A cruise was conducted on R/V Runjiang I in the Changjiang Estuary from 17 August to 30 August 2020 ( Figures 1A, B ). Water samples were collected by a 10-L Rossette hydrophore fitted with a Sea-Bird 917 conductivity-temperature-depth (CTD) recorder. Nutrient and chlorophyll a (Chl a) samples were collected from Niskin bottles attached to the CTD rosette.

The mean monthly Changjiang discharge in July and August of 2020 was 72,722 m³ s⁻¹ and 60,600 m³ s⁻¹, respectively, which were higher than the 58,871 m³ s⁻¹ and 44,423 m³ s⁻¹ in July and August of 2019. The mean annual runoff was 11180 × 10⁸ m³ in 2020, which was 1.2 times that (9266  × 10⁸ m³) of the previous five years (from 2015 to 2019) ( Figure 1C ). Discharge data were collected at the Datong Hydrological Gauge Station (117.62°E, 30.76°N), which were typically used to represent the Changjiang discharge (Changjiang Water Resources Commission, 2022). The Datong Hydrographic Gauge Station is located in the lower reach of the Changjiang River—about 624 km upstream from the river mouth.

Dissolved inorganic nutrient samples were filtered by 0.45 μm cellulose acetate filters and stored frozen for later laboratory analysis. Concentrations of nitrate (NO₃ ⁻), nitrite (NO₂ ⁻), ammonium (NH₄ ⁺), phosphate (PO₄ ³⁻), and silicate [Si(OH)₄] were measured with an Auto Discrete Chemical Analyzer (Smartchem 600, AMS Alliance, Italy) in the laboratory by colorimetric methods, as described by Grasshoff et al. (1999). The detection limits for NO₃ ⁻, NO₂ ⁻, NH₄ ⁺, PO₄ ³⁻, and silicate were 0.02 μmol L⁻¹, 0.02 μmol L⁻¹, 0.30 μmol L⁻¹, 0.03 μmol L⁻¹, and 0.20 μmol L⁻¹, respectively. The precisions of NO₃ ⁻, NO₂ ⁻, NH₄ ⁺, PO₄ ³⁻, Si(OH)₄ measurements were ±0.1, ± 0.02, ± 0.1, ± 0.03, ± 0.18 μmol L⁻¹, respectively. In this study, the sum of NH₄ ⁺, NO₂ ⁻, and NO₃ ⁻ was considered as dissolved inorganic nitrogen (DIN). Chl a samples were filtered on a GF/F filter and stored at −20 °C, they were extracted with 10 mL of 90% acetone and measured using a Turner Designs 10-AU fluorometer according to the fluorometric acidification procedure. The detection limits and precisions of Chl a measurement are 0.025 μg L⁻¹ and 5%, respectively. Total suspended matter (TSM, mg L⁻¹) samples were filtered through pre-weight GF/F filters and rinsed with Milli-Q waters

In this study, the average monthly fluxes of NO₃ ⁻ from the Changjiang entering the estuary were calculated as follows:

where F is the Changjiang nutrients flux (mol d^―1) (NO₃ ⁻, PO₄ ³⁻, Si(OH)₄), C  is the average concentration (μmol L⁻¹) of nutrients in the Datong Hydrological Gauge Station (salinity=0), and Q is the average monthly discharge (m³ d⁻¹) of the Changjiang measured in the Datong Hydrological Gauge Station. The concentrations of NO₃ ⁻, PO₄ ³⁻, and Si(OH)₄ (C ) were 91.89, 0.74 and 115.70 μmol L⁻¹ in August 2020. The average discharge (Q ) of 2020 was 60,600 m³ s⁻¹, which was equivalent to 5.2 ×  10⁹ m³ d⁻¹. Hence, the flux (F ) of NO₃ ⁻, PO₄ ³⁻, and Si(OH)₄ in August 2020 were 4.8, 0.03, and 6.0 × 10⁸ mol d⁻¹, as calculated by Equation 1.

A three end-member mixing model was constructed to estimate the nutrient contributions of different water masses, and to distinguish the biological process-induced changes from the physical mixing process. Potential temperature and salinity (θ-S) were used to identify the characteristics of three water masses in the study area ( Supplemental Figure 1 , Gong et al., 1995; Cao et al., 2011). The mixing model was based on mass balance equations for potential temperature and salinity as follows:

where f ₁ , f ₂ , and f ₃ are the fractions of the end-members; θ ₁ , θ ₂ , and θ ₃  are the potential temperature of the three end-members; s ₁ , s ₂ , and s ₃ are the salinities of the three end-members, respectively; and θ  and S are the potential temperature and salinity of the samples.

