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The significant role of submarine groundwater discharge in an Arctic fjord nutrient budget
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Xueqing Yu1, 2, Jian’an Liu3, *, Zhuoyi Zhu4, 5, Xiaogang Chen6, Tong Peng2, Jinzhou Du2
Acta Oceanologica Sinica | 2024, 43(10) : 74 - 85
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Acta Oceanologica Sinica | 2024, 43(10): 74-85
• Marine Chemistry •
The significant role of submarine groundwater discharge in an Arctic fjord nutrient budget
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Xueqing Yu1, 2, Jian’an Liu3, *, Zhuoyi Zhu4, 5, Xiaogang Chen6, Tong Peng2, Jinzhou Du2
Affiliations
  • 1 College of Geography and Environmental Science, Key Laboratory of Tropical Island Land Surface Processes and Environmental Changes of Hainan Province, Hainan Normal University, Haikou 571158, China
  • 2 State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200241, China
  • 3 State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou 570228, China
  • 4 Shanghai Key Laboratory of Polar Life and Environment Sciences, School of Oceanography, Shanghai Jiao Tong University, Shanghai 200030, China
  • 5 MNR Key Laboratory for Polar Science, Polar Research Institute of China, Shanghai 200136, China
  • 6 Key Laboratory of Coastal Environment and Resources of Zhejiang Province, School of Engineering, Westlake University, Hangzhou 310024, China
Published: 2024-10-25 doi: 10.1007/s13131-024-2418-4
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Under global climate change, water flow and related nutrient biogeochemistry in the Arctic are changing at an unprecedented rate, and potentially affect nutrient cycling in the Arctic Ocean. However, nutrient fluxes via submarine groundwater discharge (SGD) are potentially important yet poorly understood in the Arctic. Here we quantified that nutrient fluxes through radium-derived SGD were three orders of magnitude higher than those from the local river and constituted 25%−96% of the total nutrient inputs into the Kongsfjorden. These large groundwater nutrient fluxes with high NIN/DIP molar ratio (average 99) may change the biomass and community structure of phytoplankton. Meanwhile, combining other SGD study cases around the Arctic region, SGD rates tend to increase over the past three decades, possibly on account of the effects of global warming. The SGD-derived nutrient may cause the increase of net primary productivity in the Arctic Ocean. The results will provide important basic data for land-ocean interactions in the typical fjord of the Arctic under the influence of global warming.

Arctic  /  submarine groundwater  /  nutrient biogeochemistry  /  primary productivity  /  radium isotopes  /  global climate change
Xueqing Yu, Jian’an Liu, Zhuoyi Zhu, Xiaogang Chen, Tong Peng, Jinzhou Du. The significant role of submarine groundwater discharge in an Arctic fjord nutrient budget[J]. Acta Oceanologica Sinica, 2024 , 43 (10) : 74 -85 . DOI: 10.1007/s13131-024-2418-4
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1 Introduction
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The Arctic region is one of the most important places to study climate change and climate records because it is highly vulnerable to climate change (Peterson et al., 2002; Polyakov et al., 2012; Semenov et al., 2020). Under the influence of global warming amplification, the rate of temperature increases in the Arctic subsurface is about two times as much as that of the middle and low latitudes, which contributes to rapid and widespread permafrost thawing (Collins et al., 2013; Guimond et al., 2022; Smith et al., 2007; Walvoord and Striegl, 2007). The processes of glacial meltwater and sea ice melting in summer make large amount of fresh water enter the Arctic Ocean, one way through the riverine, and others directly fall into the sea by the frontal interface of glaciers and surface seas. This fresh water with the matter and energy balance changing has a significant impact on the ecological environment (Bridgestock et al., 2021a; Kipp et al., 2018; Vonk et al., 2012). In addition, freshwater from glacier melting can be also infiltrated into the aquifers and then enters the ocean through coastal groundwater (Bridgestock et al., 2021a; Dimova et al., 2015; Kipp et al., 2018; Lecher, 2017). Except that temperature rises, the interaction between coastal groundwater and surface water in the Arctic Ocean may cause heat transfer to sediments or deeper soil layers along the Arctic Ocean coastline, leading to the permafrost melting. This phenomenon would enhance the flux of terrestrial freshwater into the coastal area and its-derived nutrient input to the sea, which results in a change in the structure and composition of the plankton community (Dimova et al., 2015; Lecher et al., 2016a, b; Piquet et al., 2014).
Submarine groundwater discharge (SGD) is defined as the water flow (including fresh SGD and saline SGD) on the continental margin from the seabed to the coastal ocean, regardless of fluid composition or driving force (Burnett et al., 2003). SGD also exists in the Arctic and is very susceptible to the effect of global warming. It is unique in that glacial meltwater permeates into underground aquifers and discharges as SGD into coastal waters (Charkin et al., 2017). Most importantly, SGD also has been widely recognized as a significant mechanism for transporting related solutes into the ocean (Lecher, 2015; Liu et al., 2017; Moore, 2010; Rodellas et al., 2015; Santos et al., 2021). Specifically, SGD-derived solutes have been shown to be comparable to rivers, benthic sediments and atmospheric inputs in coastal areas on regional and global scales (Hwang et al., 2010; Kim et al., 2005; Rodellas et al., 2015; Santos et al., 2021; Swarzenski, 2007). As a naturally occurring radioactive tracer, radium (Ra) isotopes (224Ra, 223Ra, 228Ra, and 226Ra) have widely varying half-lives (3.66 d, 11.4 d, 5.75 a, and 1602 a, respectively). Radium tracing is one of the most effective methods for quantifying SGD flux into coastal waters within different temporal and spatial scales (Garcia-Orellana et al., 2021; Moore, 1996).
