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The Yellow River, originating from the Qinghai–Tibet Plateau and stretching from southwest to northeast, empties into the Bohai Sea in Kenli County of Dongying City ( Figure 1 ) (Cai et al., 2023). With a total length of 5,464 km and a drainage area of approximately 7.95 × 10⁵ km² (Yuan et al., 2024), the Yellow River discharged an annual average of 18.42 × 10⁹ m³ of water into the sea between 2008 and 2014 (Yan, 2019). The region has a warm temperate continental monsoon climate, characterized by gentler waves in summer due to mild southerly winds (3–6 m/s) and intensified wave activity in winter driven by stronger northerly winds (>10 m/s) (Wang et al., 2014). In this area, the tides are irregular semidiurnal, with coastal currents with velocities between 0.5 and 1.0 m/s. These currents exhibit a reciprocating pattern, flowing southeastward during flood tides and northwestward during ebb tides (Li et al., 2023). Since the 1950s, extensive dam construction has taken place in the Yellow River watershed, with over 3,100 reservoirs collectively boasting a capacity exceeding 72 × 10⁹ m³. These reservoirs play a pivotal role in regulating water flow and mitigating sedimentation issues in the Yellow River basin (Lu et al., 2022). Although the expansion rate of the current Yellow River delta has gradually slowed down due to decreases in sediment discharges, the Yellow River delta still covers an area of 5,113 km² (Liu et al., 2020b). The main channel was artificially moved northward from the Qingshuigou waterway to Qingbacha in 1996, forming the current YRE between Bohai Bay and Laizhou Bay (Fu et al., 2021). Additionally, the estuarine distributary mouths have undergone notable shifts in recent years, exhibiting a distinct seaward extension (Li et al., 2023).

High-resolution surface reflectance images, including Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI acquired from the Google Earth Engine (GEE; https://earthengine.google.com/), plus HJ-1A/B (Huanjing) CCD, HJ-2A/B CCD, and GF-1 (GaoFeng) WFV obtained from the China Centre for Resources Satellite Data and Application (CRESDA; https://data.cresda.cn/), were used to analyze the spreading dynamics of the YRP ( Table 1 ). A total of 26 high-quality scenes (i.e., cloud cover <10%, low tide level) covering the YRE, acquired both before and after the implementation of the WSRS, were selected for this study.

Long time series of daily runoff and sediment load data recorded at the Lijin Hydrological Station (2003–2023), the closest station to the YRE, were collected to analyze variations in water discharge and sediment supply influenced by the WSRS. To assess the effects of wind forcing and ocean current effects on the river plume, hourly sea surface wind data at a 0.125° × 0.125° grid resolution from the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis dataset (ERA5) were utilized, along with 3-hourly ocean surface currents derived from the global 1/12° product of the Hybrid Coordinate Ocean Model (HYCOM) surface product. These datasets have demonstrated high accuracy in the Bohai Sea region (Lv et al., 2014; Wang et al., 2016).

The ocean color signal of river plumes, often characterized by high turbidity, is typically well correlated with surface salinity, which serves as a natural tracer of freshwater plumes (Binding and Bowers, 2003; Molleri et al., 2010; Mendes et al., 2017). Among the visible spectrum bands available in Landsat imagery, the Rrs645 band is more suitable for mapping the YRP due to its strong correlation with river discharge and its high sensitivity to river plume dynamics (Aurin et al., 2013; Fernández-Nóvoa et al., 2015; Guo et al., 2017; Maciel et al., 2021). Thus, a red band threshold approach was adopted in this study to detect the plume area, with a threshold value of 0.14 determined based on the findings of Chang et al. (2022). Through visual inspection, it is evident that our method effectively captures plume information ( Figure 2 ).

The plume area was calculated by counting the number of pixels with Rrs645 equal to or above the threshold and multiplying by pixel size. The workflow structure is illustrated in Figure 3 . The entire Landsat data processing was conducted using GEE, while the processing of CRESDA images was performed using ENVI 5.6.