The conservative nutrient concentrations by mixing of the end-member  (NUT _mix ) can then be calculated as follows:

where NUT ₁ , NUT ₂ , and NUT ₃ are the nutrient concentrations of the three end-members, respectively. NUT  is the nutrient concentration of the specific water sample, and ΔNUT is the difference between NUT  and NUT _mix , which reflects the amount of nutrients produced (positive) or removed (negative) associated with biological processes (Han et al., 2012). ΔNUT is used to estimate the biological carbon uptake (NCP _DIN ) in the euphotic zone according to Equation 7 (Wang et al., 2014a).

where  I _ΔDIN   is the inventory in the whole box calculated by Δ DIN data from 22 stations at transects B, A, J, and N (according to Wang et al., 2014a).  R _C/N   is the carbon to DIN stoichiometric ratio, which is assumed to be 6.6 in this study (Redfield et al., 1963). The area (A) in this study mainly covers the CDW (transects B, A, J, and N are covered, as seen in the white dashed rectangle in Figure 1 ), which coincides with the boundaries used by Wang et al. (2014a). The euphotic zone depth (Z_eu) is defined as a water depth with >1% available surface photosynthetic radiation, which is estimated from multi-year summer observational averaged data (Z_eu is defined as 7.7 m) (Li et al., 2021). The residence time (τ _DIN )  is calculated to be about 5–10 d, based on the trajectories of drifting buoys in the Changjiang Estuary (Zhang et al., 2020).

The extension of the CDW was observed during the cruise in August 2020. The CDW (S ≤31) widely distributed over the Changjiang Estuary and extended to outside the estuary under flooding conditions ( Figure 2A ). The salinity of surface waters was less than 31 in the whole study area, except for a few stations of transect C and transect D. Along the CDW extension, the main body of CDW mainly spread along transects J and A, and a low-salinity water patch (S ≤20) separated from the main body of the CDW along 122.5°E at station J3, with an area of ~120 km × 40 km covering stations J4, J5, and J7 ( Figure 2A ). As for the vertical profile, the CDW (S ≤31) occupied the space from nearly the surface to a depth of 15 m. At stations J1 and A1, the salinity of the entire water column were less than 31 ( Figures 2B, C ).

The surface nutrient distributions exhibited a tongue-like shape in the estuary, which was consistent with the distribution pattern of salinity. At the estuary mouth, nutrient levels were extremely high. The surface DIN, PO₄ ³⁻, and Si(OH)₄ were 88.70 μmol L⁻¹, 1.55 μmol L⁻¹, and 102.30 μmol L⁻¹ at B3, respectively. These values sharply decreased to 2.60 μmol L⁻¹, 0.03 μmol L⁻¹, and 2.70 μmol L⁻¹, respectively, to the south of the study area, which had a salinity of ~31. The extremely high nutrient concentrations in B3 were probably caused by inflow of the Changjiang. The relatively low nutrient and high salinity in the south area indicated that the Changjiang’s influence decreased.

At station J7 of low-salinity water patch, the surface DIN and Si(OH)₄ were 22.92 μmol L⁻¹ and 23.80 μmol L⁻¹, respectively. While, the surface PO₄ ³⁻ decreased to less than 0.10 μmol L⁻¹ ( Figures 3A–C ). Chl a concentrations in the low-salinity patch were high. The Chl a at station J3, J5 were 28.53 μg L⁻¹ and 29.62 μg L⁻¹, respectively ( Figure 3D ). The high Chl a and low phosphate in the patch indicated that the CDW nutrients could trigger significant phytoplankton bloom. The total sediment matter (TSM) was extremely high over a narrow area of estuary, where Chl a was relatively low, regardless of high nutrient concentration ( Figures 3D, E ). The high nutrients but low Chl a condition was probably caused by light limitation of algal growth.

In this study, observation results of the Changjinag Estuary in drought year 2006, non-flooding years (August 2009 and August 2021) and in flooding years (August 1998 and August 2020) are compared to reveal the difference of CDW extension and its effects on nutrient transport.

