# Urban Water Ecosystem Health Evaluation Based on the Improved Fuzzy Matter-Element Extension Assessment Model: Case Study from Zhengzhou City, China

Authors: Han Han; Huimin Li; Kaize Zhang
Journal: Mathematical Problems in Engineering
 (2019)

---

## Abstract

The urban water ecosystem is a core foundation for the urban construction of ecological civilization. Ecosystem health is directly related to the economic development of the region and the quality of urban residents’ lives. Evaluating the health state of an urban water ecosystem is an important prerequisite for the construction of an ecologically civilized city. This study used Zhengzhou City in China as research area. Firstly, a Pressure-State-Response (PSR) model was used to construct an urban water ecosystem evaluation index system. Secondly, after analyzing the deficiency of traditional fuzzy matter-element extension model in urban water ecosystem health assessment, an improved fuzzy matter-element extension assessment model (FMEAM) was constructed by introducing the variable weight theory. Finally, using the proposed model above and the data from 2007 to 2016, this study evaluated the water ecosystem health status of Zhengzhou based on water ecosystem health integrated index (WHI). The results showed that the state of the urban water ecosystem in Zhengzhou generally improved during the study period. However, the overall level still remained low and retained an unhealthy state throughout the timeframe. The pressure on the Zhengzhou water ecosystem mainly originates from the increasing urbanization rate, the increased consumption of ecological environmental resources, and household water. Corresponding countermeasures in Zhengzhou have achieved certain results, and the health of the state’s subsystem and response subsystem has improved. However, it remains necessary to further strengthen the protection of the ecological environment, particularly with respect to water resources.


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## Body

## 1. Introduction

Water is a basic element of the ecological environment and is the material basis for human survival and development [1]. Recently, the conflict between humans and water resources intensified, due to the irrational use of water resources. Water resources are being increasingly threatened by factors such as urbanization, agricultural intensification, and climate change [2]. Climate change and significant water pollution have destroyed water ecosystems in many areas, resulting in imbalances in the supply and demand of water resources [3–5]. In addition, the destruction of water ecosystems significantly affects the sustainable development of nature, the economy, and the society. This can lead to the deterioration of the urban environment [6]. China is one of the largest developing countries and has a surprising economic growth rate in the past 10 years. However, the rapid growth of the Chinese economy poses a huge threat to the eco-environment, especially the water environment [7]. To respond to the problem of a deteriorating water environment, in 2007, China national government proposed the construction of an ecologically civilized city to achieve the sustainable development of the country. An ecologically civilized city is a human settlement aimed at the harmonious development of human beings, natural environment, and resources, so as to realize the environmental friendliness. As an important part of ecologically civilized city, city’s water ecosystem health state directly affects the sustainable development of society. Therefore, it is important to systematically diagnose the health of the urban water ecosystem to support sustainable ecological management.An ecosystem is described as “a unified whole composed of biology and environment in a particular physical space of nature. In this unified system, biology and environment interact with and mutually restrict each other, and they are in a relatively stable state during a certain period” [8, 9]. According to the components of the ecosystem, the ecosystem is divided into forest ecosystem, grassland ecosystem, marine ecosystem, freshwater ecosystem, farmland ecosystem, tundra ecosystem, wetland ecosystem, and urban ecosystem [10, 11]. Among them, an urban ecosystem mainly refers to a system composed of natural environment, economic system and social system in the urban. The economic system mainly involves various human economic activities in the social development, including production, distribution, circulation and consumption. The social system is mainly composed of human and socio-economic factors, involving all aspects of the social, economic and cultural activities of urban residents. The natural environment includes basic resources such as water, air, food, and energy [12] and provides the material basis for human survival and socioeconomic development [13]. A healthy urban ecosystem can provide ecological services for human beings and ensure the sustainable development of society.At present, the issue of urban ecosystem health has attracted the attention of scholars and government organizations worldwide [14, 15]. The concept of urban ecosystem health was first proposed by Rapport [16]. The cities and human settlements link the concepts related to the ecosystem and human health, which aims to achieve the sustainable development of human beings and natural environment, without compromising ecological services or ecosystem health. Ecosystems satisfy human needs by providing resources [17]. An urban water ecosystem is a unified system, composed by the interaction between urban residents and their water environment; water ecosystem is an important part for constructing an ecologically civilized city with respect to water and is interconnected with the construction of and research about an ecologically civilized city [18]. The health of urban water ecosystems focuses on the reasonable structure and efficient functioning of a water ecosystem from the perspective of ecology. This mainly means that the urban water ecosystem maintains its integrity and health and continues to provide healthy ecological services for human beings [19].As the key source of providing water, the urban water ecosystem is an important part of urban ecosystems and plays a great role in urban socioeconomic system, which provides material basis for socioeconomic development. On the one hand, the urban water ecosystem provides freshwater for human’s subsistence and meets the human needs for water [20]. On the other hand, the urban water ecosystem satisfies industry, agriculture, and other economic activities needs by acting as a source of water and can treat sewage by water ecological circulation system to ensure these economic activities’ healthy operation [21]. So, a healthy urban water ecosystem is the foundation of the urban socioeconomic system. However, with the growth of GDP and acceleration of urbanization, the urban socioeconomic system brings a larger pressure on the urban water ecosystem. Water shortages and deterioration of water quality are becoming more serious. Faced with increasing pressure on urban water ecosystem, some response measures such as treatment of water environment and investment in water environmental protection projects are taken to reduce the pressure on the water environment and realize the efficient utilization of water resources.Current academic research of the urban water ecosystem health mainly involves the restoration of urban water ecosystems [22], urban storm water management [23, 24], and urban flood control and drainage [25, 26]. For example, Rai focused on improving and enhancing the health status of the urban water ecosystem, by studying key elements of water ecological restoration technology [27]. Jooste focused on improving the health state of rivers, by studying the mechanism of aquatic plants on ecological restoration [28]. Wenk studied ways to achieve the stability of urban water ecosystem by controlling, using, and comprehensively managing urban stormwater [29]. Evaluating water ecosystem health has mainly involved evaluating the river basin ecological health [30–32], and selecting indicators has been mainly based on the indicator species method of the natural ecosystem and systematic index evaluation [33].In summary, the existing studies provide reference for this research; however, the current studies of the evaluation of urban water ecosystem still have some shortcomings. As a complex system composed of nature, society, and economy, an urban water ecosystem is a network of multiple interactions, and its health status should account for various factors in an integrated way, instead of only focusing on partial elements such as water, soil, and aquatic organisms [34]. Selecting evaluation indexes should turn from a traditional perspective of “water quality” to a way of more comprehensive evaluation of water ecosystem health [35]. However, several studies evaluated the health status of urban water ecosystem only via water quality and failed to integrate social, economic, and water environment factors to comprehensively evaluate the health status of urban water ecosystem.A recent study shows that a truly sustainable water ecosystem management requires estimating the pressures on water ecosystems [36]. To address these problems, first, an urban water ecosystem health evaluation index system is constructed based on the Pressure-State-Response (PSR) model. Second, an improved fuzzy matter-element extension assessment model (FMEAM) is constructed by introducing the variable weight theory. Finally, the urban water ecosystem health of Zhengzhou City from 2007 to 2016 was evaluated by using the urban water ecosystem health integrated index (W
H
I). The W
H
I is a comprehensive index for urban water ecosystem health status; it is calculated using the FMEAM. Based on this, the reasons for variations in Zhengzhou health are discussed and countermeasures are proposed. This investigation and assessment of urban water ecosystem health may provide a vital basis for the construction of an ecological civilization with respect to water.


