In the last 10 years, the Minjiang River, which is the longest river in the Fujian Province in Southeast China, has been facing a downward trend of dissolved oxygen (DO) and a frequent occurrence of hypoxia. In this study, the development of the continuous and short-term presence of low DO was investigated by using the water age concept and average DO consumption concept based on a three-dimensional Environmental Fluid Dynamics Code in the Minjiang River. The results revealed that the spatial distribution of DO was affected by temperature, runoff, pollution emission, tidal advection, and hypoxic water discharge from the reservoir bottom. The continuous low DO in the water of the North Channel occurred frequently when the enough pollutants were aerobically decomposed faster than the rate of oxygen reaeration during the high temperature and low river discharge period. In addition, the water age and reaeration time decreased with a rapid increase in the water flow from the Shuikou dam when the reservoir capacity was released via drainage. The results of this study provide scientific insights on the mechanism involved in the occurrence of hypoxia and suggest countermeasures for addressing hypoxic problems in estuaries.

  • Water age concept and average dissolved oxygen (DO) consumption concept were used to investigate the low DO by an Environmental Fluid Dynamics Code (EFDC) model.

  • The spatial distribution of DO was affected by temperature, runoff, pollution emission, tidal advection, and hypoxic water discharge from the reservoir bottom.

  • The continuous low DO occurred frequently during the high temperature and low river discharge period.

Graphical Abstract

Graphical Abstract
Graphical Abstract

Dissolved oxygen (DO) plays a significant role in maintaining the health of an aquatic ecosystem, and significantly affects the ecosystem and biogeochemical cycle of rivers and oceans (Herrmann & Keister 2020; Li et al. 2020b; LaBone et al. 2021). The occurrence and long-term persistence of hypoxia (low DO) negatively affects aquatic and benthic organisms, resulting in the deterioration of water quality and the loss of water ecosystem (Rabalais et al. 2002; Turner et al. 2005; Yang et al. 2020). Hypoxic and anoxic aquatic environments are normally observed in naturally formed oxygen minimum zones, fjords, and upwelling zones (Diaz 2001; Rabouille et al. 2008; Rabalais et al. 2009, 2018). However, anthropogenically induced hypoxia and low DO development and persistence in rivers, estuaries, and adjacent coastal waters around the world are commonly associated with an increase in nutrient loading as population growth and resource intensification rises (Wei et al. 2007; Rabouille et al. 2008; Rabalais et al. 2009, 2010; Xu et al. 2020; Zhang et al. 2020; Testa et al. 2021).

It is now widely accepted that low DO in water column is associated with eutrophication and increasing allochthonous inputs of organic matter and nutrients, such as dissolved organic carbon (DOC) and ammonia (NH4), that require oxygen for oxidation (Rabouille et al. 2008; Buranapratheprat et al. 2021; Rigaud et al. 2021). Additionally, the phenomenon of low DO develops when organic matter-rich silt at the bottom of deep-water lakes or reservoirs accelerates the absorption of DO with minimal reaeration under the situation of thermal stratification (Noori et al. 2021, 2022). Moreover, oxygen depletion in estuaries is related to the residence time of waters, which is determined by freshwater inflow, depth, water volume, wind mixing, and tidal exchange (Wang 2009; Quinones-Rivera et al. 2010; Wang et al. 2012; Hong & Shen 2013; Rabalais et al. 2018). Therefore, the investigation of these factors that affect the kinetic process of DO will facilitate the prediction of the spatial and temporal distributions of DO, for determining the extent of hypoxic water and suggesting mitigation measures (Turner et al. 2006; Zhang et al. 2016; Wenjing et al. 2020).

The hydrodynamic changes and pollutant migration and transformation processes involved in estuarine hypoxic water environment are very complex (Cai et al. 2020; Sun et al. 2020a). Numerous researchers have qualitatively analysed the response state of the physical, biological, and chemical factors in hypoxic water environment using observation data (Chi et al. 2020; Guo et al. 2020; Sun et al. 2020b). For example, Wehmeyer & Wagner (2011) evaluated the relationship between water flows and DO in the Roanoke River between Roanoke Rapids Dam and Jamesville, North Carolina using the hydrological, water quality, and meteorological data from 2005 to 2009. However, observational analyses cannot meet the requirements of an extensive, detailed, and quantitative research for evaluating the causes of the long-term evolution of watershed water environment. In the past decades, numerous numerical modelling studies that simulate the underlying dynamic mechanisms of the development and variability of hypoxia in numerous rivers and estuaries have been developed (Scavia et al. 2004; Wei et al. 2016; Yau et al. 2020; Jarvis et al. 2021; Yu et al. 2021). For example, Xia et al. (2010) investigated the effects of river discharge, atmospheric winds, and tidal forcing on the spatial and temporal distributions of DO in the Caloosahatchee River Estuary using a numerical estuarine and coastal ocean circulation hydrodynamic and eutrophication model based on an Environmental Fluid Dynamics Code (EFDC).