The Arctic region has always been an under-studied area of SGD, with a few of those trying to understand the nature of groundwater discharge and its impact on aquatic ecosystems. In particular, because of the impact of climate change, the large area of permafrost and floating ice melts, the SGD in the Arctic region (especially the SGD from the permafrost) need for more attention. Lecher (2017) summarized SGD studies in the Arctic, which showed the important role of SGD on nutrient and trace elements supply (Dimova et al., 2015; Lecher, 2015; Lecher et al., 2016a, b). Kipp et al. (2018) found that 228Ra activities in the surface waters of the central Arctic Ocean increased due to shelf input into the central basin, revealing the transport of elevated concentrations of nutrient and dissolved organic carbon, which can through shelf sediments and/or SGD. Connolly et al. (2020) presented substantial fluxes of dissolved organic matter delivered by supra-permafrost groundwater to the Alaska Beaufort Sea, and the fluxes are expected to increase in a warming Arctic. As a result, SGD is expected to become an increasing source of nutrient in the Arctic Ocean as permafrost thaws, where the nutrient cycling is undergoing major changes that have the potential to affect biological productivity and species composition in the Arctic waters (Kipp et al., 2018).
However, there are few studies on the effects of SGD on the nutrient structures in the Arctic region. Therefore, the research on the SGD-associated nutrient under the influence of global climate change has become an attention-grabbing hotspot in the Arctic. Rapid changes in the ice cover of Svalbard make it one of the key regions for the interaction of Arctic ice dynamics and climate change on geological time scales (Kim et al., 2022; Polyakov et al., 2012). The accelerated shrinkage of the cryosphere has attracted the attention of researchers on the potential effects of hydrology, fluid dynamics, sediments and bio-communities from land to ocean (Hodson et al., 2019; Kim et al., 2022; Yoshikawa and Harada, 1995). So far, most studies of freshwater discharges in Svalbard have focused on local rivers and glacier meltwater discharge (Haldorsen and Heim, 1999; Kim et al., 2022; Olichwer et al., 2013), less attention was paid to the impact of SGD on the coastal environment. The early Holocene was a relatively warm period with a large influx of warm Atlantic water, leading to the formation of sea ice and the reduction of glacial extent in the Kongsfjorden (Chen et al., 2016; Kim et al., 2022; Peral et al., 2022). Land-ocean interactions are key to understand and predict hydrology and nutrient cycling in Svalbard during past, present and future under global climate change.
Here, we analyze Ra and nutrient concentrations in seawater, river and coastal groundwater around the Kongsfjorden, a typical Arctic fjord. The goals of our study are to (1) use 226Ra and 228Ra mass balance models, including uncertainty analysis, to estimate SGD and its derived nutrient fluxes in Kongsfjorden; (2) build nutrient budget in Kongsfjorden to assess the environmental impacts of SGD; (3) evaluate SGD-derived nutrient fluxes around the Arctic Ocean with the support of available literature, hope to contribute to a deeper understanding and better prediction of global warming impacts on SGD which may affect the Arctic Ocean ecosystem.
2 Materials and methods
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2.1 Study area
The Kongsfjorden (78.49°–79.24°N, 10.89°–13.45°E) is located in the northwestern part of the Svalbard Islands (Fig. 1). Only one major river, the Bayelva River flows into the fjord, with a length of ~4 km and a small runoff of 8.18 × 104 m3/d (Zhu et al., 2016), the other rivers have less runoff and generally do not melt into the fjord in summer, so we ignore their contributions in our following SGD calculation. Due to the influence of the North Atlantic Warm Current flowing through the archipelago, the temperature is much milder than in other parts of the Arctic, with an average annual temperature of −4℃, but it’s usually above freezing between July and September (https://www.pric.org.cn/). The mean monthly precipitation here was 48 mm, both rain and snow may occur in the Kongfjorden at any time throughout the year (Hop and Wiencke, 2019). The maritime climate of the archipelago is more pronounced, and the pelagic ecosystem is sensitive to the effects of the Atlantic and Arctic Ocean, while the benthic ecosystem is mainly affected by long-term changes in glacial runoff and sedimentation (Svendsen et al., 2002). An irregular diurnal tide exists in this region, with a mean tidal range of 200 cm (Sinha et al., 2017). Sediment in Kongsfjorden exhibits glacial till characteristics and the major sediment types were moraine lacking silt and mud, moraine containing sand, and moraine lacking sand (Sinha et al., 2017).
Seasonal sea ice is an important feature of Kongsfjorden, significantly affecting the physical environment and ecosystem. The inner fjord is usually covered with seasonal ice, initially forming between December and March and continuing through April to June. Seasonal ice has been confined to the northern inner fjords over the past decades (Hop and Wiencke, 2019; Polyakov et al., 2012; Zhu et al., 2016). The maximum sea ice sonic thickness is about 0.6 m or more, and the snow thickness on the fjord has decreased by about 0.2 m in the last decade (Hop and Wiencke, 2019). Warmer horizontal Atlantic currents entering the fjord also contributed to reducing rapid ice formation. Seasonal dynamics of sea ice extent have important implications for pelagic and benthic production as well as for seabirds and marine mammals in the marine ecosystem of Kongsfjorden (Hop and Wiencke, 2019). The landscape around Kongsfjorden is influenced by glacial, and during the summer, there are many places where glacial melt not only directly enters the fjord, but also feeds into the rivers and underground aquifers, which are the main source of fresh water for the Kongsfjorden (Kuliński et al., 2014).