## 2. Material and Methods

### 2.1. Research Area

Zhengzhou, the capital of Henan province, is one of the most important economic cities in China. Zhengzhou is located in the lower reaches of the Yellow River and covers a total area of 7446 square kilometers, which lies between E 112°42′—114°14′ and N 34°16′—34°58′ (Figure1). It has 12 districts (counties) with a resident population of 7.57 million and an urbanization rate of 69.7%. The annual average water resources are about 1/10 of the national average, only 1.323 billion m3, with less than 178 m3 per capita in 2016 [37]. Water resources are in relatively short supply. Zhengzhou is one of the first pilot cities for the construction of ecologically civilized city in China.Figure 1
Location of the Zhengzhou City.


### 2.2. Methods

The “Pressure-State-Response” urban water ecosystem health evaluation index system was established by using the PSR model. The model covers 20 indicators and reflects the water ecosystem health conditions in Zhengzhou City. An improved FMEAM model was used to determine theW
H
I to evaluate the health status of the water ecosystem in Zhengzhou.


#### 2.2.1. The PSR Model

The Pressure-State-Response (PSR) model was first proposed by the Organization for Economic Co-operation and Development (OECD) and has been widely used in environmentally relevant issues [38]. The PSR model is a dynamic model structure and includes three major indexes: pressure, state, and response, and the three indexes mutually interact and restrict each other [39]. The PSR model includes a causality of “what happened, why, and how to deal with it” and has the characteristics of flexibility and comprehensiveness [40]. Here, the urban water ecosystem health PSR model covers three dimensions: the pressure on water ecosystem, the maintenance state of the water ecosystem, and the dynamic response of human society. The pressure subsystem mainly refers to the negative impact of economic development and the water resource consumption on the water ecosystem. The state subsystem mainly refers to a comprehensive state of the various conditions of the water eco-environment under the pressure. The response subsystem represents the protective measure humans take to overcome water resource pressures. This model analyzes the interaction between humans and the environment using a system theory perspective. Figure 2 shows the PSR model of the urban water ecosystem health evaluation.Figure 2
PSR model.Selecting evaluation indicators should follow uniform criteria and principles. Based on the principle of constructing a scientific, reasonable, and representative index, we established an index system to evaluate water ecosystem health in Zhengzhou. According to the PSR model, the indicator system mainly includes pressure subsystem (B1), state subsystem (B2), and response subsystem (B3). The indicator layer is determined by 20 indicators, after fully considering the condition of the socioeconomic development and water eco-environment in Zhengzhou. Urban water ecosystem health is a relative and dynamic concept, but it needed to determine the health standard of the evaluation index. In this study, the 20 evaluation indexes in Table1 mainly come from existing research results [41–47], and the grade standard of the indicators for Zhengzhou is determined based on several existing studies and Environmental Quality Standards for Surface Water (GB3838-2002) [44–48]. The water ecosystem health evaluation index system of Zhengzhou City is shown in Table 1, and the grade standard of the evaluation index system is shown in Table 2.Table 1
Evaluation index system of urban water ecosystem health.
Factor
Indicators
Unit
Description
Pressure (B1)
GDP Growth Rate (P1)
%
Represents the increasing economic development pressures on urban water ecosystem [41].
Urbanization Rate (P2)
%
Represents the increasing population pressures on urban water ecosystem [42].
The Proportion of Tertiary Industry (P3)
%
Represents the urban water ecosystem pressures from tertiary industry, such as catering industry and service industry [43].
Water Consumption Per Unit of GDP (P4)
m3 / 10− 4 Yuan
Represents the water consumption per unit of GDP pressures on urban water ecosystem [42].
Water Consumption of Industrial Output (P5)
m3 / 10− 4 Yuan
Represents the urban water ecosystem pressures from industrial development [44].
Water Consumption of Eco-environment (P6)
109 m3
Represents the urban water ecosystem pressures from eco-environment water consumption [43].
Household Water Consumption (P7)
109 m3
Represents the urban water resource pressures from household water consumption [45].
Sewage Discharge (P8)
109 m3
Represents the water pollution pressures on urban water ecosystem [42].
State (B2)
Water Resources Amount Per Unit Area (S1)
104 m3  ·  km−2
Refers to the ratio of surface water resource quantity and the land area [46].
Per Capita Water Resources (S2)
m3
