Two-dimensional Hydrodynamics and Water Environment

Simulation: A Case Study in the Guanlan River Basin in China

Xiaoqi Zhang

1,2,3

, Shuai Xie

1,2,3

, Tao Zhou

1,2,3

, Yongqiang Wang

1,2,3,*

, and Yilin Du

1,2,3

Changjiang River Scientific Research Institute, Changjiang Water Resources Commission of the Ministry of Water

Resources of China, Wuhan 430010, China

Hubei Key Laboratory of Water Resources & Eco-Environmental Sciences, Changjiang River Scientific Research Institute,

Wuhan 430010, China

Research Center on the Yangtze River Economic Belt Protection and Development Strategy, Hubei Wuhan 430010, China

Keywords: Urban River, Hydrodynamics, Water Environment, Guanlan River

Abstract: As an important resource and environmental carrier, urban rivers are related to the survival of the city and

restrict the development of the city. However, situations caused by environmental degradation, water pollution

occurs in urban rivers. Therefore, comprehensive treatment of urban water pollution has become a necessity.

This study establishes a two-dimensional Hydrodynamics and Water Environment (HWE) model based on

MIKE21 FM, and then the simulation effect of the proposed HWE model is verified by comparison with the

measured data. With Shenzhen city’s Guanlan River as a case study, the results indicate that (1) the water

level and water quality of the proposed HWE model have a good fit; (2) the flow velocity of the main stream

in the Guanlan River shows a gradual increase trend from the upstream to the downstream, that is, the average

flow velocity values of the upstream, middle, downstream reaches are 0.034 m·s

-1

, 0.041m·s

-1

, and 0.183 m·s

; and (3) the temporal and spatial distribution of the water quality parameters in the Guanlan River shows

that the flow of river water has a diluting effect on the sewage discharged from the sewage treatment plant.

These findings are helpful to the analysis of urban river’s hydrodynamics and water environment

characteristics.

1 INTRODUCTION

Urban rivers are an integral part of human life, and

the ecological foundation of the urban environment

(Zhang et al., 2017). However, urban rivers are facing

problems such as water degradation, water pollution,

and the gradual decline of the aquatic ecological

environment due to anthropogenic factors as

consequence of rapid economic development and

global climate change (Ge et al., 2020; Niu et al.,

2021; Zhang et al., 2021). Therefore, the

comprehensive management for the rivers is of

significance for the urban development with the

purpose of the harmony between human beings and

water resources.

Hydrodynamics is the basis for studying the

evolution of river flow. The two main methods

commonly adopted for researching on

hydrodynamics are mathematical statistics and

mathematical model simulation (Sun et al., 2017).

Generally, there exists certain errors between the

results of mathematical statistics and the real results

due to the complexity of the actual situation, and the

method lacks an analysis of the mechanism. With the

development of computer technology, mathematical

model methods have gradually been applied to the

field of water resources, and this method can make up

for the deficiencies of mathematical statistics in

mechanism research (Huang et al., 2015; Shchepetkin

et al., 2005). Correspondingly, numerical simulation

software has also been widely applied, and commonly

used simulation software includes EFDC, ROMS,

MIKE, HEC-RAS 2D, Iber 2D, Flood Modeller 2D,

and PCSWMM 2D etc. (Chen et al., 2003; Pinos et

al., 2019; Yuan et al., 2006).

Research on river water environment mostly

focuses on the source and migration process of water

quality elements, which is the research foundation for

comprehensive treatment of water environment in

rivers (

Zuo & Li, 2013). Cui et al. (2021) analyzed the

characteristics of temporal and spatial changes in

river water quality with the help of logarithmic power

Zhang, X., Xie, S., Zhou, T., Wang, Y. and Du, Y.

Two-dimensional Hydrodynamics and Water Environment Simulation: A Case Study in the Guanlan River Basin in China.

