Effects of wave-current interaction on the Pearl River Estuary during Typhoon Hato

Estuarine, Coastal and Shelf Science 228 (2019) 106364

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Effects of wave-current interaction on the Pearl River Estuary during Typhoon Hato

T

Yuren Chena,c, Lianghong Chena,c, Heng Zhanga,b,c,d,∗∗, Wenping Gonga,b,c,∗ a

School of Marine Science, Sun Yat-sen University, Guangzhou, 510275, China Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), 519000, China c Guangdong Provincial Key Laboratory of Marine Resources and Coastal Engineering, Guangzhou, 510275, China d Guangdong Provincial Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Guangzhou, 510275, China b

A R T I C LE I N FO

A B S T R A C T

Keywords: Typhoon Hato Wave current interaction Pearl river Recovery time COAWST

The response of the Pearl River Estuary (PRE) to Typhoon Hato (2017) and the effects of wave-current interaction (WCI) are evaluated by a three-dimensional wave-current coupling hydrodynamic model (COAWST). Typhoon Hato is one of the strongest tropical cyclones in over 7 decades: it struck southern China and caused immense destruction. Our model results show that the maximum storm surge near the western shore of the PRE increased by 20%–30% due to WCI effects. Moreover, both the tidally averaged surface and bottom currents flowed landward with the energy input from the strong winds and waves during the event. The storm triggered a notable landward salt flux and strong vertical mixing in the middle and lower PRE. The Stokes drift and wave forces played important roles in coastal storm surge and landward water transport, but the waves had a limited effect on enhancing mixing during the storm. Moreover, no evident changes were identified by the effect of surface wave roughness and WCI-enhanced bottom stress in the PRE. For the momentum balance, the local momentum balance was among the pressure gradient force, the Coriolis force and bottom stress before the storm, whereas both pressure gradient force and bottom stress were greatly enhanced with waves, resulting in a main balance among the surface stress, wave forces and pressure gradient force during the storm. After the typhoon, the PRE experienced a recovery with the recovery time varying from hours for water level to a week for river plume structure. This research highlights that the WCI effects are important in both storm surge and water transport.

1. Introduction A typhoon, which is a strong tropical cyclone, is one of the most destructive natural hazards affecting coastal zones. The strong energy input to the ocean surface can trigger significant changes in coastal ocean circulation and mixing. The coastal current is almost dominated by intense surface winds and waves during a storm, and both the momentum balance for currents and the mass transport patterns are affected. In addition to the effect of winds, the atmospheric pressure anomaly can also have non-negligible effects on the coastal storm surge height through the inverted barometric effect. Strong waves are ubiquitous during storms and play important roles in generating wave setup/setdown, altering water mixing and coastal circulation. There are numerous studies focusing on the coastal ocean dynamics during storms. For instance, Li et al. (2007) studied the storm surges, currents and destratification in Chesapeake Bay induced by Hurricane Isabel in ∗

2008. They noted that the hurricane changed the current structure and caused destratification of the water column, but the estuary was restratified quickly (within one day) after the passage of the hurricane. Gong et al. (2018a) noted that typhoon Hagupit in 2008 significantly enhanced the landward water transport and salt intrusion in the Modaomen estuary, which is located in the Pearl River Delta in southern China. Moreover, as for the sediments, Warner et al. (2017) found that strong hurricanes, such as Sandy, could rapidly modified the continental shelf morphology and induced alternating patterns of erosion and accretion along the east coast of the New York Bight. During storms, wave-current interactions (WCI) are very intensive. According to the previous studies (e.g., Bolaños et al., 2014), the effects of WCI in a tidal dominant estuary is considered less important without the presence of large wave events, but stronger waves resulting from extreme wind stress during typhoon events could have important effects on coastal circulation, mixing and materials transport. It has been

Corresponding author. School of Marine Science, Sun Yat-sen University, Guangzhou, 510275, China Corresponding author. School of Marine Science, Sun Yat-sen University, Guangzhou, 510275, China E-mail addresses: [email protected] (H. Zhang), [email protected] (W. Gong).

∗∗

https://doi.org/10.1016/j.ecss.2019.106364 Received 23 January 2019; Received in revised form 6 August 2019; Accepted 3 September 2019 Available online 06 September 2019 0272-7714/ © 2019 Published by Elsevier Ltd.

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In this study, a three-dimensional wave-current coupling model, COAWST (Coupled Ocean-Atmosphere Wave Sediment-Transport), was implemented to analyze the WCI effects in the PRE during Typhoon Hato. The main purpose of this study is to quantify and separate the contribution of each WCI mechanism to storm surges, coastal circulation, mass transport and wave propagation in this shallow, funnelshaped estuary. In addition, the recovery time of the PRE from the typhoon was also evaluated, and the findings could be helpful for regional disaster warning and management. The remainder of the paper is organized as follows. In Section 2, the details of the configurations of both the wave and current models are described, and the results of the model validation are presented. The main results are presented in Section 3. In Sections 4 and 5, the recovery processes of the PRE and change in local momentum balance during the typhoon event are discussed in detail, and a brief summary of the entire study is given at the end.