However, there is an increase of peer-reviewed articles reporting the different types of models to detect DO variation trends in many coastal regions mainly ascribed to individual hydrodynamic factors or water quality factors (Xia et al. 2011; Zhang et al. 2016; Lajaunie-Salla et al. 2017). Low DO occurs when the amount of DO in the water column is decreased by the process of respiration at a faster rate than resupply through air–water exchange or advection (Kumarasamy 2015; Swanson et al. 2016; Harano et al. 2018). How to quantitatively describe the reaeration rate and DO consumption involved in the kinetic process of DO is the key to the study of low DO. In this study, the water age concept and average dissolved oxygen consumption (ADOC) concept were used to investigate the development of continuous and short-term low DO in the Minjiang River Estuary by using a three-dimensional EFDC model. The EFDC is a multi-purpose, open-source, and free-of-charge 3D fluid dynamics and water quality model that has been extensively used and documented to simulate circulation, thermal stratification, water quality and eutrophication, and sediment transport in a number of lakes, reservoirs, rivers, and estuaries (Hamrick 1992; Li et al. 2011). Therefore, EFDC could more accurately simulate the spatial and temporal variation of DO in the Minjiang River than CE-QUAL-W2 and other vertical two-dimensional models. As water age reflects the time elapsed for water body or dissolved substances to be transported from one point to another, making it a useful timescale for describing the reaeration time or contaminants residence time in rivers and estuaries (Deleersnijder et al. 2001; Shen & Haas 2004). In addition, four sensitivity analysis model scenarios were developed to examine the impacts of normal power generation and rapid increase in the water flow from the Shuikou dam on the spatial and temporal variability of the water age, ADOC, and DO in the lower reaches of the Minjiang River.

Study area

The Minjiang River (Zhang et al. 2016, 2021), which is the largest river in Fujian Province in Southeast China that leads to the sea, has a basin area of 60,992 km2 (Figure 1). It has a subtropical monsoon climate with an average annual rainfall of 1,519–2,044 mm. However, the annual runoff distribution of the Minjiang River is extremely uneven. For example, the river runoff during the main flood season (from April to July) accounts for 61% of the annual runoff, whereas the river runoff from October to February of the following year only accounts for 18%. To meet the ecological water demand of the Minjiang River, the minimum ecological flow from the Shuikou Dam was set to 308 m3· s−1. In the last 10 years, the DO in the lower reaches of the Minjiang River has generally decreased and the duration and frequency of low DO has increased in several river reaches, and this has attracted significant attention from the local government and society (Zhang et al. 2016).
Figure 1

The location of Minjiang watershed, model cells, and topographical sketch map. Unit: Luo-zero elevation (m).

Figure 1

The location of Minjiang watershed, model cells, and topographical sketch map. Unit: Luo-zero elevation (m).

Close modal

Model description

EFDC (Zou et al. 2006; Li et al. 2011), a general purpose and open-source three-dimensional numerical model, was applied in the Minjiang River Estuary, including hydrodynamics, water ages, and water quality. The process and equation of DO is shown as follows:
formula
(1)
where x = c, d, and g representing cyanobacteria (blue-green algae), diatoms, and green algae, respectively; PNx is preference for ammonium uptake by algal group x (0 ≤ PNx ≤ 1); Px is the production rate of algal group x (day−1); FCDx is the fraction of respired carbon produced as DOC for algal group x (0 < FCDx < 1); KHRx is the half saturation constant of DO for algal DOC excretion for group x (gO2 · m−3); BMx is the basal metabolism rate of algal group x (day−1); Bx is the algal biomass of algal group x (gC · m−3); AONT is the mass of DO consumed per unit mass of ammonium nitrogen nitrified (4.33 gO2/gN); AOCR is the dissolved oxygen/carbon ratio in respiration (2.67 gO2/gC); Nit is nitrification rate (day−1); KHR is the heterotrophic respiration rate of DOC (day−1); DOC is the concentration of DOC (gC · m−3); COD is the chemical oxygen demand concentration (gO2-equivalents m−3); KHCOD is the half saturation constant of DO required for oxidation of COD (gO2 ·m−3); KCOD is the oxidation rate of COD (day−1); Kr is the reaeration coefficient (day−1), applied to the surface layer only; DOs is the saturation concentration of dissolved oxygen (gO2· m−3); SOD is sediment oxygen demand (gO2·m2·day−1), applied to the bottom layer only; WDO is external loads of dissolved oxygen (gO2· day−1).
When wind effects are excluded, the empirical formulas for the reaeration rate are based solely on velocity and depth:
formula
(2)
where KR (20 °C) is the reaeration rate at 20 °C (day−1), u is the water velocity (m · s−1), H is the water depth (m), and A, B, C are empirical parameters.