A salinity of 31 is typically used as a threshold in defining CDW (Pu, 1983). In our cruise area, as the boundary of 31 isohaline was not observed, a salinity of 26 was defined as the core zone of CDW (CDW_core) (Mao et al., 1963). Such a definition was also used by Beardsley et al. (1985); Zhou et al. (2009) and Li et al. (2021). The 26 isohaline (white dashed line in Figure 4C ) of the CDW_core in 2020 reached a farther easterly distance than that in drought year and non-flooding years (white dashed line in Figures 4E, G, I ), which was similar to that reported by Gong et al. (2011). The monthly averaged discharge for the flooding period was 60600 m³ s⁻¹ in August 2020, as recorded at the Datong Hydrological Gauge Station, which is ~1.5 times the multi-year mean discharge in non-flooding years (August 2013, 2017, 2018, 2019 and 2021) (Changjiang Water Resources Commission, 2022). It is reasonable that flooding intensified the CDW_core expansion by increasing the Changjiang runoff discharge, which was also observed in the Mississippi River plume and the Pearl River plume (Shi and Wang, 2009; Ren et al., 2020).

In addition, a low-salinity water patch (S ≤20) separated from the main body of the CDW_core. The area of the low-salinity water patch bound by the 20 isohaline in 2020 was ~102 km × 40 km, which was much larger than that in 2006 (33 km × 16 km) (Xuan et al., 2012). The monthly averaged discharge in August 2020 was ~2.4 times that in 2006, which suggested that increased runoff input under the flooding conditions resulted in a larger area of low-salinity water patch. Compared with the salinity of 1998, although the CDW_core covered a larger area in 1998 than in 2020, the 26 isohaline in 2020 moved farther north than that in 1998 ( Figures 4C, A ). In addition, the mean monthly discharge in August 1998 was 77332 m³ s⁻¹, which exceeded the water flux in 2020 (Changjiang Water Resources Commission, 2022). Previous studies showed that the northeastward extension of the CDW is resulted by south wind and northward intrusion of the Taiwan Warm Current (Chang and Isobe, 2003). While, the complex and dynamic nature of the Changjiang estuary made it hard to clarify the reason for different extension behaviors of the Changjiang Dillluted Water in 1998 and 2020. Unlike the characteristics of CDW extension in 1998, low-salinity water detachment occurred in 2020, and the CDW extended northeasterly in the form of a low-salinity water patch. The detachment of plume waters had been frequently observed in the CDW (Lie et al., 2003; Chen et al., 2008; Wei et al., 2021b), which was attributed to the influence of wind and current (Xuan et al., 2012). Detachment could be more favorable for offshore spreading compared with spreading of the main body of CDW (Xuan et al., 2021), which can explain the more northerly 26 isohaline in 2020 than in 1998.

However, the concentration of NO₃ ⁻ at Changjiang Datong Hydrological Gauge Station in August 2020 (91.89 μmol L⁻¹) was similar to the multi-year mean value (99.50 μmol L⁻¹) in non-flooding years (August 2013, 2017, 2018, 2019 and 2021). The flux of NO₃ ⁻ (4.8 × 10⁸ mol d⁻¹) in August 2020 calculated by Equation 1 was 1.4 times higher than the mean value in non-flooding years (3.3 × 10⁸ mol d⁻¹). The fluxes of PO₄ ³⁻ and Si(OH)₄ also increased, which were 1.6 and 1.4 times higher than the mean value in non-flooding years, respectively. It suggested that flooding increased the nutrient fluxes into the Changjiang Estuary.

Typically, nutrient levels decrease along the salinity gradient of the CDW and undergo rapid depletion after passing through the turbidity maximum zone (Zhang et al., 2007b; Chen et al., 2010). Nutrients of surface waters around 122.5°E decreased rapidly, DIN was ~10 μmol L⁻¹ in the vicinity of 123°E, 31–32°N in Figure 4F , in the vicinity of 123.5–124°E, 31–32°N in Figures 4H, J , and other non-flooding years (Liu et al., 2016; Xu et al., 2019). However, in this study, we found the waters near 124°E, 32°N could still maintain high levels of DIN and Si(OH)₄ (22.92 μmol L⁻¹ and 23.80 μmol L⁻¹ at station J7, respectively), which converged at the low-salinity water patch in August 2020 ( Figure 3 ). A high DIN concentration of 30.67 μmol L⁻¹ was observed outside the 123°E, 32°N region in flooding years ( Figure 4D ), whereas it was 15–20 μmol L⁻¹ around 123°E, 31–32°N in non-flooding years ( Figures 4H, J ), which suggested that flooding changed the distribution of DIN and Si(OH)₄ in the Changjiang Estuary. Such high levels of nutrients offshore transport was rarely reported (Wei et al., 2021b). As the CDW plume spread, the 10 μmol L⁻¹ isoline of DIN in 2020 (white dashed line in Figure 4D ) extended farther to the outer estuary compared to that in 2006, 2009 and 2021 (white dashed line in Figures 4F, H, J ). The DIN concentration in 2020 was about 25.0–30.0 μmol L⁻¹, located at the 10.0 μmol L⁻¹ isoline of DIN in 2006. The distribution of Si(OH)₄ was consistent with that of DIN ( Figure 3C ). In the flooding year of 1998, extremely high nutrient levels in the estuary and shelf waters were also observed Figure 4B which were similar to those in our study (Wang et al., 2003). It suggested that the high DIN and Si(OH)₄ offshore transport under flooding conditions could not be a coincidence.