demonstrated that the wave setup during Typhoon Morakot can contribute about 24% of the total storm surge in the Taiwan Strait (Yu et al., 2017). Besides, the vertical current profiles and vertical mixing can also be modified by WCI during storms depending on the angle between the directions of the currents and waves (Olabarrieta et al., 2010). The effects of WCI can be divided into two aspects: the effects of waves on mean currents and effects of currents on waves. On the one hand, the effects of waves on mean currents are mainly summarized into the following four categories: (1) Stokes drift; (2) Wave-induced extra momentum flux, expressed as either radiation stresses or vortex forces, referred to as wave forces herein; (3) Modulation of the surface wind stress by wave roughness; (4) Enhancement of bottom stress owing to the development of wave-current bottom boundary layer. On the other hand, there are two main mechanisms for the effects of currents on waves: (1) Doppler shift, which cause the wave lengthening or steepening; (2) water levels modulating the depth-induced breaking. Though many studies had worked on the response of coastal areas to strong storms, few studies have analyzed the effects of WCI during extreme storms and the recovery processes of a shallow, convergent estuary, such as the Pearl River Estuary (PRE). As described in previous studies (e.g., Gong et al., 2018b), the PRE is a funnel-shaped estuary, with its width decreasing from 50 km at the mouth to 6 km at the head (the Humen outlet Fig. 1a). It is further connected to the upstream river network. Its water depth ranges from < 5 m in the shoals to > 20 m in the channels. The PRE is frequently struck by tropical cyclones in the wet season (from May to September), when river discharge in the estuary exceeds 10,000 m3/s. Strong river input and weaker tidal forcing (tidal range < 1.5 m) make the whole PRE highly stratified in the wet season. Typhoon Hato in 2017 is one of the strongest tropical cyclones to make landfall in southern China since 1947. On August 19, it was a tropical depression located southeast of Taiwan. It then moved northeastward, reaching the coastal areas of the Pearl River Delta on August 23. Its maximum wind speed reached 48 m/s and featured a 945 mb low pressure center. This intensive typhoon event was concurrent with a spring tide and large amount of river discharge, which caused immense damage to the local economy and society (Fig. 2). Thus, it is important to understand the response of the PRE to this storm and how long it takes for the estuary to recover. Especially, the effects of WCI during the storm are essential for improve our understanding.

2. Model implementation 2.1. Configuration of the COAWST model system The COAWST (Version 3.2) model system (Warner et al., 2010), an open-source ROMS (Haidvogel et al., 2000; Shchepetkin et al., 2005), SWAN (Booji et al., 1999), and WRF-based model system (Skamarock et al., 2005), was used in this study to estimate the effects of WCI. Because of its advantages in investigating the coupling processes, this model has been widely used in many studies (Brown et al., 2013; Bolaños et al., 2014; Zambon et al., 2014; Warner et al., 2017; Gong et al., 2018a; Wu et al., 2018). The model domain of this study, which is shown in Fig. 1a, includes the whole Pearl River Delta and part of the continental shelf of the north South China Sea. The size of the model grid is 627×546, with 15 vertical layers. The finest horizontal resolution of the grid is about 110 m in the PRE. The circulation model, which is based on the ROMS model, was configured based on a similar setting used by Gong et al. (2018a, 2018b). Following Uchiyama et al. (2010) and Kumar et al. (2012), the vortex force method was used in this model to better assess the wave effects in coastal zone. The method separates conservative wave forces

Fig. 1. (a) The COAWST model system. The black box shows the location of the PRE, and the contour map with a blue box shows the domain of the COAWST model. The path of Typhoon Hato is represented by the red broken line. The red triangles indicate the locations of three wave floats in the South China Sea. (b) The range of the PRE and its bathymetry. The position of the tidal gauge stations (Zhuhai, Dahengqin, and Sanzao) and the sections (PA, PB) are shown in the middle. The filled black triangles shows stations a–f selected for further analysis. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.) 2

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Fig. 2. Forcing condition around the landfall of Hato. (a) shows the river discharge at the upstream boundary, and (b) to (f) show the water level, surface wind speed, significant wave height, wave period, and wave direction at station d, respectively. The red line is placed at the peak of wind speed. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

wave–current bottom boundary layer module were activated. The method proposed by Drennan et al. (2005) was used to evaluate the changes in the surface roughness due to waves. The submodel based on Madsen (1994) was activated to simulate the wave-current bottom boundary layer. The methods for the boundary condition in the open ocean include the Chapman (1985), Flather (1976), and radiation methods (Orlanski, 1976; Raymond and Kuo, 1984) for the free-surface elevation, 2D momentum variables, and 3D momentum variables, respectively. The water level and velocity open boundary conditions were divided into two parts: tidal and subtidal. The tidal component was derived from the OTPS database (Egbert et al., 2002), while the subtidal component was interpolated from the HYCOM outputs (http://hycom. org/hycom). The initial field and boundary conditions of the active tracers were also interpolated from the HYCOM results. The surface forces, which include the downward shortwave radiation, upward longwave radiation, background air temperature, background atmosphere pressure, humidity, and precipitation, were all specified using data from the Climate Forecast System Reanalysis (CFSR) database (https://rda.ucar.edu/datasets/ds094.0/). Due to limitations in the CFSR database, the typhoon-induced wind forcing and atmosphere pressure anomaly are significantly underestimated from the reanalysis data. Therefore, the Holland model (Holland, 1980) was used to modify the wind forcing and atmosphere pressure fields based on the CFSR

(Bernoulli head and vortex force) from non-conservative wave forces (wave dissipation induced acceleration, e.g., wave breaking, WCI-enhanced bottom friction and wave streaming). The momentum equation with wave-induced momentum terms can be written as (Kumar et al., 2012):