Figure 4 presents the daily average runoff and sediment load recorded at Lijin Hydrological Station since 2002. The data reveal that the WSRS was generally implemented from mid-June, with the exception of 2003, when it commenced on September 6 due to unusual autumn floods (Yu et al., 2013b). The duration of the WSRS varied significantly across years, ranging from a minimum of 7 days in 2014 to a maximum of 20 days in 2011 and 2019 ( Figure 4c ).

The first sudden increase in discharge was observed around June 25 at the Lijin Hydrological Station, occurring 4 or 5 days after the implementation of the WSRS. This decay is attributed to the distance of approximately 800 km between Lijin station and Xiaolangdi (Li et al., 2017). Subsequently, the discharge at Lijin station increased steadily from less than 800 to an average of 3,500 m³/s, reaching its peak 10–15 days post-WSRS initiation. The high kinetic energy flow scoured the riverbed, leading to a significant increase in sediment concentration (Li et al., 2017). As a result, the sediment content at Lijin station rose sharply from 3 to approximately 20 kg/m³, reaching its first peak within 4 to 6 days. Then, the export of fine-grained sediment from the Xiaolangdi Reservoir during the sediment regulation period contributed to the formation of the second sediment peak around mid-July (Wang et al., 2017b).

The maximum water discharge, maximum sediment content, total water discharge, and sediment load to the sea during the WSRS varied significantly from 2003 to 2023 ( Figure 4c ). These variations were primarily influenced by the volume of water stored in the Xiaolangdi Reservoir and upstream reservoirs prior to the WSRS (Wang et al., 2017a).

As shown in Figure 5 , the spatial structure of the YRP exhibited significant interannual variability. Before the WSRS, the YRP occupied a relatively narrow stripe along the coastline, with its extension axis aligned with the estuary. The maximum seaward extension distance ranged from 3.70 to 16.36 km. After the WSRS, the plume morphology displayed considerable variation in horizontal scale, often characterized by a distinct fan-shaped diffusion extending 30° on either side of the river-to-sea extension line ( Figure 5a ) as the typical ideal, undisturbed pattern, similar to the prototypical large-scale plume described by Horner-Devine et al. (2015). Then, using it as a judgment criterion, the extracted plumes were further categorized based on the extent of lateral displacement of different plume areas. Based on the plume structure, after the WSRS, three major patterns of the YRP could be identified by satellite snapshots of turbidity images ( Figure 5 ): 1) Pattern I, prototypical spreading along the direction of river channel expansion, such as the plumes observed in 2003, 2008, 2009, 2014, 2021, and 2022; 2) Pattern II, rightward spreading toward Laizhou Bay, observed in 2007, 2011, 2019, and 2020; and 3) Pattern III, leftward spreading toward the Bohai Bay, represented by 2010, 2015, and 2023.

Among the three patterns described above, Pattern I (46.15%) occurred most frequently, followed by Pattern II (30.77%), while Pattern III (23.08%) was observed to have the lowest occurrence frequency. Plumes classified as Pattern I mainly extend along the direction of river channel expansion. A stronger buoyant flow could broaden the seaward extension distance, particularly in years with a single estuary. In such cases, the plumes exhibit a significant northeastward extension, reaching up to 24.06 km, as far as 119°25′E and 38°01′N. Pattern II plumes usually have a southeastward tongue in the front, with the southern boundary of the plume extending as far as 37°40′N. In contrast, Pattern III plumes extend entirely northwestward, with most of the plume water moving toward nearshore, accompanied by limited offshore extension. However, year 2010 was an exception, with the northernmost tip reaching 37°58′N, approximately 16.36 km from the estuary.