Refers to the proportion of freshwater resource quantity and the population [47].
Per Capita Green Area (S3)
m2
Refers to the ratio of green area and the population [46].
Flood Control Rate (S4)
%
Refers to the state of flood control [46].
Response (B3)
Sewage Treatment Rate (R1)
%
Represents the ability of sewage treatment [42].
Green Coverage Rate (R2)
%
Represents the response to quantity of water resources [42].
River Water Quality Compliance Rate (R3)
%
Represents the ability of river water resources protection [42].
Source Water Quality Compliance Rate (R4)
%
Represents the response to quality of freshwater resources [42].
Rate of Wastewater up to Discharge Standard for Urban (R5)
%
Represents the response to water resource security condition [46].
Water Functional Area Compliance Rate (R6)
%
Represents the response to water resource security condition [45].
Rate of Water Ecosystem Project Investment to GDP (R7)
%
Represents the response to water environmental protection [47].
Rate of Environmental Protection Investment to GDP (R8)
%
Represents the response to ecological management and protection [43].Table 2
The grade standard of evaluation index system.
Factor
Indicators
Unit
Character
healthy
sub-healthy
unhealthy
sick
very sick
Pressure (B1)
GDP Growth Rate (P1)
%
-
≤3
(3, 5]
(5, 8]
(8, 10]
>10
Urbanization Rate (P2)
%
-
≤30
(30, 40]
(40, 50]
(50, 60]
>60
The Proportion of Tertiary Industry (P3)
%
-
≤30
(30, 40]
(40, 50]
(50, 60]
>60
Water Consumption Per Unit of GDP (P4)
m3 / 10− 4 Yuan
-
≤100
(100, 200]
(200, 300
(300, 400]
>400
Water Consumption of Industrial Output (P5)
m3 / 10− 4 Yuan
-
≤30
(30, 60]
(60, 90]
(90, 120]
>120
Water Consumption of Eco-environment (P6)
109 m3
-
≤1
(1, 2]
(2, 3]
(3, 4]
>4
Household Water Consumption (P7)
109 m3
-
≤4
(4, 6]
(6, 8]
(8, 10]
>10
Sewage Discharge (P8)
109 m3
-
≤4
(4, 6]
(6, 8]
(8, 10]
>10
State (B2)
Water Resources Amount Per Unit Area (S1)
104 m3  ·  km−2
+
≥200
[150, 200)
[100, 150)
[50, 100)
<50
Per Capita Water Resources (S2)
m3
+
≥1000
[750, 1000)
[500, 750)
[250, 500)
<250
Per Capita Green Area (S3)
m2
+
≥12
[10, 12)
[8, 10)
[5, 8)
<5
Flood Control Rate (S4)
%
+
≥95
[95, 90)
[85, 90)
[80, 85)
<80
Response (B3)
Sewage Treatment Rate (R1)
%
+
≥80
[60, 80)
[40, 60)
[20, 40)
<20
Green Coverage Rate (R2)
%
+
≥40
[30, 40)
[20, 30)
[10, 20)
<10
River Water Quality Compliance Rate (R3)
%
+
≥90
[80, 90)
[70, 80)
[60, 70)
<60
Source Water Quality Compliance Rate (R4)
%
+
≥95
[80, 95)
[65, 80)
[50, 65)
<50
Rate of Wastewater up to Discharge Standard for Urban (R5)
%
+
≥95
[85, 95)
[75, 85)
[60, 75)
<60
Water Functional Area Compliance Rate (R6)
%
+
≥80
[60, 80)
[40, 60)
[20, 40)
<20
Rate of Water Ecosystem Project Investment to GDP (R7)
%
+
≥1.5
[1, 1.5)
[0.6, 1)
[0.3, 0.6)
<0.3
Rate of Environmental Protection Investment to GDP (R8)
%
+
≥1
[0.8, 1)
[0.5, 0.8)
[0.3, 0.5)
<0.3


#### 2.2.2. Fuzzy Matter-Element Extension Assessment Model and Deficiency

The concept of extenics was first proposed and analyzed by Chinese scholar Cai Wen [49]. Fuzzy matter-element extension model is an evaluation model based on matter-element analysis theory and extenics, selecting matter-element features to be evaluated as evaluation indexes, and using the measured data to calculate the correlation of the object to be evaluated. The fuzzy matter-element expansion assessment model holds that all objects can be represented by name, characteristics, and measures, which creates a new idea of evaluating things and has been successfully applied in many projects’ evaluation [50].In the evaluation method with the fuzzy matter-element extension, the selection of weights is very important and directly affects the final evaluation result. The traditional fuzzy matter-element expansion assessment model usually uses subjective weighting methods such as expert grading and Analytical Hierarchy Process (AHP). The expert grading method is a method of assigning weight values by expert assessment of the importance of each indicator, and the AHP is a method of subjectively determining weights based on the assessment of relative importance of different indicators [51, 52]. However, the evaluation of the urban water ecosystem health by using these traditional weighting methods has certain limitations and disadvantages. On the one hand, these subjective weighting methods have much discretionary subjectivity, which will cause weight values to be influenced by human factors, resulting in inaccuracy in the evaluation results. On the other hand, the evaluation indexes of urban water ecosystem health are all quantitative indexes with measured data. The weight values of the indexes should be determined based on the objective information of the indicator [44]. It is difficult for the weight obtained by subjective weighting to reflect the real health status accurately and objectively. So, the subjective weighting methods are not suitable for urban water ecosystem health evaluation.


