𝐾𝐾 𝑁𝑁𝑁𝑁 3

is the half-saturation constant for nitrate limitation (µmol.L -1 ), 𝑄𝑄 𝑖𝑖 and 𝑄𝑄 𝑏𝑏𝑏𝑏𝑏𝑏 are the discharge on day i and the discharge at bank full depth, 𝑇𝑇 𝑖𝑖 and 𝑇𝑇 𝑜𝑜𝑜𝑜𝑜𝑜 are the temperature in the subbasin on day i and the optimal temperature for denitrification. 𝑇𝑇 𝑜𝑜𝑜𝑜𝑜𝑜 was fixed to 27°C [START_REF] Saad | Temperature dependence of nitrification, denitrification, and turnover of nitric oxide in different soils[END_REF][START_REF] Canion | Temperature response of denitrification and anaerobic ammonium oxidation rates and microbial community structure in Arctic fjord sediments: Temperature and N cycling in Arctic sediments[END_REF][START_REF] Brin | Similar temperature responses suggest future climate warming will not alter partitioning between denitrification and anammox in temperate marine sediments[END_REF]. The stoichiometric ratio between the consumption of nitrate and OC in the denitrification is 0.8𝑥𝑥 as in (3). More details on the conceptualization of the model could be found in [START_REF] Peyrard | Longitudinal transformation of nitrogen and carbon in the hyporheic zone of an N-rich stream: A combined modelling and field study[END_REF].

Our global modelling strategy consists in the application of the former model (equation 4) with the help of N and C entry data coming from two different sources (Figure 3). Firstly, a generic model calculates the DOC concentrations in rivers, and secondly, the SWAT model estimates nitrate concentrations in aquifers. We correlated the daily DOC concentrations to the daily discharge with the relation proposed by [START_REF] Fabre | Assessment of sediment and organic carbon exports into the Arctic ocean: The case of the Yenisei River basin[END_REF] for the study case of the Yenisei River. We assumed that POC concentrations in soils are not profoundly affected in time. POC concentrations were considered much larger than the other nutrients involved in the denitrification model. Thus, we fixed the values of average POC content in soils for each watershed based on [START_REF] Batjes | Harmonized soil profile data for applications at global and continental scales: updates to the WISE database[END_REF].

DOC concentrations in the river and NO3 -content in aquifers were extracted or calculated in each subbasin, as explained in the following paragraphs. Then, our model estimates the denitrification rate at a daily time step for each water body. Finally, these calculations helped to determine an average annual denitrification rate. Figure 3 summarizes our approach used to estimate the daily denitrification rate in the floodplains of the three watersheds. Denitrifying bacteria are more efficient at an optimal temperature of around 25-30°C [START_REF] Saad | Temperature dependence of nitrification, denitrification, and turnover of nitric oxide in different soils[END_REF][START_REF] Canion | Temperature response of denitrification and anaerobic ammonium oxidation rates and microbial community structure in Arctic fjord sediments: Temperature and N cycling in Arctic sediments[END_REF][START_REF] Brin | Similar temperature responses suggest future climate warming will not alter partitioning between denitrification and anammox in temperate marine sediments[END_REF]. Therefore a temperature term following a Gaussian function with an optimum was added into the model of [START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF] to better describe the denitrification variability according to the watersheds with various climates.

We fixed the half-saturation constant for nitrate limitation based on [START_REF] Peyrard | Longitudinal transformation of nitrogen and carbon in the hyporheic zone of an N-rich stream: A combined modelling and field study[END_REF] estimations in the hyporheic zone from in-field measurements. The two OC mineralization rate constants were calculated by [START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF] based on in-situ observations on the Garonne River. These two parameters integrate the temperature effect on the microbial ability to degrade the organic matter. New 𝑘𝑘 𝑃𝑃𝑁𝑁𝑃𝑃 and 𝑘𝑘 𝐷𝐷𝑁𝑁𝑃𝑃 values independent from the temperature allow exporting this calibration to the two other watersheds. These new values were obtained by dividing 𝑘𝑘 𝑃𝑃𝑁𝑁𝑃𝑃 and 𝑘𝑘 𝐷𝐷𝑁𝑁𝑃𝑃 of [START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF] by the temperature term of (4) filled with the average temperature in the Garonne watershed (𝑇𝑇 𝐺𝐺𝐺𝐺𝐺𝐺𝑜𝑜𝑏𝑏𝑏𝑏𝐺𝐺 ) as followed: ( 5 )

