# Carbon emission from the Lower Ob River floodplain during spring flood

Sergey N. Vorobyev, Yuri Kolesnichenko, Jan Karlsson, Oleg S. Pokrovsky

► To cite this version:

Sergey N. Vorobyev, Yuri Kolesnichenko, Jan Karlsson, Oleg S. Pokrovsky. Carbon emission from the Lower Ob River floodplain during spring flood. Science of the Total Environment, 2024, 954, pp.176294. 10.1016/j.scitotenv.2024.176294. insu-04831456

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# Carbon emission from the Lower Ob River floodplain during spring flood

Sergey N. Vorobyev<sup>a</sup>, Yuri Kolesnichenko<sup>a</sup>, Jan Karlsson<sup>b</sup>, Oleg S. Pokrovsky<sup>c,*</sup>

<figure><img src="image_3.png" /></figure>

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## HIGHLIGHTS

* Water coverage of the lower Ob River floodplain is 30 %.

* The main stem of Ob accounted for only 34 % and 18 % of CO₂ and CH₄ emissions.

* Floodplain lakes provided 59 % and 50 % of overall CO₂ and CH₄ emissions.

* Organic matter-rich flooded wetlands provide elevated pCO₂ in the main channel.

* Possible underestimation of C evasion from large rivers if ignoring floodplain water surfaces.

## GRAPHICAL ABSTRACT

<figure><img src="image_4.png" /></figure>

## ARTICLE INFO

Editor: Ashantha Goonetilleke

**Keywords:**

CO₂

Emission

Arctic

River

Permafrost

Siberia

## ABSTRACT

Carbon emission from Arctic rivers constitutes a positive feedback between the climate warming and C cycle. However, in case of rivers with extensive floodplains, the impacts of temporary water bodies and secondary channels on CO₂ exchange with atmosphere, compared to the main stem and tributaries, remain strongly understudied. In order to quantify the relative role of various water bodies of the Arctic river basin in the C cycle, the hydrochemical variables and greenhouse gases GHG concentrations and fluxes were measured within the floodplain of the largest Arctic River, Ob, in its low reaches located in the permafrost zone. These included the main stem, secondary channels, tributaries and floodplain lakes sampled over a 900 km north-south transect (25,736 km² of the main stem and adjacent floodplain area; 7893 km² water surface) during peak of spring flood (May 2023). In addition to main stem and tributaries, providing less than a half of overall C flux, floodplain lakes and secondary channels acted as important factor of C emission from the floodplain water surfaces. Multi-parametric statistical treatment of the data suggested two main processes of C emission from the Ob River floodplain waters: terrestrial organic matter-rich flooded wetlands (fens) provided elevated pCO₂, whereas the sites of possible groundwater discharge in the secondary channels decreased the CO₂ fluxes due to more alkaline environments, rich in labile metals and anionic elements.

<footnote><sup>a</sup> BIO-GEO-CLIM Laboratory, Tomsk State University, Tomsk, Russia</footnote>

<footnote><sup>b</sup> Climate Impacts Research Centre (CIRC), Department of Ecology and Environmental Science, Umeå University, Linnaeus väg 6, 901 87 Umeå, Sweden</footnote>

<footnote><sup>c</sup> Geosciences and Environment Toulouse, UMR 5563 CNRS, 14 Avenue Edouard Belin, 31400 Toulouse, France</footnote>

<footnote>* Corresponding author.
E-mail address: oleg.pokrovsky@get.omp.eu (O.S. Pokrovsky).</footnote>
Based on available high-resolution Landsat-8 images, which matched the period of field work, it was found that the total water coverage of the floodplain during spring 2023 was 30 % of overall territory, compared to 18 % during the baseflow. Based on chamber-measured CO₂ fluxes (1.56 ± 0.47 g C-CO₂ m⁻² d⁻¹), overall CO₂ emissions during 2 months of the spring flood from the entire Lower Ob River floodplain water surfaces including the main stem amounted to 0.73 ± 0.25 Tg C. Diffuse CH₄ flux represented <1 % of total C flux. The main stem of the Ob River accounted for 34 % and 18 % of CO₂ and CH₄ emissions, respectively, whereas the floodplain lakes provided 59 % and 50 % of CO₂ and CH₄ emission, respectively. Considering that the low reaches of the Ob River represent >70 % of total river basin floodplain, and that during some years, the entire floodplain can be covered by water, emissions from the river – if assessed solely from summer (July–August) measurements – can be at least 3 times underestimated. It is therefore important to account for extended water surface during high water levels on Arctic rivers when assessing global riverine C emissions.

# 1. Introduction

The response of Arctic rivers catchments to the ongoing climate change is crucially important for understanding the positive feedback relationships of these fragile, essentially pristine ecosystems to the global carbon (C) cycle. Most Arctic and subarctic watersheds are covered by organic-rich soils within the permafrost context, subjected to degradation and CO₂ emission to the atmosphere (Holmes et al., 2013; Hutchins et al., 2019). It has been recently recognized that in many permafrost-affected rivers, fluvial emission of CO₂ largely exceeds the lateral export of C (Serikova et al., 2018; Vorobyev et al., 2021, 2022; Krickov et al., 2024). This is especially important for lowland Arctic regions, where highly developed floodplain of large rivers (Ob, Kolyma, Mackenzie, Yukon) provide sizable water coverage during open water period of the year and may greatly contribute to CO₂ and CH₄ emissions (Denfeld et al., 2013; Striegl et al., 2012; Cunada et al., 2018; Krickov et al., 2021).

However, the information on C emissions from the floodplain of Arctic rivers remains very limited which does not allow integrating these potentially important hot spots of C cycle into global models of GHG exchange between the continental water surfaces and the atmosphere. Further, given that both temperature and precipitation are predicted to change strongly at high latitudes and influence riverine ecosystems thus providing a feedback onto the climate system (Mack et al., 2021), the change in hydrological regime of the floodplains may turn out to be a key factor in modification of the balance between C evasion and uptake. Despite the importance of Arctic floodplains in overall C balance of the river basins, there exist just a few relevant studies of the Mackenzie River (Cunada et al., 2018; Gareis and Lesack, 2020) and Kolyma main stem and tributaries (Denfeld et al., 2013; Castro-Morales et al., 2022a, 2022b), whereas the fluxes in other Arctic river floodplains remain unknown.

Among all Arctic rivers, Ob has the largest floodplain, second globally after the Amazon River (Vorobyev et al., 2015, 2019; Serikova et al., 2018). Thus, Krickov et al. (2021) assessed the emissions from Ob's middle course (permafrost-free) floodplain including temporary and permanent lakes and channels over a small (3 km²) test sites across the seasons and demonstrated sizable contribution (65 %) of the floodplain to the total (river+floodplain) C evasion. Recently, the size of the test site of the floodplain was extended to 1900 km² which allowed to demonstrate that ignoring the temporary flooded surfaces may underestimate the overall annual evasion during open water season by a factor of 3 to 10 (Vorobyev et al., 2024).

However, these studies were performed the middle course of the Ob River, which is permafrost-free and thus cannot serve as an analogue of the permafrost-affected, low reaches of this river. Other, snap-shot studies of emissions from the northern part of the Ob River (Karlsson et al., 2021) and its tributaries as well as other, permafrost-affected, rivers of the western Siberia lowland (Serikova et al., 2018; Vorobyev et al., 2022) dealt solely with the main stem without considering the water objects located within the floodplain. Overall, despite sizable research efforts on assessment of relative role of the Ob River main stem

and its floodplain water bodies in overall C emissions in the southern, permafrost-free part of the basin (Krickov et al., 2021; Vorobyev et al., 2024), the C emissions in the northern reaches of the Ob River remains unknown.