∂u ∂u ∂ + (u⋅∇⊥ ) u + w + fzˆ × u + ∇⊥ ϕ − F − D + ∂t ∂z ∂z ⎛u′w′ − v ∂u ⎞ = −∇⊥ K + J + Fw ∂z ⎠ ⎝

(1)

where u is the horizontal Eulerian velocity; w is the vertical Eulerian velocity; f is the Coriolis coefficient; ϕ is the normalized dynamic pressure; F is the non-wave non-conservative force; D is the diffusive term; u′w′ is the Reynolds stress; v is the kinematic viscosity factor; K is the lower order Bernoulli head; J is the vortex force, which arises from the interaction between the current shear and Stokes drift; and Fw is the non-conservative wave force, such as wave breaking, bottom and surface streaming. In addition, for the vertical turbulence parameterization, the k− ε submodel of Generic Length Scale (GLS) method was implemented, and the method of Smagorinsky (1963) was used to calculate the horizontal eddy viscosity and diffusivity. Moreover, to take into account the effects of waves on the surface and bottom layers, the bulk flux module and the 3

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submodel was the same in above three experiments (Madsen, 1994). Besides, in wave model W1, waves were modulated only by water level variations from the ocean circulation model, whereas in W2, both variations of water level and current were excluded for modulating waves. As the coupled model was established, it was run from July 20 to September 2, 2017. The model was spun up for 31 days to achieve a quasi-equilibrium status. Although the observed data during the typhoon were rare, two groups of observation data were obtained and used to assess the performance of the model. The observation data contain water-level data collected from the tidal gauges located in Sanzao, Dahengqin, and Zhuhai (Fig. 1) and wave data from the moorings in the South China Sea and AVISO datasets (Archiving, Validation, and Interpretation of Satellite Oceanographic data, https:// www.aviso.altimetry.fr/). The skill score, root mean square error (RMSE), and mean bias were selected to assess the model's accuracy. These three metrics are defined as:

Table 1 Implementation of the model experiments. Run Case

CW C1 C2 W1 W2

Waves Surface wave roughness

WEC_VF

SSW_BBL

✓ ✓

✓

✓

✓

✓ ✓ ✓ ✓

Current

Water level variation

✓ ✓ ✓

✓ ✓ ✓ ✓

database. This simplified typhoon model has been used in several studies, and has been shown to reproduce reasonable typhoon wind speed and pressure fields based on the best track data (Zhang et al., 2013, 2015; Guo et al., 2015). In addition, the river discharge data from the upstream hydrological stations near the northern boundary of model domain (i.e. Gaoyao, Shijiao, Qilinzui, Boluo stations in Fig. 1) were specified. The wave model is driven by the surface atmosphere force, real-time water level, and current fields from the ROMS and boundary reanalysis data. Both its model grid and atmosphere force are the same as in the circulation model. The open ocean boundary data of the wave model was specified by the nonstationary wave parameters from the outputs of the WAVEWATCH III model (ftp://polar.ncep.noaa.gov/pub/history/ waves). Information is exchanged between the circulation and wave models in an interval of 30 min to introduce the WCI.

n

Skill = 1 −

∑i = 1 (Oi − Mi )2 n

∑i = 1 (Oi − O ‾i )

2

 

Bias =  Oi − Mi RMSE =

1 n

(2) (3)

n

∑ (Oi − Mi)2 i=1

(4)

where n is the number of observations; Mi and Oi are the model and observation result, respectively; and O ‾i is the mean of observations. The modeled and observed water levels in the three selected stations are shown in Fig. 3. The amplitude, phase, and maximum water level were reproduced accurately (Skill > 0.94) at the Dahengqin and Sanzao stations. At the Zhuhai station, although the phase of the water level variation was captured by the model, its amplitude before and after the storm was slightly underestimated, while the maximum water level was overestimated during the storm. This mismatch at the Zhuhai station may result from the inaccuracy of both the bathymetry and the missing of small coastal features such as jetties. In this area, several jetties were built around the station to protect a nearby fishery port. Comparing the results among CW, C1 and C2, the maxima of water level were

2.2. Model experiments and model validation To decompose the mechanisms responsible for typhoon induced changes, five model experiments (CW, W1, W2, C1, and C2) were conducted. The configuration of each model run is shown in Table 1. CW was a fully wave-current coupled model designed to reproduce the surges, currents and waves during the storm. C1 only considered the WCI effects modifying surface roughness and bottom stress, while no any other wave effects were considered. In C2, the model did not include any wave effects and the surface roughness was estimated based on the wind speed (Large and Pond, 1981). The bottom boundary