In Proceedings of the 7th International Conference on Water Resource and Environment (WRE 2021), pages 275-283

ISBN: 978-989-758-560-9; ISSN: 1755-1315

275

function universal index formula. Wang et al. (2021)

analyzed the influence of environmental changes on

system attributes by establishing 14 Ecopath models

composed of 28 functional groups along a subtropical

urban river. Zhang et al. (2020) selected Chemical

Oxygen Demand (COD), Total Phosphorus (TP) and

Ammonia nitrogen content index (NH

-N) as

characteristic indexes to simulate the hydrodynamic

and water quality of the Shunyi section of Chaobai

river based on MIKE21 model. However, the research

on joint analysis of the two-dimensional

hydrodynamic and water environment of urban rivers

by considering the impact of sewage treatment plants

still have room for exploration, which are necessary

for comprehensive management of urban river

environment. Therefore, the aim of this paper is to

establish a coupling model of hydrodynamics and

water environment based on MIKE21 FM, and then

analyze the hydrodynamic characteristics and

pollutant migration law, which serves to find the key

influencing factors for the comprehensive

management of urban rivers.

2 STUDY AREA AND

METHODOLOGY

2.1 Study Area

The Guanlan River Basin (22.58°-22.76°N, 113.96°-

114.16°E) was selected as the study area (Figure 1),

which is in the north-central part of Shenzhen city,

south-central Guangdong province, southeastern

China. The Guanlan River, one of the five major

rivers in Shenzhen with a catchment area of more than

100 km

, is the upstream section of the Shima River

in the Dongjiang water system. It originated in

Jigongtou, Niuzui Reservoir in the Cerebral Shell

Mountain (385.4 masl). The mainstream passes

through Longhua New District from south to north,

enters the territory of Dongguan City below Qiping,

Guanlan Street, and merges into Dongjiang River at

the junction of Dongguan and Huizhou. The Guanlan

River Basin referred to in this article includes the

Guanlan River sub-basin and other tributaries of the

Shima River system located in Shenzhen, with a total

area of 247.3 km

Figure 1: A schematic diagram of the study area.

The underlying surface of the Guanlan River

Basin is divided into six categories: green space,

water body, roof, bare soil and pavement. The area of

green land (including mountains) is 104.25 km

water area is 11.25 km

, roof area is 40.17 km

, road

area is 38.39 km

, bare soil area is 2.64 km

, paving

area is 50.55 km

, and the above-mentioned area is

247.3 km

in total.

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276

2.2 Database

The data involved in this study mainly include the

measured water quality data of the Guanlan River’s

main stream (GRMS) from January 1st to June 1st,

2019, and the current water environment monitoring

data acquired during the project period. The main

water quality indicators include COD, NH

-N and TP.

The 13 amphibious boundaries (only 6 have flow

sequence data, among which Niuzui River and

Minzhi River merge into Yousong River, and

Dashuikeng River merges into Baihua River) and 13

point-source hydrodynamic boundaries are shown in

Figure 2.

Figure 2: Generalized diagram of model hydrodynamic boundary.

2.3 Model Governing Equation

The GRMS is a relatively smooth river with a slope

of 1.2‰. The vertical mixing of the water body is

relatively uniform, and the uneven distribution of the

spatial plane is relatively significant. Therefore, a flat

two-dimensional mathematical equation with average

water depth is used to describe the water quality

movement characteristics of the GRMS from the

perspective of reflecting the overall change

characteristics of water quality in the study area. The

mathematical model of the water environment in the

GRMS based on the MIKE21 model is established.

The hydrodynamic control equation of MIKE21

FM module can be expressed as:

(1) Continuity equation

() ()hhu hv

tx y

∂∂ ∂

++=

∂∂ ∂

(1)

Two-dimensional Hydrodynamics and Water Environment Simulation: A Case Study in the Guanlan River Basin in China

277

(2) Momentum equation

000

+()()

asxbx

xx xy s

hu hu huv h gh

fvh gh

tx y x x x

hT hT hu S

xy x y

ττ

ρρ

∂

∂∂ ∂ ∂ ∂

++=− − − +−

∂∂ ∂ ∂ ∂ ∂

∂



∂

∂∂

−+++



∂∂ ∂ ∂



(2)

+()()

yby

yx yy

xy yy s

hv huv hv h gh

fuh gh

tx y y y y

hT hT hu S

xy x y

ττ

ρρ

∂

∂∂ ∂ ∂ ∂

++=−− − − +−

∂∂ ∂ ∂ ∂ ∂

∂∂



∂∂

−+++



∂∂ ∂ ∂



(3)

The MIKE21 FM water quality module adopts

the convection-diffusion equation, and the governing

equation is:

