REVIEWER: The reviewer No 1 correctly pointed out that “some of the conclusions draw by the article to be lacking complete discussions and support by references and other supporting ideas”.

RESPONSE: In fact, the present study was not designed to address the mechanisms of CO₂ generation in the Lena River main stem and tributaries. Such an investigation requires quite different sampling and measurement design. We would like to note that some discussion on CO₂ -related processes is provided in L 302-336, whereas thorough comparison with relevant literature data is given in section 4.2. In the revised version, we extended the discussion and provided necessary references.

REVIEWER: Some of the parameters discussed in the methods and results section are not discussed in the discussion section. Discussion of these parameters would strengthen the arguments made by the authors.

RESPONSE: The reviewer made a good point here. However, most of these parameters turned out to be non-correlated to pCO₂ in the river water. As such, there is no reason to discuss the lack of control by this or that environmental parameter given that we cannot ascertain the reason for this case.

REVIEWER: PCA results are presented in the results sections with no description in the methods section. The PCA results should be revisited in the discussion section.

RESPONSE: We totally agree with this pertinent comment and we would like to provide more discussion on the PCA results. However, the PCA demonstrated extremely low ability to describe the data variability (12% by F1 and only 3.5% by F2). We believe that the most likely reason of weak PCA capacity is rather homogeneous distribution of CO₂ and CH₄ across the river transect and among tributaries, primarily linked to the specific hydrological period, studied in this work - the springflood. During this high flow period, the local lithological and soil heterogeneities among tributaries or the segments of the main stem virtually disappear and surface flow (via vegetation leaching) becomes most important driver of riverine chemistry, as it is known from adjacent permafrost territories of Central Siberia (i.e., Bagard et al., 2011). Nevertheless, some specific features of the data structure could be established. The first factor, significantly linked to pCO₂  (0.72 loading), strongly acted on the sample location at the Lena transect, the watershed coverage by deciduous needle-leaf forest and shrubs, riparian vegetation, but also the proportion of tundra, bare rock and soils, water bodies,  peatland and bogs (> 0.90 loading). This is fully consistent with spatial variation of pCO₂ along the permafrost and climate gradient in the main channel and sampled tributaries. Positive loading of riparian vegetation, peatlands and bogs on F1 (0.927 and 0.989, respectively) could reflect a progressive increase in the feeding of the river basin by mire waters, increase in the proportion of needle-lead deciduous trees, and an increase in the width of the riparian zone from the SW to the NE direction.

Methods: For the PCA treatment, all the variables were normalized as necessary in standard package of STATISTICA-7 (http://www.statsoft.com) because the units of measurements of various components were different. The factors were identified via the Raw Data method. To run the scree test, we plotted the eigenvalues in descending order of their magnitude against their factor numbers. There was significant decrease in the PCA values between F1 and F2 suggesting therefore that maximum two factors were interpretable.

REVIEWER: The reviewer also stated that ‘On line 322, the authors suggest that in-stream processing of dissolved terrestrial organic C is not the main driver of CO₂ supersaturation in the river waters of the Lena River basin, but offer no alternative pathways for this phenomenon.’

RESPONSE: The relevant mechanisms of CO₂ supersaturation are discussed in L327-334. We extended this discussion in the revised version as following. The main sources of CO₂ in the river water include but not limited to i) underground discharge of CO₂-rich waters, ii) lateral influx of CO₂-rich soil waters; iii) DOC and POC processing in the water column via bio- and photodegradation, and iv) phyto, zoo-plankton, periphyton and sediment respiration. As indicated in the text (L327-331), there was no relationship (p < 0.05) between the proportion of carbonate rocks on the watershed and the pCO2 in the tributaries (Fig. S6 B), whereas for the Lena River main stem, the lowest CO2 concentrations were recorded in the upper reaches (first 0-800 km) where the carbonate rocks dominate the background lithology. This makes unlikely the impact of underground CO2 from carbonate reservoirs on river water CO2 concentrations. Given that we have not recorded any sizable diurnal variations in pCO₂ over the full transect of the Lena River, the respiration of photosynthetic organisms (plankton and periphyton) cannot be the reason for persistent CO₂ supersaturation over day and night.  Furthermore, these was no significant (p < 0.05) link between DOC and CO₂ concentration, so we do not expect sizable impact of bio- and photodegradation of DOM.  A lack of lateral (across the river bed) variations in pCO₂ witnesses against sizable input of soil waters from the shore, although we admit that much higher spatial coverage along the river shore is needed to confirm this hypothesis. Therefore, other sources of riverine CO2 may include POC processing in the water column (Attermeyer et al., 2018), river sediments (Humborg et al., 2010) and within the riparian zone (Leith et al., 2014, 2015). Quantifying these impacts at the scale of the Lena River basin will certainly require further investigation.