Fig. 3. The modeled and observed water levels (m) at each tidal gauge station. 4

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Fig. 4. The modeled (black lines) and observed (green circles and red crosses) significant wave heights (m). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

clearly observed in the wind field. The maximum of the wind speed increased from about 5 m/s before the storm (1:00 on August 22) to near 40 m/s during the storm (6:00 on August 23), while the wind direction also changed rapidly along with the approaching of the typhoon. In order to estimate the coastal storm surges, the model results from the CW run were processed by the t-tide toolbox to extract the tidal components (Pawlowicz et al., 2002). In this study, the skew surge method (Vries, 1995; Horsburgh et al., 2007) was applied to estimate the storm surges. During typhoons, the tidal signal experiences phase shifting due to the water depth changes brought by the storms. With the exclusion of these effects from the storm surge, the skew surge method has been proven to be a more reliable metric for storm surge evaluation (Lowe et al., 2010; Mawdsley et al., 2016; Williams et al., 2016). The maximum storm surge (skew surge) in the Pearl River Delta during Typhoon Hato is shown in Fig. 6a. Storm surge was only about 0.5 m in the coastal ocean, but it increased rapidly towards the land. The surge within most of the PRE was larger than 1 m. Although the height of storm surge was significantly decreased when it entered the river network, the surge still extended to upstream rivers, indicating that the influence of Typhoon Hato was remarkable throughout almost the entire river delta. With the strong winds and waves, shallow bathymetry and landward Ekman transport during the storm, the maximum storm surge reached over 3 m at the west coast of the PRE. The islands (e.g., Lantau Island) at the southeast part of the PRE acted as an effective barrier, weakening the surge near northern Hong Kong notably and resulting in a northwestward surge height gradient. The effect of Lantau Island will be further discussed in Section 4.3. To evaluate the effects of waves on storm surges and the contribution of each WCI mechanism, comparisons were conducted between the CW, C2 experiments. Fig. 6b showed that the patterns of the maximum surges from CW and C2 were very different. The distribution pattern of the wave contribution (Fig. 6b) was slightly different from that of the maximum surge. Wave setup occurred mainly in the coastal areas, while wave setdown was distributed in the deeper coastal ocean, which was consistent with previous studies (Bowen et al., 1968; Yu et al., 2017). The contribution of waves to the maximum surge reached 30%–40% near the shoals, especially in the northeast of Lantau Island

reproduced better with the fully coupled model, and the difference between C1 and C2 was minor. Moreover, the sudden decreases of coastal water level before the peaks were better simulated by the model run which did not include the wave forces. According to a previous study, this sudden decrease maybe mainly owing to the mismatch between the peaks of high tide and storm surge during the storm (Zhang et al., 2017). Moreover, the data shown in Fig. 4 demonstrate that the wave model reproduced a wave field similar to the observation during Typhoon Hato. Due to the insufficiency of available mooring data, the simulated significant wave height (Hs) was compared with the combination of mooring data (State Oceanic Administration, SOA) and satellite products (AVISO). Both the wave heights of the pre-storm and typhoon conditions were reasonably reproduced by the coupled COAWST model (Skill > 0.87). However, the reason for the relatively larger deviation at QF306 during the storm is unknown. It might be attributed to the inaccuracy in the observation time series or the inaccuracy of the wind field in our model. For example, the wind field and pressure field simulated by the Holland model was an ideal circle shape, but the actual typhoon was irregular and asymmetry when interacting with lands. Unfortunately, the salinity data in the PRE were unavailable because of instrument failure during the extreme storm weather. The same model with similar configurations were used by Gong et al. (2018a, 2018b) in this region and was well validated during another typhoon event. Therefore, the results of the modeled salinity in this study are considered credible. 3. Results 3.1. WCI effects on the storm surge in the PRE One of the most significant coastal responses to a typhoon event is the abnormal storm surge brought by strong winds and waves. In Fig. 5, four snapshots of the wind speed at 10 m above ground are shown, representing the situations before, during, and after the landfall of Hato, respectively. The vortex produced by the Holland model could be 5

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Fig. 5. Snapshots of wind speed at 10 m above ground before and during the landfall of Hato.

showed that in Chesapeake Bay, the additional storm surges brought by the strong hurricane Isabel in 2003 reached about 5%–20%. Yu et al. (2017) noted that the contribution of waves in the Taiwan Strait to the total surge was about 4%–24% during Typhoon Morakot. Among the wave effects on storm surge, the wave forces (vortex force, breaking and dissipation processes) transfer the energy of waves into the potential energy of ambient waters, resulting in a pressure

and the nearshore area southwest of the PRE. The importance of the waves in the total surge height decreased landward in the upper estuary. The waves had limited effects on the areas landward of the river outlets, mainly because of the small wave height (< 0.6 m) in the river network. Overall, the wave contribution in the areas whose maximum storm surge height exceeded 2 m was about 10%–30% on average. This result is similar to the results of other studies. Sheng et al. (2010)

Fig. 6. (a) Maximum skew surge during the typhoon. (b) The contribution (%) of waves to the total skew surge. (c) Surge difference between C2 and C1. 6