⎩ ⎪ ⎪ ⎨ ⎪ ⎪ ⎧𝑘𝑘 𝑃𝑃𝑁𝑁𝑃𝑃 = 𝑘𝑘 𝑃𝑃𝑁𝑁𝑃𝑃,
These new 𝑘𝑘 𝑃𝑃𝑁𝑁𝑃𝑃 and 𝑘𝑘 𝐷𝐷𝑁𝑁𝑃𝑃 values were assumed valid to be used for the two other watersheds since the daily temperatures control the denitrification rates variations. [START_REF] Sun | Modélisation des échanges nappe-rivière et du processus de dénitrification dans les plaines alluviales à l'échelle du bassin versant[END_REF], the denitrification rate is linked to the water volume stored in floodplains aquifers. The latter is linked to the water level in the channel [START_REF] Helton | Relative influences of the river channel, floodplain surface, and alluvial aquifer on simulated hydrologic residence time in a montane river floodplain[END_REF][START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF]. Therefore, we considered a ratio between the daily discharge in the stream extracted from SWAT and the discharge at bank full depth. The ratio is limited to 1 and depicts the gap between the current discharge and the discharge needed to produce a flooding. It is linked to the aquifers filling and trigger denitrification when it is close to 1. SWAT accurately simulates the discharges at different time steps and at small or large scales [START_REF] Ferrant | Understanding nitrogen transfer dynamics in a small agricultural catchment: Comparison of a distributed (TNT2) and a semi-distributed (SWAT) modelling approaches[END_REF][START_REF] Lu | Assessing the climate forecast system reanalysis weather data-driven hydrological model for the Yangtze river basin in China[END_REF]. However, the SWAT model encounters difficulties to estimate discharges at bank full depth with accuracy due to the different resolutions of the Digital Elevation Models (DEMs) used. Based on rating curves in gauging stations of the three watersheds, we adjusted the value of the discharge at bank full depth (Q bnk) to allow better variations of the Qi/Qbnk ratio in time and space. We used ratios of 7/8, 1/5 and 1/4 to refine bank full depth discharges for the Amazon, the Garonne and the Yenisei, respectively.

Model choice to estimate Nitrate and DOC dynamics

Consequently, bank full depth discharges were changed from 262,000 m 3 .s -1 to around 200,000 m 3 .s -1 at Obidos for the Amazon River, from 7,700 m 3 .s -1 to 640 m 3 .s -1 at Verdun for the Garonne River and from above 1,400,000 m 3 .s -1 to 140,000 m 3 .s -1 at Dudinka for the Yenisei River.

Hydrology calibration

Hydrology was first manually calibrated. Then an automatic calibration with three loops of 500 calibrations was done on the Yenisei and the Garonne basins as evoked in [START_REF] Fabre | Using Modeling Tools to Better Understand Permafrost Hydrology[END_REF] and [START_REF] Cakir | Assessment of ecological function indicators related to nitrate under multiple human stressors in a large watershed[END_REF] with the SWAT-CUP software. For the Amazon River, the hydrology was calibrated manually as for the OC and the nitrate dynamics. The calibration was performed with available observations in rivers extracted from the Observation Service SO HYBAM (https://hybam.obs-mip.fr/), the French Water Agency of the Garonne River (http://www.eauadour-garonne.fr/) and the Arctic Great Rivers Observatory [START_REF] Holmes | Arctic Great Rivers Observatory[END_REF]

Validity of simulated Nitrate and DOC dynamics

We used two indices to validate our simulated riverine nitrate and DOC concentrations with observed data: the coefficient of determination (R²) and the percentage of bias (PBIAS). These indices are detailed in [START_REF] Moriasi | Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations[END_REF]. R² ranges from 0 to 1, with higher values indicating less error variance. R² higher than 0.3 could be considered acceptable for daily biogeochemical modelling [START_REF] Moriasi | Hydrologic and Water Quality Models: Performance Measures and Evaluation Criteria[END_REF]. PBIAS expresses the percentage of deviation between simulations and observations. Thus, the optimal value is 0. PBIAS can be positive or negative, which reveals a model underestimation or overestimation bias, respectively [START_REF] Moriasi | Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations[END_REF].