REVIEWER: The reviewer also noted that the text ‘needs to be reviewed and edited by a native English speaker’. The revised text will be subjected to thorough editing by a native English speaking scientist. We would like to point out that the APC of Biogeosciences include thorough English style and grammar revision, and we hope to use this option for our manuscript.

Specific comments of Reviewer No 1:

Line 331 POC is not defined. Response: Particulate Organic Carbon, will be added to revised text.

Line 344 FCo2 not defined. Response: This is CO2 emission flux, will be corrected.

Line 344 Unites should be United. Response: We are sorry for this misprint and will correct it accordingly.

REVIEWER: The reviewer No 2 correctly argued that ‘some of the drawn conclusions are lacking proof, and likely overestimate the annual carbon emissions.’

RESPONSE: We revised our conclusions and estimations, following his/her detailed comments below.

REVIEWER: Comment to line 167-169. A fixed k_CO2 value for the entire open water season of 4.6 m day ^-1 is rather high, especially since floating chambers often overestimate the fluxes (Long et al., 2017; Ribas-Ribas et al., 2018). Particularly when using floating chambers during the freshet, where the water velocity and turbulences are several times above the summer low which then lasts for 4 to 5 months. Used reference measured a median of 4,464 m d^-1, which were all sampled during June. In addition, since many k measurements were made, I would suggest separating main stems and tributaries. Also, when looking up the k values from the given ref. Serikova et al., all reported k values were given in cm^-1 h^-1, ranging between 5.1 and 16.5 cm^-1 h^-1 (which is 1.2 to 4 m day^-1). Please double check that the proper k value unit was used.

RESPONSE: This is very pertinent comment. In our calculations, we used a fixed value of 4.464 m d^-1 as recommended for the Ob River by Karlsson et al. (2021). This river is similar to Lena in size, but exhibits lower velocity and turbulence than those of the Lena River. In fact, due to more mountainous relief, the Lena River main stem and tributaries have much higher turbulence than that of the Ob River and tributaries and as such this estimation can be considered rather conservative. Decreasing the k to even more conservative value of 3 m d^-1 (which is the lowest range of world’s rivers as recommended by Raymond et al., 2013) provide the values of specific emissions which are 30 to 50% lower than those obtained in this study (k = 4.464 m d^-1). The resulted corrections in aerial emissions yield the from value ranging between 0.8 and 1.5 g C m^-2 d^-1 corresponding to total value of 4 to 7.5 Tg C y^-1. For convenience, we attached the revised tables to this response (Tables R1 and R2). Note that main stem and tributaries are always separated in the text, figures and tables (see Tables 1 and 2).

REVIEWER: Comment to section 3.4 on aerial emissions. As your own data shows, there are strong temporal and spatial variability in pCO₂ levels.

RESPONSE:  We do not completely agree with this statement. As we show in our work, the pCO₂ in Lena and tributaries remain generally stable over the night and day period (Abstract, Fig. 4, Fig. S2). The local lateral variability over the tributaries and across the channel is also low (Fig. S1B, Fig. S3). The global variability in pCO₂ over the largest part (~2400 km) of the main stem is “only” ±20% (from 800 to 1200 µatm, see Fig. 2 A). The variability of pCO₂ in the tributaries is indeed, higher (from 600 to 1100 atm) and this explicitly taken into account during our overall estimations of C emissions.

REVIEWER: Upscaling spring flood concentrations, where >50% of annual water masses discharges, for the remaining 4 summer months is highly uncertain. Summer concentrations from e.g. the Kolyma are reported to be 0.35 g C m^-2 d^-1. Also, in line 266 you report that 5022 km² water area are seasonal. This area needs to be removed when calculating the areal summer fluxes.

RESPONSE: We agree with sizable uncertainty on our estimations, which amounts to ca. 50% (from 1 to 2 g C m^-2 d^-1). We demonstrate, via analysis of available literature data, that seasonal variations of pCO₂ in the Lena River main stem do not exceed the range of our uncertainties (section 3.4, L 270-279). We do acknowledge sizable uncertainties on our first order estimations, especially in view of lack of direct pCO₂ data for the northern tributaries including a very large river Vilyi (L377-382). We further agree that rigorous aerial estimation should include 4 summer months with lower surface water coverage. However, introducing this correction changes the global value by less than 15% which is below the range of our uncertainties.