#### 2.2.3. Improved Fuzzy Matter-Element Extension Assessment Model

The improved fuzzy matter-element extension assessment model introduces the variable weight theory to determine the weight value of each evaluation index, so as to reduce the subjectivity. The variable weight theory is an integrated weighting method based on the theory of factor space, which is applicable to the calculation of the weight of the quantitative index [53, 54]. The fuzzy matter-element extension assessment model combines the extenics and fuzzy matter-element concept to calculate relationship degrees. The degree of the relationship is used to diagnose the health state of the urban water ecosystem. The steps of the improved fuzzy matter-element extension assessment method are as follows.(1) Determination of the Matter-Element Matrix of Urban Water Ecosystem Health and the Classical Domain. Everything can be described in terms of three elements: name (N), characteristics (C), and measures (x). The core content of extenics is the combination set including name (N), characteristics (C), and measures (x). Assume that an the evaluation matter-element N is described by n characteristics C
1
,
C
2
,
…
,
C
n with measured values x
1
,
x
2
,
…
,
x
n. When all values in the complex elements R
n are fuzzy, they are called compound fuzzy matter-elements. The composite matrix R of the urban water ecosystem health evaluation in Zhengzhou is defined:(1)
R
=
M
1
M
2
⋯
M
j
⋯
M
10
C
1
x
11
x
12
⋯
x
1
j
⋯
x
1,10
C
2
x
21
x
22
⋯
x
2
j
⋯
x
2,10
⋮
⋮
⋮
⋮
C
i
x
i
1
x
i
2
⋯
x
i
j
⋯
x
i
,
10
C
20
x
m
1
x
m
2
⋯
x
m
j
⋯
x
20,10whereM indicates the sample of evaluation index system.The classical domain can be found:(2)
R
o
p
=
N
o
p
,
C
i
,
X
o
i
p
=
c
1
x
o
p
1
c
2
x
o
p
2
N
o
p
⋮
⋮
c
20
x
o
p
20
=
c
1
a
o
p
1
,
b
o
p
1
c
2
a
o
p
2
,
b
o
p
2
N
o
p
⋮
⋮
c
20
a
o
p
20
,
b
o
p
20whereN
o
P represents health level of the evaluation object N; X
o
i
P represents the critical threshold a
o
i
p
,
b
o
i
p of the i index corresponding to the rank p, namely, the classical domain. The classical domain matrix of urban water ecological health evaluation in Zhengzhou is defined.(3)
R
=
N
,
C
,
X
=
c
1
≤
3
3,5
5,8
8,10
>
10
c
2
≤
30
30,40
40,50
5,60
>
60
N
⋮
⋮
c
20
≥
1
0.8,1
0.5,0.8
0.3,0.5
<
0.3(2) Determination of the Evaluation Matter-Element
N
0
(4)
R
=
c
1
x
1
c
2
x
2
N
0
⋮
⋮
c
20
x
20whereN
0 is the health state of water ecosystem in Zhengzhou and x
i represents the measured value of c
i.(3) Determination of Correlation Function. To reflect the health state of the water ecosystem in Zhengzhou, the correlation function is established according to matter-element theory. The dimensions of the evaluation factors in water ecological health are different. For the positive indicators, larger value indexes are better; for the negative indicators, smaller value indexes are better. This leads to differences in the form of the correlation function. We define the new threshold value between “very sick” and “sick” and the new threshold value between “healthy” and “sub-healthy” in Table 2 as a
i and b
i (i
=
1,2
,
…
,
20), respectively.(5)
k
x
i
=
x
i
-
a
i
b
i
-
a
i
x
i
i
s
p
o
s
i
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
∈
a
i
,
b
i
1
x
i
i
s
p
o
s
i
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
≥
b
i
0
x
i
i
s
p
o
s
i
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
≤
a
i
(6)
k
x
i
=
b
i
-
x
i
b
i
-
a
i
x
i
i
s
n
e
g
a
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
∈
a
i
,
b
i
0
x
i
i
s
n
e
g
a
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
≥
b
i
1
x
i
i
s
n
e
g
a
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
≤
a
iThen relation degree matrixM
k is as follows.(7)
M
k
=
m
1
m
2
⋮
m
20(4) Determination of the Variable Weights. The variable weight theory is used to calculate weight values of different indexes. It is necessary to build the variable weight comprehensive operation model, before the calculation of the weight [39]. Assume that W
=
w
1
,
w
2
,
⋯
,
w
n is factor weight variable, X
=
x
1
,
x
2
,
⋯
,
x
n is factor state variable, and S
(
X
)
=
S
1
(
X
)
,
S
2
(
X
)
,
⋯
,
S
n
(
X
) is state variable weight vector.Then the variable weight vectorW
(
X
)
=
W
1
(
X
)
,
W
2
(
X
)
,
⋯
,
W
n
(
X
) can be represented by the Hadamard product of W and S
(
X
).The main steps are(8)
S
i
X
=
e
x
i
-
x
¯
(9)
w
i
X
=
e
x
p
α
d
i
m
a
x
-
d
i
m
i
n
∑
i
=
1
n
e
x
p
α
d
i
m
a
x
-
d
i
m
i
n
(10)
W
i
X
=
w
i
S
i
X
∑
i
=
1
n
w
i
S
i
Xwhered
i
m
a
x
=
m
a
x
x
i
-
a
i
p
,
b
i
p
-
x
i
;
d
i
m
i
n
=
m
i
n
x
i
-
a
i
p
,
b
i
p
-
x
i,α
=
-
1.(5) Determination of
W
H
I
(11)
W
H
I
P
=
∑
i
=
1
8
k
i
P
W
i
P
∑
i
=
1
8
W
i
P
(12)
W
H
I
S
=
∑
i
=
1
4
k
i
S
W
i
S
∑
i
=
1
4
W
i
S
(13)
W
H
I
R
=
∑
i
=
1
8
k
i
R
W
i
R
∑
i
=
1
4
W
i
R
(14)
W
H
I
=
W
i
T
•
M
kwhereW
H
I
P represents the pressure subsystem integrated index; k
i
P and W
i
P represent the relation degree and weight of pressure subsystem indicator, respectively; W
H
I
S and W
H
I
R represent state subsystem integrated index and response subsystem integrated index, respectively; and W
H
I is the urban water ecosystem health integrated index.(6) Criterion of
W
H
I
. The health state threshold of W
H
I can be obtained by using improved fuzzy matter-element assessment method to calculate converted health level threshold value of each index. The urban water ecosystem health state can also be divided into five grades as shown in Table 3.Table 3
Classification of urban water ecosystem health.
Assessment level
very sick
sick
unhealthy
sub-healthy
healthy
W
H
I
0
(0,0.335)
[0.335,0.671)
[0.671,1)
1