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estimated from a simple scaling of u= 0.003Uw , in which u  is the windinduced current,  Uw is the wind speed. The Stokes flows almost disappeared near the bottom layer owing to the downward decaying of wave energy (not shown). Besides, comparing C1 and C2, it was shown that circulation changes brought by the surface wave roughness and WCI-enhanced bottom stress was negligible. These results also indicated that the Stokes drift and wave forces were the most important mechanisms for the modulation of coastal circulation during the storm. To estimate the overall effects of the wave and wind forces on the net water transport in PRE, two sections (PA and PB) were selected near the interfaces between the coastal ocean and the estuary. The locations of these sections are shown in Fig. 1b. Section PA is located between Macao and Lantau Island, while section PB is located in Ma Wan Strait (Fig. 1). The time series of the tidally averaged flux at these two sections are displayed in Fig. 8. Typhoon Hato affected the study area on around August 23. Before the arrival of the storm, the water exchange between the ocean and estuary mainly occurred at PA. For the pre-storm condition, the average flux through PA was about 104 m3/s, which was about five times greater than the water flux through PB. Both sections were governed by net seaward flows because of strong river inflow. However, the water transport pattern during the storm was totally changed, and the net flux turned into a landward direction as soon as the typhoon passed. The amount of water flux through PB increased more dramatically than that through PA. From the effects of Hato, the net landward flux was about 2 × 104 m3/s at Section PA and 104 m3/s at Section PB. In the aftermath of the storm, the net flows through Section PB returned to seaward and decreased sharply, recovering to the prestorm state in one day. For Section PA, the seaward flux after the storm was much larger than the pre-storm, reaching about 3.5 × 104 m3/s. One of the possible explanation is that a massive amount of water induced by net landward transport (from both PA and PB) and river runoff was dumped into the river channels during the storm, which actually served as water storage during this time. As the landward wind forces relaxed, the seaward pressure gradient between the rivers and the estuary drove the stored water into the estuary, which could contribute to the intensified seaward transport. The inclusion of waves significantly increased both landward and seaward water transport during the typhoon. At Section PA, during the storm, the wind-induced surface crossshore flow was landward in the central estuary (0.1–0.25 m/s) and seaward near the western coast (0.2–0.3 m/s), while the landward surface Stokes flow was about 0.12 m/s. By integrating the cross-shore Stokes flow vertically at Section PA, it was found that the Stokes flow

gradient and thus increasing the surge height directly. Besides, in the surface and bottom boundaries, waves could modulate the momentum through surface wave roughness and wave-induce bottom stress, respectively. In order to separate the effect of wave roughness and wave bottom stress from other wave effects, results from C1 and C2 were also compared (Fig. 6c). Interestingly, the maximum skew surge considering the surface wave roughness and WCI-enhanced bottom stress was slightly smaller inside the PRE. This result suggested that other than the wave-induced surface roughness and bottom stress, wave-induced pressure gradient contributed obviously to the storm surge increment. This is consistent with the study by Mao et al. (2018), who also concluded that the WCI-enhanced bottom friction and sea surface roughness was of secondary importance when comparing to the other processes of WCI. 3.2. Wave-induced net water flux during the typhoon event The water flux through the estuary mouth also experienced great changes during the storm, which were significant for local material transport. In summer, the PRE receives high river discharge from the Pearl River. Before the storm, the tidally averaged velocity structure in the estuary was consistent with the mode of estuarine circulation, with surface flow going seaward (0.2–0.7 m/s) and bottom water flowing landward (0.03–0.1 m/s), while the landward surface Stokes flow is about 0.025 m/s. During the storm, under the forcing of the extremely strong winds and waves, both the surface and bottom flow patterns were altered. To eliminate the tidal effects, the velocity data for the 25 h when Hato struck the PRE were averaged temporally (Fig. 7a and 7b). At the surface layer, the lower part of the estuary was taken over by westward flows, while the flows in the upper estuary turned northwestward. The speed of the surface current increased to about 0.3–1.1 m/s. The velocity field in the bottom layer was similar to that of the surface, but the bottom flow was only 0.08–0.45 m/s in magnitude, and it went nearly northward in the upper estuary. Comparing the results from CW and C2, most residual currents at the surface layer were enhanced more landward with WCI effects, except several areas near the shoals and islands. In the bottom layer, currents were also enhanced landward. From Fig. 7c, the tidally averaged Stokes drift flowed northwestward inside the PRE, and was ~0.2 m/s in the surface layer, which was of the same magnitude as the surface current flow before the storm. This Stokes drift was larger than the wind-induced current, which was approximately 0.13 m/s,

Fig. 7. (a) and (b) show the surface and bottom tidally averaged velocities during Hato. (c) shows the tidally averaged surface Stokes flow inside PRE. 7

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Fig. 8. Tidally averaged water flux through section PA and PB. A positive value indicates seaward flux.

transport contributed 44.8% of the total landward flow on August 23, while the overall effects from waves made up about 49.7% (Fig. 8). It indicates that the Stokes drift and wind effect contributed almost equally to the landward water flux during the storm. Meanwhile, the WCI effects was not obvious at Section PB. The consideration of surface wave roughness and WCI-enhanced bottom stress slightly increased the seaward water flux before the typhoon landfall and reduced the landward water flux near the typhoon landfall on August 23, with the reason examined in Section 4.2.

shown in Fig. 10. In general, a small Richardson number (< 0.25) indicated a more unstable status of the water column. In most stations (bf), due to the intensive surface stress and landward water flux, the stratification of the estuary was destroyed during the storm. However, in the upper estuary, the water column was well mixed in the pre-storm condition, but enhanced salt intrusion in the bottom layer during the storm increased the vertical salinity stratification. By including wave effects, the vertical mixing was slightly enhanced in the lower bay before the storm (Fig. 10 d-f). However, there was more rapid restratification in stations c, d and f due to the waves. This might resulted from the fact that waves induced more water flux into the river network, which directly accelerated the seaward currents after the typhoon. For local stratification, the surface wave roughness and WCIenhanced bottom stress still did not cause obvious changes (not shown). Generally, the duration of well mixed status at each station was closely related to the distance of the station from the river outlet. The duration was shorter at the stations located near the river outlets. As the waveinduced sediment resuspension is generally intensive during typhoon events (Reniers et al., 2004; Miles et al., 2017), the intensive vertical mixing and its duration time for the entire estuary might also be important to sediment transport in both the estuary and the adjacent continental shelf, but is beyond of the scope of this study.

