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Article

Seasonal and Spatial Variations of δ13CDIC Values in the Mun River, Northeast Thailand

by
Xiaoqiang Li
,
Guilin Han
* and
Man Liu
Institute of Earth Sciences, China University of Geosciences (Beijing), Beijing 100083, China
*
Author to whom correspondence should be addressed.
Water 2022, 14(9), 1340; https://doi.org/10.3390/w14091340
Submission received: 16 March 2022 / Revised: 15 April 2022 / Accepted: 19 April 2022 / Published: 20 April 2022
(This article belongs to the Section Hydrology)
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Abstract

:
As an important part of the global carbon cycle, dissolved inorganic carbon (DIC) concentration and its stable carbon isotopic composition (δ13CDIC) have been used to constrain the sources of DIC in rivers. In this study, we systematically investigated the water chemistry, DIC contents, and δ13CDIC values in a tropical agricultural river in northeast Thailand. The water temperature ranged from 20.3 to 31.3 °C, and water pH values ranged from 6.4 to 8.4, with seasonal variations. Based on the major ion compositions, the hydro-chemical type of the Mun River water was a unique Na–Ca–Cl–HCO3 type, controlled by evaporite and silicate weathering. Seasonal variation of DIC concentrations and its carbon isotopic composition was obvious; DIC and δ13CDIC were significantly lower in the wet season (135 to 3146 μmol/L and −31.0‰ to −7.0‰) compared to the dry season (185 to 5897 μmol/L and −19.6‰ to −2.7‰). A high level of 12C-enriched DIC/CO2 from soil respiration and organic matter oxidation may cause the low pH values, δ13CDIC values, and high partial pressure of CO2 (pCO2) in the middle and lower reaches during the wet/rainy season compared to the dry season. This may be responsible for the seasonal and spatial variations of DIC concentrations and δ13CDIC values in the Mun River. According to the relationship between pCO2 and δ13CDIC values, CO2 outgassing may be more significant in the dry season, due to the greater influx of groundwater with higher pCO2 levels; and the rapid CO2 diffusion into the atmosphere will continuously increase the δ13CDIC values and decrease pCO2 levels. These results show that riverine biologic effects and CO2 outgassing play important roles in the DIC and δ13CDIC evolution of this typical agriculturally-dominated watershed.

1. Introduction

Carbon is one of the basic elements of life and is widely distributed in the ocean, atmosphere, rocks, and living organisms [1,2,3]. The global carbon cycle plays a key role in maintaining the stability of the earth’s climate system [4,5,6,7,8]. Rivers are the main channel for transporting terrigenous matters to the ocean [9,10,11,12,13,14,15,16,17,18,19,20,21], and the estimated annual carbon transport is about 1 Pg C, while about 0.43 Pg C is dissolved inorganic carbon (DIC) [22,23,24]. Dissolved inorganic carbon in rivers includes bicarbonate, CO32−, H2CO3, and dissolved CO2 [25], and the relative proportion of these chemical species depends on temperature and pH [26]. Riverine DIC is mainly derived from atmospheric CO2, soil-respiration CO2, and carbonate weathering [27,28,29,30,31,32,33]. Previous studies have shown that HCO3− is the main component of DIC and influenced by both natural and anthropogenic processes [31], such as mineral dissolution [25]; bio-respiration/degradation and photosynthesis [34,35]; human activities (e.g., sewage inputs) [36,37,38]; CO2 outgassing and equilibrium exchange processes [39,40,41,42]; and other factors (hydrology, geology, and climate) [33,43,44]. At present, the stable carbon isotopes of DIC (δ13CDIC) are widely used to study the origin and evolution of DIC in rivers [26,27,29,42,45], because of the great difference of δ13C in different carbon reservoirs.
Soil respiration usually causes high CO2 contents and the partial pressure of CO2 (pCO2, 1000 to 100,000 μatm) in the soil profile, and the differences in CO2 contents between soil and atmosphere drives gas diffusion [22]. The initial δ13C of soil CO2 is related to the type of plants (C3 or C4 plants) and CO2 diffusion rate [27]. The δ13C of soil CO2 from respiration in C3 plants, which dominate globally, is about −24‰~−30‰ [25]. The soil CO2 can dissolve in rain water and then enters rivers, and dissolved CO2 is hydrated and ionized into HCO3− and H+, which contributed to mineral dissolution [27]. Recently, studies found that riverine δ13CDIC values are connected to many processes, sush as the reaction between carbonate minerals (e.g., CaCO3) and soil CO2 [27,29,43,45,46,47,48]. However, groundwater with high pCO2 levels being discharged into rivers will cause obviously high pCO2 values in river water compared to the atmosphere (~400 μatm) [39,40,49]; thus, riverine CO2 evasion to the atmosphere is unavoidable and this process will cause a strong diffusion fractionation, with an increasing of δ13CDIC values and decreases of DIC concentrations [50]. Besides the above diffusional fractionation, which can shift the DIC concentrations and δ13CDIC values, the carbon isotopic equilibrium exchange between the riverine DIC and atmospheric CO2 has a similar effect in the increasing of δ13CDIC values [26]. In addition, the riverine DIC and δ13CDIC values are also affected by biological activity, such as bio-respiration, the degradation of the organic carbon (OC), and photosynthesis in river water [35], and the in-river respiration of phytoplankton results in the enrichment of 12C in DIC [51]. All these biogeochemistry processes can change the DIC contents and the carbon isotopic compositions in river waters. Therefore, the relationship between δ13CDIC and soil respiration, carbonate mineral dissolution, aquatic biologic effect, CO2 outgassing, and the isotopic equilibrium exchange should be identified and studied; but, currently, they are not.
The Mun River, as a major tributary of the Mekong River, is located in northeast Thailand. Local industrial development and long-term agricultural activities can release a lot of organic carbon into river water [52,53,54,55,56,57], and affect the DIC and δ13CDIC evolutions at watershed scale. Our previous research reported the major ions and δ13CDIC values in the Mun River under base flow conditions (dry season) [58]. In this study, we provide more data in the wet season, to study the spatial and temporal variations in both the DIC concentration and δ13CDIC values under complex biogeochemical processes. The aim of this research was to investigate the sources of DIC and the controlling factors of δ13CDIC in a typical agriculturally-dominated watershed.

2. Material and Methods

2.1. Mun River Watershed

The geomorphology, geology, and samples sites were described in detail by [54,59,60,61]. Briefly, the Mun-chi River watershed is located in northeast Thailand (14° N to 18° N and 101° E to 106° E) (Figure 1), and the drainage area covers roughly 120,000 km2 [62]. The Chi River is the largest tributary of Mun River, and is located in the north of the watershed and joins the Mun River in the lower reaches. The study watershed has an elevation of 170~1000 m. As shown in the lithology map of the Mun River watershed (Figure 1), clastic sedimentary rocks with evaporites, together with few igneous rocks (granites, basalts, and rhyolite), spread in most areas within the watershed [63], while the permian limestone (less than 1% of the total area) is mainly distributed in the headwater. Paddy fields, in which extensive agriculture activities occur, cover most areas (70.8%) of the watershed, while forests (13.5%) cover the southern part of the watershed [58]. The local climate is mainly controlled by the southwest monsoon (wet/rainy season, mid-May to mid-October) and northeast monsoon (dry season, mid-October to mid-February). The average annual rainfall amount is around 1308 mm, and increases progressively along the river flow direction [64]. The rainy season accounts for about 85% of the annual rainfall [58].