Minjiang River model

The Minjiang River model was developed by Zhang et al. (2016, 2021) based on the EFDC. This model used quadrilateral grids consisting of 2,743 active cells with a cell size varying from 50 to 1,000 m resulting from grid optimisation and orthogonality. Three uniform vertical sigma layers were applied to better fit the bottom topography. The model was driven by the tidal level, discharge of Shuikou Hydropower Station, inflow tributaries, atmospheric forcing, and surface wind field. The 15 state variables in the water column were simulated by the water quality model, which contained green algae, three types of carbon, five types of nitrogen, four types of phosphorus, DO, and chemical oxygen demand (Zhang et al. 2021). The model was initially run for several days for each flow condition to obtain a dynamic equilibrium condition. For this model, a 60-second time step was used in the simulations with no signs of numerical instability.

Data used

The Year Book of Hydrology P.R. China and the China Meteorological Network provided the daily atmospheric data for 2013. Since 2013, the Hydropower Station, hydrological stations (at YBHC), and frequent monitoring locations along the Minjiang River have provided data on the Shuikou daily discharge, water quality, and inflows of tributaries. The daily tidal level, salinity, and temperature data were provided by the hydrodynamic model of Shuikou Hydropower Station–Minjiang open (Zhang et al. 2021). In addition, the refined data of 2013 used three automatic water quality monitoring stations (Zhuqi, Wenshanli, and Baiyantan), including turbidity, DO, conductivity, pH, permanganate index (CODMn), total phosphorus (TP), and ammonia nitrogen (NH3-N), with a frequency of daily or 3 h.

Boundary and initial conditions

The data used to fuel the model came from the China Meteorological Network and include the wind field, air pressure, temperature, relative humidity, evaporation, rainfall, solar radiation, and cloud cover. The nearby hydrological stations were where the mainstream and tributary flow information was collected. Each tributary's water border in the basin where the pollutants were estimated and assigned. The Oregon State University-developed TPXO 6.2 global tidal model calculated the tide level. The detailed boundary settings for this model had been described in our previous research (Zhang et al. 2021).

In the initial test settings of the model, the DO, temperature, and other water quality parameters were set in accordance with the measured values, and the water surface height was set at 2.5 m. For each flow condition, the flow field, salinity, and water quality concentration were set as the equilibrium conditions derived from the model simulation over a number of days.

Calibration and validation

Model parameter calibration was performed using data from January through December 2012, and verification was performed using data from January through December 2013. Hydrological calibration mainly verified the tide level, flow, and temperature. The model validation showed that the average absolute error of the tidal level, water temperature, and the average relative error of flow were 0.23 m, 1.04 °C, and 19.9%, respectively. Water quality calibration mainly verified the DO, TN, TP, NH3-N, and BOD5. Each monitoring station's relative error range for DO concentration was 3.86–36.83%. The detailed model calibrations and verification could be found in Zhang et al. (2021). The Minjiang River model could better describe the hydrodynamic and water quality in the lower reaches of the Minjiang River, and could fully reflect the real-time (frequency per hour) variation of DO in Minjiang River.

Average dissolved oxygen consumption

The ADOC of each cell could reflect the spatial and temporal distribution characteristics of DO consumption in the lower reaches of the Minjiang River, which could intuitively reveal the causes of low DO in specific areas. The ADOC in water mainly included oxidation of DOC, nitrification of ammonia nitrogen, respiration of algae, and SOD (Equation (1)). The values of DOC, NH4, Bx, and SOD of each cell in two tidal cycles per day were extracted according to the calculation results of the Minjiang River model. The ADOC of each cell was calculated by Equation (1) (Equation (2)). The equation of ADOC is defined as
formula
(3)
where Pi is the ADOC of No. i cell (g · O2· m−2·day−1); i is the cell number (i is from 1 to 2,743 in this paper); j is the time step (j is from 1 to 24 when the per hour calculation result is calculated at a whole day); x is the water quality index (DOC, NH4, Bx, etc.); Cx,ij is the x index concentration of No. i cell at j time step (mg · L−1); Kx,ij is the x index degradation coefficient of No. i cell at j time step (day−1); hij is the water depth of No. i cell at j time step (m).