REVIEWER: Comment to line 358ff: What published data and I would like to see a table with this literature data. What are the numbers? If available with seasonal resolution as this is what you are comparing with.

RESPONSE: Extensive description of all the relevant literature data is provided in section 3.4, L 270-279. We believe that adding an explicit table will lengthen the paper and preferred to use the current format which is easier for the reader.

REVIEWER: Comment to the discussion section. Especially here English needs to be revised and restructured. Some parts can be shortened, while several other parameters which were introduces, were not discussed at all.

RESPONSE: We agree and reorganized this sections and revised the English. The three parameters of the river water chemistry (pH, DOC and DIC) were indeed, only partially discussed in the manuscript (L320-321, Fig. S6A). The correlation of pCO₂ with DIC and pH was not pronounced (see attached Fig. R1 A). The pH did not control the CO₂ concentration in the main stem, and only weakly impacted the CO₂ in the tributaries (Fig. R1 B). The latter could reflect an increase in pCO₂ in the northern tributaries which exhibited generally lower pH compared to the SW tributaries; the latter draining through carbonate rocks. Overall, such low correlations of CO₂ with DIC and pH reflected generally low predictive capacity to calculate pCO₂ from measured pH, temperature and alkalinity as stated in L 280-281: the ratio of calculated to measured pCO₂ was 0.67±0.15 (n = 47). This, again, demonstrates highly dynamic and non-equilibrium behavior of CO₂ in the river waters, with possible local hot spots from lateral input of CO₂-rich soil or suprapermafrost waters. For these reasons, in-situ, high spatial resolution measurements of CO₂ concentration in rivers such as those reported in this study of the Lena Basin, are crucially important for quantifying the C emission balance in lotic waters of high latitudes.

REVIEWER: Figure 1 and S1 A: Since you have graticules, you do not need a north arrow. Actually, your north is not always “up” on the figures. Please remote them.

RESPONSE: Agree and edited accordingly.

REVIEWER: Figure S1 A: Change Landscape to Landcover map. Also, reference for this data.

RESPONSE: Agree and edited accordingly. The land cover information sources are described in section 2.4 (L183-191) and we will present them in the Figure caption of revised version.

REVIEWER: Figure 2. This data is very interesting, but what I am missing is the discussion on that. Are the peaks where conflux occurs? Higher fluxes due to turbulences? More information on differences between the tributaries.

RESPONSE: This is a good point. We do not have straightforward explanation for peaks shown on the diagram of the main stem. These peaks are not necessarily linked to CO₂-rich tributaries but likely reflect local processes in the main stem, including lateral influx from the shores and shallow subsurface waters, typical for permafrost regions of forested Siberian watersheds (i.e., Bagard et al., 2011). Given that the data were averaged over 20-km distance, these peaks are not artifacts but reflect local heterogeneity of the main stem (turbulences, suprapermafrost water discharge, sediment resuspension and respiration. Note that such a heterogeneity was not observed in the tributaries, at least at the scale of our spatial coverage (see Fig. S2, S3).

Bagard, M. L.; Chabaux, F.; Pokrovsky, O. S.; Viers, J.; Prokushkin, A. S.; Stille, P.; Rihs, S.; Schmitt, A. D.; Dupre, B. Seasonal variability of element fluxes in two Central Siberian rivers draining high latitude permafrost dominated areas. Geochim. Cosmochim. Acta 75, 3335-3357, 2011.

The differences between tributaries (presentation of results and their discussion) make the central part of our study, and this information is provided in section 3.3. and 4.1.

REVIEWER: Table 1: CH₄ concentrations are illustrated twice. Please remove or exchange one.

RESPONSE: Thanks a lot for catching this! Instead of 2^nd CH₄ column, we will add the FCO₂ calculated for most conservative scenario of k = 3 m d^-1.

REVIEWER: Organic C and OC, choose one and use consistently.

RESPONSE: We homogenized as OC.

REVIEWER: Additional data from tables (DIC, pH) not really discussed and incorporated.

RESPONSE: The correlations of pCO₂ with DIC and pH were poorly pronounced (see response above and Fig. R1) and as such neither DIC nor pH could serve as sole controlling factors of CO₂ concentration in the Lena River main stem and tributaries.