Among other Arctic rivers, channel and lake network of the Mackenzie River Floodplain were thoroughly studied in the past (Cunada et al., 2018; Gareis and Lesack, 2020). However, there was no quantitative assessment of the relative role in C evasion from the main stem, floodplain zone, secondary channel and tributaries within the Mackenzie River basin. Recently, fluvial emissions of CO₂ and CH₄ were assessed in the Ambolikha River floodplain, NE Siberia (Castro-Morales et al., 2022b).

Taken together, the information on C emissions from the floodplain of artic rivers remains very limited which does not allow integrating these potentially important hot spots of C cycle into global models of GHG exchange between the continental water surfaces and the atmosphere.

The present study attempts filling up the above mentioned gaps via measuring C emissions from the floodplain waters in the previously unknown permafrost-affected reaches of Ob, during peak of the spring flood. For this, ten times larger floodplain area, compared to previous work in permafrost-free zone (Vorobyev et al., 2024) has been chosen, which included both main stem and tributaries. The main objectives of this study were to (1) quantify the C concentration and emission pattern over the main stem, secondary channels, floodplain lakes and tributaries of the Ob River, (2) assess the water coverage of the floodplain in order to estimate the total aquatic C evasion of the territory, and (3) test possible environmental factors and hydrochemical parameters of the water column that can control CO₂ and CH₄ concentration in the main stem and water bodies of the floodplain.

# 2. Study site, materials and methods

## 2.1. Low reaches of the Ob River, its floodplain and flooded area assessment

The low reaches of the Ob River catchment, after Ob confluence with Irtysh, between Khanty-Mansiysk in the south and Salekhard in the north (70 % of the total river floodplain, Pokrovsky, 2016) are located within the boreal taiga and forest-tundra biome (Fig. 1). The lithology of the Ob River basin is represented by Quaternary clays, sands, and silts ranging in thickness from several meters to 200–250 m. These deposits have alluvial, lake-alluvial and aeolian origin south of 60°N and fluvial-glacial and lake-glacial origin north of 60°N. The older (i.e., Paleogene and Neogene) rocks are rarely exposed on the surface and are represented by sands, siltstones and clays, where carbonate material is present as concretions of individual shells.

The Lower Ob River flows in the permafrost-impacted zone: from sporadic/isolated in the south to discontinuous/continuous at the Ob River mouth. However, in the major part of the floodplain, the permafrost is absent due to high heat flux of the Ob River. The dominant soils are podzols in forest areas and histosols in peat bog regions. The climate
<figure><img src="image_5.png" /><figcaption>Fig. 1. Geographical context of the Ob River basin in western Siberia and the floodplain of the Lower Ob (encircled in red dot line).</figcaption></figure>

is semi-continental with a mean annual temperature of -0.1 °C and a mean annual precipitation of 580 mm. The width of the floodplain in this part of the Ob River is between 20 and 60 km. The flow velocity of the main channel is between 4 and 5 km h⁻¹ during the flood and 2 and 3 km h⁻¹ during the low flow period (Zemtsov et al., 2023).

The typification of the floodplain water bodies include permanent channels, lakes, and temporary flooded grasslands or meadows (Fig. 2). The flooded wetlands (fens) were not explicitly typified in this approach, although they are known to be important components of floodplain landscape of the Ob River middle course, especially during summer period (e.g., Vorobeyev et al., 2024). These wetlands were entirely covered by water and could not be unambiguously identified at the peak of spring flood in the Lower Ob River floodplain. A particularity of the low Ob region is that the mouth zones of some tributaries are represented by large (10–100 km²) terminal lakes on the floodplain, so-called “sors” (Fig. S1 A); the hydrochemistry of these sors is similar to that of tributaries rather than to the main channel. As such, the sors were typified as being different from other floodplain (oxbow) lakes, not related to incoming tributaries. Note that sores are always connected to the main river, even during winter baseflow. However, during baseflow, the water coverage of the sors is limited solely by the main channel of the tributary as shown in Fig. S1 B.

The floodplain forms a system of interconnected shallow ephemeral and permanent lakes and primary and secondary water channels which extend over 10–30 km in both direction from the main water channel. For this study, a large (25,736 km²) sector of the main stem and adjacent floodplain was selected. The flooded area was calculated for the entire floodplain from Khanty-Mansiysk till the Ob mouth. The Landsat-8 images of high resolution, layers 6, 5 and 4 were used for optimal delineation of water bodies. Ten images were selected exactly for the period of this expedition, from May 18 to May 25, 2023. In the year of 2023, one of the lowest water level and discharge (since 2008) have been recorded at the Belogorie gauging station (Fig. S2). In order to delineate the areas of baseflow period, the images of September (different years) were used, with typical water level of 390 to 400 cm. The month of

September is considered here as most representative baseflow open water period (Zemtsov et al., 2023).

The delineation of the Ob River watershed, tributaries and the floodplain was performed using Jaxa images and the topographical maps. Altogether, 105,000 polygons were distinguished (Fig. 2). The minimal size of the water body recognized by remote sensing was 225 m². Altogether, 90,000 of water objects were identified; 43,000 among them were larger than 1000 m² and 19,000 are larger than 5000 m². Therefore, the majority of inventoried water objects are small (< 1000 m²).

## 2.2. *In-situ* measurements and sampling design strategy

From May 18 to May 23, 2023, the boat trip started from the confluence of Ob and Irtysh (town of Khanty-Mansiysk), and included, first, 865 km downstream the Ob River main stem, while visiting all main floodplain lakes connected to the river and passing by numerous secondary channels. These are especially abundant over ca. 450 km length of the low Ob (so called “DvuObie”) where the river flows via two main channels (Bolshaya Ob and Malaya Ob) which are separated by ca 20 to 50 km distance on the floodplain. In the first part of the trip, 1206 km was covered, with an average speed of 30 km h⁻¹. There was a stop each ~50 to 100 km of the boat route which allowed 1) measuring CO₂ flux by two floating chambers over 30–40 min, and 2) sampling for GHG, major hydrochemical parameters, river suspended matter and total bacterial number of the main stem, secondary channels and floodplain lakes. The boat also moved 500–1500 m upstream of selected tributaries to record CO₂ concentrations for at least 1 h, and at the farthest upstream point from the tributary mouth, to measure CO₂ flux by chambers and sample for river hydrochemistry. During the night time, the pCO₂ was continuously monitored in the river water and the CO₂ flux was measured each 1–2 h by floating chambers (see below) on 5 sites (main stem, lake, tributary and flooded meadow) during stable anticyclone weather conditions. From the Salekhard town (Ob's mouth), the boat returned upstream the river till Khanty-Mansiysk (833 km, chiefly the
<figure><img src="image_6.png" /><figcaption>**Fig. 2.** Map of the Lower Ob River floodplain during spring flood (May 20–May 27, 2023) and typical baseflow (September, mean multi-annual average). The inserts present daily water level (in mm) of 2023 (dark green line) and range of variations over last 20 years (2002–2022, blue shaded) at the Khanty-Mansiysk and Salekhard gauging stations.</figcaption></figure>

main stem) over 3 days (May 25–28, 2023), while recording continuous $pCO_2$ in the river water and occasionally performing chamber measurements, both on the main stem and secondary channels.