The time series of YRP areas ( Figure 6 ) revealed significant interannual variability in the plume both before and after the implementation of the WSRS. Before the WSRS, the average YRP value was 67.41 ± 25.27 km². The maximum area of the YRP could reach 117.47 km² in 2015, while the minimum area was only 18.27 km² in 2007. After the implementation of the WSRS, the plume area increased to 1.11–2.86 times its pre-WSRS size, with a sharp rise observed in 2010 when the area reached as high as 150.39 km². Notably, the plume area exhibits a slight interannual increasing trend both before and after the implementation of the WSRS.

Among many forcings influencing the dispersion and dynamics of river plumes, river discharge has commonly been recognized as the primary driver dominating river plume dynamics (Salcedo-Castro et al., 2023; Fu et al., 2024). Focusing on the YRP, previous studies have documented that river discharge mainly determined the plume diffusion area and controlled the plume temporal variation on seasonal and daily scales (Wang et al., 2011; Cheng et al., 2021b). As illustrated in Figure 7 , the significant correlation between the plume area and the total river discharge (R² = 0.45) indicated that upstream freshwater release also plays a major role in the significant interannual variations of the YRP. For instance, accompanied by a water discharge of 4.38 km³, the river plume increased sharply to 150.39 km² in 2010. However, the relationship between plume area and river discharge revealed here was notably weaker than those derived from daily-scale data analysis (Guo et al., 2017). We speculate that this discrepancy may be attributed to external interannual forcing factors such as wind and tides (Wang et al., 2011; Jia and Yi, 2023). Furthermore, the method used to extract the plume boundary may align more closely with the suspended sediment boundary, potentially leading to an underestimation of the waterflow’s effect on plum dispersion.

Focused on the significant interannual variations of the peak values and duration of the WSRS, no significant correlation was found between peak river discharge and plume area. In contrast, daily water discharge was significantly correlated with plume area (R² = 0.30). This finding suggested that, under the assumption of a constant total water discharge, impulsive delivery of water within a shorter duration may be more efficient in transporting plume waters further offshore.

Wind forcing is widely recognized as a critical factor influencing the plume structure and orientation (Chen et al., 2017). In summer, upwelling-favorable southerly and southeasterly winds prevail in the YRE; the northeastward Ekman transport pushed the low-saline water offshore, often extending to the central area of Bohai Sea in 2003, 2008, 2009, 2014, 2020, 2021, and 2022 ( Figure 8 ). This phenomenon revealed using satellite data here was consistent with previous model results (Cheng et al., 2021b; Jia and Yi, 2023). However, in other years, including 2007, 2011, and 2019, when the wind was similarly southerly and southeasterly oriented, the estuarine plume moved southward into Laizhou Bay. This exceptional feature was also noted by Cheng et al. (2021b), with potential driving forces including the Coriolis, buoyancy, or tide currents (Yang et al., 2017; Cheng et al., 2021b; Jia and Yi, 2023). Occasionally, easterly wind fields occurred in 2015 and 2023, transporting plume water onshore along the west coast of the Bohai Sea.

In addition to wind directions, wind speed significantly impacted the plume’s offshore spreading, similar to previous studies (Wang et al., 2008; Qin et al., 2023).

We observed that weak (<3.5 m/s) wind forcing favored plume offshore spreading, as seen in 2010, 2014, and 2015. On the contrary, strong (>5 m/s) winds tend to hinder the spreading of the YRP, thereby reducing its area. However, possibly due to the increased mixing and vertical extension of the plume water under high wind stress (Sandeep and Pant, 2019), no obvious relationship exists between wind speed and plume area.

To further clarify the favorable wind conditions for three YRP patterns, we used the wind rose plots to provide the overall view of the intensity and direction of the winds ( Supplementary Figure S1 ). Plumes of Pattern I occur mostly under low (<6 m/s) southerly and southeasterly wind forcing, with the occurrence frequency exceeding 60%. Low (<8 m/s) and variable wind forcing usually result in Pattern II plumes. The favorable wind conditions for Pattern III are the easterly and southeasterly winds. However, years with special wind fields existed in any patterns of plumes: 2003 in Pattern I, 2011 in Pattern II, and 2023 in Pattern III. Winds in those years share similar characteristics: they were all strong (>10 m/s), in association with plume-oriented wind forcing. Thus, consistent with the study of Chen et al. (2017), we speculate that the strong wind forcing caused by episodic weather events may significantly affect the direction of the plume expansion.