2.2. Sampling and Analysis

The river water samples were collected from 56 sites along the Mun-chi River and one adjacent sample S57 in the main stream of the Mekong River in August of 2017 and March of 2018. The distribution of each sampling site is presented in Figure 1. In the field, samples were collected approximately 50 cm below the surface, at the center of the river, and were kept in pre-cleaned high-density polyethylene (HDPE) bottles. A handheld multi-parameter water meter (YSI Inc., Yellow Springs, OH, USA) was used to measure in situ pH, temperature, total dissolved solids (TDS), and dissolved oxygen (DO) of river water samples, and the alkalinity was determined by pure HCl titration. After filtration via a membrane of 0.22 μm (Millipore), major cations (Na+, K+, Mg2+, and Ca2+) and SiO2 were analyzed through ICP-OES (Optima 5300DV, PerkinElmer Inc., Waltham, MA, USA) with a precision of ±3%, the anions (Cl−, SO42−, and NO3−) were measured via ionic chromatography (Dionex 1100, Sunnyvale, CA, USA) with a precision of ±5% in IGSNRR, Chinese Academy of Sciences (CAS).
The DIC compositions, calcite saturation indexes (CSI), and pCO2 values of river water samples were calculated using the program PHREEQC version 2.2 and are shown in Supplementary Table S1. The samples for δ13CDIC analyses were kept in polyethylene bottles and HgCl2 was added to avoid the decomposition of organic matters. All bottles were stored under frozen and dark conditions, for further measurements. The analysis method of δ13CDIC values was described in Atekwana and Krishnamurthy [65]. About 10 mL of sample was injected with a syringe into glass bottles that already contained 1 mL 85% H3PO4 and magnetic stir bars. After reaction, the CO2 was extracted to flow through an N2 cooled ethanol trap in a vacuum line to separate H2O, the CO2 was, finally, kept under cryogenic conditions in a tube. The measurement of isotopic compositions was completed using a Finigan MAT 252 mass spectrometer in the state key laboratory of environmental geochemistry in Guiyang. The results were converted to the δ notation and refer to PDB in per mil: δ13C (‰) = [(13C/12C)sample/(13C/12C)VPDB − 1] × 1000. The routine precision of δ13C was within ±0.1‰, based on the repeated measurement of standards NBS19, GBW04416, and GBW04417.

2.3. Statistical and Spatial Analysis

In this study, ArcGIS 10.2 was used to show the lithology and sampling sites of the Mun River watershed. A Piper diagram was made using the software, AqQa (RockWare Inc., CO, USA). The software, Adobe Illustrator 2018, was used to make the figures.

3. Results and Discussion

3.1. General Characteristics of Water Chemistry

The variation range and mean value of temperature, pH, TDS, and major ion concentration of the river water samples in the Mun River are shown in Table 1, and full data is listed in the Supplementary Table S1. River water samples displayed a temperature from 20.3 °C to 31.3 °C (Table 1) and were weakly acidic to alkaline, with a pH of 6.4–8.4 (mean value 7.0) in the wet season, which are similar to the values of samples collected in March 2018 (dry season). Dissolved oxygen (DO) ranged from 3.0 mg/L to 7.1 mg/L during the wet season, and from 3.3 mg/L to 11.8 mg/L during the dry season. The ranges of TDS (9.0–998.0 mg/L) in the wet season were lower than in the dry season (15.0–1502 mg/L), and gradually increased at first and then decreased along the mainstream. The precipitation amount of the wet season represented about 85% of annual rainfall (1308 mm) [66,67]. At the outlet (S56) of the river, the TDS was 44.0 mg/L and 161 mg/L in the wet and dry seasons, respectively [58], and showed a lower TDS and cation concentrations in the wet season due to the heavy rainfall. An ionic balance was also applied for the river water samples; that is, the total cation concentration (TZ+ = Na+ + K+ + Mg2+ + Ca2+, in meq/L) and total anion concentration (TZ− = Cl− + NO3− + SO42− + HCO3−, in meq/L) of river water presented good ion balances (R2 = 0.99). The normalized ionic charge balance ([TZ+−TZ−]/TZ+) was less than 10% for both seasons (Table S1), suggesting the data were reliable and the effect of the organic matter was negligible.
As for the major ions in the river water, Na+ was the most abundant cation, with concentrations from 1.0 to 369.6 mg/L (Table 1), contributing 9–87% of the total cations (based on meq/L values), with an average value of 52% (Figure 2); and Ca2+ was second to Na+, varying from 1.1 to 62.4 mg/L and 15 to 78% (average as 30%), the sum of Na+ and Ca2+ represented 65–90% of the total cations. While, Mg2+ and K+ ranged from 0.3 to 14.0 mg/L and from 0.8 to 12.2 mg/L, respectively, and showed a small contribution to total cation concentrations. The order of anions was HCO3− > Cl− > SO42− > NO3−. Cl− and HCO3− were the dominant anions (Figure 2), accounting for more than 80% of the total anions for most samples. In comparison, the concentrations of SO42− and NO3− were lower, only accounting for 1–18% and 0–5% of the total anions. Dissolved SiO2 contents varied between 1.1 and 21.3 mg/L, with an average value of 8.3 mg/L, higher than the range of major world rivers (3.9~6.1 mg/L) [69,70]. A previous study showed that the dissolved organic carbon (DOC) ranged from 1.7 mg/L to 40.1 mg/L during the wet season and from 2.6 mg/L to 17.2 mg/L during the dry season in the Mun River [52,53].
In the Mun River, the major ion concentrations in the mainstream exhibited very different spatial variations between upstream and downstream, and generally displayed a trend of first increasing and then decreasing, especially Na+, Cl−, and HCO3−, which is similar to the variation trend of TDS. The concentrations of TDS and ion concentrations measured at the source sites (Table S1) with low water flow rate were significantly lower than those of the whole mainstream. The upper reaches have a relatively dry climate, with low annual precipitation [64], and the evaporation amount obviously exceeds the rainfall, which makes the water body evaporate and concentrated to a certain extent [66]. In addition, the inflow of the tributary Khlang river with high TDS value is also an important factor. In the process of transition from the upstream to the downstream, the increased precipitation finally leads to a gradual decline of ion concentrations in the river water. The massive evaporite (NaCl) sedimentary rock distribution in such a watershed creates advantageous conditions for evaporite weathering [71]. Generally, the weathering rate of evaporite is much higher than other rocks in the same situations, implying that the Na+ and Cl− are derived from evaporite sedimentary rock weathering and exported into the Mun River water [63]; far more than the K+ that originated from the weathering of siliciclastic sedimentary rock. Therefore, the hydrochemical type of Mun-chi River water is a unique Na–Ca–Cl–HCO3 type, controlled by evaporite and silicate weathering [63].