A DIN front existed at the perimeter of the ~17 μmol L⁻¹ isoline and extended to 124°E, 31.5–32°N in 2020 (red line in Figure 4D ), whereas that in drought year 2006 existed around 123°E, 31.5–32°N, which coincided with the front of Si(OH)₄. Ocean front is typically a region characterized by an anomalous maximum in the horizontal gradient of some water property (e.g., temperature, salinity, nitrate) (Largier, 1993). In this study, DIN front is the location with the largest horizontal DIN gradient. A DIN front was also observed in Chen (2009) in the vicinity of the ~4 μmol L⁻¹ isoline, which existed at the ~8 μmol L⁻¹ isoline of DIN (123–124°E, 31.5–32°N) (Ye et al., 2020). In addition, a turbidity front was located west of 123°E, 31–32°N in 2020 ( Figure 3E ), which suggested the DIN front under the flooding conditions moved offshore beyond the turbidity maximum zone and extended farther than that in non-flooding years. Apart from flooding, such offshore extension of the nutrient fronts could also be partly attributed to low-salinity water detachment, as inferred from salinity distributions ( Figures 4C, D ).

To further verify the impact of low-salinity water detachment during flooding on the offshore transport of nutrients, we compared the DIN concentration of detached low-salinity water in 2020 with those of nearby station in 2006 (transects J and A). We found that the surface DIN concentrations at the detached low-salinity water patch and offshore stations affected by CDW extension (stations J7 and A9) were 22.92 μmol L⁻¹ and 9.00 μmol L⁻¹ (~177 km and ~190 km away from the coast) in 2020, respectively. These values were approximately 16 times and 6 times those at nearby stations in 2006 (1.40 μmol L⁻¹ at station L2-13 and 1.40 μmol L⁻¹ at station M2-12), respectively. Furthermore, the 30 μmol L⁻¹ isoline of DIN in 2020 was observed farther north relative to 1998, suggesting that detachment of low-salinity water patch possibly facilitated the northerly transport of nutrients (Wei et al., 2021b). Therefore, the high DIN and silicate offshore transports were the combined result of flooding and detachment, and it was hard to tell one influence from the other.

Unlike nitrate, PO₄ ³⁻ was depleted in the low-salinity patch. Low PO₄ ³⁻ concentrations were observed east of 123°E. The PO₄ ³⁻ front was also located at 123°E ( Figure 3B ). The PO₄ ³⁻ distributions were similar to previously reported results for flooding (Wang et al., 2003), non-flooding periods (Chen et al., 2011) and drought year (Wang et al., 2014a). The PO₄ ³⁻ should also be transported farther northeast, as indicated by the low salinity and high DIN distribution east of 123°E. Two reasons may explain the low PO₄ ³⁻ but high DIN we observed. Firstly, the Chl a concentration in the high-DIN/low-salinity patch was as high as 29.62 mg m⁻³. Strong biological uptakes of PO₄ ³⁻ by phytoplankton probably reduce PO₄ ³⁻ significantly (Tseng et al., 2014). As the riverine N/P ratio was as high as 60, excess DIN still existed. Secondly, PO₄ ³⁻ in the turbid estuary could be removed by particle adsorption (Shen et al., 2008). Such PO₄ ³⁻ adsorption capacity was strong at low salinity (<6), but it decreased with increasing salinity (Meng et al., 2015). The complicated mixing/adsorption behavior of PO₄ ³⁻ makes it hard to evaluate the contribution of inorganic PO₄ ³⁻ adsorption on PO₄ ³⁻ transport. The high DIN low PO₄ ³⁻ situation (N/P=307) also suggested limited PO₄ ³⁻ levels in the Changjiang Estuary, even with the strong nutrient transport as a result of flooding, which will be discussed in detail in section 4.3