3.3. WCI effects on stratification and salt intrusion As mentioned above, the storm surge, current, and water transport were obviously affected by the WCI effects during the storm. It could be inferred that the material transport dynamics in the estuary, such as salt intrusion, might also be changed by the waves. The model CW, C1, C2 runs were again used for comparison. The tidally averaged surface and bottom isohalines inside the PRE are depicted in Fig. 9. The patterns of the isohalines were similar in the surface and bottom layers, indicating that the stratification in the PRE was broken during the event. Under the extreme winds and waves brought by Hato, the saltwater in the estuary intruded much more landward compared with that before the storm. Also, because of the strong net landward transport at PB, the salt intrusion near northeast of Lantau Island was severe. However, the changes in river discharge competed against the effects of winds and waves during the typhoon. The intensive fresh water input and strengthened land-sea pressure gradient constrained the salt intrusion, keeping the 5-psμ isohalines out of the river outlets in the estuary. The wave effects, especially the Stokes flow, caused strong landward water flux during the storm and thereby enhanced surface salt intrusion in the upper and southeastern estuary (Fig. 9). However, in other parts, the total differences brought by the waves were not large. The effect of surface wave roughness and WCI-enhanced bottom stress were still insignificant in the deep channels, and it slightly reduced the salt intrusion near the shoals. To estimate the typhoon-induced changes in the estuary stratification and its recovery process, the Richardson numbers (Ri =

N2

3.4. Effects of WCI on waves The effects of currents on waves are mainly related to the Doppler shift effect and local water depth changes which modulate the depthinduced breaking. In this study, the role of the effects of WCI on waves was estimated from the results of the CW, W1 and W2 runs. During the typhoon, the wave direction near the estuary was mainly controlled by the surface southeasterly wind, as shown in Fig. 11 (a). The tidally averaged significant wave height reached more than 5 m near the continental shelf, while the breaking of these strong waves occurred just before it entered the PRE. The significant wave height in the PRE was about 1–2 m, which would be only 0.2–0.5 m under pre-storm conditions in summer. Because of Lantau Island, the wave height on the east coast of the estuary (~1.2 m) was much smaller than that on the west coast (~2 m). With the modification of currents and water levels, the significant wave height inside the estuary increased (Fig. 11c), while that of the

2,

⎛ ∂u ⎞ ⎝ ∂z ⎠

where N is the Brunt–Väisälä frequency and u is the velocity) of six selected stations a-f in the estuary were calculated (Fig. 1), and are 8

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Fig. 9. Distribution of tidally averaged salinity in PRE from model CW, C1 and C2. (a) and (b) depict the isohalines in surface and bottom layer. The water level at the seaward green dot is shown in the subplot. The black box in the subplot shows the period used for averaging. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 10. The time series of the Richardson number in six selected stations a–f from CW (red) and C2 (green) model. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

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Fig. 11. Effects from current to waves in PRE. (a) Significant wave height (m) from CW. (b) and (c) show the difference in significant waves height between CW and W1, CW and W2, respectively.

Fig. 12. The contour maps of the tidally averaged surface salinity in the PRE from August 19 to August 30.

(Fig. 11b) showed that the effects from Doppler shift was negligible during the storm, and the reduced depth-induced breaking was the main reason for the wave enhancement.

area outside of the estuary decreased. Results from CW and W2 suggest that the strong WCI effects during the typhoon event created significant changes in wave height with a magnitude of 0.5 m, which is almost the same as the significant wave height before the storm. Besides, the nonobvious differences between the wave heights from CW and W1

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Fig. 13. (a–d) Snapshots of surface stress in PRE before and during the storm. (e–h) ratio between the surface stresses estimated with (CW) and without (C2) surface wave roughness. (i–l) Snapshots of the significant wave height at the same time.

4. Discussion

show that the abnormal surge and intensive vertical mixing recovered in about 1–2 days and 8–26 h, respectively. Furthermore, to estimate the recovery time of some important tracers, such as salinity, the evolution of the PRE river plume due to Hato was also analyzed. Fig. 12 shows the tidally averaged surface salinity for 12 successive days. The surface salinity data from 1:00 am on each day to 1:00 am of the next day were extracted to calculate the average fields. On August 19, the pre-storm river plume extended outside of the estuary mouth. The fastmoving typhoon started to affect the PRE on about August 22, and the plume suffered slight landward shrinking at its southeast corner. When the PRE was struck directly by Hato on August 23, the plume moved landward rapidly, and its coverage area also decreased substantially, which was mainly resulted from the enhanced vertical mixing and landward water transport during the storm. After another 5 days of recovery, driven by the reduced vertical mixing and seaward residual currents, on August 29, the plume had nearly recovered to its pre-storm pattern. Therefore, in terms of the river plume, the recovery time of the PRE to the storm event was about 5–7 days. This weeklong abnormality from the storms could also apply for other materials, such as nutrients, heavy metals, and sediments. In addition, by comparing the river plume patterns (not shown), the waves could intensify the landward shrinking of the plume during the storm through increasing landward transport and vertical mixing, but its overall effects on the recovery time were