## 2.3. $CO_2$ and $CH_4$ concentrations and fluxes

Surface water $CO_2$ concentration was measured in-situ by deploying a portable infrared gas analyzer (IRGA, GMT222 CARBOCAP® probe, Vaisala®; accuracy ±1.5 %) of two ranges (2000 and 10,000 ppm) as

described in previous work of our group on the Lena and Ket Rivers (Lim et al., 2022; Vorobyev et al., 2021). In brief, the probe was enclosed within a waterproof membrane made of expanded polytetrafluoro-ethylene (PTFE) sleeve that is permeable to $CO_2$ (Johnson et al., 2009). The sensor was placed into air-tight, bubble-free 5-L polypropylene equilibrator. Using a portable electric pump, the equilibrator was continuously fed by river water ($3 \text{ L min}^{-1}$) via a Teflon tube which was submerged 0.5 m below the water surface. A Campbell logger was connected to the system allowing continuous recording of the $CO_2$
concentration, water temperature and pressure. The membrane response time was <10 min (90 % of equilibrium value). The sensors were calibrated in the laboratory prior and after the boat trip, against standard gas mixtures (0 (zero control), 800, 3000, 8000 ppm). This provided linear regression with R² > 0.99). The sensors' drift was <0.1 % d⁻¹, and the overall error was equal to 6 %. Following calibration, post-measurement correction of the sensor output induced by changes in water temperature and barometric pressure was done by applying empirically derived coefficients following Johnson et al. (2009). These corrections never exceeded 5 % of the measured values. Further, during the cruise, atmospheric CO₂ was routinely measured with the probe as a check for its good functioning.

For CH₄ analyses, unfiltered water was sampled in 20-mL serum bottles and closed without air bubbles using vinyl stoppers and aluminum caps and immediately preserved by adding 2 mL of saturated KCl via a two-way needle system. Headspace was created in the laboratory and CH₄ concentrations were analyzed using a Bruker GC-456 gas chromatograph (GC) equipped with flame ionization and thermal conductivity detectors. Further details of CH₄ analyses are described elsewhere (Serikova et al., 2019; Vorobyev et al., 2021).

The CO₂ fluxes were measured via two floating 30-L volume plastic chambers equipped with non-dispersive infrared SenseAir CO₂ loggers (Bastviken et al., 2015), at each of the 4 sampling location of the main stem, 4 secondary channels, 6 floodplain lakes, 10 tributaries and 1 temporary flooded meadow on the river bank, following the procedure described in details in Serikova et al. (2019) and Krickov et al. (2021). The chambers were deployed in non-anchored (freely drifting) mode, which is the most reliable method for flux measurement (i.e., Lorke et al., 2015). The CO₂ accumulation rate inside the chamber was calculated by linear regression (r² > 0.95) for 30–60 min exposure time, with a time step of 5 min. It was verified that, for each measurement, the time – pCO₂ regression slope was constant over the entire deployment period, and that r² was higher than 0.90. Based on measured FCO₂ and CO₂ concentration in the river water, the gas transfer coefficient K_T using Fick's law was obtained (Eq. (1)):

$$FCO_2 = K_H \times K_T (C_{water} - C_{air}) \quad (1)$$

where K_H is Henry's constant corrected for temperature and pressure (mol L⁻¹ atm⁻¹) which also incorporates a pH-dependent chemical enhancement factor, C is the water CO₂ concentration, and Cₐir is the CO₂ concentration in the ambient air (421 ppmv, which is a world average value for May 2023; https://www.climate.gov).

For overall C emission balance calculation, continuous pCO₂ measurements from the boat were prioritized (594 data points) coupled with measured chamber-based transfer coefficient (K_T, Eq. (1)). This method adequately approximated the entire diversity of studied water bodies, such as large and small rivers including tributaries and channels as well as floodplain lakes. It also allowed homogeneous coverage of both lentic and lotic waters of the entire floodplain. For this, the average K_T value of two adjacent points of chamber measurements on each water body was used. For the main stem and long channels, the 50 to 100-km averaged K_T value was used.

In addition to in-situ chamber and pCO₂ measurements, the CO₂ flux was calculated from measured CO₂ concentration over the boat track using standard approaches based on relationship between gas transfer coefficient (k₆₀₀) and wind speed (Cole and Caraco, 1998):

$$k_{600} = 2.07 + 0.215 \cdot U_{10}^{1.7} \quad (2)$$

where U₁₀ is the wind speed taken at 10 m height, taken from nearest meteo-stations at the day of measurement. The k₆₀₀ value was normalized to Schmidt number at a given temperature (Wanninkhof, 1992) and converted into wind-based gas transfer velocity.

## 2.4. Chemical analyses of surface waters and data treatment

The dissolved oxygen (CellOx 325; accuracy of ±5 %), electrical conductivity (TetraCon 325; ±1.5 %), and water temperature (±0.2 °C) were measured in-situ at 20–30 cm depth using a WTW 3320 Multi-meter. The pH was measured using WTW multimeter via combined Schott glass electrode calibrated with NIST buffer solutions (4.01, 6.86 and 9.18 at 25 °C), with an uncertainty of 0.01 pH units. The water was sampled in pre-cleaned polypropylene bottle from 20 to 30 cm depth in the middle of the river and immediately filtered through disposable single-use sterile Sartorius filter units (0.45 µm pore size). The first 20 mL of filtrate was discarded. The dissolved organic and inorganic carbon (DOC and DIC, respectively) were determined by a Shimadzu TOC-VSCN Analyzer (Kyoto, Japan) with an uncertainty of 3 % and a detection limit of 0.1 mg L⁻¹. Blanks of MilliQ water passed through the filters demonstrated negligible release of DOC from the filter material. For calculating SUVA₂₅₄, ultraviolet absorbance at 254 nm (UV₂₅₄) was measured using a 10-mm quartz cuvette on a Bruker CARY-50 UV-VIS spectrophotometer.

To preserve the filtered samples for nutrient and organic acid analyses, a portable cryoconservator filled by liquid nitrogen (−40 °C) was used, into which the polypropylene vials (2.5 mL) were immersed immediately after on-site filtration. Fifteen carboxylic acids (quinate, lactate, acetate, propionate, formate, butyrate, galacturonate, glutarate, malate, tartrate, maleate, oxalate, fumarate, phthalate and citrate) and main inorganic anions (F⁻, Br⁻, Cl⁻, SO₄²⁻, NO₃⁻, NO₂⁻ and PO₄³⁻) were measured by high-performance ionic chromatography (Dionex Ics-5000+) with an uncertainty of 2 %. An in-house standard for organic acid analysis and two ISO standards (ISO 10304-1 and ISO 10304-2) for inorganic anion analysis was used. The certified reference materials Ion-915 and Ion-964 were used to verify the accuracy of analyses; the reference material measured concentrations were within 10 % of certified values. Quantification limits were equal to 0.05 mg L⁻¹ for Cl⁻, 0.001 mg L⁻¹ for F⁻, Br⁻, PO₄³⁻, 0.01 mg L⁻¹ for NO₃⁻, SO₄²⁻ and 0.002 mg L⁻¹ for quinate, lactate, acetate, propionate, formate, butyrate, galacturonate, glutarate, malate, tartrate, maleate, oxalate, fumarate, phthalate and citrate.