Water quality efficiency ratio

We used an efficiency ratio 𝑅𝑅 based on the exported fluxes out of the basin (𝐹𝐹 𝑜𝑜𝑆𝑆𝑜𝑜𝑎𝑎𝐺𝐺𝑜𝑜 ) to test the denitrification efficiency in the watershed. This ratio compares the nutrients flux consumed by denitrification (𝐹𝐹 𝑑𝑑𝐺𝐺𝑏𝑏𝑖𝑖𝑜𝑜 ) to the total fluxes exported, e.g. exported at the watershed outlet and removed by denitrification:

𝑅𝑅 = 𝐹𝐹 𝑑𝑑𝐺𝐺𝑏𝑏𝑖𝑖𝑜𝑜 𝐹𝐹 𝑑𝑑𝐺𝐺𝑏𝑏𝑖𝑖𝑜𝑜 + 𝐹𝐹 𝑜𝑜𝑆𝑆𝑜𝑜𝑎𝑎𝐺𝐺𝑜𝑜 ( 6 )

Results

Nitrate and DOC simulations from SWAT in the three watersheds

The results of nitrate and DOC dynamics at the Amazon outlet are in the range of in-situ observations regarding the PBIAS index. Still, they show discrepancies with the temporal variations (Figure 4a and Figure 5a). On the Garonne River, the simulated nitrate concentrations are in the range of observations during high flow periods but display underestimations during low flow periods (Figure 4b). Concerning DOC concentrations, the simulations are in agreement with the observations ranges on the three watersheds. They do not simulate the dynamics of observed data in the Garonne and Amazon rivers accurately (Figure 5). However, these simulations are conserved because the PBIAS index and the pvalues show that they are in the range of the observations with regards to the low number of observed data [START_REF] Moriasi | Hydrologic and Water Quality Models: Performance Measures and Evaluation Criteria[END_REF]. Based on this assessment, the simulated DOC fluxes (Appendix 1) are assumed to describe the observed data adequately. In the same way, the good representation of low-water nitrate concentrations upstream to the floodplains indicates that the simulated nitrate content in the floodplains aquifers should be close to reality. Table 1 shows the fitted parameters used to obtain these theoretical C and N concentrations.

Table 1: Fitted values of the SWAT parameters for the three watersheds for nitrate and organic carbon. The parameters for the Amazon River were calibrated manually based on riverine observations from the Observation Service SO HYBAM. The settings for the Garonne and Yenisei Rivers were adapted from Cakir et al. (2020) and Fabre et al. (2019), respectively. The SWAT parameters linked to denitrification refer to the one in soils. SWAT does not integrate the denitrification occurring in floodplains aquifers.

Simulated average denitrification rates in contrasting watersheds

With the help of the new denitrification model (exposed in Equation 4), the parameters detailed in Table 2 and the previous works on DOC exports, we were able to assess the floodplains denitrification rates for the three considered watersheds. The average annual rates of the floodplain denitrification are at 73.0 ± 6.2 kgN.ha -1 .yr -1 for the Amazon, 4.5 ± 1.4 kgN.ha -1 .yr -1 for the Garonne and 0.7 ± 0.2 kgN.ha -1 .yr -1 for the Yenisei. [𝑃𝑃𝑁𝑁𝐶𝐶] (µmol.L -1 ) 1 1.5 33

𝐾𝐾 𝑁𝑁𝑁𝑁 3 (µmol.L -1 ) 30
𝑇𝑇 𝑜𝑜𝑜𝑜𝑜𝑜 (°C) 27

Figure 6 shows the annual average denitrification fluxes in floodplains found in this study. It highlights the hot spots of denitrification for each of the three watersheds. The hot spots for the Amazon basin are located in the Northern part of the watershed. At the same time, the denitrification in the Garonne basin is usually higher in the primary active floodplains between the stations G3 and G4 but also in the upstream parts near G5 (see Figure 1 for stations locations). For the Yenisei watershed, the hotspots are located in the unfrozen parts of the basin and in the Lake Baikal.