From the above analysis, the performance of the coupled wavecurrent model with the modified wind field was acceptable in the typhoon simulation for the PRE, and this modeling system could be applied to similar estuaries all over the world. Our results suggested strong effects from the WCI to surges, currents and water transport, and the accurate estimation of wave forces was very important for the coastal modeling during the storm. However, this model system could still be improved in the future. For example, the simple Holland model requires further improvements for taking land-storm interactions into consideration. Besides, more accurate coastal bathymetry and inclusion of the effects of coastal wetlands would also be helpful to further improve the modelling results. 4.1. The recovery time of the PRE after typhoon events As one of the most devastating typhoons to hit the PRE, it is reasonable to regard Hato as a typical event for understanding the recovery time of the PRE after strong typhoon events. The recovery time of the estuary is important to the local ecosystem due to its great effects on biological activity. The water level data for three gauge stations (Fig. 3) and the Richardson number for six selected stations (Fig. 10) 11

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Fig. 14. (a–d) Bottom stresses from the overall tidally, wind-driven circulation in PRE before and during the storm. (e–h) ratio between the bottom stresses estimated with (CW) and without (C2) waves.

(1981) based on wind speed. The former estimates the surface roughness with wave age and wave height, while the latter is only related to the wind speed. Four snapshots of the surface wind stress and comparisons between results from CW and C2 are shown in Fig. 13. In the normal condition (Fig. 13a), the surface stress in the PRE was 0.1–0.3 N/m2, while the significant wave height was about 0.1–0.2 m. On the second half of August 22, when Hato started to significantly affect the study area, the wind speed was about 10–25 m/s (Fig. 5) and the significant wave height was about 1–3 m in the PRE (Fig. 13 j-k). At this period, the surface stress of CW was about 10–30% larger than that of C2 (Fig. 13 f-g), but the total surface stress was still not lager than 1.5 N/m2 inside the PRE. With the approaching of Hato, the wind speed and surface stress increased rapidly, but the ratio of surface stress of CW and C2 decreased. When the typhoon landed at 00:00 on August 23, the maximum surface stress reached > 3 N/m2 (Fig. 13d) and the maximum wind speed was near 40 m/s (Fig. 5). Interestingly, the surface stress of CW became ~10% smaller than that of C2 (Fig. 13h) at this time. This phenomenon might result from the topography of the PRE and the extreme wind speed during Hato. The abrupt shoaling near the estuary mouth reduced both the wave age and wave height significantly (Pareja-Roman et al., 2019). Therefore, with the strong wind during the typhoon, the surface stress considering surface wave roughness (i.e. Drennan method) could be smaller than that from the wind speed-based method. Besides, the bottom stress also increases rapidly under the attack of Hato. In Fig. 14, the variations of bottom stress and the effect of waves were shown at four selected hours to show the situation before and during the storm. Before the storm (Fig. 14 a and e), the bottom stress in the PRE was 0.1–0.3 N/m2, and the WCI-induced bottom stress

limited. Compared to shallow bar-built estuaries, such as Galveston Bay (~2 month), the recovery time of the PRE was much shorter, mainly due to the lack of barriers near its mouth and free exchange between the estuary and the continental shelf (Du et al., 2018). However, the relatively quicker recovery process might still exert obvious environmental effects. Accompanied by the strong precipitation brought by the storm, the non-point source pollutants produced by the watersheds would be brought to the estuary rapidly, which would cause an instantaneous peak of coastal pollutant discharge. This was difficult to illustrate by using the variations of the river plume. Although the seaward flux was strong after the storm, the extension of the river plume was limited because a massive amount of salt from the coastal ocean was brought into the PRE before the recovery. In contrast, terrigenous pollutants would not suffer from this constraint. The massive pollutants entering the estuary after the storm would be spread to the coastal ocean and continental shelf, inducing more severe environmental problems. 4.2. Depth-averaged momentum budget In the COAWST model, the balance among the momentum terms is: ACC = HADV + PGF + COR + SSTR + BSTR + WT

(5)

where terms from the left to right denote: the acceleration, horizontal advection, pressure gradient, Coriolis force, surface stress, bottom stress and wave-induced momentum (i.e. horizontal vortex force, wave breaking and roller force, and Stokes-Coriolis force terms), respectively. The calculation of surface stress in CW and C1 is based on the Drennan method, while that of C2 is obtained by Large and Pond 12

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Fig. 15. Variability of the depth-averaged momentum balance from CW (a–d), C1 (e–h) and C2 (i–l), including the acceleration (black), horizontal advection (yellow), pressure gradient (blue), Coriolis force (red), surface stress (magenta), bottom stress (green) and wave-induced momentum (brown). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

enhancement was about 0.1 N/m2. During the storm, the current-induced bottom stress gradually increased from 0.3 N/m2 to > 7 N/m2 inside the estuary (Fig. 14 b-d). However, with the approaching of typhoon, including waves only increased the bottom stress in the coastal shoals near the estuary mouth (Fig. 14 f-h), and limited effects could be observed in other areas. Moreover, before the landfall of Hato, the seaward surface stress was enhanced by surface wave roughness, while WCI-enhanced bottom stress was almost insignificant. Near the landfall of Hato on August 23, the landward surface stress decreased by about 10% when considering the surface wave roughness, but the WCI-enhanced bottom stress was increasingly significant near PA at the same time. Therefore, the overall effects of including surface wave roughness and WCI-enhanced bottom stress could induce slightly stronger seaward water flux and weaker landward water flux on August 22 and 23, respectively. We next explored the changes of depth-averaged momentum balance inside the PRE. All three model runs (CW, C1, C2) were selected for comparison (Fig. 15). Before the storm, the pressure gradient was mainly balanced by the Coriolis force and bottom stress (O(10−1)),