Major and trace elements were analyzed in filtered and on-site acidified solutions by inductively coupled plasma mass spectrometry (ICP MS) using an Agilent iCap Triple Quadrupole (TQ). About 3 µg L⁻¹ of In and Re were added as internal standards along with 3 various external standards, which were placed each 20 experimental samples. Detection limits of trace elements (TE) were determined as 3 times the blank signal. The typical uncertainty for elemental concentration measurements was 5 % at 1–1000 µg L⁻¹ and 10 % at 0.001–0.1 µg L⁻¹. The Milli-Q blanks were routinely processed to monitor for any potential contamination introduced by our sampling and handling procedures. The SLRS-6 (Riverine Water Reference Material for Trace Metals certified by the National Research Council of Canada) was analyzed every 20 samples to check for accuracy and reproducibility of analyses. All certified elements exhibited good agreement between replicated measurements of SLRS-6 and the certified values (with relative difference < 10–15 %). The concentrations of particulate C and N (POC and PON, respectively) were determined via filtration of freshly collected river water (1–2L) on-site (at the river bank or in the boat) with pre-weighted GFF filters (47 mm, 0.45 µm) and Nalgene 250-mL polystyrene filtration units using a Mityvac® manual vacuum pump. The C and N concentration in the particulate suspended material (PSM) was measured using catalytic combustion with Cu–O at 900 °C with an uncertainty of ≤0.5 % using Thermo Flash 2000 CN Analyzer at EcoLab, Toulouse. The samples were analyzed before and after 1:1 HCl treatment to distinguish between total and inorganic C; however the ratio of Cₐrganic: Cₐcarbonate in RSM was always above 20 and the contribution of carbonate C to total C in the RSM was equal in average 0.3 ± 0.3 % (2 s.d., n = 30).

Bacterial and algal cell concentrations were measured after sample fixation in glutaraldehyde, by a flow cytometry (Guava® EasyCyteTM
systems, Merck). The water sample was filtered through sterilized 40 µm nylon mesh, diluted two times by sterile Milli-Q water, and 150 µL of the sample was marked with 10 µL SYBR GREEN solution (10,000×, Merck). Particles were identified as cells based on green fluorescence and forward scatter (Marie et al., 1999), following the recent optimization of this procedure for algae and bacteria in organic-rich, peatland-related waters (Hamard et al., 2021; Sytiuk et al., 2022).

The Pearson rank order correlation coefficient ($R_{Pearson}$, $p < 0.05$) was used to determine the relationship between CO₂ concentrations and emission fluxes and main landscape parameters of the Ob River floodplain water bodies, as well as other potential drivers such as DIC, DOC, SUVA, POC, PON and microbial number. To assess the difference in major hydrochemical parameters among different aquatic systems of the floodplain, a t-criterion at $p = 0.95$ was used. The hydrochemical data were also treated via multiparametric statistical approaches, which included a Principal Component Analysis using a variance estimation method, which allowed to test the effect of various environmental factors (water temperature, bacterial number) and minor and major components of the river and lake water column on dissolved and gaseous C pattern including CO₂ emissions. Hierarchical Cluster Analysis (HCA) helped to distinguish the groups of inter-connected components, including both major and trace elements, nutrients and dissolved gases. All graphics and figures were created using MS Excel 2010, MS Visio Professional 2016 and GS Grapher 11 package. Statistical treatment was performed using STATISTICA-7 (http://www.statsoft.com).

# 3. Results

## 3.1. Water coverage of the Lower Ob River floodplain by remote sensing

The peak of annual discharge in 2023 occurred in the end of May-mid June in the north (Salekhard) and in the middle of May-beginning of June in the south (Khanty-Mansiysk), being equal to 22,000 and 32,000 m³ s⁻¹, respectively. In August, when much lower area of the floodplain is covered by water (Fig. 2), the discharge and the water level was 1.5 times lower (14,000 and 22,000 m³ s⁻¹, respectively). Note that the year 2023 was among the driest over past decades as illustrated by lowest water level and the discharge measured at the Belogorie gauging station located 20 km downstream of Khanty-Mansiysk (Fig. S2 of the Supplement).

The overall water-covered area of the Ob River floodplain during spring flood in May–June 2023 between Khanty-Mansiysk and Salekhard (25,736 km² of land) was calculated to be 7893 km², i.e., 30 % of the study area (Table 1; Fig. 2). This is sizably higher than the water coverage of the studied area during baseflow (4600 km², or 18 % of the floodplain). The main contribution to the total water area coverage was provided by the Ob River main stem, its secondary channels and tributaries (73 % in spring; 64 % during baseflow). The floodplain lakes accounted for 26 % of all floodplain water coverage during spring flood 2023 and 36 % during average baseflow (Table 1).

The highest water coverage of the floodplain was observed north of 63°N (Figs. 2, 3). There was strongly pronounced flooding of the tributaries' mouth zones (Fig. S1 A of the Supplement), where the size of sores increased by a factor of 2 to 3 during the spring flood compared to

the baseflow period. In the end of summer – early autumn, the sores were solely represented by water channels connecting the tributaries and the main river (Fig. S1 B). However, the water flow always occurred from the sores to the main river. There was no sizable difference in water coverage between right and left tributaries mouth zones.

## 3.2. Greenhouse gases in the main stem, floodplain lakes and secondary channels of the Lower Ob River

The concentrations of organic and inorganic carbon, greenhouse gases and CO₂ emission fluxes were separately averaged for the Ob River main stem, secondary channels, floodplain lakes and Ob's tributaries (Table 2). Mean values of continuous pCO₂ measurements from the boat were averaged for each type of the water body of the floodplain (Table S1). There was no significant (t-test) difference in main hydrochemical parameters and C concentration and emission pattern between the Ob River main stem and secondary channels (Table S2). The differences between main stem and tributaries was observed for pH, E.C., DOC and pCO₂, while differences between the main steam and lakes were detected for pH and CH₄ concentrations. The tributaries and lakes also differed in E.C. and CH₄ concentrations. The chamber-measured CO₂ fluxes did not exhibit significant (at $p = 0.05$) difference between any of the studied water bodies of the floodplain including the main stem.

Continuous measurements of CO₂ partial pressure in the Ob River main stem and secondary channels over 1200 km distance between Khanty-Mansiysk and Salekhard demonstrated sizable variations between 500 and 2500 µatm, with slightly higher values in the south compared to the north (Figs. 4 and 5). Elevated pCO₂ values were associated with some tributaries and floodplain lakes. Occasionally, extremely low concentrations in secondary channels connecting the main stem and sores were found; the concentration of dissolved CO₂ decreased by a factor of 5 to 10 compared to the main channel. Spatial variations of pCO₂ within each individual water body of the floodplain lakes, secondary channels, tributaries as well as across the main stem were within 20 to 30 % and not systematic (left vs right bank or mid-stream), as illustrated in Fig. S3. The CH₄ partial pressure was low (1–5 µatm in the main stem, secondary channels, tributaries and floodplain lakes without any systematic spatial pattern). This is much lower than typical pCH₄ in the Kolyma River (26–33 µatm, Castro-Morales et al., 2022a). Only the stagnant water bodies of the Ob River floodplain exhibited ~50 µatm of pCH₄, comparable to that in NE Siberian fluvial waters. Chamber-measured CO₂ emissions together with CO₂ concentration yielded gas transfer velocity ($K_T$) with generally weak variations among the main stem, tributaries and floodplain lakes (0.9 to 2.1 m d⁻¹; Table 2). Note that the CO₂ transfer velocity obtained in this study is comparable to those reported for other Arctic floodplain rivers (e.g., Castro-Morales et al., 2022b).