2.2 Sampling collection
Field research was conducted in the Kongsfjorden (Fig. 1) during summer between late August and early September 2017 with the sampling locations shown in Fig. 1. All the Ra samples were obtained from the surface water (~60 L) at a depth of ~1 m using a submerged pump. Moreover, coastal groundwater (porewater) and river water were collected as endmembers for the Kongsfjorden. Porewater samples (n = 2, ~20 L, <2 m) were collected within 50 m offshore and in the active area of permafrost in summer with a push-point piezometer using a peristaltic pump (Moore et al., 2006). River water (40 L) was collected using an organic glass hydrophore. At the same time, suspended particulate matter is obtained by collecting river water (i.e., RW in Fig. 1) and filtering it using a glass fiber membrane with a pore size of 0.45 μm. The salinity, temperature, pH and dissolved oxygen were determined in situ using a conductance-temperature-depth sensor (Multi 3430 WTW, Germany). The Ra samples were collected into plastic buckets, passed slowly through columns filled with ~20 g MnO2 fibers and then were stored for measurement (Moore and Arnold, 1996). Samples for nutrient concentrations analyses (~60 mL) were first filtered through 0.45 μm sterile cellulose acetate filters, rinsed the low-density polyethylene bottles (these bottles were 60 mL nominal size and pre-cleaned with 1 mol/L hydrochloric acid) with filtered water sample, then filtered water samples were collected and stored in dark at −20℃.
2.3 Desorption experiment of suspended particulate matter
To estimate the Ra desorbed from suspended particulate matter, we performed desorption experiments using suspended particulate matter. The dried suspended particulate matter (0.5 g) was suspended in 5 L of Ra-free seawater with salinity 33. Mixed the seawater and suspended particulates for 2 h using an electric mixer with the appropriate speed. The suspension was allowed to settle and the particulates were separated from the seawater using a 0.45 mm filter. Ra in the filtrate was enriched on MnO2 fibers and brought back to the laboratory for measurement.
2.4 Analytical methods
Upon back to the laboratory, the MnO2 fibers were ashed at 800℃ for 8 h, homogenized, loaded into a plastic vial to a height of ~30 mm (same height for the standards) and sealed with an epoxy sealant. After aging to allow ingrowth of 222Rn, 226Ra and 228Ra were determined by a calibrated HPGe gamma spectrometry (Ortec, GWL-120-15XLB-AWT) in our laboratory, which the detector was calibrated to ensure its accuracy using certified reference materials (batch number: 08121) obtained from the National Institute of Metrology, China (Liu et al., 2021). Generally, 226Ra activities were obtained using 214Pb (295 keV and 352 keV) and 214Bi (609 keV) peaks, while 228Ra activities were obtained using the 338 keV and 911 keV peaks of 228Ac.
The samples for nutrient concentrations were analyzed for the measurement of dissolved nitrate ( ${\rm{NO}}_3^{-} $), nitrite ( ${\rm{NO}}_2^{-} $), ammonium ( ${\rm{NH}}_4^{+} $), dissolved inorganic phosphorus (DIP) and dissolved silicate (DSi) using an autoanalyzer (Model: Skalar SANplus; Liu et al., 2009). The concentration of dissolved inorganic nitrogen (DIN) is expressed as the sum of ${\rm{NO}}_2^{-} $, ${\rm{NO}}_3^{-} $, and ${\rm{NH}}_4^{+} $ concentrations. The analytical precisions of ${\rm{NO}}_2^{-} $, ${\rm{NO}}_3^{-} $, ${\rm{NH}}_4^{+} $, ${\rm{PO}}_4^{3-} $ and Si (OH)4 were all better than 5% and the detection limits were 0.01 μmol/L, 0.05 μmol/L, 0.05 μmol/L, 0.01 μmol/L and 0.1 μmol/L, respectively (Liu et al., 2022).
3 Results
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3.1 Hydrographic parameters distributions
In the surface water of the Kongsfjorden, the salinity ranged from 30.8 to 32.3, with an average of 31.5 (n = 9). The temperature changed from 3.70℃ to 7.30℃, with an average of 6.01℃. The dissolved oxygen (DO) changed from 12.6 mg/L to 13.4 mg/L and pH ranged from 8.3 to 8.6 (Table 1). Surface water showed higher temperature and lower salinity in the nearshore waters. Station K1 is the farthest offshore station with a maximum salinity of 33.2, which we selected as the open-sea water endmember. To explore the vertical mixing degree of water, we selected K2, K3, and K5 profiles for observation, and a thermocline is observed in the upper 10 m layer of this fjord (Fig. 2). In the coastal groundwater, the salinity ranged from 0 to 16.5, with a mean value of 8.25. The temperature ranged from 3.5℃ to 4.0℃, with a mean value of 3.8℃. The DO concentration ranged from 0.2 mg/L to 12.5 mg/L and pH changed from 8.1 to 8.3. In the river water of the Kongsfjorden, salinity and temperature were 0.2 and 1.9℃, DO and pH were 13.0 mg/L and 8.6, respectively.
3.2 226 Ra and 228 Ra distributions
The activities of the 226Ra and 228Ra isotopes in the Kongsfjorden at various stations are presented in Table 1. In surface water, 226Ra and 228Ra activities ranged from (2.1 ± 0.20) Bq/m3 to (3.3 ± 0.20) Bq/m3 and (1.7 ± 0.27) Bq/m3 to (3.1 ± 0.45) Bq/m3, respectively. In coastal groundwater, 226Ra activities varied from (6.1 ± 0.28) Bq/m3 to (8.6 ± 0.28) Bq/m3 while 228Ra activities varied from (8.6 ± 0.30) Bq/m3 to (19.2 ± 0.37) Bq/m3. The main river entering Kongsfjorden is the Bayelva River, 226Ra and 228Ra activities were (2.7 ± 0.28) Bq/m3 and (3.5 ± 0.436) Bq/m3, respectively. Since the other rivers were barely discharged into the bay during the sampling period, the following discussion will be based solely on data from the Bayelva River station. In open-sea water of the Kongsfjorden, the 226Ra and 228Ra activities were (2.0 ± 0.28) Bq/m3 and (1.5 ± 0.48) Bq/m3, respectively. Figure 3 shows the distribution of activities of Ra isotopes in different sources of the Kongsfjorden. It can be seen that the Ra activities of groundwater were 2 to 4 times greater than those in surface water and river water, providing evidence that groundwater may be one of the major Ra sources of the Kongsfjorden.