3.2. DIC and δ13CDIC in River Water

In the river water, DIC concentrations displayed a wide range, from 134.9 to 3145.5 μmol/L (mean 808.9 μmol/L) in the wet season, and from 185 to 5897 μmol/L (mean 1376 μmol/L) in the dry season, which is significantly lower than the groundwater DIC (1669 to 17,551 μmol/L, mean 8793 μmol/L) [58]. At pH 6.1–8.5 of river water, HCO3− was the main component of DIC, comprising about 37.7−97.9% (mean 82.7%) of DIC in the Mun River, while the HCO3−/DIC ratios were less than 50% when pH <6.4, and the rest was dissolved CO2 [68]. The partial pressure of CO2 (pCO2) in river water, for most samples, was above the atmospheric level (400 μatm) (Figure 3a), from 326 to 7312 μatm in the wet season, and from 283 to 30,150 μatm in the dry season. Only two sample (S2 collected in August of 2017 and S33 collected in March of 2018) had pCO2 values lower than 400 μatm. The CSI values ranged from −4.0 to 0.9, with a mean value of −1.6 and median value of −1.6, respectively, showing that most river water samples were undersaturated with respect to calcite, and only samples collected from the upstream tributary, the Takhong River, showed calcite supersaturation, due to its higher Ca2+ and HCO3− and lower temperature. The δ13CDIC values of river water ranged from −31.0‰ to −2.7‰, with seasonal variations. The δ13CDIC had large ranges, and lower values in the wet season (−31.0‰ to −7.0‰, mean −19.1‰) than the dry season (−19.6‰ to −2.7‰, mean −10.8‰) (Figure 3c,d). The δ13CDIC values of the groundwater samples varied from −19.0‰ to −9.3‰, with a mean value of −16.1‰ (n = 10) [58].

4. Discussion

4.1. Seasonal and Spatial Variations of DIC and δ13CDIC

The seasonal variation of pH and DIC concentration in river water was obvious in the mainstream (Figure 4a,b), and DIC and pH were significantly higher in the dry season, especially in the middle and lower reaches. The highest DIC concentrations were found in the upper reaches for both seasons, and this may be attributed to the influx of higher HCO3− concentrations from the upstream tributary, the Takhong River, which drains carbonate rocks. The lower DIC contents in the wet season also show that heavy rainfall during the rainy season could dilute DIC in river water, and this effect was more obvious downstream, with higher precipitation in the rainy season [64]. On the contrary, pCO2 showed a weak seasonal dependence, being slightly higher in the wet/rainy season. The pCO2 in river water depends on the influx of soil CO2, bio-respiration, and photosynthesis [29]. A previous study showed that soil CO2 supply may be the main controlling factor for pCO2 levels in river water [27].
The δ13CDIC values changed seasonally, which cannot be explained by a simple dilution effects [27]. Lower δ13CDIC values were also found in the wet season in a karst river [27], and other rivers such as Canada’s Cordillera River [73] and the Strengbach Catchment [74]. It is believed that two key factors control the seasonal fluctuation of δ13CDIC values in rivers, one is the greater soil CO2 produced due to the temperature in the wet season, and another is the large influx of soil CO2 to river water because of heavy rainfall. Although the water temperature difference is small between different seasons in the Mun River, this observation does not necessarily deny the idea that the more soil CO2 were produced due to the higher temperature in the wet season. The water temperatures may not necessarily reflect the temperature at the production of soil CO2. A southwest monsoon brings about 85% of the annual rainfall in the wet season [66,67]; thus, this will promote the reaction of rainwater with silicate minerals in the soil [27]. This process is always accompanied by a consumption of soil CO2 and produces negative δ13CDIC values in the soil solution. Therefore, a lot of 12C-enriched DIC/CO2 from soil may infiltrate into the river water during the wet/rainy season, causing low pH values, δ13CDIC values, and high pCO2 in river water, especially in the middle and lower reaches. This may be responsible for the seasonal and spatial variations of DIC concentrations and δ13CDIC values in the Mun River.

4.2. Chemical Weathering and the δ13CDIC in River Water

Dissolved inorganic carbon in river water generally comes from four sources: air CO2, soil CO2 from microbiologic activities, plant respiration, and carbonate weathering [28,29,30,31,32,33]. The CO2 from air and soil can dissolve in rain water and then enters rivers, or forms carbonic acid to participate in weathering [27]. However, considering the high pCO2 of soil and low pH (<5.6) of local rain water [67], the contribution of air CO2 is negligible. Moreover, some studies found that riverine Ca2+/Na+, Mg2+/Na+ and HCO3−/Na+ molar ratios can reflect the lithological control of riverine major ions [17,75]. Different original end-members (silicates, carbonates, and evaporites) were estimated using solute chemistry data on small rivers draining one primary lithology [17]. As shown in Figure 5a,b, a three-end-member mixing model cannot account for all data variability of the Mun River; thus, new end-members (shown in diamonds) were proposed to explain all the river samples in the Mun River [71]. Most of the samples collected from the Mun River fall in two end-member intervals of evaporites and silicates, and only samples from the upstream tributary, Takhong River, showed a slight carbonate contribution, which implies the dominant role of halite dissolution and silicate weathering; and this is consistent with the geological background of sedimentary rock containing evaporites in this area [63,76,77]. The dissolution process of evaporates has no effect on riverine DIC concentrations; therefore, the influx of soil CO2 should be the primary source of DIC in the river water.
The δ13C of soil CO2 depends on many factors, including plant types (C3 or C4 plants), the rate of CO2 respiration, depth, and so on [27,50]. Our previous study showed that the δ13C of soil organic carbon (SOC) in the study area were concentrated from −28.4‰ to −22.3‰ [55], within the range of typical C3 plants (−30~−24‰) [25]. The δ13C of soil CO2 is derived primarily from the δ13C of soil carbon [25]. Considering an isotopic enrichment (13C-enriced of ~+4.4‰) because of molecular diffusion of CO2 in soil [50,78], the δ13C of soil CO2 should be −24~−18‰ in our study area. This mean DIC, derived from silicate weathering by soil CO2, will cause δ13CDIC values of −16‰ ~ −10‰ with the equilibrium fractionation (enriched about 8‰) exchange between soil CO2 and DIC under an open system [50]. Possible silicate mineral weathering reactions are shown in Figure 5c, all water samples are close to point (0.1, 0.5); thus, reflecting a relatively complex mixing of multiple reactions [71], such as Ca–Mg-bearing silicate weathering by H2CO3 and/or H2SO4 [71]. The δ13CDIC values of river water samples ranged from −31.0‰ to −2.7‰. For δ13CDIC values much lower −16‰ or higher than −10‰ in the Mun River (Figure 5d), other processes or mechanisms may be responsible.