Discrete, chamber-measured emissions were comparable among tributaries, main stem, and floodplain lakes (Table 2). The lowest emissions were measured in small secondary channels. Continuous FCO₂ from the water bodies of the floodplain were calculated based on continuous pCO₂ data along the boat trek (594 data points) and chamber-based $K_T$ (Eq. (1)) for each type of aquatic landscape (Fig. 6). These values ranged from 0.5 to 2.5 g C m⁻² d⁻¹, being the highest in the

<table><caption>**Table 1**

Quantitative assessment of water coverage in the low Ob River floodplain (25,793 km²).</caption><thead><tr><th>Object</th><th>Water area, km²<br>(May 20–May 31, 2023)</th><th>Water area, km²<br>(Mean multi-annual baseflow over past 15 years, September)</th></tr></thead><tbody><tr><td>Ob's tributaries on the floodplain</td><td>334</td><td>227</td></tr><tr><td>Ob main stem</td><td>2187</td><td>1808</td></tr><tr><td>Secondary channels</td><td>887</td><td>394</td></tr><tr><td>Floodplain lakes, connected</td><td>569</td><td>63</td></tr><tr><td>Floodplain lakes, not connected</td><td>2089</td><td>1670</td></tr><tr><td>Sores (lakes of tributary mouth zones)</td><td>1827</td><td>428</td></tr><tr><td>All water objects</td><td>7893 (30.6 % of floodplain)</td><td>4600 (18 % of floodplain)</td></tr></tbody></table>
<figure><img src="image_7.png" /><figcaption>Fig. 3. Real-time typification of water objects of the low Ob River floodplain, during the period of expedition (May 20–31, 2023).</figcaption></figure>

tributaries, and approximately the same in the main stem and floodplain lakes. Of note are the highest emissions of both CO₂ and CH₄ from a temporary flooded meadow (Table 2). However, such ultra-shallow water objects were not sufficiently sampled in the present study due

to very difficult ground access to flooded meadows, isolated from the main interconnected hydrological network of the floodplain.

The C emissions (> 99 % CO₂; < 1 % CH₄) from the Ob River main and secondary channels, lakes and tributaries assessed in this study
<caption>**Table 2**</caption>

Measured water temperature, pH, CO₂ flux, DOC, DIC, anions, nutrients and trace metal concentrations, CO₂ and CH₄ partial pressures in the Lower Ob River main stem, secondary channels, floodplain lakes and tributaries (mean ± s.d.; (n) is number of measurements). The CO₂ flux was obtained with chamber-based gas transfer velocity K_T (Eq. (1)).

<table><thead><tr><th>Parameter</th><th>Main stem of Ob, n = 4</th><th>Secondary channels, n = 4</th><th>Tributaires, n = 10</th><th>Floodplain lakes, n = 6</th><th>Flooded meadow n = 1</th></tr></thead><tbody><tr><td>CH₄, µatm</td><td>1.67 ± 0.91</td><td>2.80 ± 0.41</td><td>4.50 ± 0.95</td><td>1.93 ± 0.50</td><td>48.8</td></tr><tr><td>CO₂, µatm</td><td>1440 ± 75</td><td>879 ± 315</td><td>1813 ± 134</td><td>1645 ± 510</td><td>2330</td></tr><tr><td>FCO₂, g C m⁻² d⁻¹</td><td>1.89 ± 0.16</td><td>0.20 ± 0.27</td><td>2.28 ± 0.15</td><td>1.61 ± 0.69</td><td>3.47</td></tr><tr><td>K_T, m d⁻¹ (chamber-based)</td><td>2.1 ± 1.7</td><td>0.9 ± 2.5</td><td>1.8 ± 0.9</td><td>1.9 ± 1.4</td><td>3.8</td></tr><tr><td>K_T, m d⁻¹ (wind-based)</td><td>1.55 ± 0.02</td><td>1.64 ± 0.02</td><td>1.57 ± 0.08</td><td>1.82 ± 0.05</td><td>2.3</td></tr><tr><td>FCH₄, g C m⁻² d⁻¹</td><td>0.0045 ± 0.0033</td><td>0.010 ± 0.0024</td><td>0.022 ± 0.0045</td><td>0.006 ± 0.0004</td><td>0.372</td></tr><tr><td>T<sub>water</sub> °C</td><td>9.1 ± 0.21</td><td>10.4 ± 0.3</td><td>9.1 ± 1.1</td><td>12.7 ± 0.6</td><td>18.6</td></tr><tr><td>pH</td><td>7.50 ± 0.17</td><td>6.21 ± 0.11</td><td>6.49 ± 0.29</td><td>6.69 ± 0.22</td><td>6.26</td></tr><tr><td>O₂, mg L⁻¹</td><td>11.6 ± 0.26</td><td>11.6 ± 0.44</td><td>11.0 ± 0.29</td><td>10.9 ± 0.44</td><td>9.4</td></tr><tr><td>E.C., µS cm⁻¹</td><td>175 ± 12</td><td>154 ± 7.6</td><td>42.9 ± 6.5</td><td>148 ± 35</td><td>119</td></tr><tr><td>Bacterial cell L⁻¹</td><td>(2.5 ± 1.6) × 10⁵</td><td>(2.7 ± 0.9) × 10⁵</td><td>(1.8 ± 2.6) × 10⁵</td><td>(0.9 ± 0.8) × 10⁵</td><td>4.0 × 10⁴</td></tr><tr><td>Algal cell L⁻¹</td><td>(3.9 ± 2.5) × 10⁵</td><td>(3.8 ± 1.4) × 10⁵</td><td>(1.4 ± 1.5) × 10⁵</td><td>(1.5 ± 1.2) × 10⁵</td><td>6.5 × 10⁴</td></tr><tr><td>Ca, mg L⁻¹</td><td>18.2 ± 1.9</td><td>17.8 ± 3.2</td><td>5.7 ± 2.8</td><td>12.6 ± 3.8</td><td>15</td></tr><tr><td>Mg, mg L⁻¹</td><td>5.22 ± 0.5</td><td>5.75 ± 0.59</td><td>2.79 ± 0.88</td><td>4.36 ± 1.0</td><td>4.8</td></tr><tr><td>Al, µg L⁻¹</td><td>24.5 ± 5.95</td><td>30.0 ± 1.6</td><td>118 ± 24</td><td>42.6 ± 20.4</td><td>2.92</td></tr><tr><td>Fe, µg L⁻¹</td><td>335 ± 63</td><td>380 ± 35</td><td>799 ± 167</td><td>506 ± 63</td><td>791</td></tr><tr><td>Mn, µg L⁻¹</td><td>30.2 ± 9.6</td><td>49 ± 25</td><td>112 ± 28</td><td>36 ± 9</td><td>235</td></tr><tr><td>Cl, mg L⁻¹</td><td>5.97 ± 0.757</td><td>6.62 ± 1.200</td><td>3.28 ± 2.178</td><td>5.611 ± 1.869</td><td>7.9</td></tr><tr><td>SO₄, mg L⁻¹</td><td>4.3 ± 0.66</td><td>3.9 ± 0.66</td><td>1.93 ± 1.0</td><td>3.2 ± 0.95</td><td>8.0</td></tr><tr><td>DIC, mg L⁻¹</td><td>10.7 ± 3.8</td><td>15.9 ± 2.3</td><td>4.3 ± 2.0</td><td>9.7 ± 2.6</td><td>1.18</td></tr><tr><td>DOC, mg L⁻¹</td><td>6.7 ± 0.78</td><td>9.1 ± 1.2</td><td>13 ± 1.6</td><td>10.1 ± 2.0</td><td>10.6</td></tr><tr><td>POC, mg L⁻¹</td><td>1.3 ± 0.25</td><td>2.5 ± 0.656</td><td>1.17 ± 0.19</td><td>1.34 ± 0.202</td><td>1.48</td></tr><tr><td>SUVA<sub>254</sub></td><td>3.83 ± 0.09</td><td>3.90 ± 0.07</td><td>4.35 ± 0.15</td><td>4.04 ± 0.116</td><td>3.6</td></tr><tr><td>P-PO₄, mg L⁻¹</td><td>0.062 ± 0.001</td><td>0.061 ± 0.002</td><td>0.083 ± 0.009</td><td>0.083 ± 0.017</td><td>0.063</td></tr><tr><td>N-NO₂, mg L⁻¹</td><td>0.031 ± 0.0001</td><td>0.030 ± 0.0001</td><td>0.029 ± 0.0001</td><td>0.031 ± 0.001</td><td>n.a.</td></tr><tr><td>N-NO₃, mg L⁻¹</td><td>0.419 ± 0.044</td><td>0.365 ± 0.047</td><td>0.305 ± 0.012</td><td>0.297 ± 0.014</td><td>0.277</td></tr></tbody></table>