Temporal variability of the denitrification

Figure 7 shows the average daily denitrification rates (𝑅𝑅 𝑁𝑁𝑁𝑁3 ) on the 2000-2010 period for the three watersheds. For the Amazon, 𝑅𝑅 𝑁𝑁𝑁𝑁3 is maximal in April with a removal around 0.31 kgN.ha -

1

.day -1 . The lowest values are around 0.09 kgN.ha -1 .day -1 in October. 𝑅𝑅 𝑁𝑁𝑁𝑁3 reaches 0.06 kgN.ha -1 .day -1 in May on the Garonne and is lower during the cold season between October and February. With the same pattern, the Yenisei shows higher rates during the unfreezing period around May, but these rates are still low compared to the two other basins.

Discussion

Methodologies used

This paper exposed the capability of a simple model to describe daily denitrification rates in floodplains of contrasting watersheds. It is the first attempt to simulate, understand and compare daily denitrification rates in three different basins by applying a dynamic model.

Previous large-scale denitrification models provided either estimation of interannual fluxes or assessed the denitrification contribution to the nitrogen budget [START_REF] Birgand | Nitrogen Removal in Streams of Agricultural Catchments-A Literature Review[END_REF][START_REF] Boyer | Modelling denitrification in terrestrial and aquatic ecosystems at regional scales[END_REF][START_REF] Groffman | Terrestrial denitrification: challenges and opportunities[END_REF]Thouvenot-Korpoo et al., 2009). Others studies used models to estimate the denitrification at the global scale [START_REF] Seitzinger | Denitrification across landscapes and waterscapes: a synthesis[END_REF]. However, none have supplied daily denitrification rates yet. The need for a daily time step is important, particularly for basins subjected to sudden changes in the hydrological dynamic (as flash-flood in the Garonne River).

Compared to previous research, the model used in this paper was modified to integrate a new temperature dependence of 𝑅𝑅 𝑁𝑁𝑁𝑁3 with an optimal set at 27°C. This term allowed the comparison of the denitrification rates between watersheds with different climates. This dependence is essential, especially for the Yenisei River, where the solutes are available, but the cold climate inhibits the microbial activity. Other studies mentioned an optimal temperature around 45°C for this process in soils [START_REF] Benoit | Temperature dependence of nitrous oxide production of a luvisolic soil in batch experiments[END_REF][START_REF] Billen | Nitrate retention at the river-watershed interface: a new conceptual modelling approach[END_REF]. More research is needed to better understand and consider this temperature effect in the proposed method.

The significant improvement of this model comes from the integration of the different carbon sources, together with nitrates as substrates, so that the stoichiometric ratio controls the denitrification rates. This operation was made possible with the help of C & N data sources with accurate temporal and spatial scales. The integration of the model of [START_REF] Fabre | Assessment of sediment and organic carbon exports into the Arctic ocean: The case of the Yenisei River basin[END_REF] to estimate the daily variations of DOC concentrations in the river as a source of C data to use for control of stoichiometric ratio the new model makes part of the new aspect. DOC plays a predominant role in the denitrification process. Therefore, the integration of the simulated DOC concentrations at a daily time step in the river is a notable improvement to refine denitrification estimates at the watershed scale.

The other part of the model concerned by the organic carbon integrates the role of the POC.

POC was set up in the model depending on the average soils OC content of the three watersheds floodplains. A first improvement would be to spatialize more accurately the POC content at the subbasin scale. Therefore, more research should be conducted to validate global datasets of soil OC. Plus, the POC content used in this study does not consider the POC renewal by deposition during flooding events. The soil OC turnover may boost floodplain denitrification but was not studied yet.

Nonetheless, this model does not consider OC lability, which is essential in the estimation of denitrification rates [START_REF] Zarnetske | Labile dissolved organic carbon supply limits hyporheic denitrification[END_REF]. Around 20% of the DOC is labile in freshwater ecosystems [START_REF] Søndergaard | A cross-system analysis of labile dissolved organic carbon[END_REF][START_REF] Guillemette | Reconstructing the various facets of dissolved organic carbon bioavailability in freshwater ecosystems[END_REF][START_REF] Mclaughlin | Biological lability of dissolved organic carbon in stream water and contributing terrestrial sources[END_REF]. Integrating the lability in the denitrification model may improve C and N dynamics in floodplains. Moreover, DOC is the most consumed form in denitrification [START_REF] Peyrard | Longitudinal transformation of nitrogen and carbon in the hyporheic zone of an N-rich stream: A combined modelling and field study[END_REF][START_REF] Zarnetske | Labile dissolved organic carbon supply limits hyporheic denitrification[END_REF]. Yet, the model does not integrate the dominant use of the DOC compared to the POC.