### 2.3. Data Collection

The indicator data from 2006 to 2007 was collected. Among them, the indicators data ofP
1
~
P
4, R
7
~
R
8 in this paper are all from the Zhengzhou Statistical Yearbook (2007–2016) [55]. The indicators data of P
5
~
P
8, S
1
~
S
4, R
1
~
R
6 are all from the Henan Water Resources Bulletin (2007–2016) [37].


## 2.1. Research Area

Zhengzhou, the capital of Henan province, is one of the most important economic cities in China. Zhengzhou is located in the lower reaches of the Yellow River and covers a total area of 7446 square kilometers, which lies between E 112°42′—114°14′ and N 34°16′—34°58′ (Figure1). It has 12 districts (counties) with a resident population of 7.57 million and an urbanization rate of 69.7%. The annual average water resources are about 1/10 of the national average, only 1.323 billion m3, with less than 178 m3 per capita in 2016 [37]. Water resources are in relatively short supply. Zhengzhou is one of the first pilot cities for the construction of ecologically civilized city in China.Figure 1
Location of the Zhengzhou City.


## 2.2. Methods

The “Pressure-State-Response” urban water ecosystem health evaluation index system was established by using the PSR model. The model covers 20 indicators and reflects the water ecosystem health conditions in Zhengzhou City. An improved FMEAM model was used to determine theW
H
I to evaluate the health status of the water ecosystem in Zhengzhou.


### 2.2.1. The PSR Model

The Pressure-State-Response (PSR) model was first proposed by the Organization for Economic Co-operation and Development (OECD) and has been widely used in environmentally relevant issues [38]. The PSR model is a dynamic model structure and includes three major indexes: pressure, state, and response, and the three indexes mutually interact and restrict each other [39]. The PSR model includes a causality of “what happened, why, and how to deal with it” and has the characteristics of flexibility and comprehensiveness [40]. Here, the urban water ecosystem health PSR model covers three dimensions: the pressure on water ecosystem, the maintenance state of the water ecosystem, and the dynamic response of human society. The pressure subsystem mainly refers to the negative impact of economic development and the water resource consumption on the water ecosystem. The state subsystem mainly refers to a comprehensive state of the various conditions of the water eco-environment under the pressure. The response subsystem represents the protective measure humans take to overcome water resource pressures. This model analyzes the interaction between humans and the environment using a system theory perspective. Figure 2 shows the PSR model of the urban water ecosystem health evaluation.Figure 2
PSR model.Selecting evaluation indicators should follow uniform criteria and principles. Based on the principle of constructing a scientific, reasonable, and representative index, we established an index system to evaluate water ecosystem health in Zhengzhou. According to the PSR model, the indicator system mainly includes pressure subsystem (B1), state subsystem (B2), and response subsystem (B3). The indicator layer is determined by 20 indicators, after fully considering the condition of the socioeconomic development and water eco-environment in Zhengzhou. Urban water ecosystem health is a relative and dynamic concept, but it needed to determine the health standard of the evaluation index. In this study, the 20 evaluation indexes in Table1 mainly come from existing research results [41–47], and the grade standard of the indicators for Zhengzhou is determined based on several existing studies and Environmental Quality Standards for Surface Water (GB3838-2002) [44–48]. The water ecosystem health evaluation index system of Zhengzhou City is shown in Table 1, and the grade standard of the evaluation index system is shown in Table 2.Table 1
Evaluation index system of urban water ecosystem health.
Factor
Indicators
Unit
Description
Pressure (B1)
GDP Growth Rate (P1)
%
Represents the increasing economic development pressures on urban water ecosystem [41].
Urbanization Rate (P2)
%
Represents the increasing population pressures on urban water ecosystem [42].
The Proportion of Tertiary Industry (P3)
%
Represents the urban water ecosystem pressures from tertiary industry, such as catering industry and service industry [43].
Water Consumption Per Unit of GDP (P4)
m3 / 10− 4 Yuan
Represents the water consumption per unit of GDP pressures on urban water ecosystem [42].
Water Consumption of Industrial Output (P5)
m3 / 10− 4 Yuan
Represents the urban water ecosystem pressures from industrial development [44].
Water Consumption of Eco-environment (P6)
109 m3
Represents the urban water ecosystem pressures from eco-environment water consumption [43].
Household Water Consumption (P7)
109 m3
Represents the urban water resource pressures from household water consumption [45].
Sewage Discharge (P8)
109 m3
Represents the water pollution pressures on urban water ecosystem [42].
State (B2)
Water Resources Amount Per Unit Area (S1)
104 m3  ·  km−2
Refers to the ratio of surface water resource quantity and the land area [46].
Per Capita Water Resources (S2)
m3
Refers to the proportion of freshwater resource quantity and the population [47].
Per Capita Green Area (S3)
m2
Refers to the ratio of green area and the population [46].
Flood Control Rate (S4)
%
Refers to the state of flood control [46].
Response (B3)
Sewage Treatment Rate (R1)
%
Represents the ability of sewage treatment [42].
Green Coverage Rate (R2)
%
Represents the response to quantity of water resources [42].
River Water Quality Compliance Rate (R3)
%
Represents the ability of river water resources protection [42].
Source Water Quality Compliance Rate (R4)
%
Represents the response to quality of freshwater resources [42].
Rate of Wastewater up to Discharge Standard for Urban (R5)
%
Represents the response to water resource security condition [46].
Water Functional Area Compliance Rate (R6)
%
Represents the response to water resource security condition [45].
Rate of Water Ecosystem Project Investment to GDP (R7)
%
Represents the response to water environmental protection [47].
Rate of Environmental Protection Investment to GDP (R8)
%
Represents the response to ecological management and protection [43].Table 2
The grade standard of evaluation index system.
Factor
Indicators
Unit
Character
healthy
sub-healthy
unhealthy
sick
very sick
Pressure (B1)
GDP Growth Rate (P1)
%
-
≤3
(3, 5]
(5, 8]
(8, 10]
>10
Urbanization Rate (P2)
%
-
≤30
(30, 40]
(40, 50]
(50, 60]
>60
The Proportion of Tertiary Industry (P3)
%
-
≤30
(30, 40]
(40, 50]
(50, 60]
>60
Water Consumption Per Unit of GDP (P4)
m3 / 10− 4 Yuan
-
≤100
(100, 200]
(200, 300
(300, 400]
>400
Water Consumption of Industrial Output (P5)
m3 / 10− 4 Yuan
-
≤30
(30, 60]
(60, 90]
(90, 120]
>120
Water Consumption of Eco-environment (P6)
109 m3
-
≤1
(1, 2]
(2, 3]
(3, 4]
>4
Household Water Consumption (P7)
109 m3
-
≤4
(4, 6]
(6, 8]
(8, 10]
>10
Sewage Discharge (P8)
109 m3
-
≤4
(4, 6]
(6, 8]
(8, 10]
>10
State (B2)
Water Resources Amount Per Unit Area (S1)
104 m3  ·  km−2
+
≥200
[150, 200)
[100, 150)
[50, 100)
<50
Per Capita Water Resources (S2)
m3
+
≥1000
[750, 1000)
[500, 750)
[250, 500)
<250
Per Capita Green Area (S3)
m2
+
≥12
[10, 12)
[8, 10)
[5, 8)
<5
Flood Control Rate (S4)
%
+
≥95
[95, 90)
[85, 90)
[80, 85)
<80
Response (B3)
Sewage Treatment Rate (R1)
%
+
≥80
[60, 80)
[40, 60)
[20, 40)
<20
Green Coverage Rate (R2)
%
+
≥40
[30, 40)
[20, 30)
[10, 20)
<10
River Water Quality Compliance Rate (R3)
%
+
≥90
[80, 90)
[70, 80)
[60, 70)
<60
Source Water Quality Compliance Rate (R4)
%
+
≥95
[80, 95)
[65, 80)
[50, 65)
<50
Rate of Wastewater up to Discharge Standard for Urban (R5)
%
+
≥95
[85, 95)
[75, 85)
[60, 75)
<60
Water Functional Area Compliance Rate (R6)
%
+
≥80
[60, 80)
[40, 60)
[20, 40)
<20
Rate of Water Ecosystem Project Investment to GDP (R7)
%
+
≥1.5
[1, 1.5)
[0.6, 1)
[0.3, 0.6)
<0.3
Rate of Environmental Protection Investment to GDP (R8)
%
+
≥1
[0.8, 1)
[0.5, 0.8)
[0.3, 0.5)
<0.3