3.3 Nutrient distribution
The nutrient concentrations in different water types of the Kongsfjorden are shown in Table 1 and Fig. 4. The DIN, DIP and DSi concentrations of the surface water ranged from 5.17 μmol/L to 7.68 μmol/L, 0.07 μmol/L to 0.23 μmol/L and 0.59 μmol/L to 2.0 μmol/L, respectively. The DIN, DIP, and DSi concentrations were 11.8 μmol/L, 0.33 μmol/L, and 10.5 μmol/L in the Bayelva River, and 4.53 μmol/L, 0.21 μmol/L, and 0.76 μmol/L in the open-sea water, respectively. In coastal groundwater, the DIN, DIP, and DSi concentrations had wide ranges from 5.76 μmol/L to 63.7 μmol/L, 0.23 μmol/L to 0.37 μmol/L and 8.02 μmol/L to 48.8 μmol/L, respectively. DIN and DSi concentrations in groundwater were much higher than that in river water and surface water, while the DIP concentration in groundwater was slightly higher than that in river water and surface water. The nutrient distribution in the fjord also reflects the strong signature of groundwater inputs, while the contribution of the river is smaller.
4 Discussion
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4.1 Flushing time in the upper Kongsfjorden
In order to estimate the SGD flux, it is necessary to know the water age of the fjord. Flushing time can provide a timescale for the accumulation of components in the water column. Assuming that the influence of the wind is neglected, we concerned the water volume in the upper 10 m layer above the thermocline, and the flushing time is only affected by the tide and the fresh water from the land. The flushing time (T f , d) in the bay area can be expressed by the equation modified from Sanford et al. (1992) as follows:
$ {T_f} = \frac{V}{{(1 - b)\dfrac{P}{T} + {D_{{\mathrm{RIV}}}} + {D_{{\mathrm{GLA}}}}}} ,$
$ P = \int_H^0 {A{\rm d}z} ,$
where V is the volume of the bay of 2.75 × 109 m3, T is the tidal period of 0.52 d (data from https://www.tide-forecast.com/). P is the tidal prism from ebb tide to high tide bay calculated by Eq. (2), which is 5.50 × 108 m3. b is the return flow portion from the open-sea water. A is the water surface area of the study region of 275 km2 (Yang et al., 2022), and z is the water depth within the tidal range (H = 2.0 m; Sinha et al., 2017). ${D_{{\mathrm{RIV}}}}$ and ${D_{{\mathrm{GLA}}}}$ refer to the flows of the Bayelva River and glacier melt water during the sampling period, which are 8.18 × 104 m3/d and 1.73 × 105 m3/d, respectively (Torsvik et al., 2019; Zhu et al., 2016). Based on the assumptions similar to those of Moore et al. (2006), b can be estimated by the average salinity of the surface water in the Kongsfjorden divided by the salinity of open-sea water, and the value is obtained to be 0.93 here. The method is based on the physical renewal capability of the bay water (Baléo et al., 2001; Geyer et al., 2000) and obtains a single value rather than a different age range for each point. Then, we calculated the flushing time of the bay to be (39.1 ± 8.3) d.
4.2 Radium isotopes mass balance model
Here we used the Ra mass balance model that is based on the balance of Ra sources and sinks to obtain SGD flux. As mentioned above, a thermocline is observed in the Kongsfjorden, thus to make it more accessible and to emphasize the importance of SGD, the upper 10 m layer was used as the research object. Besides, Ra-traced SGD flux in coastal zones generally represents groundwater from shallow aquifers (Garcia-Orellana et al., 2021), and this is another reason why we chose the upper layer for our calculations. In our study area, the major inputs of Ra are from SGD, river, desorption of and glacial melt water, while the major output included two main processes: mixing between fjord water and open seawater and radioactive decay. If it is assumed that the system is in a steady state condition, the Ra mass balance model can be described as follows:
$ {F_{{\mathrm{RIV}}}} + {F_{{\mathrm{DES}}}} + {F_{{\mathrm{SGD}}}} + {F_{{\mathrm{GLA}}}} = {F_{{\mathrm{MIX}}}} + {F_{{\mathrm{DEC}}}}, $
where $ {F_{{\mathrm{RIV}}}} $, $ {F_{{\mathrm{DES}}}} $, $ {F_{{\mathrm{SGD}}}} $, $ {F_{{\mathrm{GLA}}}} $ and $ {F_{{\mathrm{DEC}}}} $represent the fluxes of Ra entering the bay through rivers, desorption of suspended particulate matters, SGD, glacial melting and decay losses, respectively. $ {F_{{\mathrm{MIX}}}} $ represents the output of Ra via mixing with open sea water. $ {F_{{\mathrm{DEC}}}} $ is ignored here due to the short time scale in the sampling period. After all other Ra isotope sources and sinks in Eq. (3) are available, the $ {F_{{\mathrm{SGD}}}} $ can be calculated. And then SGD fluxes can be calculated by selecting the appropriate groundwater endmember as follows:
$ {\text {SGD}} = \frac{{{F_{{\mathrm{SGD}}}}}}{[{{{\mathrm{Ra}}_{{\mathrm{SGD}}}]}}}, $
where $ [{\mathrm{Ra}}{_{{\mathrm{SGD}}}}] $ represent the appropriate groundwater endmember activity.