Model application

Estimate the effect of river discharge on DO dynamics by the validated EFDC model. Three model scenarios (Table 1) were developed at the most unfavourable water temperature (30 °C), the minimum ecological flow, average annual flow, and maximum generation flow of the water discharge from the Shuikou dam were 308, 1,360, and 2,100 m3· s−1, respectively. The influence of river flow on the kinetic process of DO was investigated from three major aspects (Wehmeyer & Wagner 2011): (1) the discharge of water from the bottom of the Shuikou dam for electricity generation or the spillway for discharging flood. The DO of the water from the bottom of the dam was very low with a minimum monitoring value of approximately 1.5 mg · L−1. In contrast, the DO of the spillway water was very high; thus, leading to the over saturation of DO. (2) The decrease in the concentrations of Bx, NH4, DOC, and COD in the lower reaches of the Minjiang River with an increase in the water discharge from Shuikou, which resulted in a decrease in DO consumption. (3) Reaeration time (∂t) (Shen & Wang 2007; Alosairi et al. 2011) and reaeration coefficient (KR) (Bansal 1973; Palumbo & Brown 2014; Kumarasamy 2015) were determined by the discharge of Shuikou (Equation (1)), which affected the kinetic process of DO in the lower reaches of the Minjiang River. The flow diversion ratio of the North Channel (FDRNC) had a significant impact on the DO of the North and South Channels (Zhang et al. 2015). To analyse the impact of the flow diversion ratio on the DO of the North Channel under the L0 model condition, a retaining dam was set at the bifurcation of Huaiantou to increase the FDRNC to approximately 50%.

Table 1

Model simulation scenarios

Model scenariosRiver runoff (m3 · s−1)Temperature (°C)The FDRNCRemark
L0 1,360 30 Model calculation  
L1 308 30  
L2 2,100 30  
L3 1,360 30 50% Retaining dam was set at the bifurcation of Huaiantou 
Model scenariosRiver runoff (m3 · s−1)Temperature (°C)The FDRNCRemark
L0 1,360 30 Model calculation  
L1 308 30  
L2 2,100 30  
L3 1,360 30 50% Retaining dam was set at the bifurcation of Huaiantou 

Effect of flow on DO during normal power generation

The DO concentrations calculated using the model were analysed and estimated in eight reaches, which were divided according to the characteristics of the lower reaches of the Minjiang River (Figure 2). Compared with that of the L0 model (1,360 m3· s−1, Figure 3(a) and 3(b)), the DO of the water flow from Shuikou to the open sea reaches in the L1 model (308 m3· s−1, Figure 3(c) and 3(d)) increased, significantly except in the North Channel (Figure 2). In addition, the DO in the three reaches from Geyangkou to Huaiantou increased by 1.39, 1.77, and 1.44 mg · L−1 respectively, indicating that the DO reaeration concentration in the L1 model was higher than that in the L0 model. In addition, with a decrease in the water discharge from Shuikou, the DO in the water flow from Baiyantan to the open sea reaches increased slightly at rising tide, which could be attributed to the enhancement in the tidal jacking (Figure 3(d)). The same phenomenon had been found in the author's article (Lanoux et al. 2013; Zhang et al. 2015). In addition, there was no significant change in the overall DO in the North Channel; however, the DO in the upper half increased, whereas that in the lower half decreased, which could be attributed to the high DO of the water from the upstream.
Figure 2

The DO of each reach in the L0–L3 models.

Figure 2

The DO of each reach in the L0–L3 models.

Close modal
Figure 3

DO spatial distribution at LWS (a and c) and HWS (b and d) in the L0–L1 models, respectively.

Figure 3

DO spatial distribution at LWS (a and c) and HWS (b and d) in the L0–L1 models, respectively.

Close modal
Compared with that of the L0 model, the DO in the water flow from Shuikou to open sea reaches in the L2 model (2,100 · m3·s−1, Figure 4(a) and 4(b)) significantly decreased (Figure 2). Particularly, the DO in the water flow from Geyangkou to Huaiantou reaches decreased by 0.2–0.5 mg · L−1. In addition, the DO of the South Channel and the North Channel decreased by 0.35 and 0.32 mg · L−1, respectively. When the DO in the water from the upstream was low, the DO decreased, even if the pollutant could be diluted with an increase in river runoff. In contrast, there was no significant change in the DO in the water from Shuikou to Huaiantou reaches and from Min'an to the open sea reaches in the L3 model (Figure 4(c) and 4(d)).
Figure 4

DO spatial distribution at LWS (a and c) and HWS (b and d) in the L2–L3 models, respectively.

Figure 4

DO spatial distribution at LWS (a and c) and HWS (b and d) in the L2–L3 models, respectively.

Close modal
The ADOC of each cell in the lower reaches of the Minjiang River for an entire day in models L0–L3 was estimated (Figure 5). The oxidation of DOC was the largest consumer of DO, which was responsible for approximately 45–54%. The SOD was the second largest cause of DO depletion, accounting for 37–40% of the total DO depletion rates, while the contribution of NH4 and Bx were relatively small (Zhang & Li 2010; Cui et al. 2019). Compared with that of the L0 model, the ADOC of the North Channel, Baiyantan–Min'an, and Min'an–Open sea in the L1 model increased significantly by 1.18, 1.52, and 0.88 g · O2· m−2·day−1, respectively. Even if the DO of water from the upstream was high (6.49 mg·L−1), the DOC and NH4 concentrations in the North Channel increased by approximately 0.45 · mg·L−1. The increase in the ADOC could be attributed to the decrease in the river runoff of the North Channel from 359 (L0) to 81 m3· s−1 (L1). Consequently, the DO in the water of the upper half of the North Channel increased, and the DO in the lower half decreased. In addition, the ADOC of the North Channel significantly increased owing to the sewage discharge from the municipal district of Fuzhou, and the proportion of the DO consumption of NH4 increased from 13.00 (L0) to 25.00% (Figure 6).
Figure 5

The ADOC of each reach in the L0–L3 models.