REVIEWER: This study presents a very interesting dataset. There is a significant lack of data on GHG emissions during the spring flood of Arctic rivers, so the data collected and presented is very insightful. Because of this I recommend putting in some extra work to make the most of the data, streamline this paper and make the conclusions stronger.

RESPONSE: We thank the reviewer for positive evaluation of our work and we revised the data presentation and interpretation as recommended.

REVIEWER: Comment to line 170: You change to comparing to k₆₀₀ values from literature, which is not the same as k values but you do not define k₆₀₀.

RESPONSE: We thank the reviewer for pointing out this inconsistency. In this study, we used the value of k_t (a median gas transfer coefficient) of 4.464 m d^-1 measured in 4 largest rivers of Western Siberia (June 2015) of the Ob’, Pur, Pyakupur and Taz rivers (Karlsson et al., 2021).

To standardize k_tto a Schmidt number of 600, we used the following equation (Alin et al., 2011; Vachon et al., 2010):

k₆₀₀ = k_t (600/Sc_CO2)^-n

where Sc_CO2 is CO₂ Schmidt number for a given temperature (t, °C) in the freshwater (Wannikhof, 1992):

Sc_CO2 = 1911.1-118.11t + 3.4527t² - 0.041320t³

and exponent n is a coefficient that describes water surface (2/3 for a smooth water surface regime while 1/2 for a rippled and a turbulent one), and the Schmidt number for 20°C in freshwater is 600. We used n = 2/3 because all water surfaces of sampled rivers were considered flat and had a laminar flow (Alin et al., 2011; Jähne et al., 1987) and the wind speed was always below 3.7 m s^-1 (Guérin et al., 2007).

Alin, S. R. et al. Physical controls on carbon dioxide transfer velocity and flux in low-gradient river systems and implications for regional carbon budgets. J. Geophys. Res. 116, G01009 (2011).

Guérin, F., Abril, G., Serça, D., Delon, C., Richard, S., Delmas, R., Tremblay, A., Varfalvy, L., 2007. Gas transfer velocities of CO2 and CH4 in a tropical reservoir and its river downstream. J. Mar. Syst., 66, 161–172. https://doi.org/10.1016/j.jmarsys.2006.03.019

Jähne, B., Heinz, G. & Dietrich, W. Measurement of the diffusion coefficients of sparingly soluble gases in water. J. Geophys. Res. Ocean. 92, 10767–10776 (1987).

Vachon, D., Prairie, Y. T. & Cole, J. J. The relationship between near-surface turbulence and gas transfer velocity in freshwater systems and its implications for floating chamber measurements of gas exchange. Limnol. Oceanogr. 55, 1723–1732 (2010).

REVIEWER: Comment to line 176-177: Why did you use air concentrations from Mauna Loa Observatory and not closer stations such as Cherski or Barrow? What pCO₂ air concentration values were used to calculate the fluxes?

RESPONSE: The use of world medium CO₂ concentrations for gas transfer fluxes from water surfaces is the most standard approach in this field and we did so for consistency with numerous previous works. In this study we used pCO₂ = 402 ppm. It represents the average of 129 stations all over the world (World Meteorological Organization, 2009: Technical Report of Global Analysis Method for Major Greenhouse Gases by the World Data Center for Greenhouse Gases (Y. Tsutsumi, K. Mori, T. Hirahara, M. Ikegami and T.J.Conway). GAW Report No. 184 (WMO/TD-No. 1473), Geneva, https://www.wmo.int/pages/prog/arep/gaw/documents/TD_1473_ GAW184_web.pdf) taken from The World Data Centre for Greenhouse Gases (WDCGG) which is a World Data Centre (WDC) operated by the Japan Meteorological Agency (JMA) under the Global Atmosphere Watch (GAW) programme of the World Meteorological Organization (WMO). WDCGG (World Data Centre for Greenhouse Gases) (kishou.go.jp) https://gaw.kishou.go.jp

Specifically, for the year of this study (2016) the world monthly average CO₂ concentration is as following (https://community.wmo.int/wmo-greenhouse-gas-bulletins):

Thus, taking the period of this study, end of May - beginning of June, the average value is 402 ppm which was used in our calculations. This value is consistent with that directly measured at the Tiksi station in 2016: 404±0.9 ppm (Ivakhov et al., 2019)

Ivakhov, V. M., Paramonova, N. N., Privalov, V. I., Zinchenko, A. V., Loskutova,  M. A., Makshtas, A. P., Kustov, V. Y., Laurila, T., Aurela, M., and Asmi, E.: Atmospheric Concentration of Carbon Dioxide at Tiksi and Cape Baranov Stations in 2010–2017, Russian Meteorol. Hydrol., 44(4), 291–299, DOI: 10.3103/S1068373919040095, 2019.