4.2.1 The major input of Ra isotopes into the upper Kongsfjorden
Ra from river input can be an important source and is usually estimated by multiplying the river flow by the Ra activities in the river water endmember. In the present study, the measured 226Ra and 228Ra activities were comparable to other Arctic rivers (Bullock et al., 2022). Therefore, with the activities measured in river water, the dissolved 226Ra and 228Ra fluxes from the river into the upper Kongsfjorden were calculated to be (0.22 ± 0.023) × 106 Bq/d and (0.29 ± 0.035) × 106 Bq/d, respectively.
Ra from desorption of suspended particulate matters in mid-salinity carried by rivers also contributed to dissolved radium in the upper water. The concentration of suspended particulate matter in the Bayelva River during our sampling period is 103 mg/L (Zhu, 2022). Based on the results of desorption experiment, the activity of 226Ra and 228Ra desorbed by particle matters is (0.20 ± 0.16) Bq/g and (0.18 ± 0.14) Bq/g. By multiplying the activity of desorbed radium with the sediment runoff of 8.42 × 103 kg/d, the desorbed radium flux input by the Bayelva River can be calculated as (0.17 ± 0.14) × 107 Bq/d for 226Ra and (1.49 ± 0.96) × 106 Bq/d for 228Ra.
The local geologic structure is permeable (Zhu et al., 2016), a portion of glacial meltwater in summer flows into rivers and tectonic layers of permafrost and drains into bays (Charkin et al., 2011), and the other part is directly discharged into the fjord through the active part of the glacier front. The meltwaters from Kongsbreen and Blomstrandbreen input into the fjord is about 1.73 × 105 m3/d (Torsvik et al., 2019). The activities of 228Ra and 226Ra from meltwater are (6.42 ± 0.27) Bq/m3 and (0.50 ± 0.058) Bq/m3 (Linhoff et al., 2020). So the Ra fluxes from meltwater can be calculated as (0.86 ± 0.10) × 106 Bq/d for 226Ra and (1.11 ± 0.46) × 107 Bq/d for 228Ra.
4.2.2 The major output of Ra isotopes into the Kongsfjorden
The Ra loss of exchange between open-sea water and the inner bay water is an important Ra sink in the bay. The loss of Ra via mixing with open seawater is described by Eq. (5) (Kim et al., 2011; Luo et al., 2014):
$ {F_{{{{\mathrm{MIX}}}}}} = \frac{{{{Ra}} - {{Ra}}_{{\rm{O}}} \times b - (1 - b) \times {{Ra}}_{{\rm{RIV}}}}}{{{T_f}}} \times V, $
where Ra is the average Ra activities (Bq/m3) measured in bay water, for 226Ra and 228Ra, the values were (2.52 ± 0.24) Bq/m3 and (2.33 ± 0.32) Bq/m3, respectively. Ra O and Ra RIV are the Ra activities (Bq/m3) measured in open-sea water and river water, respectively. With other parameters mentioned above, the mixed loss fluxes ( ${F_{{\mathrm{MIX}}}} $) of 226Ra and 228Ra in Kongsfjorden were (0.33 ± 0.12) × 108 Bq/d and (0.38 ± 0.083) × 108 Bq/d, respectively.
4.2.3 SGD flux in the upper Kongsfjorden
Based on the Ra isotopes mass balance model, the 226Ra and 228Ra fluxes through SGD input can be determined to be (0.30 ± 0.11) × 108 Bq/d and (0.25 ± 0.068) ×108 Bq/d, which accounted for approximately 91.4% and 65.7% of the total sources into the upper Kongsfjorden, respectively. Commonly, the selection of an appropriate end-member is the main source of uncertainty in SGD estimates (Burnett et al., 2008; Cho and Kim, 2017; Cerdà-Domènech et al., 2017). In this study, although only two coastal groundwater samples were obtained, considering the high 226Ra and 228Ra activities in groundwater, they both have the potential to be the significant Ra source to coastal water. At the same time, the groundwater sampling stations are located within 50 m offshore and are located in the area where the permafrost is active in summer, so the permafrost and glacier will melt in a large area during our sampling period (McGovern et al., 2022), which provides a conduit between the coastal aquifer and the fjord and then promotes the SGD. Thus, our limited groundwater samples are also representative to a certain extent. In order to avoid the uncertainty caused by the difference between the endmember values, we use high value (conservative value) to represent the general level of coastal groundwater. The groundwater endmember values were (8.62 ± 0.28) Bq/m3 for 226Ra and (19.2 ± 0.37) Bq/m3 for 228Ra. Then, according to Eq. (9), the SGD fluxes are calculated to be (3.45 ± 0.39) × 106 m3/d and (1.28 ± 1.01) × 106 m3/d by 226Ra and 228Ra, respectively. SGD fluxes calculated by different methods are within the same order of magnitude. Therefore, SGD fluxes ranged from 1.28 × 106 m3/d to 3.45 × 106 m3/d, with an average of (2.37 ± 0.70) × 106 m3/d. We can see that SGD fluxes were ~29 times the flow of the local river and ~14 times the flow of the glacier meltwater during our sampling period. It should be noted that our estimated SGD flux is not just a freshwater flux, but a mixture of seawater and terrestrial water mixtures from the coastal aquifer.
Generally, different subterranean estuaries have different forcing conditions, such as tides, waves, freshwater gradients, density gradients, and seasons (Michael et al., 2005; Santos et al., 2012). We summarized the typical SGD fluxes entering the coastal regions in different parts of the Arctic (the details are shown in Section 4.4), indicating that the SGD rate in Kongsfjorden is within the SGD rates of the Arctic coastal system. Due to the special form of groundwater in the Arctic, tidal range research in the study area is relatively small, and the melting of the permafrost and glaciers in summer is intensifying. Arctic glacial meltwater can be transported from the near shore to the central area of ​​the Arctic Ocean, one part is directly entering the ocean, and the rest of it can be infiltrated into the aquifers and enter the ocean as groundwater (Kipp et al., 2018), so parts of the estimated SGD flux overlaps with glacier meltwater discharge, but it is difficult for us to quantitative separate from them. Therefore, the SGD in the coastal areas of the Arctic Ocean occurs primarily during the summer, and, undoubtedly, the SGD flux is also very sensitive to the effects of global warming in the Arctic region.