Figure 5

The ADOC of each reach in the L0–L3 models.

Close modal
Figure 6

Weights of DO consumption factors of each reach in the L0–L3 models.

Figure 6

Weights of DO consumption factors of each reach in the L0–L3 models.

Close modal

Compared with that of the L0 model, the ADOC of the L2 model decreased by 0.14 gO2 ·m−2 · day−1. Furthermore, the ADOC in the South Channel and the North Channel of the L2 models decreased by 0.22 and 0.14 g · O2· m−2 · day−1, respectively. In addition, the concentration of DO consumption factors in the downstream decreased, which could be attributed to the rapid washing away of the pollutants with an increase in the river runoff. Compared with the L0 model (FDRNC = 26%), there was a change in the ADOC of the South and North Channels of the L3 model (the FDRNC was approximately 50%). Particularly, the ADOC of the North Channel of the L3 model decreased by 0.24 g·O2 · m−2· day−1, and the proportion of the DO consumption of NH4 in the North Channel decreased by 2.92% compared with that of the L0 model, which could be attributed to the increase in the river flow (Figure 6).

The KR of each reach in the L0–L3 models was calculated using Equation (2) according to the water depth and the flow velocity. Compared with the L0 model, the flow velocity in each reach of the L1 model decreased. In addition, the flow velocity in the downstream of the Shuikou dam decreased by 0.5 m · s−1; however, there was no significant change in the flow velocity of the open sea owing to the influence of the tide. In addition, compared with the L0 model, the water level of the L1 model in the reaches from Shuikou–Geyangkou decreased by 1.47 m; however, that in the reaches from Min'an–Open sea increased by 0.45 m, which could be attributed to the enhancement in the tidal jacking. Furthermore, KR decreased with a decrease in the river runoff. Compared with those of the L0 model, the KR of each reach in the L1 model decreased slightly from 0.15 day−1 in the upstream to 0.02 day−1 in the downstream. However, compared with that of the L0 model, the DO from Shuikou to Huaiantou reaches in the L1 model increased by 1.40–1.80 mg · L−1. In addition, compared with that of the L0 model, the DO in each reach of the L2 model decreased by 0.10–0.50 mg · L−1 at a constant KR. This indicated that KR was not the main factor affecting the decrease in the DO in the lower reaches of the Minjiang River with an increase in the water discharge from the Shuikou dam.

Water age reflects the temporal and spatial heterogeneity of estuarine dynamics and water exchange, which is mainly affected by river flow and tide. The distribution of the water age was simulated in models L0–L3 (Figures 7 and 8). The water ages of five typical sections were calculated at high water slack (HWS) and low water slack (LWS) (Table 2). The results revealed that there was a negative correlation between the water age in the downstream and the water discharge from the Shuikou dam. The residence time of water in the North Channel decreased with an increase in the FDRNC. In addition, in the L0 model, at a LWS, the time taken for the water discharged from the Shuikou dam to reach Huaiantou was approximately 1.79 days, and the time taken for the discharged water to reach the South Channel export, North Channel export, and finally reach Min'an was 4.13, 4.30, and 5.86 days, respectively. Furthermore, the water age from Baiyantan to the open sea reach was small, in which the Min'an water age was 0.15 days; however, the water ages of the Huaiantou, South Channel export, and North Channel export were 2.25, 5.98, and 5.64 days, respectively, which could be attributed to tidal jacking. The spatial distribution of the water age (Figure 7(b)) revealed that the largest water age was observed at the intersection of the South Channel and North Channel. In addition, there was a gradual decrease in the horizontal gradient of the water age isoline from Shuikou to the open sea reaches. The water age isoline from Baiyantan–Min'an was densely distributed, indicating that the downward transport speed of water in this reach was slow, which could be attributed to the large channel volume and tidal jacking.
Table 2