REVIEWER: Comment to section 3.3: The discussion of the correlation of pCO2 with landscape parameters is not entirely consistent from the results to the conclusion. For example according to Table 3 pCO2 is correlated with riparian vegetation, but later on in the conclusion it is stated that it is correlated with the width of the riparian zone. So the riparian vegetation is a proxy for the width of the riparian zone? I note you did these correlations for the tributaries which gives interesting results, but how about for the main stem? It would be interesting to see since in the main stem pCO2 increases from south to north. The first sentence in the results section (L247-250) gives to understand that you did this but based on the captions of Table 3 and Figure 5 you only did the correlations with data from the tributaries- correct?

RESPONSE: The reviewer is totally correct. Yes, the riparian vegetation is a proxy for the width of the riparian zone. And yes, we run the landscape control correlations only for the tributaries. The size and huge diversity of the main stem watershed did not allow producing sufficient information on land cover of the Lena River and this can be a subject of another study.

REVIEWER: Comments to section 3.4: The calculations of the areal lotic C emission for the entire open water season are not entirely clear to me. Did you use different pCO2 and k values for the main stem and the tributaries? You state that 1 to 2 g C m-1 d-1 covers full variability of the large and small tributaries and the Lena River main channel (L291-293) but Tables 1-2 show that there is values lower and higher than this. Also L348 states that the range in the tributaries is (0.2 to 3.2 g C m-2 d-1) and L289 that the Aldan river had considerable higher emissions than Lena river main stem, how was this taken into consideration in the areal C emission calculation?

RESPONSE: This is very pertinent comment and we thank the reviewer for bringing it out. The k value for the main stem and tributaries was the same (4.464 m d^-1); it represents the average measured in 4 largest rivers of Western Siberia in June 2015 (Ob’, Pur, Pyakupur and Taz rivers, Karlsson et al., 2021). These 4 rivers are fairly representative for the Lena River and its tributaries, although the k value should be considered as highly conservative. The pCO₂ used for flux calculation (Table2) was directly measured in the full transect of the main stem and the tributaries. When providing the largest possible span of average emission values (1 to 2 g C m^-2 d^-1), we used the median values of the main stem and tributaries.

We further revised the calculations following the comments of this and other reviewers. For this, we explicitly took into account the water area of the main stem (43%) relative to the total Lena basin and we introduced the partial weight of emission from three largest tributaries (Aldan, Olekma and Vitim) according to their catchment surface areas (43, 12 and 14% of all sampled territory, respectively). We summed up the contribution of the Lena river main stem and the tributaries and we postulated the average emission from the main stem upstream of Aldan (1.25±0.30 g C m^-2 d^-1) as representative for the whole Lena River. This resulted to updated value of 1.65±0.5 g C m^-2 d^-1 which is within the range of 1 to 2 g C m^-2 d^-1 assessed previously. Note that this value is most likely underestimated because the emissions from the main stem downstream of Aldan are at least 10 % higher (Table 1, Fig. 1 B), and it could be so for the whole remaining part of the basin, not sampled in this work.  

REVIEWER: In terms of the k values used: You answered to the comment from reviewer 2 that you use the k values 4.46 m/d from Karlsson et al., 2021, this is not clear in L167-169. It reads as if you used the value 4.6 m/d based on Serikova et al., 2018 and Karlsson et al., 2021. You do then in L218 state that 4.46 m/d from Karlsson et al., 2021 is used. I would suggest changing L167-169 so this is consistent.

RESPONSE: Good point; thanks for catching this. We will correct all numbers accordingly. One single value of k (4.464) was used throughout all calculations.