4.3. δ13 CDIC Decline Induced by Biologic Causes

The riverine DIC derived from in-stream respiration and degradation of organic carbon can decline δ13CDIC values [27]. A previous study observed a positive relationship between DOC concentrations and δ13CDIC values in a typical small karstic catchment [27], reflecting the effect of organic degradation on δ13CDIC values. However, in the Mun River, there is a general negative relationship between δ13CDIC values and DOC concentrations in the wet season (Figure 6a), but not in the dry season. Compared to the dry season, the DOC concentrations of river water are higher in the wet season, especially in the lower reaches, and intense agricultural activities may be the cause of DOC overloading (>15 mg/L) [52]; and this may indicate that the riverine biological processes were influenced by anthropogenic activities. Moreover, the high rainfall in the wet season can bring more terrestrial OC into rivers, and then influence the riverine DIC concentrations through OC decomposition [79]. The degradation and respiration processes produce organic acids and CO2, resulting in low pH and high CO2/DIC ratios in river waters (Figure 4a and Figure 6b).
The bio-degradation/respiration is also accompanied by the consumption of O2 [80,81]; as shown in Figure 6c, LogpCO2 shows a negative relationship with DO concentrations for both seasons in river waters, suggesting that pCO2 levels can be influenced by CO2 derived from respiration or/and degradation of organic carbon [82,83]. The in-stream respiration and/or degradation will result in a decline in δ13CDIC values [51], which was generally observed in the Mun River (Figure 6d), when excluding some samples collected in the lower reaches during the wet season, due to obvious anthropogenic inputs [52]. Therefore, the aquatic biologic processes and anthropogenic activities play important roles in the pCO2 level and δ13CDIC values in the study area, especially in the lower reaches, during the wet season.

4.4. CO2 Outgassing and Equilibrium Exchange Processes

The pCO2 levels in river water are higher than the atmospheric pCO2 ~400 μatm (Figure 7), and may be partly consumed because of silicate weathering by H2CO3 and CO2 outgassing [27], the latter will lead to an increasing of δ13CDIC values, because of the faster diffusion coefficient of 12C in CO2 [31]. Therefore, the δ13CDIC values will increase δ13CDIC values with a pCO2 decrease, due to the diffusional fractionation [50]. As shown in Figure 7, δ13CDIC did not show a clear relationship with pCO2 in the Mun River water, which may indicate complex biogeochemical processes. Nevertheless, the δ13CDIC have higher values in the wet season (−19.6‰ to −2.7‰, mean −10.8‰) than the wet season (−31.0‰ to −7.0‰, mean −19.1‰), and this can be attributed to the significant effect of CO2 outgassing on riverine δ13CDIC during the base flow season [50]. After the DIC flux from groundwater with higher pCO2 levels is added to river water in the dry season [58], the rapid diffusional fractionation of CO2 between river water and atmosphere will increase the δ13CDIC values and decrease pCO2 levels [31], which can explain the high δ13CDIC and low pCO2 in the mainstream during the dry season. Compared to the dry season, the samples collected in the wet season were far above the fractionation trend, due to the significant biologic effect in rivers. In addition to the diffusional fractionation, the carbon isotopic equilibrium exchange between the riverine DIC and atmosphere CO2 also increase riverine δ13CDIC values [26]; although, with a limited contribution of about 1~2‰ [31].

5. Conclusions

We systematically investigated the water chemistry, DIC concentrations, and δ13CDIC values in the Mun River watershed during different seasons. River water samples displayed a temperature range from 20.3 to 31.3 °C, and were weakly acidic to alkaline, with a pH of 6.4–8.4 (mean value 7.0). Na+ was the most abundant cation, contributing 10–77% of the total cations (based on meq/L values); and Ca2+ was second to Na+; the sum of Na+ and Ca2+ represented 65–90% of the total cations. Mg2+ and K+ showed a small contribution to total cation concentration. The order of anions was HCO3− > Cl− > SO42− > NO3−. Cl− and HCO3− were the dominant anions, accounting for more than 80% of the total anions for most samples. Therefore, the hydrochemical type of the Mun River water is a unique Na–Ca–Cl–HCO3 type, controlled by evaporite and silicate weathering. The massive evaporite (NaCl) sedimentary rock distribution in such a watershed creates advantageous conditions for evaporite weathering.
Considering the high pCO2 of soil and low pH (<5.6) of local rain water and limited carbonate outcrops in the study watershed, the influx of soil CO2 should be the primary source of DIC in the study river. Seasonal variations of DIC concentrations and δ13CDIC values of river water were obvious in the mainstream, and DIC and δ13CDIC were significantly lower in the wet season, especially in the middle and lower reaches. A southwest monsoon brings about 85% of annual precipitation in the wet season, a large amount of 12C-enriched DIC/CO2 from soil respiration and organic matter oxidation may infiltrate into the river water during the wet/rainy season, causing low pH values, δ13CDIC values and high pCO2 in river water, especially in the middle and lower reaches. This may be responsible for the seasonal and spatial variations of DIC concentrations and δ13CDIC values in the Mun River mainstream. While CO2 outgassing is more significant in the dry season, due to the greater influx of groundwater with higher pCO2 levels, the rapid diffusional fractionation of CO2 between river water and atmosphere will increase the δ13CDIC values and decrease pCO2 levels, which can explain the high δ13CDIC and low pCO2 in the mainstream during the dry season.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w14091340/s1. Table S1: Data sets for sampling locations, water parameters, chemical compositions, Carbon isotopic composition of DIC and calculated partial pressure of CO2 of Mun River during the wet season.

Author Contributions

Conceptualization, G.H. and X.L.; Data curation, X.L.; Formal analysis, X.L. and M.L.; Funding acquisition, G.H.; Investigation, G.H., X.L. and M.L.; Methodology, G.H., X.L. and M.L.; Project administration, G.H.; Validation, G.H. and X.L.; Writing–original draft, G.H. and X.L.; Writing–review and editing, G.H. and X.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was financially supported by the National Natural Science Foundation of China (41661144029, 41325010).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available in the supplementary materials.

Acknowledgments

The authors are grateful the group members of Fairda Malem, from the Ministry of Natural Resources and Environment of Thailand, for their help in field work. The manuscript benefited greatly from the comments of three anonymous reviewers and the editor Wendy Gao.

Conflicts of 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 article.