Water ages of six sections in the L0–L3 models unit: days

Model scenariosTidal momentXiaxiyuanZhuqiHuaiantouSouth Channel exportNorth Channel exportMin'an
L0 HWS 0.42 1.19 2.25 5.98 5.64 0.15 
LWS 0.44 1.18 1.79 4.13 4.30 5.85 
L1 HWS 1.63 5.29 9.47 13.47 14.79 0.23 
LWS 1.59 4.70 7.58 16.25 15.46 12.28 
L2 HWS 0.31 0.86 1.59 4.26 3.95 0.16 
LWS 0.33 0.84 1.26 2.97 2.96 4.11 
L3 HWS 0.43 1.22 2.09 6.03 5.52 0.15 
LWS 0.45 1.22 1.89 4.96 3.23 5.87 
Model scenariosTidal momentXiaxiyuanZhuqiHuaiantouSouth Channel exportNorth Channel exportMin'an
L0 HWS 0.42 1.19 2.25 5.98 5.64 0.15 
LWS 0.44 1.18 1.79 4.13 4.30 5.85 
L1 HWS 1.63 5.29 9.47 13.47 14.79 0.23 
LWS 1.59 4.70 7.58 16.25 15.46 12.28 
L2 HWS 0.31 0.86 1.59 4.26 3.95 0.16 
LWS 0.33 0.84 1.26 2.97 2.96 4.11 
L3 HWS 0.43 1.22 2.09 6.03 5.52 0.15 
LWS 0.45 1.22 1.89 4.96 3.23 5.87 
Figure 7

Water age spatial distribution at LWS (a and c) and HWS (b and d) in the L0–L1 models, respectively.

Figure 7

Water age spatial distribution at LWS (a and c) and HWS (b and d) in the L0–L1 models, respectively.

Close modal
Figure 8

Water age spatial distribution at LWS (a and c) and HWS (b and d) in the L2–L3 models, respectively.

Figure 8

Water age spatial distribution at LWS (a and c) and HWS (b and d) in the L2–L3 models, respectively.

Close modal

At the minimum ecological flow (L1, Figure 7(b) and 7(c)), the time taken for the water to reach the intersection of the South Channel and the North Channel at a HWS and LWS was approximately 14 and 16 days, respectively. In addition, the water age of Min'an at HWS and LWS was 0.23 and 12.28 days, respectively, which was smaller than that at the North Channel, and this could be attributed to the tidal advection and dilution of the seawater at high tide. Compared with that of the L0 model, the water age of the North Channel export and the South Channel export of the L1 model increased by 12.12 and 11.16 days, respectively, at a LWS, and 7.49 and 9.15 days, respectively, at high tide. This indicates that the time taken for hypoxic water to reach the downstream in the L1 model was several days longer than that of the L0 model, which resulted in an increase in the ∂t.

The ∂t of water is affected by river runoff. With an increase in the discharge runoff, the flow velocity increased, and the ∂t decreased. The KR of the hypoxic water from Shuikou was significantly larger than the DO consumption, which could be attributed to the low water quality concentration of the discharged water from the Shuikou reservoir. In addition, the decrease in the DO caused by a decrease in the time was more notable than the change in KR caused by the increase in the river runoff.

At the maximum generation flow condition (L2, Figure 8(a) and 8(b)), the time taken for water to reach Min'an at a LWS was 4.26 days. In addition, compared with the L0 model, the water ages of the North Channel export and South Channel export in the L2 model decreased by 1–2 days. Consequently, the ∂t increased, which resulted in a decrease in the DO of the L2 model compared with that of L0 in the lower reaches of the Minjiang River. Compared with the L0 model, there was no significant change in the water age of Min'an in the L3 model (Figure 8(c) and 8(d)); however, the water age of the North Channel increased by 0.83 days and that of the South Channel decreased by 1.07 days.

The aforementioned results confirmed that under the same meteorological conditions, the increase in the runoff and the decrease in the water age, ∂t, and DO in the lower reaches of the Minjiang River resulted in a low DO and low water quality concentration of the water discharged from the Shuikou reservoir (refer to L0–L3). In addition, it should be noted that the DO of the downstream might decrease with a decrease of runoff when a large amount of pollutants are discharged (refer to L1). For example, the residence time of L1 increased by 9 days in the North Channel, which received 80% of the domestic and industrial pollutants of the municipal district of Fuzhou. Consequently, the concentration of DO-consuming pollutants gradually accumulated and could not be discharged into the ocean quickly owing to tidal jacking. Thus, the amount of DO in the water column of the North Channel decreased by the process of respiration was higher than the quantity of DO re-supplied via air–water exchange or advection (Rabalais et al. 2009; Kumarasamy 2015).

The impact of river runoff on the DO and water age in the lower reaches of the Minjiang River at low flow was more significant than that at high flow. In addition, the water age in the upper reaches of the Minjiang River was mainly controlled by river runoff, and the water age in the lower reaches near the open sea was mainly determined by tidal advection (Zhang et al. 2015, 2016, 2021).