### 2.2.2. Fuzzy Matter-Element Extension Assessment Model and Deficiency

The concept of extenics was first proposed and analyzed by Chinese scholar Cai Wen [49]. Fuzzy matter-element extension model is an evaluation model based on matter-element analysis theory and extenics, selecting matter-element features to be evaluated as evaluation indexes, and using the measured data to calculate the correlation of the object to be evaluated. The fuzzy matter-element expansion assessment model holds that all objects can be represented by name, characteristics, and measures, which creates a new idea of evaluating things and has been successfully applied in many projects’ evaluation [50].In the evaluation method with the fuzzy matter-element extension, the selection of weights is very important and directly affects the final evaluation result. The traditional fuzzy matter-element expansion assessment model usually uses subjective weighting methods such as expert grading and Analytical Hierarchy Process (AHP). The expert grading method is a method of assigning weight values by expert assessment of the importance of each indicator, and the AHP is a method of subjectively determining weights based on the assessment of relative importance of different indicators [51, 52]. However, the evaluation of the urban water ecosystem health by using these traditional weighting methods has certain limitations and disadvantages. On the one hand, these subjective weighting methods have much discretionary subjectivity, which will cause weight values to be influenced by human factors, resulting in inaccuracy in the evaluation results. On the other hand, the evaluation indexes of urban water ecosystem health are all quantitative indexes with measured data. The weight values of the indexes should be determined based on the objective information of the indicator [44]. It is difficult for the weight obtained by subjective weighting to reflect the real health status accurately and objectively. So, the subjective weighting methods are not suitable for urban water ecosystem health evaluation.