Footnote: E.C. is electrical conductivity.

(0.2–2.4 g C m⁻² d⁻¹) can be compared to previous results in Siberian rivers obtained during open water period (June to August). Our data are comparable to fluxes reported by Serikova et al. (2018) for the low reaches of the other two mid-sized rivers of the WSL, Taz and Pur, in summer and spring (1.2 to 1.6 g C m⁻² d⁻¹), small rivers of permafrost-affected part of the WSL (0.5 to 3.0 g C m⁻² d⁻¹, Krickov et al., 2024), the main stem of the Taz river in July (1.0 ± 0.4 g C m⁻² d⁻¹, Vorobyev et al., 2022), fluvial waters of the Indigirka lowland (1.8 ± 1.1 g C m⁻² d⁻¹, Dean et al., 2020), waters of the Kolyma River (0.35 g C m⁻² d⁻¹ in the main stem; Denfeld et al., 2013) and its tributary Ambolikha River (0.97 g C m⁻² d⁻¹, Castro-Morales et al., 2022b), the Ob River main channel in summer (1.3 ± 0.14 g C m⁻² d⁻¹ in the permafrost-free zone, Karlsson et al., 2021), and the Lena River during spring flood (0.8–1.7 g C m⁻² d⁻¹, Vorobyev et al., 2021).

The CO₂ flux varied by a factor of 2 to 3 between day and night in several water bodies of the floodplain (Fig. S4 of the Supplement). The differences in flux values (typically each 1–2 h, between 8 pm and 7–9 am) between day and night period were not systematic, and did not follow the temporal pattern CO₂ concentration. For example, the sors and flooded meadow demonstrated the range of pCO₂ variation between 1400 and 2000 µatm, with maximal pCO₂ in the first half of the night, whereas there were non-systematic variations of FCO₂ between the beginning and the end of the night. For these reasons, and given extremely short duration of night in late spring – early summer at these latitudes, the diel flux variations were not explicitly accounted for when upscaling (see Section 3.4) the C evasion from the low Ob floodplain.

### 3.3. The impact of the water chemistry on C emission from the water surfaces

To test the existence of possible internal factors controlling C emission from the floodplain water surfaces, Pearson correlations between GHG parameters and the main physico-chemical parameters of the water column which are likely to control CO₂ and CH₄ pattern such as DOC quality, DIC, O₂, pH, E.C., POC, microbial number, macro- and micro-

nutrients were run (Table S3 of the Supplement). Chamber-measured CO₂ fluxes positively correlated with SUVA and average molecular weight of DOM and strongly negatively correlated with pH, E.C., DIC, major and trace anions and labile neutral molecules, alkaline and alkaline-earth metals and uranyl concentration. The pCH₄ correlated with sulfate, Li and some nutrients (K, P, Mn, Rb). Concerning the hydrochemical parameters of the water column, two main groups of solutes were distinguished in the waters of the Ob River floodplain depending on their correlation with either DOC (lithogenic trace elements) or Electric Conductivity (labile monovalent and divalent cations and anions). This correlation pattern was further supported by multi-parametric statistics, which confirmed the presence of two main group of solutes, identified by correlation analyses described above (Fig. S5 and S6 of the Supplement). Concentration of CO₂, DOC, its aromaticity and humification degree as well as concentrations of lithogenic low-solubility elements constituted the first factor of PCA (34.8 %) and 1st cluster in HCA. The second PCA factor (29 %) acted negatively on pH, E. C., all labile components of the river water such as major and trace anions/neutral molecules, anionic micro-nutrients (V, Se, Mo), alkalis and alkaline earth metals, and uranyl. These solutes constituted the second cluster of the HCA.

### 3.4. Upscaling of C emission from the Ob River floodplain

Spring-time total C emissions (> 99 % CO₂, < 1 % CH₄) from the floodplain of the low Ob River were assessed based on total water coverage of the floodplain during two months of the spring flood (7893 km², Table 1) and the partial contribution of main channel, tributaries, secondary channels and lakes (Table 2), which allowed to account for flux and area of specific types of water systems for the entire territory of Ob low reaches floodplain (25,793 km²). This provided average area-weighted emissions of 1.56 ± 0.47 g C m⁻² d⁻¹. The total emission from water surfaces of the low Ob floodplain is 0.734 ± 0.25 Tg of C-CO₂ during 60 days of spring flood (Table 3). One should note the importance of spatial variations in individual water bodies on total error in the flux
<figure><img src="image_8.png" /><figcaption>**Fig. 4.** Continuous CO₂ concentration over the boat course from Khanty-Mansiysk to Salekhard (downstream, 20–27.05.2023 and upstream, 29–31.05.2023). Symbols represent discrete sampling of the main stem, secondary channels, floodplain lakes and tributaries. Grey numbers illustrate measured pCO₂ (µatm) during the boat trip.</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>**Fig. 5.** Continuous CO₂ concentration in water measured during spring flood (May 20–May 27, 2023) on the Ob River main stem, secondary channels, floodplain lakes and tributaries. The distance is by water, from Khanty-Mansiysk to Salekhard (see Fig. 4).</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>**Fig. 6.** Continuous CO₂ emission fluxes, calculated based on in-situ pCO₂ (Fig. 5) and experimental gas transfer coefficients from discrete chamber measurements on the Ob River main stem, secondary channels, floodplain lakes and tributaries over the distance by water (Khanty-Mansiysk to Salekhard) measured on May 20–May 27, 2023. See Fig. 4 for geographic positions of sampling points. The green circle shows temporary flooded meadow (puddle 20 cm depth), representative for large shallow water-covered surfaces of the floodplain covered by grass (Carex) vegetation.</figcaption></figure>

calculation. The present work did not explicitly address spatial variations of pCO₂ across the main river channel, and in several cases illustrated in Fig. S3 these variations were between 20 and 30 %. Although these uncertainties are implicitly accounted for in the mean value of emissions, the main stem contributed only 30 % to overall CO₂ flux. As a result, spatial variations across the river could not sizably modify the uncertainty on the total value. In contrast, floodplain lakes that provided the largest contribution to overall C emissions (59 %) exhibited much higher uncertainties on the fluxes (i.e., ± 42 %), which largely exceeded the spatial variations within each individual water body.