Short-term low DO caused by the rapid increase in the water flow from the Shuikou dam

The Zhuqi automatic monitoring revealed that there was a significant decrease in the DO several times in 2013, such as between 15 and 22 December (Julian day: 348–355; Figure 9) and 29 September–1 October (Julian day: 271–273; Figure 11). During the period of the short-term low DO in the lower reaches of the Minjiang River, the water flow from Shuikou increased significantly from approximately 500 to 1,500 m3· s−1, even to a maximum power generation flow of 2,100 m3· s−1 at the beginning of a rainstorm. The relationship between the DO, water age, and flow of sections in the lower reaches (Figures 9 and 10: zone I) from 15 to 22 December (Julian day: 348–355) was investigated. During this period, the average water temperature and wind speed was 17.44 °C and 2.95 m · s−1, respectively, and the wind direction was mainly northwest or northeast. From 12 to 17 December, the water discharge from the Shuikou dam increased significantly from 480 (on the 15th) to 2,332 m3 · s−1 (on the 18th), with an increase in the quantity of water (more than 2,100 m3 · s−1) discharged through the spillway, after which the water discharged decreased to 888 m3 · s−1 on the 22nd. The regional average rainfall during this period was 81.61 mm. Before the 15th of December, the water flow was low, and the DO of the Geyangkou, Xiaxiyuan, Zhuqi, and Wenshanli sections were relatively stable. However, with an increase in the power generation flow, the DO of the Geyangkou section initially decreased. As the hypoxic water gradually reached the downstream, the DO of each section decreased sequentially (the time (Δt1) taken for the water to flow from Geyangkou to Zhuqi was approximately 1.0 days) and there was no significant change in the DO of water under the dam. With a further increase in the flow, the time taken for the hypoxic water to reach the downstream decreased (the water age of Zhuqi decreased from 3.04 to 0.82 days). With a decrease in the ∂t, the DO of Xiaxiyuan, Zhuqi, Wenshanli, and other sections in the downstream continued to decrease (for example, the DO of Zhuqi decreased by 1.8 mg·L−1). In addition, some water (more than 2,100 m3 · s−1) was discharged through the spillway on the 18th, thus increasing the DO of the mixed water from the dam by 0.75 mg · L−1. Furthermore, the DO of each downstream section increased successively. With a decrease in the time taken for water to flow from Geyangkou to Zhuqi (Δt2 = 0.5 days, Δt1 > Δt2), the difference in the DO from Geyangkou to Zhuqi decreased. With the end of rainfall, the discharge flow gradually recovered to 700–800 m3 · s−1 after the 22nd of December, and the DO and water ages of the downstream sections gradually recovered. However, the effect of the flood discharge on the DO of Kuiqi was low, which could be attributed to the superposition of water pollutant DO consumption and tidal advection (Figure 9).
Figure 9

Variation diagram of DO and runoff volume in the downstream sections from 12 to 27 December 2013 (Julian day: 345–360).

Figure 9

Variation diagram of DO and runoff volume in the downstream sections from 12 to 27 December 2013 (Julian day: 345–360).

Close modal
Figure 10

Variation diagram of water age and runoff volume in the downstream sections from 12 to 27 December 2013 (Julian day: 345–360).

Figure 10

Variation diagram of water age and runoff volume in the downstream sections from 12 to 27 December 2013 (Julian day: 345–360).

Close modal
Figure 11

Variation diagram of DO and runoff volume in the downstream sections from 18 September to 8 October 2013 (Julian day: 260–280).

Figure 11

Variation diagram of DO and runoff volume in the downstream sections from 18 September to 8 October 2013 (Julian day: 260–280).

Close modal
The relationship between the DO, water age, and flow in the sections in the lower reaches (Figures 11 and 12: zone I) from 29 September to 1 October (Julian day: 271–273) was also reflected the phenomenon of the short-term low DO. During this period, the water temperature was relatively high (27.73 °C), the DO of the water from Shuikou Dam to Zhuqi was below 5.0 mg · L−1, and the DO of water from dam bottom was lower than 2.0 mg · L−1, which is lower than the Grade III requirement of Environmental Quality Standards for Surface Water (GB3838-2002). The water discharge from the bottom of the Shuikou dam increased from 460 (on the 29th) to 1,748 m3 · s−1 (on the 30th), and then decreased to 391 m3 · s−1 (on October 1st). In addition, there was a notable inflection point of DO (short-term low DO) at each section from Zhuqi to Wenshanli (Figure 11). Subsequently, ∂t increased with an increase in the water age, after which DO returned to the previous concentration. There was no significant change in the DO of Kuiqi, which was lower than that of Wenshanli owing to the high DO consumption of the North Channel during the high-temperature period.
Figure 12

Variation diagram of water age and runoff volume in the downstream sections from 18 September to 8 October 2013 (Julian day: 260–280).

Figure 12

Variation diagram of water age and runoff volume in the downstream sections from 18 September to 8 October 2013 (Julian day: 260–280).