### 2.2.3. Improved Fuzzy Matter-Element Extension Assessment Model

The improved fuzzy matter-element extension assessment model introduces the variable weight theory to determine the weight value of each evaluation index, so as to reduce the subjectivity. The variable weight theory is an integrated weighting method based on the theory of factor space, which is applicable to the calculation of the weight of the quantitative index [53, 54]. The fuzzy matter-element extension assessment model combines the extenics and fuzzy matter-element concept to calculate relationship degrees. The degree of the relationship is used to diagnose the health state of the urban water ecosystem. The steps of the improved fuzzy matter-element extension assessment method are as follows.(1) Determination of the Matter-Element Matrix of Urban Water Ecosystem Health and the Classical Domain. Everything can be described in terms of three elements: name (N), characteristics (C), and measures (x). The core content of extenics is the combination set including name (N), characteristics (C), and measures (x). Assume that an the evaluation matter-element N is described by n characteristics C
1
,
C
2
,
…
,
C
n with measured values x
1
,
x
2
,
…
,
x
n. When all values in the complex elements R
n are fuzzy, they are called compound fuzzy matter-elements. The composite matrix R of the urban water ecosystem health evaluation in Zhengzhou is defined:(1)
R
=
M
1
M
2
⋯
M
j
⋯
M
10
C
1
x
11
x
12
⋯
x
1
j
⋯
x
1,10
C
2
x
21
x
22
⋯
x
2
j
⋯
x
2,10
⋮
⋮
⋮
⋮
C
i
x
i
1
x
i
2
⋯
x
i
j
⋯
x
i
,
10
C
20
x
m
1
x
m
2
⋯
x
m
j
⋯
x
20,10whereM indicates the sample of evaluation index system.The classical domain can be found:(2)
R
o
p
=
N
o
p
,
C
i
,
X
o
i
p
=
c
1
x
o
p
1
c
2
x
o
p
2
N
o
p
⋮
⋮
c
20
x
o
p
20
=
c
1
a
o
p
1
,
b
o
p
1
c
2
a
o
p
2
,
b
o
p
2
N
o
p
⋮
⋮
c
20
a
o
p
20
,
b
o
p
20whereN
o
P represents health level of the evaluation object N; X
o
i
P represents the critical threshold a
o
i
p
,
b
o
i
p of the i index corresponding to the rank p, namely, the classical domain. The classical domain matrix of urban water ecological health evaluation in Zhengzhou is defined.(3)
R
=
N
,
C
,
X
=
c
1
≤
3
3,5
5,8
8,10
>
10
c
2
≤
30
30,40
40,50
5,60
>
60
N
⋮
⋮
c
20
≥
1
0.8,1
0.5,0.8
0.3,0.5
<
0.3(2) Determination of the Evaluation Matter-Element
N
0
(4)
R
=
c
1
x
1
c
2
x
2
N
0
⋮
⋮
c
20
x
20whereN
0 is the health state of water ecosystem in Zhengzhou and x
i represents the measured value of c
i.(3) Determination of Correlation Function. To reflect the health state of the water ecosystem in Zhengzhou, the correlation function is established according to matter-element theory. The dimensions of the evaluation factors in water ecological health are different. For the positive indicators, larger value indexes are better; for the negative indicators, smaller value indexes are better. This leads to differences in the form of the correlation function. We define the new threshold value between “very sick” and “sick” and the new threshold value between “healthy” and “sub-healthy” in Table 2 as a
i and b
i (i
=
1,2
,
…
,
20), respectively.(5)
k
x
i
=
x
i
-
a
i
b
i
-
a
i
x
i
i
s
p
o
s
i
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
∈
a
i
,
b
i
1
x
i
i
s
p
o
s
i
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
≥
b
i
0
x
i
i
s
p
o
s
i
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
≤
a
i
(6)
k
x
i
=
b
i
-
x
i
b
i
-
a
i
x
i
i
s
n
e
g
a
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
∈
a
i
,
b
i
0
x
i
i
s
n
e
g
a
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
≥
b
i
1
x
i
i
s
n
e
g
a
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
≤
a
iThen relation degree matrixM
k is as follows.(7)
M
k
=
m
1
m
2
⋮
m
20(4) Determination of the Variable Weights. The variable weight theory is used to calculate weight values of different indexes. It is necessary to build the variable weight comprehensive operation model, before the calculation of the weight [39]. Assume that W
=
w
1
,
w
2
,
⋯
,
w
n is factor weight variable, X
=
x
1
,
x
2
,
⋯
,
x
n is factor state variable, and S
(
X
)
=
S
1
(
X
)
,
S
2
(
X
)
,
⋯
,
S
n
(
X
) is state variable weight vector.Then the variable weight vectorW
(
X
)
=
W
1
(
X
)
,
W
2
(
X
)
,
⋯
,
W
n
(
X
) can be represented by the Hadamard product of W and S
(
X
).The main steps are(8)
S
i
X
=
e
x
i
-
x
¯
(9)
w
i
X
=
e
x
p
α
d
i
m
a
x
-
d
i
m
i
n
∑
i
=
1
n
e
x
p
α
d
i
m
a
x
-
d
i
m
i
n
(10)
W
i
X
=
w
i
S
i
X
∑
i
=
1
n
w
i
S
i
Xwhered
i
m
a
x
=
m
a
x
x
i
-
a
i
p
,
b
i
p
-
x
i
;
d
i
m
i
n
=
m
i
n
x
i
-
a
i
p
,
b
i
p
-
x
i,α
=
-
1.(5) Determination of
W
H
I
(11)
W
H
I
P
=
∑
i
=
1
8
k
i
P
W
i
P
∑
i
=
1
8
W
i
P
(12)
W
H
I
S
=
∑
i
=
1
4
k
i
S
W
i
S
∑
i
=
1
4
W
i
S
(13)
W
H
I
R
=
∑
i
=
1
8
k
i
R
W
i
R
∑
i
=
1
4
W
i
R
(14)
W
H
I
=
W
i
T
•
M
kwhereW
H
I
P represents the pressure subsystem integrated index; k
i
P and W
i
P represent the relation degree and weight of pressure subsystem indicator, respectively; W
H
I
S and W
H
I
R represent state subsystem integrated index and response subsystem integrated index, respectively; and W
H
I is the urban water ecosystem health integrated index.(6) Criterion of
W
H
I
. The health state threshold of W
H
I can be obtained by using improved fuzzy matter-element assessment method to calculate converted health level threshold value of each index. The urban water ecosystem health state can also be divided into five grades as shown in Table 3.Table 3
Classification of urban water ecosystem health.
Assessment level
very sick
sick
unhealthy
sub-healthy
healthy
W
H
I
0
(0,0.335)
[0.335,0.671)
[0.671,1)
1