Further uncertainties on the global value may stem from spatial and temporal variations of emissions from the main stem and various water bodies of the floodplain. The uncertainties on water coverage of the floodplain are especially difficult to assess. Note that in some years, much higher area of the floodplain is covered by water (at least × 2–3 times higher; Vorobeyev et al., 2015, 2024; Pokrovsky, 2016) which

<caption>**Table 3**</caption>

Total C-CO₂ and C-CH₄ emissions (mean ± s.d.) from floodplain water bodies, over 2 months of the spring flood. Tributaries* include only the part of tributaries that belongs to the Ob River floodplain. Lakes** include connected, non-connected lakes and sors (tributary mouth zones).

<table><thead><tr><th></th><th>FCO<sub>2</sub>, Tg</th><th>FCH<sub>4</sub>, Tg</th></tr></thead><tbody><tr><td>Main stem</td><td>0.248 ± 0.055</td><td>0.00059 ± 0.00043</td></tr><tr><td>Tributaries*</td><td>0.0457 ± 0.0031</td><td>0.00044 ± 0.00009</td></tr><tr><td>Secondary channels</td><td>0.0106 ± 0.14</td><td>0.00053 ± 0.0001</td></tr><tr><td>Lakes**</td><td>0.433 ± 0.186</td><td>0.0016 ± 0.0011</td></tr><tr><td>Total</td><td>0.738 ± 0.25</td><td>0.0032 ± 0.0017</td></tr></tbody></table>

would increase the overall emission value. The methane (C-CH₄) emission (0.0032 ± 0.0017 Tg) over 2 month of the flood is <1 % of that of C-CO₂ (Table 3). Partial contribution of different water objects of the floodplain to overall emission (Fig. 7) demonstrates that floodplain lakes (including sores) and main stem provide by far the largest share in both CO₂ and CH₄ emissions (59 % and 34 % for CO₂; 50 % and 18 % for CH₄). These upscaling assessments should be taken with caution, given sizable uncertainties (30 % and 50 % for CO₂ and CH₄, respectively), associated with global values.

Assuming the same emissions during the remaining four months of the base flow open water period (July to October), when the water coverage of the Ob floodplain between Khanty-Mansiysk and Salekhard amounts to 4600 km² (Table 1), this adds 0.86 Tg C. Therefore, specific land-area normalized aquatic emissions of C from the low Ob floodplain (1.59 Tg C-CO₂) over 6 month of open water period equal to 62 ± 9 t C km² land y⁻¹. This is more than an order of magnitude higher than the typical annual DOC+DIC yield of the entire Ob River catchment (3.5 ± 0.1 t C km² land y⁻¹; Vorobeyev et al., 2019). These assessments are highly conservative and likely strongly underestimate the total emissions. However, regardless of the absolute values, which can strongly vary from one year to another, even at the minimal water coverage of the floodplain such as in 2023, the contribution of main stem to the total emission did not exceed 40 % for a large transect of the river (900 km long, 25,793 km² of the floodplain).
C-CO₂ flux, Tg over 2 month

<figure><img src="image_11.png" /></figure>

■ Main stem

■ Secondary channels

■ Lakes

C-CH₄ flux, Tg

<figure><img src="image_12.png" /><figcaption>Fig. 7. Partial contribution of different aquatic landscapes to the upscaled flux of CO₂ and CH₄ from the floodplain during 60 days of the spring flood.</figcaption></figure>

# 4. Discussion

## 4.1. Magnitude of carbon emission from the low Ob River floodplain

The present study reports unprecedented coverage of the floodplain in the permafrost-affected Ob River basin. Previously, Krickov et al. (2021) assessed the emissions from temporary and permanent lakes and channels over a small (3 km²) test site of the floodplain in middle course (permafrost-free) part of the Ob River, across the seasons and demonstrated sizable contribution (65 %) of the floodplain to the total (river+floodplain) C emission. These authors reported the C emission ranged from 0 to 0.8 g C m⁻² d⁻¹ for the Ob main channel and from -2 to 5 g C m⁻² d⁻¹ for the floodplain (lakes and secondary channels; Krickov et al., 2021). They noted huge difference in C emissions between spring flood (0–1 g C m⁻² d⁻¹ for all water objects of the floodplain) and summer baseflow (10–18 g C m⁻² d⁻¹ in permanent channels; 2–6 g C m⁻² d⁻¹ in temporary channels and floodplain lakes). At present, there is no measurements of the low Ob River floodplain during summer baseflow, but, assuming certain similarity with permafrost-free, Ob middle course zone, one can expect several times higher areal emissions than the global average (1.6 g C m⁻² d⁻¹) assessed in this work for the spring flood.

Recently, the size of the test site of floodplain was extended to 1900 km², which allowed to demonstrate that ignoring the temporary flooded surfaces may underestimate the overall annual emission by a factor of 3 to 10 (Vorobyev et al., 2024). However, these studies were performed the middle course of the Ob River, which is permafrost-free and thus cannot serve as an analogue of the permafrost-affected, low reaches of

this river. Other studies of emissions from rivers of the western Siberia lowland (Serikova et al., 2018; Vorobyev et al., 2022) dealt solely with the main stem without considering the water objects located within the floodplain. Among other Arctic rivers, channel and lake network of the Mackenzie River were studied in the past (Cunada et al., 2018; Gareis and Lesack, 2020), however, there was no quantitative assessment of the relative role in C evasion of the main stem, floodplain zone, secondary channel and tributaries within any Arctic river basin.

The Mackenzie Delta channel network during maximal flood in May exhibited a flux of 0.07 to 0.18 g C-CO₂ m⁻² d⁻¹ (Gareis and Lesack, 2020) which is sizably lower than chamber-based values measured in the present study for the Ob River main stem and secondary channels. With its 13,000 km² of land area, the Mackenzie Delta emitted only 0.002–0.005 Tg C-CO₂ during full month of May (Gareis and Lesack, 2020), which is two orders of magnitude lower than the entire low Ob floodplain (25,736 km²) assessed in the present work (0.73 Tg C-CO₂ for the two months of the spring flood). Similarly, evasion of CH₄ for the low Ob River floodplain over two months of spring flood amounted to 3.2 ± 1.7 Gg C-CH₄ which is an order of magnitude higher than the range reported in the Mackenzie Delta (0.086 to 0.433 Gg; Gareis and Lesack, 2020). This clearly demonstrates an importance of the Ob River floodplain in total arctic/subarctic C emissions from water surfaces.

## 4.2. Possible mechanisms controlling CO₂ pattern in the Lower Ob River floodplain

The first important result is that, despite sizable variations of CO₂ concentrations and emissions at relatively short distances between the main stem, secondary channels and connected floodplain lakes, there was no south-north trend in the CO₂ pattern. Further, rather constant pattern of organic and inorganic solutes– DOC, DIC, SUVA₂₅₄, nutrients and microbial number across the south-north gradient of the Ob River main stem, channels (and tributaries) was observed. In agreement with previous observations of a mid-size WSL river (Taz; Vorobyev et al., 2022) and across small and medium rivers of the WSL (Krickov et al., 2023, 2024), this suggests high landscape-level homogeneity of external factors responsible for CO₂ emission and DOC transport in the floodplain of the Ob River during the spring flood.