while the surface stress at the same time was only around 0.003 m/s2. As the typhoon approached, the surface stress increased rapidly and changed the local balance. Due to the reduction in the relative importance of Coriolis force, the strong pressure gradient force in the most areas of the PRE was now mainly balanced by the large surface stress in the opposite direction (Fig. 15 d, h, l). Results from C1 and C2 showed that including surface wave roughness did not greatly alter both the surface stress and the local balance. Meanwhile, the impacts from waveenhanced bottom stress to the momentum balance mainly occurred near the shoals in southwest estuary. Moreover, around the landfall of Hato, the wave-induced momentum, which mainly introduced additional pressure gradient, changed the main momentum balance at the west coast of the PRE and the south coast of Lantau Island, contributing directly to the large increase in coastal pressure gradient. Meanwhile, as for each wave-induced term (not shown), the wave breaking and roller term (O(10−4)) was much larger than the horizontal vertex force (O (10−5)) and Stokes Coriolis terms (O(10−6)).

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Fig. 16. Changes without the Lantau Island. (a) shows the skew surge height. (b) and (e) show the changed surface and bottom isohalines. (d) displays the significant wave height. (c) and (d) depict the surface and bottom current velocity without the island, respectively.

Hato in 2017. The model was validated through observation data from gauge stations, moorings, and satellites. By turning on/off the different wave effects (e.g., surface wave roughness and the wave forces) in the current model, and current effects on the wave field, five individual model runs (CW, C1, C2, W1 and W2) were conducted to separate the contributions of different WCI mechanisms. We then analyzed both the responses of storm surges, circulation, and salt intrusion to the storm and the corresponding roles of WCI effects. Results showed typhoon Hato induced a large storm surge (> 0.6 m) in the PRE, especially on the west coast (> 3 m), and about 10%–30% of the maximum surge in the coastal area resulted from the effects of waves (e.g., Stokes flow, wave forces, wave setup), but no evident changes were found to be caused by surface wave roughness and WCI-enhanced bottom stress. The circulation inside the PRE was almost totally altered by the winds and waves. Intensive landward residual circulation resulted in abnormal landward transport and large amount of water trapped in both the upper estuary and river network, which returned back to the estuary in the next day as the stronger seaward water flux. Wave effects, mainly the Stokes drift (44.8% of landward flux in PA during the storm), increased both the landward flow during Hato and the seaward return flow aftermath. Meanwhile, the enhanced landward transport also aggravated the salt intrusion in the lower bay, but this intrusion was restricted at the upper bay because of the strong river discharges. However, the consideration of waves didn't affect the stratification and its recovery in the PRE significantly, probably because the strong winds had already mixed the water column well. According to the momentum balance analysis, local momentum balance was achieved among pressure gradient force, Coriolis force and

4.3. Effect of the Lantau Island In previous sections, the Lantau Island (Fig. 1) was found to play an important role in the currents, waves and WCI effects for the areas inside the PRE. Therefore, an additional sensitivity test was conducted to examine the changes by excluding the Lantau Island in the model bathymetry. According to Fig. 16a, the absence of Lantau Island caused an increase in extreme surge > 1.2 m in the whole PRE. The circulation near the eastern coast was also strengthened obviously (Fig. 16 c and f), bringing in strong westward and northward momentum. As a result, the salt intrusion became more severe at the eastern PRE. However, due to the abundant river discharge from the Humen outlet, the northern limit of the salt intrusion did not change concurrently. Without the sheltering of the island, stronger waves could enter the PRE and thus increased the significant wave height. The increment of wave height in eastern PRE was ~1 m. Moreover, the strong waves and currents would also enhance the WCI effects. The wave-induced pressure gradient force would contribute significantly to the increment in coastal surges and landward water transport during the storm. 5. Summary In recent years, typhoon disasters have received more and more attention due to great damages to both economy and society. The extreme winds and waves could result in strong coastal storm surges and salt intrusion during the storms, challenging the safety of all coastal cities. In this study, the COAWST modeling system was implemented to analyze the effects of the WCI in the PRE during the strong typhoon 14

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bottom stress before the storm. As the storm approached, the rapidly increasing surface stress and wave forces started to balance the pressure gradient force inside the PRE, causing large offshore gradient force near the coastal areas. As for the current effects on waves, the modification of water depth-induced breaking by the variations of water level played the most important role rather than the Doppler shift effect. The recovery time of the PRE and the effects of Lantau Island were also discussed. The recovery time varied from hours for water levels to a week for river plume distribution, which could be important for both sediment and nutrient transport during the storm. Moreover, the exclusion of Lantau Island significantly increases storm surges (> 1.2 m), landward transport and salt intrusion inside the PRE, while the WCI effects would also be enhanced due to stronger wave forces inside the estuary. Our results revealed the strong WCI effects in affecting storm surge, estuarine currents and material transport during storms. The effect of surface wave roughness and WCI-enhanced bottom stress seems relatively insignificant, while the wave forces and Stokes drift played important roles. These findings could be relevant to similar studies in other estuaries, and our results are of implications for regional coastal protection and environmental management.

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