() ( ) ( ) ) )

()()

hc uhc vhc c c

hE hE khc S

tx yxxyy

∂∂ ∂ ∂∂∂∂

++= + −+

∂∂ ∂∂∂∂∂

(4)

where

represent the Cartesian coordinate system,

is the time,

and

are the velocity

components in the

and

directions,

respectively,

is the total water depth,

is the

source term,

is the still water depth,

is the

water level,

is the local atmospheric pressure,

is the density of water,

is the reference water

density,

2sinf

=Ω

is the Coriolis coefficient (

is the angular rate of the earth’s rotation and

is the

geographic latitude),

are the

radiation stress component,

are the

acceleration caused by the rotation of the earth,

are the surface wind stress,

are the

bottom friction stress,

is the concentration of

pollutants,

are respectively sum of

turbulent diffusion coefficient and dispersion

coefficient in

and

directions,

are the horizontal viscous stress,

is the

attenuation coefficient.

3 GENERALIZATION OF THE

HWE MODEL

The calculation area in this study includes all areas of

the GRMS. Due to the irregular shape of the boundary

of the GRMS, the model should be divided by the

unstructured grid (triangular grid) processing method,

and the calculation stability of the mathematical

model should be ensured.

represents the east

direction,

represents the north direction, the unit

of coordinate value is meters. The model has a total

of 2750 nodes and 3835 calculation grids, which is

shown in Figure 3.

Figure 3: Meshing diagram.

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4 CALIBRATION AND

VERIFICATION FOR

PARAMETERS OF THE HWE

MODEL

4.1 Hydrodynamic Parameters

The roughness of the GRMS is n=0.033 as the initial

roughness for calculation, and the eddy viscosity

coefficient is determined according to the

Smagorinsky formula. The measured daily hydrology

and other basic data of the GRMS are the input data

for the model, and the calculated output of the model

is compared with the monitoring data of the water

level at the outlet section of the GRMS. The

comparison results of the simulated and measured

water level of the Qiping section in the GRMS from

January 1, 2019 to May 31, 2019 are shown in Figure

Figure 4: Comparison results of simulated and measured water level of Qiping section.

4.2 Water Quality Parameters

The comprehensive degradation coefficients of the

main water quality indicators, COD, NH

-N and TP,

considered for the GRMS are 8.0e

-8

/s, 1.0e

-8

/s, 1.0e

/s, respectively. The measured daily hydrology and

water quality data of the Guanlan River’s main stream

are used as the input data for the HWQ model, and the

simulation results are compared with the main

monitoring data of the GRMS to verify the reliability

of the model. The water quality results including the

four monitoring points (i.e., the Qinghu Bridge,

Meiguan Expressway, Fangmapu and Qiping

Sections on the main stream of the Guanlan River)

and the 11 first-class rivers entering the estuary from

January 1, 2019 to May 31, 2019 are simulated by the

HWQ model. The water quality (COD, NH

-N and

TP) process of the GRMS and the confluence of

various rivers simulated by the model fits well with

the measured values, indicating that the constructed

water quality model can better reflect the migration

and diffusion of pollutants in the main stream of the

Guanlan River. The Gangtou River estuary section is

selected to show the fitting effect of COD, NH

-N and

TP parameters (Figure 5).

Two-dimensional Hydrodynamics and Water Environment Simulation: A Case Study in the Guanlan River Basin in China

279

Figure 5: Comparison results of simulated and measured water quality of Gangtou River Estuary: (a) COD; (b) NH3-N; (c)

TP.

5 CHARACTERISTIC ANALYSIS

OF HYDRODYNAMICS AND

WATER ENVIRONMENT

The GRMS is divided into three areas: the upstream

(S), the middle (Z) and the downstream (X). Each

area selects four points, the monthly average value of

which is used to analyse the regional characteristics

(Figure 6).

5.1 Hydrodynamic Characteristics of

the Main Streamin Guanlan River

As shown in Figure 7, the hydrodynamic

characteristics and pollutant migration laws of the

main stream in the Guanlan River from January 1,

2019 to May 31, 2019 were analyzed based on the

simulation results derived by the proposed

hydrodynamic and water environment model. The

range of flow velocity of the GRMS is 0-0.354 m·s

-1

and the average flow velocity is 0.086 m·s

-1

. The

average flow velocity values of the upstream, middle,

downstream reaches are 0.034 m·s

-1

, 0.041m·s

-1

, and

0.183 m·s

-1

. As the upstream slope of the GRMS is

gentler than the middle and lower reaches, the upper

reaches are obviously influenced by river retention.