The delineation system from [START_REF] Rathjens | Development of a gridbased version of the SWAT landscape model: Development of a grid-based version of the SWAT landscape model[END_REF] showed its capability to visualise the floodplains as a functional and active area. This tool could be further compared to remote sensing data from SWAF on the Amazon and other systems to see if easy-to-obtain data such as the DEM are sufficient to estimate floodplains coverage at the watershed scale.

Concerning the ratio between daily discharge and discharge at bank full depth, correction parameters were applied on the discharges at bank full depth based on known parts of the three watersheds. Uncertainties could remain in some other parts of the catchments, which would have a significant impact on the denitrification variations in surrounding areas. A better definition of discharge at bank full depth in the different parts of the basins may improve floodplains denitrification estimates at the watershed scale.

Moreover, we defined the mineralization rate constants for DOC and POC based on scarce insitu measurements [START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF] which are non-representative of the entire watershed.

Indeed, 𝑘𝑘 𝑃𝑃𝑁𝑁𝑃𝑃 and 𝑘𝑘 𝐷𝐷𝑁𝑁𝑃𝑃 vary under the influence of multiple drivers such as soils characteristics, temperature and microorganism's activity (geophysical and biological characteristics). An improvement in the calculations of denitrification rates could be to measure these coefficients in different areas and determine their temporal and spatial variability in the floodplains.

Concerning the half-saturation constant for nitrate limitation, this variable was based on in-situ observations in the Garonne hyporheic zone [START_REF] Peyrard | Longitudinal transformation of nitrogen and carbon in the hyporheic zone of an N-rich stream: A combined modelling and field study[END_REF]. Again, other measurements are needed to refine the value of 𝐾𝐾 𝑁𝑁𝑁𝑁 3 in floodplains of various watersheds.

Lastly, this study outlines some weaknesses in the estimation of denitrification rates. Alluvial wetlands show higher denitrification than other areas in floodplains [START_REF] Mcclain | Biogeochemical Hot Spots and Hot Moments at the Interface of Terrestrial and Aquatic Ecosystems[END_REF][START_REF] Harrison | Denitrification in Alluvial Wetlands in an Urban Landscape[END_REF]. However, the model proposed here does not distinguish alluvial wetlands from the rest of the floodplains. Accurate mapping of alluvial wetlands at the watershed scale would help the scientific community to better estimate the specific denitrification rates in these highly reactive areas and consequently would improve the estimates in other areas of the floodplains.

Calibration of the inputs for denitrification

The concentrations of nutrients in floodplains were extracted from the SWAT model. This model, as shown in Table 1, already integrates denitrification processes. However, the denitrification represents the one occurring in uplands soils and stream but does not integrate the predominant role of floodplains aquifers [START_REF] Mcclain | Biogeochemical Hot Spots and Hot Moments at the Interface of Terrestrial and Aquatic Ecosystems[END_REF]. Therefore, our model proposed in this study could fill the gap and help to approach the floodplains denitrification contribution to N and C dynamics at the watershed scale.

This paper shows that the N and C inputs were calibrated successfully in different areas of the three watersheds. Nevertheless, these calibrations may be improved by better representing in-stream and uplands processes to improve the calibration of nitrate and organic carbon concentrations in floodplains aquifers. In the same way, nitrate concentrations in the Garonne River are underestimated and could induce lower denitrification.

Concerning OC, uncertainties remain in the simulation of DOC concentrations in the three watersheds on the one hand (Figure 5). Different processes and conditions are not considered in the model of [START_REF] Fabre | Assessment of sediment and organic carbon exports into the Arctic ocean: The case of the Yenisei River basin[END_REF] yet. Anthropogenic pressures in the Garonne River, as well as consumption, deposition, or floodplain deliveries for the Amazon River, are conditions that could explain the observed DOC variations. Process-based models could help to improve the DOC simulations by considering various in-stream processes such as in-stream assimilation or production [START_REF] Du | Hydro-climate and biogeochemical processes control watershed organic carbon inflows: Development of an in-stream organic carbon module coupled with a process-based hydrologic model[END_REF]. However, DOC and nitrate concentrations are in the range of observations. Thus, the other components of the model regulate the denitrification rates on the Amazon River and the Garonne River.