References

  1. Hilton, R.G.; West, A.J. Mountains, erosion and the carbon cycle. Nat. Rev. Earth Environ. 2020, 1, 284–299. [Google Scholar] [CrossRef]
  2. Maher, K.; Chamberlain, C.P. Hydrologic Regulation of Chemical Weathering and the Geologic Carbon Cycle. Science 2014, 343, 1502. [Google Scholar] [CrossRef] [PubMed]
  3. Liu, J.; Han, G. Tracing Riverine Particulate Black Carbon Sources in Xijiang River Basin: Insight from Stable Isotopic Composition and Bayesian Mixing Model. Water Res. 2021, 194, 116932. [Google Scholar] [CrossRef] [PubMed]
  4. Berner, R.A.; Caldeira, K. The need for mass balance and feedback in the geochemical carbon cycle. Geology 1998, 25, 955–966. [Google Scholar] [CrossRef]
  5. Goudie, A.S.; Viles, H.A. Weathering and the global carbon cycle: Geomorphological perspectives. Earth-Sci. Rev. 2012, 113, 59–71. [Google Scholar] [CrossRef]
  6. Han, G.; Tang, Y.; Liu, M.; Van Zwieten, L.; Yang, X.; Yu, C.; Wang, H.; Song, Z. Carbon-nitrogen isotope coupling of soil organic matter in a karst region under land use change, Southwest China. Agric. Ecosyst. Environ. 2020, 301, 107027. [Google Scholar] [CrossRef]
  7. Liu, M.; Han, G.L.; Zhang, Q. Effects of agricultural abandonment on soil aggregation, soil organic carbon storage and stabilization: Results from observation in a small karst catchment, Southwest China. Agric. Ecosyst. Environ. 2020, 288, 106719. [Google Scholar] [CrossRef]
  8. Li, X.; Han, G.; Zhang, Q.; Qu, R.; Miao, Z. Accurate lithium isotopic analysis of twenty geological reference materials by multi-collector inductively coupled plasma mass spectrometry. Spectrochim. Acta Part B At. Spectrosc. 2022, 188, 106348. [Google Scholar] [CrossRef]
  9. Zeng, J.; Han, G. Tracing zinc sources with Zn isotope of fluvial suspended particulate matter in Zhujiang River, Southwest China. Ecol. Indic. 2020, 118, 106723. [Google Scholar] [CrossRef]
  10. Zeng, J.; Han, G. Preliminary copper isotope study on particulate matter in Zhujiang River, southwest China: Application for source identification. Ecotoxicol. Environ. Saf. 2020, 196, 110663. [Google Scholar] [CrossRef]
  11. Han, G.; Zeng, J. Iron isotope of suspended particulate matter in Zhujiang River, Southwest China: Characteristics, sources, and environmental implications. Sci. Total Environ. 2021, 793, 148562. [Google Scholar] [CrossRef] [PubMed]
  12. Tipper, E.T.; Stevenson, E.I.; Alcock, V.; Knight, A.C.G.; Baronas, J.J.; Hilton, R.G.; Bickle, M.J.; Larkin, C.S.; Feng, L.; Relph, K.E.; et al. Global silicate weathering flux overestimated because of sediment-water cation exchange. Proc. Natl. Acad. Sci. USA 2021, 118, e2016430118. [Google Scholar] [CrossRef] [PubMed]
  13. Torres, M.A.; West, A.J.; Clark, K.E.; Paris, G.; Bouchez, J.; Ponton, C.; Feakins, S.J.; Galy, V.; Adkins, J.F. The acid and alkalinity budgets of weathering in the Andes–Amazon system: Insights into the erosional control of global biogeochemical cycles. Earth Planet. Sci. Lett. 2016, 450, 381–391. [Google Scholar] [CrossRef] [Green Version]
  14. Moquet, J.-S.; Crave, A.; Viers, J.; Seyler, P.; Armijos, E.; Bourrel, L.; Chavarri, E.; Lagane, C.; Laraque, A.; Casimiro, W.S.L.; et al. Chemical weathering and atmospheric/soil CO2 uptake in the Andean and Foreland Amazon basins. Chem. Geol. 2011, 287, 1–26. [Google Scholar] [CrossRef]
  15. Chetelat, B.; Liu, C.Q.; Zhao, Z.Q.; Wang, Q.L.; Li, S.L.; Li, J.; Wang, B.L. Geochemistry of the dissolved load of the Changjiang Basin rivers: Anthropogenic impacts and chemical weathering. Geochim. Cosmochim. Acta 2008, 72, 4254–4277. [Google Scholar] [CrossRef]
  16. Wu, W.; Yang, J.; Xu, S.; Yin, H. Geochemistry of the headwaters of the Yangtze River, Tongtian He and Jinsha Jiang: Silicate weathering and CO2 consumption. Appl. Geochem. 2008, 23, 3712–3727. [Google Scholar] [CrossRef]
  17. Gaillardet, J.; Dupre, B.; Louvat, P.; Allegre, C.J. Global silicate weathering and CO2 consumption rates deduced from the chemistry of large rivers. Chem. Geol. 1999, 159, 3–30. [Google Scholar] [CrossRef]
  18. Zeghioud, H.; Assadi, A.A.; Khellaf, N.; Djelal, H.; Amrane, A.; Rtimi, S. Photocatalytic Performance of CuxO/TiO(2) Deposited by HiPIMS on Polyester under Visible Light LEDs: Oxidants, Ions Effect, and Reactive Oxygen Species Investigation. Materials 2019, 12, 412. [Google Scholar] [CrossRef] [Green Version]
  19. Baaloudj, O.; Assadi, I.; Nasrallah, N.; El Jery, A.; Khezami, L.; Assadi, A.A. Simultaneous removal of antibiotics and inactivation of antibiotic-resistant bacteria by photocatalysis: A review. J. Water Process Eng. 2021, 42, 102089. [Google Scholar] [CrossRef]
  20. Wang, T.; Wang, L.; Chen, Q.; Kalogerakis, N.; Ji, R.; Ma, Y. Interactions between microplastics and organic pollutants: Effects on toxicity, bioaccumulation, degradation, and transport. Sci. Total Environ. 2020, 748, 142427. [Google Scholar] [CrossRef]
  21. Zeng, J.; Han, G.; Zhang, S.; Liang, B.; Qu, R.; Liu, M.; Liu, J. Potentially toxic elements in cascade dams-influenced river originated from Tibetan Plateau. Environ. Res. 2022, 208, 112716. [Google Scholar] [CrossRef] [PubMed]
  22. Marx, A.; Dusek, J.; Jankovec, J.; Sanda, M.; Vogel, T.; van Geldern, R.; Hartmann, J.; Barth, J.A.C. A review of CO2 and associated carbon dynamics in headwater streams: A global perspective. Rev. Geophys. 2017, 55, 560–585. [Google Scholar] [CrossRef]
  23. Meybeck, M. Global chemical-weathering of surfical rocks estimated from river dissolved loads. Am. J. Sci. 1987, 287, 401–428. [Google Scholar] [CrossRef]
  24. Suchet, P.A.; Probst, J.L.; Ludwig, W. Worldwide distribution of continental rock lithology: Implications for the atmospheric/soil CO2 uptake by continental weathering and alkalinity river transport to the oceans. Glob. Biogeochem. Cycles 2003, 17, 1038. [Google Scholar] [CrossRef] [Green Version]
  25. Clark, I.; Fritz, P. Environmental Isotopes in Hydrogeology; CRC Press: New York, NY, USA, 1997. [Google Scholar] [CrossRef]