Furthermore, the middle and downstream flow

velocity is relatively large due to the gravity of the

water flow. Therefore, the flow velocity of the GRMS

gradually increases from the upstream to the

downstream.

Figure 6: Schematic diagram of main points on the Guanlan

River’s main stream.

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280

5.2 Temporal and Spatial Distribution

Characteristics of Water

Environment in the Guanlan

River’s Main Stream

The sewage treatment plants are mainly distributed in

the middle and lower reaches, and the three water

quality indicators, COD, NH

-N and TP are used to

analyze the temporal and spatial distribution

characteristics of water quality in the GRMS. In

Figure 8(a), the average concentrations of COD in the

upstream, midstream and downstream are 12.36

mg·L

-1

, 12.92 mg·L

-1

and 13.31 mg·L

-1

, respectively.

Figure 8(b) shows that the average concentrations of

-N in the upstream, midstream and downstream

are 0.80 mg·L

-1

, 0.48 mg·L

-1

and 0.46 mg·L

-1

respectively, while the average concentrations of TP

in the upstream, midstream and downstream

respectively are 0.15 mg·L

-1

, 0.23 mg·L

-1

and 0.24

mg·L

-1

. The change trends of the water quality

indicators in the upper, middle and downstream

districts are due to the dilution effect of the sewage

treatment plants along the way to the water body,

which can be concluded from the results of Figure 8-

9 as follows: (i) as shown in Figure 8, the dilution

effect of the sewage treatment plants on NH

-N from

upstream to downstream is significant; (ii) take the

simulation results of water quality in the downstream

section as an example, the index values of COD and

TP show a decreasing trend from the upper section to

the lower section.

Figure 7: Changes in the flow velocity of the main stream of the Guanlan River: (a) upstream (S); (b) middle (Z); (c)

downstream (X).

Two-dimensional Hydrodynamics and Water Environment Simulation: A Case Study in the Guanlan River Basin in China

281

Figure 8: Distribution of water quality in Guanlan River’s main stream: (a) COD; (b) NH3-N; (c) TP.

Figure 9: Changes of water quality in the downstream of the Guanlan River’s main stream: (a) COD; (b) TP.

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6 CONCLUSIONS

In this paper, combined with the characteristics of the

Guanlan River project, a two-dimensional HWE

model for the GRMS was constructed based on

MIKE21 FM. Then, the measured water level and

flow data of each section of the Guanlan River is used

to calibrate and verify the rationality of the model

establishment. The main conclusions are summarized

as follows:

(1) The water level and water quality of the

proposed HWE model have a good fit, which can be

applied to the simulation analysis of the Guanlan

River’s hydrodynamic and water environment

scenarios.

(2) As the upstream slope of the GRMS is gentler

than the middle and lower reaches, the flow velocity

of the GRMS shows a gradual increase trend from the

upstream to the downstream, that is, the average flow

velocity values of the upstream, middle, downstream

reaches are 0.034 m·s

-1

, 0.041m·s

-1

, and 0.183 m·s

-1

(3) The change trends of the water quality

indicators in the upper, middle and downstream

districts are shown as follows: i) the average

concentrations of COD in the upstream, midstream

and downstream are 12.36 mg·L

-1

, 12.92 mg·L

-1

and

13.31 mg·L

-1

, respectively; ii) the average

concentrations of NH

-N in the upstream, midstream

and downstream are 0.80 mg·L

-1

, 0.48 mg·L

-1

and

0.46 mg·L

-1

, respectively; iii) the average

concentrations of TP in the upstream, midstream and

downstream respectively are 0.15 mg·L

-1

, 0.23 mg·L

and 0.24 mg·L

-1

. Moreover, the sewage treatment

plants along the way has a dilution effect on the water

body (indictor values of COD, NH

-N and TP) within

a certain range.

ACKNOWLEDGMENTS

This work is funded by National Natural Science

Foundation of China (41890822), Water Resource

Science and Technology Innovation Program of

Guangdong Province (2017-03).

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