On the other hand, the variations of observed DOC concentrations are so intense that the data quality could be discussed. Sampling nitrate and DOC in streams is difficult in large watersheds due to in-situ conditions. Thus, an improvement in the quality of data could be required to refine the parameters of the DOC model and to improve the modelling efforts for the nitrate concentrations or to confirm that the DOC model of [START_REF] Fabre | Assessment of sediment and organic carbon exports into the Arctic ocean: The case of the Yenisei River basin[END_REF] is adapted to various climatic and soils conditions.

Temporal and spatial validity of the resulting floodplains denitrification rates

We showed that even if the dynamics of nitrate and DOC concentrations in rivers are hard to obtain, these concentrations are in the range of observed data. Nevertheless, the concentrations at the outlet already integrate the complex processes occurring in the watershed. Consequently, we were able to extract from the SWAT model the average nitrate concentrations in the floodplains aquifers and compared it with the literature. In the Amazon watershed, the simulated nitrate concentrations in aquifers are around 0.9 ± 0.6 mgN-NO3.L -1 .

These values are in the range of the observations made in previous works (0.04-2.8 mgN-NO3.L -1 ; McClain et al., 1994; Leite et al., 2011). Concerning the Garonne basin, the SWAT model simulated average nitrate concentrations of 8.6 ± 5.8 mgN-NO3.L -1 in aquifers while past research measured concentrations between 3.86 and 17.95 mgN-NO3.L -1 [START_REF] Jégo | Predicting soil water and mineral nitrogen contents with the STICS model for estimating nitrate leaching under agricultural fields[END_REF][START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF]. The average nitrate concentrations in the Yenisei aquifers were far lower than the other basins with values around 0.01 ± 0.14 mgN-NO3.L -1 . As no literature is available to validate these values in the Yenisei, we assumed that they are representative and could be used to estimate denitrification rates.

To validate our simulated denitrification rates, we compared our outputs with results from other studies in the same watersheds. Sánchez-Pérez et al. (2003) and [START_REF] Sun | Using SWAT-LUD Model to Estimate the Influence of Water Exchange and Shallow Aquifer Denitrification on Water and Nitrate Flux[END_REF], based on in-situ observations, found that a highly reactive ecological corridor including efficient alluvial wetlands in the floodplains of the Garonne watershed provides a denitrification rate of 21-25 kgN-NO3.ha -1 .yr -1 . On the same part of the watershed, our study gives a nitrate removal of 19.9 kgN-NO3.ha -1 .yr -1 . Our rates are in the same order of magnitude, which could allow validating the method used in this paper.

We compared our results from the Amazon watershed with the estimation of [START_REF] Guilhen | Denitrification, carbon and nitrogen emissions over the Amazonianwetlands[END_REF]. This work focused on the three main floodplains of the Amazon: one alongside the mainstream near Obidos (station A1), one alongside the Branco and Negro rivers and one in the upstream Bolivian parts of the Madeira Basin. They found denitrification rates of 142.5 kgN.ha -1 .yr -1 on the mainstream floodplain, 38.8 kgN.ha -1 .yr -1 on the Branco floodplain and 60.4

kgN.ha -1 .yr -1 on the Madeira floodplain. In our study, we found denitrification rates of 165.7 kgN.ha -1 .yr -1 on the mainstream floodplain, 144.3 kgN.ha -1 .yr -1 on the Branco system and 67.6 kgN.ha -1 .yr -1 on the Madeira upstream part. Only the Branco floodplain shows different results.

This offset could be due to different drivers influence. [START_REF] Guilhen | Denitrification, carbon and nitrogen emissions over the Amazonianwetlands[END_REF] estimated the DOC concentrations at a monthly time step with high variations. In our study, the daily DOC concentrations are relatively constant but are still closer to the real concentrations. Their denitrification rates depend on the presence of water in the soil surface with a binary approach.

In our study, the integration of the ratio between discharge and discharge at bank full depth improves the understanding of the denitrification dynamic. This improvement is not obvious in tropical systems such as the Amazon River because denitrification is occurring during the frequent and long-lasting flooding events. Therefore, our approach may be more relevant for basins where flooding events occur at a high temporal frequency, such as the Garonne River.