Furthermore, based on the Finite Volume Coastal Ocean Model (FVCOM) three-dimensional model, Qin et al. (2023) demonstrated that intensifying winds drive a counterclockwise rotation of the YRP dispersion, shifting its trajectory from south to north. Our satellite observations align with this mechanistic understanding, as shown in Supplementary Figure S1 , which revealed that wind speeds in the YRE were significantly higher during Pattern I plume events compared to Pattern II conditions. It should be noted that critical wind speed thresholds governing plume modality transitions may vary substantially across estuarine systems. Such thresholds remain to be quantified for estuaries with distinct geometric configurations and boundary conditions.

In the previous sections, we mainly focused on the effect of river discharge and wind, which have commonly been recognized as the most important forcing mechanisms, on the dispersal of river plumes (Osadchiev et al., 2021; Machaieie et al., 2022; Salcedo-Castro et al., 2023). External forcing such as the geomorphology of river mouth (Lee and Valle-Levinson, 2013), coastal currents (Wang et al., 2008; Wang et al., 2010b; Ding et al., 2017; Xu et al., 2019), and waves (Jia and Yi, 2023) also influences the spatial and temporal dispersion of river plumes in the ocean (Horner-Devine et al., 2015; Zhi et al., 2022).

The YRE experienced dramatic morphological evolution (Ji et al., 2018), which proved to be a key parameter in determining the structure and scale of river plumes (Lai et al., 2015; Cole and Hetland, 2016). As shown in Figure 5 and Supplementary Figure S2 , in response to the dramatic evolution of the mouth channel and bar, before the WSRS, the plume fronts generally propagated offshore along the direction of channel expansion. This includes the eastward fan-shaped pattern observed in 2003, 2007, and 2008; the northeastward expansion structures from 2009 to 2015; and the bimodal structure (one extending toward the southeast and the other toward the northeast) observed since 2019. The geometric shape of the mouth bar controlled the spatial extension of the turbid plume along the shoreline. Moreover, the plume spread more offshore in the northeastward channel. Lee and Valle-Levinson’s (2013) work indicated that the direction of a submarine channel influenced plume characteristics with an ocean circulation model; the phenomenon observed confirmed this issue. However, after the WSRS, in addition to the Pattern I plume, the plume structures were no longer governed by estuarine morphology. Instead, the dispersion pattern of the plume was shown to be more complex and diverse, indicating the influence of estuarine morphology weakened under the impact of extreme freshwater discharge events.

Coastal currents are a significant forcing for nearshore sediment transport (Liu et al., 2020a; Li et al., 2021). The simulated current from the HYCOM showed that coastal circulation off the estuary generally flows northward and parallel to the coastline but exhibited significant interannual variations in current speed ( Figure 9 ). In all years, except 2008, 2009, 2014, and 2015, the distribution of the river plume was mismatched with the current field. This implied that the impact of coastal currents on the long-term variation of river plumes has been minimal, similar to that described by Chang et al. (2022). In addition, for the Pattern II and Pattern III plumes, the offshore dispersion of the YRP was significantly inhibited when coastal currents were strong. However, our study was unable to clarify the impact of hyperpycnal flows, which are triggered by high sediment concentrations and have been documented to significantly influence sediment dispersal patterns (Wang et al., 2010a; Wu et al., 2023) on the spatio-temporal variations of the river plume. Further in-depth research is needed to address this aspect in the future.

Waves and tides also are the two important ones affecting the transport of water and sediment, thus influencing the dispersion of river plumes (Cheng et al., 2023; Du et al., 2023). The roles they play in the interannual variation of river plumes under WSRS scenarios need further studies.