Similar to previous observations on fluvial organic-rich waters in permafrost-dominated high-latitude regions of northern Eurasia (Vorobyev et al., 2021, 2022), no systematic diel FCO₂ variation in the Ob River secondary channels, lakes, flooded meadow and a tributary was revealed (Fig. S4). Although CO₂ production by aquatic metabolism can contribute up to 30 % of CO₂ evasion from streams and rivers in the temperate zone (e.g., Hotchkiss et al., 2015), the diel productivity / respiration cycle could not be assessed solely from pCO₂ measurements in the present study and further work on O₂ and chlorophyll *a* monitoring on a single site coupled with incubation experiments are needed. Note, however, that rather short residence time of rapid floodwaters on the floodplain (Vorobyev et al., 2024) may overshadow the on-going productivity and respiration. This is consistent with much higher emissions from floodplain waters in July–August compared to those in May–June, as documented in the permafrost-free zone (Krickov et al., 2021).

Pairwise correlations and multiparametric statistical treatment allowed testing possible links of GHG concentration and emission pattern to hydrochemical parameters of the water column. Positive correlations of pCO₂ with DOC concentration and DOM aromaticity corresponded to maximal CO₂ concentrations in humic, low-mineralized lakes and sores, exhibiting lowest connection with groundwater. Negative correlations of pCO₂ with O₂ are common in Siberian waters and likely reflect a combination of internal metabolism (gross primary production and respiration balance) and CO₂ production in partially anoxic riparian sediments (Lim et al., 2022; Krickov et al., 2023, 2024; Vorobyev et al., 2024). Negative correlations of pCO₂ to pH and concentrations of DIC, labile anions and cations, originating from deep
underground water sources (e.g., Pokrovsky et al., 2020), reflected lower emissions in groundwater-connected floodplain sites such as some secondary channels. In contrast, positive correlations of $FCO_2$ with SUVA and WAMW reflect the highest emissions in flooded fens, as it is recently established in permafrost-free zone of the Ob's River floodplain (Vorobyev et al., 2024). Finally, positive link to some redox-sensitive nutrients (P, Mn, Fe) may indicate $CO_2$ production in partially anoxic zones of the floodplain. The latter was also evidenced in the middle course of the Ob floodplain (permafrost-free zone) across different seasons (Krickov et al., 2021). However, it was not possible to relate the magnitude of $pCO_2$ and C emissions to specific watershed features of a given tributary, such as land cover parameters, ground vegetation, wetland coverage or the degree of underground feeding. Most of these features were “obscured” at high water level of the massive spring flood period. The $CH_4$ correlation with nutrients (K, P, Mn, Rb) reflected the highest concentration of this gas in grass-affected temporary water bodies, such as flooded meadows. Indeed, these elements are known to be present in high concentrations in grass leachates such as Carex (Lim et al., 2024).

Across all types of water bodies of the floodplain, two main groups of solutes were evidenced from pairwise (Pearson) correlation analysis: (1) insoluble, low mobility (lithogenic) trace elements – mostly trivalent and tetravalent hydrolysates ($TE^{3+}$, $TE^{4+}$), which were positively correlated with DOC and (2) labile, high mobility major and trace anions (neutral molecules), alkaline and alkaline-earth metals, which were positively correlated with DIC. These two groups were further confirmed by multi-parametric statistics: they were affected by first and second factor of the PCA treatment and constituted two distinct clusters of the HCA, respectively. The first PCA factor (F1) acted on $CO_2$ concentration but also on DOC, its aromaticity and humification and concentration of lithogenic trace elements, suggesting a control of C-rich floodplain lakes containing aromatic and humic DOM on $CO_2$ accumulation in the floodplain waters. The presence of $CO_2$ and lithogenic trace elements (such as $TE^{3+}$, $TE^{4+}$) in F1 stems from the DOM-controlled, colloidal transport of these insoluble elements (e.g., Kolesnichenko et al., 2021; Krickov et al., 2019). The second PCA factor (F2) negatively acted on $CO_2$ flux, reflecting possible discharge of alkaline groundwater at the floodplain. The F2 positively acted on SUVA of the DOM-rich floodplain lakes and tributaries, which was accompanied by elevated $CO_2$ emissions. Overall, correlation analyses and multi-parametric statistics suggested two main processes controlling carbon emission from the Ob River floodplain waters: terrestrial DOM-rich flooded fens provided elevated $CO_2$ concentrations, whereas the sites of possible groundwater discharge decreased the fluxes due to more alkaline environments, rich in labile alkali, alkaline metals and anionic elements. However, the interactions among different physical, chemical and biological factors controlling carbon source, sinks and migration processes, as well as interconnection among all water bodies of the floodplain do not allow further in-depth analysis of C emission pattern due to rather small number of field measurements at the scale of each type of the water body.

## 5. Conclusions

Towards filling the gap in knowledge of fluvial C emissions from large artic rivers, the low reach, permafrost-affected, 900 km S – N transect of the Ob River has been studied during the peak spring flood period. Via combining remote sensing for real-time water coverage and continuous $CO_2$ and discrete floating chamber measurements and hydrochemical analyses, overall C emissions from the main stem, secondary channels, floodplain lakes and tributaries were quantified. Possible drivers of $CO_2$ emissions (DOC, SUVA) were identified and the areal emissions were upscaled to the entire territory of the Lower Ob River floodplain (25,736 km² surface area). Considering ensemble of the water bodies of the Ob River floodplain, positive relationships of $CO_2$ concentration with DOC, aromaticity/hydrophobicity, and some

nutrients (P, Mn, Fe) were found. This suggests the importance of $CO_2$ generation in flooded wetlands, humic lakes and tributaries and partially anoxic riparian zones. The C-$CO_2$ emission for the entire low Ob floodplain (7893 km² of water) amounted to 0.73 Tg C over two months of spring flood and likely achieve 1.6 Tg C for the entire open water period. On a land-area basis, this is more than an order of magnitude higher than the annual yield of dissolved C by the whole Ob River catchment. However, C emissions can be much higher at the end of the flood, considering an analogy with middle course, permafrost-free zone of the Ob River floodplain. This calls a need for seasonally resolved measurements of $CO_2$ emissions in the low Ob River floodplain during summer period. Of particulate importance is a comparative assessment of C release from land and water bodies after floodwater recede.

## CRediT authorship contribution statement

**Sergey N. Vorobyev:** Writing – original draft, Methodology, Investigation. **Yuri Kolesnichenko:** Visualization, Software, Methodology.

**Jan Karlsson:** Writing – review & editing, Validation. **Oleg S. Pokrovsky:** Writing – original draft, Supervision, Resources, Project administration, Investigation, Funding acquisition, Conceptualization.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Data availability

Primary hydrochemical data of sampled sites together with C concentration and emission pattern are available from the Mendeley Database repository (Pokrovsky, and Vorobyev, 2024): Pokrovsky, O.S., Vorobyev, S., 2024. Hydrochemistry of the Ob River floodplain, low reaches May 2023", Mendeley Data, V1, https://data.mendeley.com/datasets/72v7z226pb/1.

## Acknowledgements

Main support for this work was from the RSF project 24-17-00300 "Role of lakes in carbon balance of the boreal zone, western Siberia". OP was partially supported by TSU Programme Priority-2030 and project PEACE of PEPR FairCarboN ANR-22-PEXF-0011. L. Perez-Serrano is thanked for help in bacterial number measurements.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.scitotenv.2024.176294.

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