The temporal resolution of this study highlighted preferential periods of denitrification. For the three watersheds, the periods of high-water flows show a higher denitrification rate as implied by the model.

Efficiency of the different floodplains

By including contrasting watersheds, this paper brings to light a comparison of the efficiency of different types of floodplains with various anthropogenic and climatic contexts. Denitrification dynamics follow the hydrological cycles. Denitrification rates peak when and where both nitrate and DOC are not limiting factors like in the Amazon basin. On the contrary, the Garonne River has high exports of nitrate due to the anthropogenic pressures within the watershed. The DOC concentrations are always low except for some upstream parts of the watershed, which lead to higher denitrification rates. The Yenisei River has high DOC concentrations during the unfreezing period, but the low nitrate concentrations and the cold temperatures limit the denitrification. The suggested conceptualization integrates all of these contrasts between watersheds for the denitrification (Figure 8).

By comparing the average exports of nitrate and OC at the outlets of the three watersheds with the denitrification rates, we were able to evaluate the floodplains contribution to the regulating services of surface waters. The denitrification occurring in uplands and streams is already integrated into the flux exported to the oceans and is negligible compared to the one in floodplains. The DOC used for denitrification accounts for 10.4% of the total DOC flux exiting the Amazon basin (exported to the ocean or consumed by denitrification). This ratio reaches 3.0% in the Garonne and amounts to 0.9% for the Yenisei basin. Concerning nitrates, those processed in the denitrification represents 85% of the total nitrate flux exiting the Amazon basin and 34% in the Garonne watershed. For the Yenisei watershed, only 13% of the total nitrate flux exiting the basin is used for denitrification.

Concerning the Amazon and the Yenisei River, as the DOC concentrations are generally higher than nitrate, only a few of the total DOC yield is needed for the denitrification. The Garonne River, which is under high anthropogenic pressures, is characterized by soils with low organic matter contents and high exports of nitrates. The resulting concentrations in the river are quite in the same range, and a large part of the DOC export is needed to consume a small amount of the aquifers nitrate content.

Conclusion

This paper demonstrated the possibility of a simple model to simulate the floodplains denitrification rates in contrasting watersheds. We showed that tropical catchments that combine an average temperature around the optimal temperature for denitrification and large C availability show the highest amounts for the process. On the other hand, we confirmed that

Figure 1 :

 1 Figure 1: Study areas: a) The Amazon, b) The Yenisei and c) The Garonne rivers and their respective sampling stations used to calibrate the hydrology and the nutrients fluxes. Delineation of the floodplains was based on the method of Rathjens et al. (2015) and the Digital Elevation Model of de Ferranti and Hormann (2012) for the Amazon and the Yenisei rivers. For the Garonne River, floodplains delineation originate from on the soils database of Batjes (2009). Land covers came from the Global Land Cover Database 2000 (European Commission, 2003).

Figure 2 :

 2 Figure 2: Conceptual representation of the denitrification in floodplains based on the previous studies of Sánchez-Pérez and Trémolières (2003), Sauvage et al. (2018) and Sun et al. (2018).

Figure 3 :

 3 Figure 3: Details of the different steps of the denitrification model setup. First, the Soil and Water Assessment Tool (SWAT) and the Fabre et al. (2019) model are calibrated to estimate discharge and riverine nutrients concentrations. Then, these results are used to follow nutrients contents in floodplains aquifers and to calculate the denitrification rate.

  datasets for the Amazon, the Garonne and the Yenisei, respectively. For the Amazon, we calibrated and validated the model manually over the 2000-2009 period and the 2010-2016 period, respectively. For the Garonne, the model was calibrated from 2000 to 2005 and was validated from 2006 to 2010 based on Cakir et al. (2020). For the Yenisei, the model was calibrated over 2003 to 2010 and validated over the 2011-2016 period based on Fabre et al. (2019).

Figure 4 :

 4 Figure 4: Daily observed and simulated nitrate concentrations (mg.L -1 ) at the outlet of a) the Amazon, b) the Garonne and c) the Yenisei rivers. Locations of the sampling stations are found in Figure 1.