Close modal

There was a negative correlation between the DO in the downstream reach of the Shuikou dam and river flow when the water discharge from the Shuikou dam was less than the maximum generation flow (2,100 m3 · s−1). During the period of continuous low flow, the Shuikou reservoir capacity was released via drainage during the initial stage of a rainstorm, resulting in a sharp increase in the discharge from Shuikou. First, this affected the original balance process of DO along the lower reaches of the Minjiang River, which resulted in the rapid flow of the hypoxic water downstream; thus, leading to a sharp increase in the DO until the lowest point owing to the reduction of the ∂t. As the water discharge from the Shuikou dam decreased the previous magnitude of discharge, the DO in the reach from Geyangkou to Zhuqi returned to the previous concentration. Consequently, the concentration of the DO in the downstream exceeded the standard for a short time at high temperatures (Lanoux et al. 2013; Li et al. 2020a).

The above results were supported by the correlation analysis of daily average DO and discharged from the Shuikou dam in 2012. The full load power generation flow of the Shuikou power station was about 2,100 m3·s−1. DO and runoff presented a significant negative correlation in Zhuqi, Wenshanli when Q < 2,100 m3· s−1. The correlation coefficients were −0.270 and −0.526, respectively. The runoff was not correlated with DO at the Baiyantan section near the estuary. Zhuqi, Wenshanli, Baiyantan DO, and runoff showed a significant positive correlation when Q > 2,100 m3· s−1, the correlation coefficients were 0.436, 0.287, and 0.229, respectively. It could be seen that when the discharge of Shuikou Reservoir was all used for power generation (Q < 2,100 m3· s−1), the larger the discharge, the lower the DO in the downstream. When the discharge further increased beyond full load power generation flow (2,100 m3· s−1), as the flow rate increased, the downstream DO increase (Table 3).

Table 3

Pearson correlation of DO and flow when Q < 2,100 m3·s−1 and Q > 2,100 m3·s−1 in each section

StationQ (m3·s−1)Correlation coefficient between DO and QCorrelation
Zhuqi <2,100 −0.270** Significant weak correlation 
>2,100 0.436** Moderately significant correlation 
Wenshanli <2,100 −0.526** Moderately significant correlation 
>2,100 0.287** Significant weak correlation 
Baiyantan <2,100 −0.071 Uncorrelation 
>2,100 0.229** Significant weak correlation 
StationQ (m3·s−1)Correlation coefficient between DO and QCorrelation
Zhuqi <2,100 −0.270** Significant weak correlation 
>2,100 0.436** Moderately significant correlation 
Wenshanli <2,100 −0.526** Moderately significant correlation 
>2,100 0.287** Significant weak correlation 
Baiyantan <2,100 −0.071 Uncorrelation 
>2,100 0.229** Significant weak correlation 

**Significantly correlated at the 0.01 level (bilateral).

In this study, the spatial and temporal distributions of the water age and DO were simulated by using the Minjiang River model. The water age concept was introduced to quantitatively investigate the causes of DO evolution in a typical estuary area, which was mainly affected by runoff and tide. The results revealed that the spatial distribution of DO was affected by temperature, runoff, pollution emission, tidal advection, and hypoxic water discharge from the reservoir bottom. In addition, the results revealed that continuous low DO in water could be attributed to was caused by low flow, high temperature, pollution emission, and tidal jacking, in which, the low flow and tidal jacking led to an increase in the water age and accumulation of pollutants. In addition, a high temperature resulted in a decrease in the saturated DO and an increase in the DO consumption coefficient. Consequently, there was a continuous low DO in the water of the North Channel.

With an increase in the pollution emission along the Minjiang River, the ADOC increased from upstream to downstream. The proportion of the four DO consumption factors was 45–54% (DOC) > 37–40% (SOD) > 7–10% (NH4) > 2–5% (Bx). The largest DO consumption proportion of NH4 was observed in the North Channel, and the largest DO consumption proportion of DOC was observed in the estuary.

There was a negative correlation between the DO in the downstream reach of the Shuikou dam and the river flow when the water discharge from the Shuikou dam was less than the maximum generation flow (2,100 m3· s−1). The short-term low DO was attributed to the rapid increase in the water flow from the Shuikou dam, the decrease in water age (∂t), and the delayed reaeration of the hypoxic water along the Minjiang River when the Shuikou reservoir capacity was released via drainage at the initial stage of a rainstorm. With a decrease in the water flow to the previous level, the water age and DO in the downstream water recovered. In addition, the results revealed that ∂t rather than KR was the main factor affecting the decrease in DO in the lower reaches of the Minjiang River when the water discharge from the Shuikou dam was large.

Part of this work was supported by High-level Personnel Research Startup Project of North China University of Water Resources and Electric Power (NO.40768). We are grateful to the journal experts for their valuable comments on this paper.

P.Z.: Investigation, EFDC model building, Formal analysis, Writing – original draft, Writing – review & editing. B.W.: Data curation, Mapping, Writing – review & editing. Y.S.: Mapping, Writing – review & editing. Y.P.: Project administration, Writing – review & editing. C.S.: Project administration, Supervision, Writing – review & editing. R.X.: Investigation, Formal analysis, Writing – review & editing.

Data cannot be made publicly available; readers should contact the corresponding author for details.

The authors declare there is no conflict.

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