In this study, all the uncertainties are estimated based on the errors of the measured data, and then the basic rules of error propagation are widely used to estimate the uncertainties in SGD (Sadat-Noori et al., 2015). From the Ra isotope mass balance model, many factors affect the SGD calculation. Changes (10%) in our estimated flushing time resulted in 11.0%−13.4% uncertainty in SGD flux estimates, indicating that flushing time in the upper Kongsfjorden is still sensitive to SGD flux calculations. Furthermore, the river input does not strongly affect the Ra mass balance model due to its low value. Besides, SGD flux calculation is usually sensitive to Ra activity in coastal groundwater. In the present study, if activities of 226Ra and 228Ra in coastal groundwater endmembers changed by 10%, it would result in SGD uncertainty of 9.1%−11.1%. Sampling from aquifers of different geological formations results in variations in endmember values, so it is normal to observe variations of tens of Bq/m3 in the Ra activity of groundwater. Meanwhile, it shows that SGD flux in such a typical Arctic fjord remains at a relatively high level, which needs more attention from scientists.
4.3 SGD impacts the nutrient budget in the upper Kongsfjorden
4.3.1 SGD-derived nutrient fluxes
Previous studies have shown that SGD is a significant source of nutrient in the coastal waters (e.g., Oehler et al., 2018; Santos et al., 2021). Even a small volumetric SGD will also transport high-flux nutrient, thus resulting in important ecological and environmental effects. The classical method of SGD-derived nutrient fluxes was multiplying the SGD flux by the nutrient concentrations in the groundwater endmember, which has been widely used in previous studies (Kim et al., 2005; Luo et al., 2014; Luo and Jiao, 2016; Moore et al., 2006; Wang et al., 2017, 2018). So to obtain a comparable estimate of nutrient from SGD inputs to the Kongsfjorden, we also use the typical approach in our study. The nutrient concentrations selected in the coastal groundwater endmembers ranged from 5.76 μmol/L to 63.7 μmol/L, 0.23 μmol/L to 0.37 μmol/L and 8.02 μmol/L to 48.8 μmol/L, for DIN, DIP and DSi, respectively. The SGD-derived nutrient fluxes were calculated to be 0.14 × 105 mol/d to 1.51 × 105 mol/d for DIN, 5.55 × 102 mol/d to 8.74 × 102 mol/d for DIP and 0.19 × 105 mol/d to 1.16 × 105 mol/d for DSi, respectively.
4.3.2 Budgets of DIN and DIP in the upper Kongsfjorden
The Arctic region is less directly disturbed by human activities and is more sensitive to environmental changes. Global warming will lead to increased melting of glaciers and frozen soil in the Arctic region, causing SGD changes and their potential impacts on the offshore ecological environment and need to be studied urgently. Generally, river runoff, atmospheric deposition, etc., have long been recognized as major sources of nutrient in coastal areas (Berelson et al., 1998; Wang et al., 2018). The Arctic region is affected by global warming, we need to consider the impact of nutrient transported by the melting of floating ice and glacier. In order to better evaluate the nutrient level of the Kongsfjorden, we established the DIN and DIP budgets in upper 10 m water by considering the impact of SGD (Fig. 5).
Riverine nutrient fluxes into the coastal area are regarded as a crucial source for bay ecosystems (Jickells, 1998). The nutrient fluxes delivered by the river were estimated by multiplying the river discharge by the concentrations of the nutrient in the river water endmember. The measured nutrient concentrations for DIN and DIP in the Bayelva River were 11.8 μmol/L and 0.33 μmol/L, resulting in the riverine DIN and DIP fluxes being 9.67 × 102 mol/d and 27 mol/d, respectively.
Due to the influence of global warming and the North Atlantic Current, a large area of floating ice and glacier melted during the sampling period, the melting of floating ice also transported a certain amount of nutrient. The floating ice area of Kongsfjorden is 1.05 × 107 m2, and the nutrient concentrations in the floating ice meltwater were 0.53 μmol/L for DIN and 0.02 μmol/L for DIP (Zhu et al., 2016). The melting rate of the floating ice was 0.44 cm/d (Hop and Wiencke, 2019). The nutrient fluxes through the floating ice meltwater were estimated to be 2.46 × 102 mol/d and 9.22 mol/d for DIN and DIP, respectively. In addition, the DIN and DIP concentrations in glacier meltwater were 0.42 μmol/L and 0.02 μmol/L, respectively. Thus, DIN and DIP fluxes from the glacier meltwater were estimated to be 73.1 mol/d and 3.46 mol/d, respectively.
Another traditional source of nutrient is atmospheric deposition. Nutrient fluxes through atmospheric deposition were estimated by multiplying the area of the Kongsfjorfen with nutrient deposition rates. The average atmospheric deposition fluxes of DIN to the entire Arctic Ocean to be 3650 kg/(hm2·d) (in terms of N) (Stewart et al., 2014). The Kongsfjorden is adjacent to the Arctic Ocean, we substituted atmospheric deposition fluxes in the Arctic Ocean for those in the Kongsfjorden. Therefore, the DIN fluxes through atmospheric deposition in the Kongsfjorden were estimated to be 4.09 × 104 mol/d.
In general, mixing loss to the open sea and absorption by phytoplankton have been recognized as the main sinks of nutrients in coastal regions (Chen et al., 2020; Peng et al., 2021; Wang et al., 2014). The output fluxes through those processes are shown in Fig. 5.