The distribution of nutrients is mainly controlled by water mixing and biological processes along horizontal and vertical gradients, especially in the euphotic zone of the CDW. In this study, a three end-member mixing model is used to determine the contributions of different water masses to nutrient levels, and to distinguish the changes in nutrient levels induced by biological processes from those induced by physical mixing processes. We identified three water masses from potential temperature-salinity figure ( Supplemental Figure 1 ): The Changjiang Diluted Water, the colder Outer-shelf Deep Water (ODW), and the Outer-shelf Surface Water (OSW)—are the same as those used by Wang et al. (2014a) and Li et al. (2016).

The characteristics of the three water masses mentioned above are listed in Table 1 . The CDW end-member (CDW_end-member) data were obtained by averaging potential temperatures, salinity, and nutrients at the estuarine stations (122–122.5°E, 30.7–31.7°N). The OSW end-member (OSW_end-member) data were obtained by averaging parameters for offshore stations (123–124°E, 31°N) influenced by Kuroshio Surface Water and TWC Surface Water. The ODW end-member (ODW_end-member) data were obtained by averaging samples from either TWC bottom waters or Kuroshio Subsurface Water (123.5–124°E, 30–30.5°N) (Chen et al., 1995). The uncertainties of the nutrient deviation at stations (caused by uncertainties of parameters in the three end-members) were estimated using error propagation formulas (Taylor, 1997). In this study, the DIN deviation uncertainties [δ(ΔDIN)] varied from 1.14 to 2.66 μmol L⁻¹ for stations in the euphotic zone. The Si(OH)₄ deviation uncertainties [δ(ΔSi (OH)₄)] varied from 1.34 to 3.71 μmol L⁻¹ for stations in the euphotic zone. The solar heating will influence sea surface temperature, which produces bias in our model. The diurnal sea surface temperature in the East China Sea shelf in summer is in an order of 0.7–1.2°C (Tu et al., 2016), which is the upper limit of surface heating effect. In our model, even we assumed potential temperature uncertainties of 1.2°C ( Supplemental Table 1 ), nutrient uptake uncertainties created was less than the relative standard deviation of nutrient uptake values ( Supplemental Table 1 ). Therefore, the model result could be used to clarify the magnitude of nutrient uptake by phytoplankton.

The results of our model showed that the CDW_end-member was the main water mass regulating nutrients at the low-salinity water patch (123.5°E–124°E, 31.6°N–32.3°N), with a mean fraction of 0.67 ( Figure 5 ). The mean contributions of CDW_end-member to DIN, PO₄ ³⁻, and Si(OH)₄ were 48.23 μmol L⁻¹, 0.92 μmol L⁻¹, and 57.50 μmol L⁻¹, respectively, at the low-salinity water patch. In contrast, the contributions of CDW_end-member to DIN, PO₄ ³⁻, and Si(OH)₄ in similar regions in the summer of 2006 (drought year) were only 22.60 μmol L⁻¹, 0.41 μmol L⁻¹, and 22.60 μmol L⁻¹, respectively (Wang et al., 2014a). It suggested that CDW_end-member under flooding conditions contributed over twice as many nutrients compared to that under non-flooding conditions. Outside the estuary, CDW_end-member still played a dominant role in providing high nutrient levels. Even in the far east, the contributions of CDW_end-member to DIN, PO₄ ³⁻, and Si(OH)₄ in the surface waters were 47.03 μmol L⁻¹, 0.90 μmol L⁻¹, and 56.06 μmol L⁻¹ at station J7, respectively. Furthermore, the fraction of ODW_end-member was 0.82 in the water column from ~17 m to the bottom water ( Figures 2B , 5B ), which contributed 15.65 μmol L⁻¹, 0.84 μmol L⁻¹, and 22.05 μmol L⁻¹ to DIN, PO₄ ³⁻, and Si(OH)₄, respectively. The ODW brought benthic nutrients to refuel the water column at station J4, which could also consume oxygen and contribute to severe hypoxia in the ECS.