  26. Cartwright, I. The origins and behaviour of carbon in a major semi-arid river, the Murray River, Australia, as constrained by carbon isotopes and hydrochemistry. Appl. Geochem. 2010, 25, 1734–1745. [Google Scholar] [CrossRef]
  27. Li, S.-L.; Liu, C.-Q.; Li, J.; Lang, Y.-C.; Ding, H.; Li, L. Geochemistry of dissolved inorganic carbon and carbonate weathering in a small typical karstic catchment of Southwest China: Isotopic and chemical constraints. Chem. Geol. 2010, 277, 301–309. [Google Scholar] [CrossRef]
  28. Aucour, A.M.; Sheppard, S.M.F.; Guyomar, O.; Wattelet, J. Use of 13C to trace origin and cycling of inorganic carbon in the Rhone river system. Chem. Geol. 1999, 159, 87–105. [Google Scholar] [CrossRef]
  29. Barth, J.A.C.; Cronin, A.A.; Dunlop, J.; Kalin, R.M. Influence of carbonates on the riverine carbon cycle in an anthropogenically dominated catchment basin: Evidence from major elements and stable carbon isotopes in the Lagan River (N. Ireland). Chem. Geol. 2003, 200, 203–216. [Google Scholar] [CrossRef]
  30. Wachniew, P. Isotopic composition of dissolved inorganic carbon in a large polluted river: The Vistula, Poland. Chem. Geol. 2006, 233, 293–308. [Google Scholar] [CrossRef]
  31. Liu, J.; Han, G. Controlling factors of riverine CO2 partial pressure and CO2 outgassing in a large karst river under base flow condition. J. Hydrol. 2021, 593, 125638. [Google Scholar] [CrossRef]
  32. Liu, J.; Han, G. Controlling factors of seasonal and spatial variation of riverine CO2 partial pressure and its implication for riverine carbon flux. Sci. Total Environ. 2021, 786, 147332. [Google Scholar] [CrossRef] [PubMed]
  33. Qin, C.Q.; Li, S.L.; Waldron, S.; Yue, F.J.; Wang, Z.J.; Zhong, J.; Ding, H.; Liu, C.Q. High-frequency monitoring reveals how hydrochemistry and dissolved carbon respond to rainstorms at a karstic critical zone, Southwestern China. Sci. Total Environ. 2020, 714, 136833. [Google Scholar] [CrossRef] [PubMed]
  34. Catalan, N.; Marce, R.; Kothawala, D.N.; Tranvik, L.J. Organic carbon decomposition rates controlled by water retention time across inland waters. Nat. Geosci. 2016, 9, 501. [Google Scholar] [CrossRef]
  35. Porcal, P.; Dillon, P.J.; Molot, L.A. Temperature Dependence of Photodegradation of Dissolved Organic Matter to Dissolved Inorganic Carbon and Particulate Organic Carbon. PLoS ONE 2015, 10, e0128884. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Barnes, R.T.; Raymond, P.A. The contribution of agricultural and urban activities to inorganic carbon fluxes within temperate watersheds. Chem. Geol. 2009, 266, 318–327. [Google Scholar] [CrossRef]
  37. Perrin, A.S.; Probst, A.; Probst, J.L. Impact of nitrogenous fertilizers on carbonate dissolution in small agricultural catchments: Implications for weathering CO2 uptake at regional and global scales. Geochim. Cosmochim. Acta 2008, 72, 3105–3123. [Google Scholar] [CrossRef] [Green Version]
  38. Regnier, P.; Friedlingstein, P.; Ciais, P.; Mackenzie, F.T.; Gruber, N.; Janssens, I.A.; Laruelle, G.G.; Lauerwald, R.; Luyssaert, S.; Andersson, A.J.; et al. Anthropogenic perturbation of the carbon fluxes from land to ocean. Nat. Geosci. 2013, 6, 597–607. [Google Scholar] [CrossRef]
  39. Deirmendjian, L.; Abril, G. Carbon dioxide degassing at the groundwater-stream-atmosphere interface: Isotopic equilibration and hydrological mass balance in a sandy watershed. J. Hydrol. 2018, 558, 129–143. [Google Scholar] [CrossRef] [Green Version]
  40. Doctor, D.H.; Kendall, C.; Sebestyen, S.D.; Shanley, J.B.; Ote, N.; Boyer, E.W. Carbon isotope fractionation of dissolved inorganic carbon (DIC) due to outgassing of carbon dioxide from a headwater stream. Hydrol. Process. 2008, 22, 2410–2423. [Google Scholar] [CrossRef]
  41. Polsenaere, P.; Abril, G. Modelling CO2 degassing from small acidic rivers using water pCO2, DIC and δ13CDIC data. Geochim. Et Cosmochim. Acta 2012, 91, 220–239. [Google Scholar] [CrossRef]
  42. Yao, G.R.; Gao, Q.Z.; Wang, Z.G.; Huang, X.K.; He, T.; Zhang, Y.L.; Jiao, S.L.; Ding, J. Dynamics of CO2 partial pressure and CO2 outgassing in the lower reaches of the Xijiang River, a subtropical monsoon river in China. Sci. Total Environ. 2007, 376, 255–266. [Google Scholar] [CrossRef] [PubMed]
  43. Qin, C.Q.; Li, S.L.; Yue, F.J.; Xu, S.; Ding, H. Spatiotemporal variations of dissolved inorganic carbon and controlling factors in a small karstic catchment, Southwestern China. Earth Surf. Processes Landf. 2019, 44, 2423–2436. [Google Scholar] [CrossRef]
  44. White, A.F.; Blum, A.E. Effects of climate on chemical-weathering in watersheds. Geochim. Cosmochim. Acta 1995, 59, 1729–1747. [Google Scholar] [CrossRef]
  45. Van Geldern, R.; Schulte, P.; Mader, M.; Baier, A.; Barth, J.A.C. Spatial and temporal variations of pCO2, dissolved inorganic carbon and stable isotopes along a temperate karstic watercourse. Hydrol. Process. 2015, 29, 3423–3440. [Google Scholar] [CrossRef]
  46. Maher, K. The role of fluid residence time and topographic scales in determining chemical fluxes from landscapes. Earth Planet. Sci. Lett. 2011, 312, 48–58. [Google Scholar] [CrossRef]
  47. Winnick, M.J.; Maher, K. Relationships between CO2, thermodynamic limits on silicate weathering, and the strength of the silicate weathering feedback. Earth Planet. Sci. Lett. 2018, 485, 111–120. [Google Scholar] [CrossRef]
  48. Li, S.L.; Calmels, D.; Han, G.; Gaillardet, J.; Liu, C.Q. Sulfuric acid as an agent of carbonate weathering constrained by δ13CDIC: Examples from Southwest China. Earth Planet. Sci. Lett. 2008, 270, 189–199. [Google Scholar] [CrossRef]
  49. Boano, F.; Harvey, J.W.; Marion, A.; Packman, A.I.; Revelli, R.; Ridolfi, L.; Worman, A. Hyporheic flow and transport processes: Mechanisms, models, and biogeochemical implications. Rev. Geophys. 2014, 52, 603–679. [Google Scholar] [CrossRef]
  50. Liu, J.; Han, G. Effects of chemical weathering and CO2 outgassing on δ13CDIC signals in a karst watershed. J. Hydrol. 2020, 589, 125192. [Google Scholar] [CrossRef]