In the process of glacier melting in summer, glacial meltwater has a significant impact on the growth of phytoplankton in the Kongsfjorden (Piquet et al., 2014). Seasonal changes in glacier melting have changed the distribution characteristics of phytoplankton, leading to changes in nutrient structure in Kongsfjorden. The primary productivity of Kongsfjorden in summer is 700 mg/(m·d) (in terms of C) (Kim et al., 2020), the nutrient fluxes through absorption by phytoplankton were estimated to be 1.30 ×106 mol/d and 4.45 ×104 mol/d, respectively.
The change of tide leads to the mixing of the inner bay water and open-sea water, which results in the loss of nutrient. The Arctic Ocean has been considered the main nutrient sink. Nutrient fluxes via mixing losses were calculated by the method adopted from Chen et al. (2018). In this study, the mean DIN and DIP concentrations in surface water were 6.81 μmol/L and 0.279 μmol/L, respectively, while DIN and DIP concentrations in open-sea endmember were 4.53 μmol/L and 0.205 μmol/L, respectively. So the fluxes of DIN and DIP through mixing loss were calculated to be (1.60 ± 0.34) ×105 mol/d and (5.19 ± 1.11) ×103 mol/d, respectively. In contrast to SGD, the nutrient fluxes through mixing losses correspond to the major portion of the SGD-derived nutrient fluxes.
The nutrient budgets in the Kongsfjorden indicated that SGD accounted for 24.5%−78.1% of DIN and 93.3%−95.7% of DIP input and we can see SGD was the dominant nutrient source for this fjord. Besides, riverine input contributed 0.5%−1.7% of DIN and 3.0%−4.6% of DIP. Therefore, nutrient through river was negligible compared to those from SGD. In addition, we also found that the total sources were lower than the sinks, indicating that some sources in the system were not considered, such as the degradation of organic matter, which provided the material basis for nutrient.
4.4 Comparison of SGD cases around the Arctic Ocean
The scale of SGD studies varies greatly, most of those have focused on fluxes and related solutes in some regions, such as beaches, bays or estuaries (Dimova and Burnett, 2011; Knee and Paytan, 2011; Santos et al., 2021; Taniguchi et al., 2003). Some studies attempted to quantify SGD from large-scale sea areas and the model of global SGD to the ocean has become a research hotspot in recent years (Moore, 2010; Kwon et al., 2014; Santos et al., 2021). These large-scale studies basically focused on the North Atlantic basin and other easily accessible ocean basins, while the most extensive studies also ignored the Arctic Ocean in their calculations (Charette et al., 2013; Kwon et al., 2014). Despite the Arctic covering an area of about 3 × 1013 m2, the research on SGD has been only limited.
In recent years, studies on SGD flux in polar regions have been increasing. Some studies were based on coastlines, Frederick and Buffett (2015) indicated that SGD flux in the Mackenzie River Mouth was 0.16−0.38 m3/(m·d). Walvoord and Striegl (2007) found that SGD flux in the Yukon River Basin accounted for 31%−38% of the local river. For an all-around comparison, we summarized all study cases with specific SGD flux in the Arctic region to date (Fig. 6). According to the distribution of SGD cases, we found that most of those were concentrated in Alaska, and there were fewer studies in other places (Fig. 6a). In the Arctic region, the SGD rate has an extensive range from 0.01 cm/d to 187 cm/d. In the present study, the SGD rate in the Kongsfjorden was inside this wide range, and ever larger than the median value. But the value is much smaller compared to that in the Kasitsna Bay [(187 ± 67) cm/d], mainly on account of high tidal pumping effects, precipitation and topographic undulation (Lecher, 2015). Compared with the Cambridge Fjord of the same type, the SGD rate in Kongsfjord is much larger than that estimated in 1984, which may be mainly because of the global warming in the last 20 years, and then indirectly led to the increase of SGD (Hay, 1984). Furthermore, the SGD rate shows a slightly increasing trend with the increase of years, which may be due to the enhanced flow as groundwater flow paths are activated between land and coastal waters as a result of the warming climate and accelerated permafrost thawing (Duan et al., 2017; Guimond et al., 2022; Jacques and Sauchyn, 2009; Walvoord et al., 2019). It is worth noting that climate warming leads to rising sea levels, which have the potential to alter land-sea hydraulic gradients, leading to complex interactions that may control future coastal groundwater discharge dynamics along the Arctic coastline (Guimond et al., 2022). Studies have shown that coastal groundwater discharge will increase by 58% by 2100, due to the formation of supra-permafrost aquifers that enhance the ability to deliver fresh water to coastal areas (Guimond et al., 2022; Michael et al., 2005).
The surface water of the Arctic Ocean contains a large amount of fresh water, changes in the inventory of fresh water in the Arctic Ocean have been particularly dramatic in recent decades, with important implications for global climate (Bridgestock et al., 2021b; Carmack et al., 2016; Rabe et al., 2014). Riverine input is the crucial source of fresh water in the Arctic Ocean, the flux was 4200 ± 420 km3/yr, which contributes to 11% of the global rivers (Haine et al., 2015; Rosén et al., 2015). The distribution of fresh water within the Arctic Ocean is further controlled by seasonal sea ice melting and changes in wind-driven circulation (Morison et al., 2012; Rosén et al., 2015). However, previous studies only focused on the importance of riverine input on fresh water supply in the Arctic Ocean, but usually overlooked the impact of coastal groundwater input. With global warming, rising sea levels and accelerated thawing of permafrost, the SGD would act as an increasing role on hydrological and nutrient cycles in the Arctic Ocean.