Figure 5 :

 5 Figure 5: Daily observed and simulated DOC concentrations at the outlet of a) the Amazon, b) the Garonne and c) the Yenisei rivers. The Yenisei graph is adapted from Fabre et al. (2019). Locations of the sampling stations are found in Figure 1.

Figure 6 :

 6 Figure 6: Representation of the mean annual average DOC consumption (kgC.ha -1 .yr -1 ) in denitrification in floodplains of the three selected watersheds on the 2000-2010 period.

Figure 7 :

 7 Figure 7: Average daily variations of the denitrification rates in the floodplains of the three selected watersheds on the period 2000-2010.

Figure 8 :

 8 Figure 8: Conceptualization of the denitrification model for the selected watersheds. In each case of study, the different variables favouring the process shows various intensities. Adapted from Sánchez-Pérez and Trémolières (2003) and Bernard-Jannin et al. (2017). The red arrows represent nitrogen dynamics, and black arrows represent organic carbon pathways. The top-left graph shows the variation of the temperature index in the denitrification model. The coloured zones are the temperature intervals for each watershed.

  EEA Report, 2013; https://ec.europa.eu/). Finally, land-use databases were updated to better simulate the fertilizers supply in the basin and to better match with national crop yields, as demonstrated in[START_REF] Cakir | Assessment of ecological function indicators related to nitrate under multiple human stressors in a large watershed[END_REF]. The SWAT model integrates the nitrogen cycle. SWAT calculates the denitrification in soils but does not consider the denitrification occurring in aquifers.The nitrogen cycle in SWAT was calibrated with observed in-stream nitrate concentrations available at the different gauging stations shown in Figure1. Based on the correlation between observed and simulated concentrations during low flow periods, we assumed that simulated nitrate concentrations in aquifers are representative of real conditions. Thus, the nitrate concentrations in aquifers, as new denitrification model inputs (equation 4), were extracted from the SWAT model at the subbasin scale and at a daily time step. Concerning the anaerobic conditions, as it was demonstrated in

This study uses the Soil and Water Assessment Tool (SWAT) model to assess and quantify nitrate and OC dynamics based on discharge simulations of the three selected watersheds.

SWAT is a hydro-agro-climatological model developed by USDA Agricultural Research Service (USDA-ARS; Temple, TX, USA) and Texas A&M AgriLife Research (College Station, TX, USA;

[START_REF] Arnold | Large area hydrologic modelling and assessment part 1: model development[END_REF]

. Its performance has already been tested at multiple catchment scales in various climatic and soil conditions on water, sediment and water chemistry especially nitrogen

[START_REF] Fu | A review of catchmentscale water quality and erosion models and a synthesis of future prospects[END_REF]

and organic carbon

[START_REF] Oeurng | Assessment of hydrology, sediment and particulate organic carbon yield in a large agricultural catchment using the SWAT model[END_REF]

exports. Theory and details of hydrological and water quality processes integrated into SWAT are available online (http://swatmodel.tamu.edu/). For the Garonne River, we integrated most of the anthropogenic pressures in the basin to represent the watershed dynamics. Irrigation and dam management were implemented into the modelling based on national surveys from CACG (https://www.cacg.fr/fr/) and Electricité de France (REGARD-RTRA/STAE program). In the same way, city effluents were calibrated based on European databases of UWWTP -EUDB (

Table 2 : Calibrated values of the different parameters used in the floodplains denitrification rates calculations based on the work of Peyrard et al. (2011) and Sun et al. (2018) on the Garonne River.

 2

	Basin	Amazon	Garonne	Yenisei
	𝜌𝜌 (kg.dm -3 )	0.25	0.15	0.1
	𝜑𝜑	1.03	1.3	1.03
	𝑘𝑘 𝐷𝐷𝑁𝑁𝑃𝑃 (day -1 )	1.88.10 -3	3.63.10 -3	1.88.10 -3
	𝑘𝑘 𝑃𝑃𝑁𝑁𝑃𝑃 (day -1 )		2.75.10 -4

C and N availability, as well as average temperature, could be limiting factors for floodplains denitrification on both cold and temperate watersheds. This study also highlighted the role of floodplains on water quality and their contribution to the stability and the resilience of the basins subjected to future climate and land use changes.

Acknowledgements

We do acknowledge the Observation Service SO HYBAM, the French Water Agency,

Additional information

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.