  51. Wang, F.S.; Wang, B.L.; Liu, C.Q.; Wang, Y.C.; Guan, J.; Liu, X.L.; Yu, Y.X. Carbon dioxide emission from surface water in cascade reservoirs-river system on the Maotiao River, southwest of China. Atmos. Environ. 2011, 45, 3827–3834. [Google Scholar] [CrossRef]
  52. Liu, J.; Han, G.; Liu, X.; Liu, M.; Song, C.; Zhang, Q.; Yang, K.; Li, X. Impacts of Anthropogenic Changes on the Mun River Water: Insight from Spatio-Distributions and Relationship of C and N Species in Northeast Thailand. Int. J. Environ. Res. Public Health 2019, 16, 659. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Liu, J.; Han, G.; Liu, X.; Liu, M.; Song, C.; Yang, K.; Li, X.; Zhang, Q. Distributive Characteristics of Riverine Nutrients in the Mun River, Northeast Thailand: Implications for Anthropogenic Inputs. Water 2019, 11, 954. [Google Scholar] [CrossRef] [Green Version]
  54. Liu, X.; Han, G.; Zeng, J.; Liu, M.; Li, x.; Boeckx, P. Identifying the sources of nitrate contamination using a combined dual isotope, chemical and Bayesian model approach in a tropical agricultural river: Case study in the Mun River, Thailand. Sci. Total Environ. 2021, 760, 143938. [Google Scholar] [CrossRef] [PubMed]
  55. Liu, M.; Han, G.; Li, X. Contributions of soil erosion and decomposition to SOC loss during a short-term paddy land abandonment in Northeast Thailand. Agric. Ecosyst. Environ. 2021, 321, 107629. [Google Scholar] [CrossRef]
  56. Yadav, S.; Babel, M.S.; Shrestha, S.; Deb, P. Land use impact on the water quality of large tropical river: Mun River Basin, Thailand. Environ. Monit. Assess. 2019, 191, 614. [Google Scholar] [CrossRef] [PubMed]
  57. Zhao, Z.; Liu, G.; Liu, Q.; Huang, C.; Li, H.; Wu, C. Distribution Characteristics and Seasonal Variation of Soil Nutrients in the Mun River Basin, Thailand. Int. J. Environ. Res. Public Health 2018, 15, 1818. [Google Scholar] [CrossRef] [Green Version]
  58. Li, X.; Han, G.; Liu, M.; Song, C.; Zhang, Q.; Yang, K.; Liu, J. Hydrochemistry and Dissolved Inorganic Carbon (DIC) Cycling in a Tropical Agricultural River, Mun River Basin, Northeast Thailand. Int. J. Environ. Res. Public Health 2019, 16, 3410. [Google Scholar] [CrossRef] [Green Version]
  59. Han, G.; Yang, K.; Zeng, J.; Zhao, Y. Dissolved iron and isotopic geochemical characteristics in a typical tropical river across the floodplain: The potential environmental implication. Environ. Res. 2021, 200, 111452. [Google Scholar] [CrossRef]
  60. Zeng, J.; Han, G.; Yang, K. Assessment and sources of heavy metals in suspended particulate matter in a tropical catchment, northeast Thailand. J. Clean. Prod. 2020, 265, 121898. [Google Scholar] [CrossRef]
  61. Liang, B.; Han, G.; Liu, M.; Li, X. Zn isotope fractionation during the development of low-humic gleysols from the Mun River Basin, northeast Thailand. Catena 2021, 206, 105565. [Google Scholar] [CrossRef]
  62. Li, R.; Shi, J.; Ji, D.; Zhao, T.; Plermkamon, V.; Moukomla, S.; Kuntiyawichai, K.; Kruasilp, J. Evaluation and Hydrological Application of TRMM and GPM Precipitation Products in a Tropical Monsoon Basin of Thailand. Water 2019, 11, 818. [Google Scholar] [CrossRef] [Green Version]
  63. Zhang, S.; Han, G.; Zeng, J.; Xiao, X.; Malem, F. A Strontium and Hydro-Geochemical Perspective on Human Impacted Tributary of the Mekong River Basin: Sources Identification, Fluxes, and CO2 Consumption. Water 2021, 13, 3137. [Google Scholar] [CrossRef]
  64. Akter, A.; Babel, M.S. Hydrological modeling of the Mun River basin in Thailand. J. Hydrol. 2012, 452–453, 232–246. [Google Scholar] [CrossRef]
  65. Atekwana, E.A.; Krishnamurthy, R.V. Seasonal variations of dissolved inorganic carbon and delta 13C of surface waters: Application of a modified gas evolution technique. J. Hydrol. 1998, 205, 265–278. [Google Scholar] [CrossRef]
  66. Yang, K.; Han, G. Controls over hydrogen and oxygen isotopes of surface water and groundwater in the Mun River catchment, northeast Thailand: Implications for the water cycle. Hydrogeol. J. 2020, 28, 1021–1036. [Google Scholar] [CrossRef]
  67. Li, X.; Han, G.; Liu, M.; Liu, J.; Zhang, Q.; Qu, R. Potassium and its isotope behaviour during chemical weathering in a tropical catchment affected by evaporite dissolution. Geochim. Cosmochim. Acta 2022, 316, 105–121. [Google Scholar] [CrossRef]
  68. Li, S.; Lu, X.X.; Bush, R.T. CO2 partial pressure and CO2 emission in the Lower Mekong River. J. Hydrol. 2013, 504, 40–56. [Google Scholar] [CrossRef]
  69. Conley, D.J. Terrestrial ecosystems and the global biogeochemical silica cycle. Glob. Biogeochem. Cycles 2002, 16, 61–68. [Google Scholar] [CrossRef]
  70. Beusen, A.H.W.; Bouwman, A.F.; Dürr, H.H.; Dekkers, A.L.M.; Hartmann, J. Global patterns of dissolved silica export to the coastal zone: Results from a spatially explicit global model. Glob. Biogeochem. Cycles 2009, 23, GB0A02. [Google Scholar] [CrossRef]
  71. Liu, J.; Han, G. Tracing riverine sulfate source in an agricultural watershed: Constraints from stable isotopes. Environ. Pollut. 2021, 288, 117740. [Google Scholar] [CrossRef]
  72. Schulte, P.; van Geldern, R.; Freitag, H.; Karim, A.; Négrel, P.; Petelet-Giraud, E.; Probst, A.; Probst, J.-L.; Telmer, K.; Veizer, J.; et al. Applications of stable water and carbon isotopes in watershed research: Weathering, carbon cycling, and water balances. Earth-Sci. Rev. 2011, 109, 20–31. [Google Scholar] [CrossRef] [Green Version]
  73. Spence, J.; Telmer, K. The role of sulfur in chemical weathering and atmospheric CO2 fluxes: Evidence from major ions, δ13CDIC, and δ34SSO4 in rivers of the Canadian Cordillera. Geochim. Cosmochim. Acta 2005, 69, 5441–5458. [Google Scholar] [CrossRef]
  74. Cane, G.; Clark, I.D. Tracing Ground Water Recharge in an Agricultural Watershed with Isotopes. Groundwater 1999, 37, 133–139. [Google Scholar] [CrossRef]
  75. Millot, R.; Gaillardet, J.; Dupré, B.; Allègre, C.J. The global control of silicate weathering rates and the coupling with physical erosion: New insights from rivers of the Canadian Shield. Earth Planet. Sci. Lett. 2002, 196, 83–98. [Google Scholar] [CrossRef]