4.5 Eco-Environmental impacts of SGD-derived nutrient in the Kongsfjorden
Significant increases in N and P loads entering the bay can lead to an enhancement of phytoplankton biomass or ecosystem damage, such as dissolved oxygen consumption (McCoy et al., 2011), red tide (Lee et al., 2010; Luo and Jiao, 2016) and eutrophication (Hwang et al., 2005), thereby affecting global nutrient cycling (Glibert et al., 2008; Santos et al., 2021; Slomp and Van Cappellen, 2004). In the Kongsfjorden, we observed a relatively higher NIN/DIP molar ratio varied from 24.6 to 173 (average value: 98.8) in coastal groundwater than that in surface water and river water, which were 67.1 and 36, respectively (Fig. 7). Since the NIN/DIP molar ratio is often used to assess potential constraints in primary production, high NIN/DIP molar ratios in groundwater may force primary production conditions from N limitation to P limitation and affect microalgae community composition in the coastal areas (Lee et al., 2010; Su et al., 2011). The input of groundwater with a high NIN/DIP molar ratio along the coastal zones of the Kongsfjord may modify the nutrient structures and then influence the marine ecosystem. In addition, the dominant picophytoplankton in the Kongsfjorden was cryptophyta/cyanobacteria and glacial meltwater had a significant impact on the growth of this phytoplankton in the Kongsfjorden (Piquet et al., 2014). In late spring, the meltwater input caused the stratification of surface waters in the fjord. Therefore, a large amount of SGD input with a high NIN/DIP molar ratio has the potential to increase the biomass and then change community structure of phytoplankton in the fjord water, thus it is needed to be considered.
Rising temperatures in the Arctic Ocean have led to glacier reducing, permafrost melting and river flows increasing, which together alter the nutrient and carbon cycles on the vast Arctic continental shelf (Kipp et al., 2018). In the Arctic Ocean, net primary productivity is controlled by a complex interplay of light and nutrient provided by upwelling and lateral inflow from adjacent oceans and land (Terhaar et al., 2021). The input of terrigenous nutrient is a crucial process affecting the future evolution of net primary productivity in the Arctic Ocean. Up to now, we usually ignored the role of SGD-derived nutrient on the Arctic net primary productivity. Due to the unique geography of the Arctic Ocean, SGD would be a greater impact on marine net primary productivity than other ocean regions (Lewis et al., 2020; Terhaar et al., 2021). We summarized the data on Arctic Ocean net primary productivity from 2000 to 2017 and found a significant increase (approximately 42%) of net primary productivity in the Arctic Ocean. The increase in net primary productivity during 1998−2008 was due to widespread sea ice loss, which resulted in an increase in open water and a longer growing season for phytoplankton. But the subsequent increase in net primary production is mainly due to an increase in phytoplankton biomass, which must be sustained by providing more extra nutrient to the system (Arrigo and van Dijken, 2011; Lewis et al., 2020; Zhang et al., 2010). Overall, the trend of increasing net primary production in the Arctic Ocean showed a very similar trend to the increasing SGD rate sorted by years around the Arctic Ocean (Fig. 6), suggesting that SGD has the potential to enhance the net primary production in the Arctic Ocean. To the extent that the increase in nutrient supplies is driven by processes associated with climate change, such as SGD and glacial meltwater, and the Arctic Ocean may support higher nutrient level production in the future.
5 Conclusions
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In the high latitude bay of the Kongdfjorden, we used a mass balance model based on radium isotopes, to assess the environmental impact of SGD under the influence of global warming. SGD and it derived nutrient fluxes into the Kongsfjorden were quantified for the first time. SGD flux was calculated to be (2.37 ± 0.70) × 106 m3/d, which was 29 times the flow of the local river. The estimated nutrient fluxes derived by SGD were 0.14 × 105 mol/d to 1.51 × 105 mol/d for DIN, 5.55 × 102 mol/d to 8.74 × 102 mol/d for DIP and 0.19 × 105 mol/d to 1.16 × 105 mol/d for DSi, respectively, which were three orders of magnitude higher than the riverine inputs. The high NIN/DIP molar ratio by SGD (98.8) was significantly higher than that in surface water (67.1). Such high ratios can heavily impact the ecosystem by changing the biomass and community structure of phytoplankton following accelerating global warming. The form of SGD in the Arctic is unique, with global warming causing permafrost to melt faster, seep down into aquifers and discharged into the coastal region as groundwater. SGD in the Arctic is discharged in a similar proportion to river water, which means that in a rapidly changing climate, SGD may play a significant role in transporting solutes to the Arctic Ocean, which may be an important reason for the increase in net primary productivity in the Arctic Ocean in recent years.
Acknowledgements
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We greatly appreciate the staff at Kingsfjorden for their assistance during the sampling period.
Funding
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  • The National Natural Science Foundation of China under contract Nos 41976040, 41676188, 42106043 and 42006152; the Innovation Base for Estuarine and Coastal Water Security 2.0 from the Ministry of Science and Technology of P.R. China under contract No. BP0820020.
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doi: 10.1007/s13131-024-2418-4
  • Receive Date：2024-07-05
  • Online Date：2025-11-19
  • Published：2024-10-25
Article Data
Affiliations
History
  • Received：2024-07-05
  • Accepted：2024-11-04
Funding
The National Natural Science Foundation of China under contract Nos 41976040, 41676188, 42106043 and 42006152; the Innovation Base for Estuarine and Coastal Water Security 2.0 from the Ministry of Science and Technology of P.R. China under contract No. BP0820020.
Affiliations
    1 College of Geography and Environmental Science, Key Laboratory of Tropical Island Land Surface Processes and Environmental Changes of Hainan Province, Hainan Normal University, Haikou 571158, China
    2 State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200241, China
    3 State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou 570228, China
    4 Shanghai Key Laboratory of Polar Life and Environment Sciences, School of Oceanography, Shanghai Jiao Tong University, Shanghai 200030, China
    5 MNR Key Laboratory for Polar Science, Polar Research Institute of China, Shanghai 200136, China
    6 Key Laboratory of Coastal Environment and Resources of Zhejiang Province, School of Engineering, Westlake University, Hangzhou 310024, China

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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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