REVIEWER: The dataset collected is very interesting and provides a lot of great insights. To me it is a bit of a missed opportunity to not utilise it more when estimating the areal lotic C emissions of the Lena basin. I would have liked to see how estimated areal CO2 emissions during the spring flood months, calculated with a k value corresponding the higher flow, a larger water surface area (281000 km2) and your slightly higher pCO2 values compare to the summer month, calculated with a k value corresponding the lower flow, a smaller water surface area (281000 km2 - 5022 km2) and previously published slightly lower pCO2 values. I note that you replied to reviewer 2 that decreasing the water surface area for summer reduced the result by less than 15% which is below the range of your uncertainty. It would be good to see this more explicitly in the publication, this is not clear in section 3.4. Is this what the number 0.67±0.15 (n = 47) (L281) indicates? It would also be interesting to know how much the Lena River main stem contributes to the areal CO2 emissions in contrast to the tributaries.

RESPONSE: We agree with a necessity of more rigorous and extensive estimation of aerial emissions. We added more elaborated calculations of aerial fluxes, taking into account the Lena River main stem (43% of the water area, as calculated in response to this request) and partial contribution of largest tributaries (according to their catchment areas), see our answer above.

We would like to note that while the summer period non-covered in this study (July-August and September) is characterized by slightly lower water surface areas, the water temperature and in-stream organic matter processing are higher than in spring and thus the overall CO₂ emissions during these months of the year might be sizably higher than those during the spring. We prefer to avoid extensive speculation on seasonaliy as it was not within the scope of the present work (a first snapshot assessment of C pattern in the Lena basin). However, we are confident that possible variations in water surface areas (including the contribution of very small streams, see section 4.2) do not exceed the range of uncertainties on emissions estimated in this study.

REVIEWER: Comment to lines 383-385: You compare your estimated C evasion to the DOC+DIC lateral export of the Lena River determined by other studies. Since you also collected DOC and DIC data I was wondering if how your data to compares to that of those studies?

RESPONSE: The lateral C export by the Lena River is based on regular (monthly to weekly) monitoring of dissolved C concentration and daily discharges at the terminal gauging station of Kusyur, some 700 km downstream the most northern sampling point of this study. The spatial variations of DOC and DIC concentrations obtained in this study cannot be used for calculating the lateral export. The reviewer is right when requesting to present a comparison of our data with those of other studies and we did so below.

Generally, the concentrations of DOC measured in the present study during the peak of the spring flood are at the highest range of previous assessments during summer baseflow (around 5 mg L^-1; range of 2 to 12 mg L^-1, Kuzmin et al., 2009; Cauwet and Sidorov, 1996; Lara et al., 1998; Lobbes et al., 2000; Kutscher et al., 2017).

The DIC concentration in the main stem during spring flood was generally lower than that reported during summer baseflow (around 10 mg L^-1; range 5 to 50 mg L^-1) but consistent with the values reported in Yakutsk during May and June period (7 to 20 mg L^-1, Sun et al., 2018). Sizable decrease in DIC concentration between the headwaters (first 500 km of the river) and its middle course was also consistent with the Alkalinity pattern reported in previous works during summer baseflow (Pipko et al., 2010; Semiletov et al., 2011). For the Lena river tributaries, the most comprehensive data set on major ions was acquired in July-August of 1991-1996 by Huh and Edmond’s group (Huh and Edmond, 1999; Huh et al., 1998a, b) and by Sun et al. (2018) in July 2012 and end of June 2013.  For most tributaries, the concentration of DIC was a factor of 2 to 5 lower during spring food compared to summer baseflow. This is highly expected result given strong dilution of carbonate-rich groundwaters feeding the river in spring high flow compared to summer low flow.

REVIEWER: In L243 I understood that you compared it to your own collected DOC and DIC data, or is this also a comparison with published results? In that case a reference in L243 would be good. In general there is a lack of further discussion of your DOC and DIC data.

RESPONSE: In this part of the text, we describe the spatial variability of DOC and DIC concentrations obtained in this study. We do not extensively discuss these data because there are no sizable diurnal variations. We did examine the DOC variability in the tributaries, and, in response to other reviewers, we tested a link between DIC (and pH) and CO₂ concentration in the main steam and tributaries. We did not find any sizable control and these results will be presented in the revised version. In response to this comment, extensive discussion of DOC and DIC results in comparison with literature data is presented in our response above and will be included in the revised manuscript.

REVIEWER: The grammar and sentence structuring throughout needs improving, this will greatly help with the overall cohesion and readability.

RESPONSE: We agree and will invest in revision of grammar and syntax of the text seeking a help of native English speaking scientist.

Reviewer: L 327 says there was no relationship but then in brackts says: (p < 0.05)

Response: the last term is not needed here

We will correct inconsistent use of units as noted by reviewer in the revised version.