  76. Yang, K.; Han, G.; Zeng, J.; Liu, M.; Li, X.; Zhao, Y. Tracing Fe Sources in Suspended Particulate Matter (SPM) in the Mun River: Application of Fe-Stable Isotopes Based on a Binary Mixing Model. ACS Earth Space Chem. 2021, 5, 1613–1621. [Google Scholar] [CrossRef]
  77. Shen, L.; Siritongkham, N.; Wang, L.; Liu, C.; Nontaso, A.; Khadsri, W.; Hu, Y. The brine depth of the Khorat Basin in Thailand as indicated by high-resolution Br profile. Sci. Rep. 2021, 11, 8673. [Google Scholar] [CrossRef]
  78. Cerling, T.E.; Solomon, D.K.; Quade, J.; Bowman, J.R. On the isotopic composition of carbon in soil carbon dioxide. Geochim. Et Cosmochim. Acta 1991, 55, 3403–3405. [Google Scholar] [CrossRef]
  79. Bianchi, T.S.; Garcia-Tigreros, F.; Yvon-Lewis, S.A.; Shields, M.; Mills, H.J.; Butman, D.; Osburn, C.; Raymond, P.; Shank, G.C.; DiMarco, S.F.; et al. Enhanced transfer of terrestrially derived carbon to the atmosphere in a flooding event. Geophys. Res. Lett. 2013, 40, 116–122. [Google Scholar] [CrossRef]
  80. Anderson, L.A. On the hydrogen and oxygen-content of marine-phytoplankton. Deep-Sea Res. Part I-Oceanogr. Res. Pap. 1995, 42, 1675–1680. [Google Scholar] [CrossRef]
  81. Sondergaard, M.; Middelboe, M. A cross-system analysis of labile dissolved organic-carbon. Mar. Ecol. Prog. Ser. 1995, 118, 283–294. [Google Scholar] [CrossRef] [Green Version]
  82. Robinson, C.; Archer, S.D.; Williams, P.J.L. Microbial dynamics in coastal waters of East Antarctica: Plankton production and respiration. Mar. Ecol. Prog. Ser. 1999, 180, 23–36. [Google Scholar] [CrossRef]
  83. Taylor, G.T.; Way, J.; Scranton, M.I. Planktonic carbon cycling and transport in surface waters of the highly urbanized Hudson River estuary. Limnol. Oceanogr. 2003, 48, 1779–1795. [Google Scholar] [CrossRef] [Green Version]
Water 14 01340 g001 550
Figure 1. The lithology and sampling sites of the Mun River watershed in Northeast Thailand.
Figure 1. The lithology and sampling sites of the Mun River watershed in Northeast Thailand.
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Figure 2. Piper graph of river water in the Mun River.
Figure 2. Piper graph of river water in the Mun River.
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Figure 3. Values of pCO2 (a), calcite saturation indexes (b), and δ13CDIC (c) in the study water samples. (d) Numerical range of δ13C in different carbon reservoirs, data are derived from Schulte, et al. [72].
Figure 3. Values of pCO2 (a), calcite saturation indexes (b), and δ13CDIC (c) in the study water samples. (d) Numerical range of δ13C in different carbon reservoirs, data are derived from Schulte, et al. [72].
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Figure 4. The Spatio-temporal variation characteristics of (a) pH, (b) DIC, (c) pCO2 and (d) carbon isotopes along the mainstream.
Figure 4. The Spatio-temporal variation characteristics of (a) pH, (b) DIC, (c) pCO2 and (d) carbon isotopes along the mainstream.
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Figure 5. The elemental molar ratios showing the mixing relationships: (a) Mg/Na vs. Ca/Na; (b) HCO3/Na vs. Ca/Na; (c) (Ca + Mg)/HCO3 vs. SO4/HCO3; (d) (Ca + Mg)/HCO3 vs. δ13CDIC.
Figure 5. The elemental molar ratios showing the mixing relationships: (a) Mg/Na vs. Ca/Na; (b) HCO3/Na vs. Ca/Na; (c) (Ca + Mg)/HCO3 vs. SO4/HCO3; (d) (Ca + Mg)/HCO3 vs. δ13CDIC.
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Figure 6. Plot showing the relationship between δ13CDIC values and DOC concentrations (a), δ13CDIC values and CO2/DIC ratios (b), LogpCO2 and DO concentrations (c), and δ13CDIC values and DO concentrations (d).
Figure 6. Plot showing the relationship between δ13CDIC values and DOC concentrations (a), δ13CDIC values and CO2/DIC ratios (b), LogpCO2 and DO concentrations (c), and δ13CDIC values and DO concentrations (d).
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Figure 7. Relationship between the δ13CDIC and logpCO2 for the water collected from the Mun River watershed in two seasons.
Figure 7. Relationship between the δ13CDIC and logpCO2 for the water collected from the Mun River watershed in two seasons.
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Table
Table 1. A summary of the water chemistry and δ13CDIC values for the Mun River.
Table 1. A summary of the water chemistry and δ13CDIC values for the Mun River.
ParametersWet SeasonDry Season aMekong b
RangeMeanRangeMeanMean
T (°C)20.3–31.328.424.0–33.028.628.2
pH6.4–8.47.06.1–8.57.47.6
DO (mg/L)3.0–7.14.93.3–11.86.7-
TDS (mg/L)9.0–99898.315.0–1502280.7119
Na+ (mg/L)1.0–326.423.31.3–369.654.47.7
K+ (mg/L)0.8–12.23.11.2–14.14.42.0
Ca2+ (mg/L)1.2–62.410.51.1–103.520.133.4
Mg2+ (mg/L)0.3–14.02.60.5–16.24.98.3
Cl− (mg/L)1.6–603.035.21.7–668.586.16.8
NO3− (mg/L)0.0–3.40.70.0–8.01.1-
SO42− (mg/L)0.9–28.35.30.4–52.58.817.1
HCO3− (mg/L)5.5–183.142.67.3–362.377.270.6
SiO2 (mg/L)1.1–15.06.73.6–21.39.69.9
DOC (mg/L)1.7–40.111.02.6–17.29.0-
DIC (μmol/L)134.9–3146808.9184.5–60931374.3-
pCO2 (μatm)326–73123353283–30,1504154-
δ13CDIC (‰)−31.0–−7.0−19.1−19.6–−2.7−10.8-
The data of a and b are derived from Li, et al. [58] and Li, et al. [68], respectively.
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Li, X.; Han, G.; Liu, M. Seasonal and Spatial Variations of δ13CDIC Values in the Mun River, Northeast Thailand. Water 2022, 14, 1340. https://doi.org/10.3390/w14091340

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Li X, Han G, Liu M. Seasonal and Spatial Variations of δ13CDIC Values in the Mun River, Northeast Thailand. Water. 2022; 14(9):1340. https://doi.org/10.3390/w14091340

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Li, Xiaoqiang, Guilin Han, and Man Liu. 2022. "Seasonal and Spatial Variations of δ13CDIC Values in the Mun River, Northeast Thailand" Water 14, no. 9: 1340. https://doi.org/10.3390/w14091340

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