In the dynamic Changjiang Estuary, even the single water end-members could have difference ages (Gao and Zong, 2021). And it is hard to distinguish them in our end-member model. Thus the nutrient uptake we calculated represents its accumulations during the residence times in the estuary. According to the end-member mixing model, the values of ΔDIN  and ΔSi (OH)₄ were negative at the surface water, which suggested phytoplankton uptake of nutrients. The high Chl a of surface waters at J5 (29.62 mg m⁻³) also validated a strong nutrient uptake. Our model also showed that the minimum ΔNUT values (maximum absolute value) were distributed at the low-salinity water patch, which demonstrated that the nutrient delivery in flooding years indeed triggered strong phytoplankton blooms ( Figures 6 , 7 ). The model-derived biological DIN uptake was as high as 24.65 μmol L⁻¹ at the low-salinity water patch. We examined the NCP in the eutrophic zone based on Equation 7, using the model-derived biological DIN uptake. The inventory deviation of DIN (I _ΔDIN )  was 2.0 ×  10¹² mmol, which was calculated by using Z_eu and ΔDIN concentration. The residence time (τ _DIN ) was 5–10 d. When τ _DIN was 10 d, NCP _ΔDIN was 566 mg C m⁻² d⁻¹, as calculated by Equation 7, and when τ _DIN was 5 d, NCP _ΔDIN was 1131 mg C m⁻² d⁻¹. Our estimated biological carbon uptake (assessed by NCP) in the eutrophic zone was 566–1131 mg C m⁻² d⁻¹, whereas the NCP derived from DIN in 2006 was 465 mg C m⁻² d⁻¹ (Wang et al., 2014a), the NCP derived from Δ Si(OH)₄ is similar to that calculated based on ΔDIN. In 2020, the NCP _ΔSi(OH)4 is 933–1867 mg C m⁻² d⁻¹, which was also higher than that in 2006 (626 mg C m⁻² d⁻¹), which suggested that the detachment of CDW_end-member in flooding years probably increased the rate of biological carbon uptake.

At stations J4, J5, and J7, high N/P ratios (268, 307, and 229, respectively) were observed. The relatively low PO₄ ³⁻ concentration indicated PO₄ ³⁻ limitations in the low-salinity patch ( Figure 5A ). In subsurface waters, water-sediment nutrient exchange is an important PO₄ ³⁻ source in the Changjiang Estuary (Gong et al., 1996; Meng et al., 2015). If enough PO₄ ³⁻ was provided with the physical mixing of subsurface water, such as in typhoon mixing (Wang et al., 2017b) or upwelling mixing (Wong et al., 1991), the low-salinity water patch could possibly have greater phytoplankton blooms. Previous research has also demonstrated that organic phosphorus and PO₄ ³⁻ desorption from particles helps to alleviate the phosphorus limitation in the euphotic zone in the Changjiang Estuary (Froelich, 1988; Shen et al., 2008). In contrast, to the west of station J4, the nutrient depletion is minor. Zhang (2002) attributed the semi-conservative behavior of nutrients in the turbidity maximum zone to low primary production caused by limited light penetration. The turbidity front west of 123°E, 31–32°N in 2020 was most likely responsible for the positive ΔDIN  value relative to the east of 123°E.

Significantly higher measured concentrations of DIN and silicate than those measured in ambient water of the same depth suggested nutrient addition in bottom waters. ΔDIN  and  ΔSi (OH)₄ were positive in the water column from 17 m layer to the bottom water at station J4 ( Figures 6A, B ), which suggest excess DIN and Si(OH)₄ addition sourced from other process. Frequent hypoxia events were observed in the inner ECS shelf (Wang et al., 2017b; Zhu et al., 2017), which indicate continuous decomposition of organic matter. The denitrification and anammox could cause DIN lost in sediment, according to previous studies in the East China Sea shelf (Song et al., 2013; Liu, 2021). However, the effect of denitrification and anammox on DIN in water column should be minor even it diffuses to waters below the sediment. Thus, the excess DIN in bottom waters could most likely be sourced from the decomposition of organic matter falling from the productive upper layer (Anderson and Sarmiento, 1994; Chen et al., 1996b; Chen et al., 2021).

Low salinity waters have been found in large parts of the ECS in flooding years (Wang et al., 2002). Additionally, the low-salinity water detachment could enhance the offshore transport of nutrients. It was proved that about 70% of the discharge of the CDW flowed into the east Japan Sea (Chang and Isobe, 2003). Although PO₄ ³⁻ levels were low due to consumption by phytoplankton uptake at the low-salinity water patch, there were still high concentrations of DIN and Si(OH)₄. The residual nutrients carried by CDW have the potential for supporting high Chl a and NCP levels offshore, which could play an important role in regulating biogeochemical cycles in the vicinity of Korea/the Tsushima Strait even in the east Japan Sea (Kim et al., 2013; Chang et al., 2014).