## 2.2.1. The PSR Model

The Pressure-State-Response (PSR) model was first proposed by the Organization for Economic Co-operation and Development (OECD) and has been widely used in environmentally relevant issues [38]. The PSR model is a dynamic model structure and includes three major indexes: pressure, state, and response, and the three indexes mutually interact and restrict each other [39]. The PSR model includes a causality of “what happened, why, and how to deal with it” and has the characteristics of flexibility and comprehensiveness [40]. Here, the urban water ecosystem health PSR model covers three dimensions: the pressure on water ecosystem, the maintenance state of the water ecosystem, and the dynamic response of human society. The pressure subsystem mainly refers to the negative impact of economic development and the water resource consumption on the water ecosystem. The state subsystem mainly refers to a comprehensive state of the various conditions of the water eco-environment under the pressure. The response subsystem represents the protective measure humans take to overcome water resource pressures. This model analyzes the interaction between humans and the environment using a system theory perspective. Figure 2 shows the PSR model of the urban water ecosystem health evaluation.Figure 2
PSR model.Selecting evaluation indicators should follow uniform criteria and principles. Based on the principle of constructing a scientific, reasonable, and representative index, we established an index system to evaluate water ecosystem health in Zhengzhou. According to the PSR model, the indicator system mainly includes pressure subsystem (B1), state subsystem (B2), and response subsystem (B3). The indicator layer is determined by 20 indicators, after fully considering the condition of the socioeconomic development and water eco-environment in Zhengzhou. Urban water ecosystem health is a relative and dynamic concept, but it needed to determine the health standard of the evaluation index. In this study, the 20 evaluation indexes in Table1 mainly come from existing research results [41–47], and the grade standard of the indicators for Zhengzhou is determined based on several existing studies and Environmental Quality Standards for Surface Water (GB3838-2002) [44–48]. The water ecosystem health evaluation index system of Zhengzhou City is shown in Table 1, and the grade standard of the evaluation index system is shown in Table 2.Table 1
Evaluation index system of urban water ecosystem health.
Factor
Indicators
Unit
Description
Pressure (B1)
GDP Growth Rate (P1)
%
Represents the increasing economic development pressures on urban water ecosystem [41].
Urbanization Rate (P2)
%
Represents the increasing population pressures on urban water ecosystem [42].
The Proportion of Tertiary Industry (P3)
%
Represents the urban water ecosystem pressures from tertiary industry, such as catering industry and service industry [43].
Water Consumption Per Unit of GDP (P4)
m3 / 10− 4 Yuan
Represents the water consumption per unit of GDP pressures on urban water ecosystem [42].
Water Consumption of Industrial Output (P5)
m3 / 10− 4 Yuan
Represents the urban water ecosystem pressures from industrial development [44].
Water Consumption of Eco-environment (P6)
109 m3
Represents the urban water ecosystem pressures from eco-environment water consumption [43].
Household Water Consumption (P7)
109 m3
Represents the urban water resource pressures from household water consumption [45].
Sewage Discharge (P8)
109 m3
Represents the water pollution pressures on urban water ecosystem [42].
State (B2)
Water Resources Amount Per Unit Area (S1)
104 m3  ·  km−2
Refers to the ratio of surface water resource quantity and the land area [46].
Per Capita Water Resources (S2)
m3
Refers to the proportion of freshwater resource quantity and the population [47].
Per Capita Green Area (S3)
m2
Refers to the ratio of green area and the population [46].
Flood Control Rate (S4)
%
Refers to the state of flood control [46].
Response (B3)
Sewage Treatment Rate (R1)
%
Represents the ability of sewage treatment [42].
Green Coverage Rate (R2)
%
Represents the response to quantity of water resources [42].
River Water Quality Compliance Rate (R3)
%
Represents the ability of river water resources protection [42].
Source Water Quality Compliance Rate (R4)
%
Represents the response to quality of freshwater resources [42].
Rate of Wastewater up to Discharge Standard for Urban (R5)
%
Represents the response to water resource security condition [46].
Water Functional Area Compliance Rate (R6)
%
Represents the response to water resource security condition [45].
Rate of Water Ecosystem Project Investment to GDP (R7)
%
Represents the response to water environmental protection [47].
Rate of Environmental Protection Investment to GDP (R8)
%
Represents the response to ecological management and protection [43].Table 2
The grade standard of evaluation index system.
Factor
Indicators
Unit
Character
healthy
sub-healthy
unhealthy
sick
very sick
Pressure (B1)
GDP Growth Rate (P1)
%
-
≤3
(3, 5]
(5, 8]
(8, 10]
>10
Urbanization Rate (P2)
%
-
≤30
(30, 40]
(40, 50]
(50, 60]
>60
The Proportion of Tertiary Industry (P3)
%
-
≤30
(30, 40]
(40, 50]
(50, 60]
>60
Water Consumption Per Unit of GDP (P4)
m3 / 10− 4 Yuan
-
≤100
(100, 200]
(200, 300
(300, 400]
>400
Water Consumption of Industrial Output (P5)
m3 / 10− 4 Yuan
-
≤30
(30, 60]
(60, 90]
(90, 120]
>120
Water Consumption of Eco-environment (P6)
109 m3
-
≤1
(1, 2]
(2, 3]
(3, 4]
>4
Household Water Consumption (P7)
109 m3
-
≤4
(4, 6]
(6, 8]
(8, 10]
>10
Sewage Discharge (P8)
109 m3
-
≤4
(4, 6]
(6, 8]
(8, 10]
>10
State (B2)
Water Resources Amount Per Unit Area (S1)
104 m3  ·  km−2
+
≥200
[150, 200)
[100, 150)
[50, 100)
<50
Per Capita Water Resources (S2)
m3
+
≥1000
[750, 1000)
[500, 750)
[250, 500)
<250
Per Capita Green Area (S3)
m2
+
≥12
[10, 12)
[8, 10)
[5, 8)
<5
Flood Control Rate (S4)
%
+
≥95
[95, 90)
[85, 90)
[80, 85)
<80
Response (B3)
Sewage Treatment Rate (R1)
%
+
≥80
[60, 80)
[40, 60)
[20, 40)
<20
Green Coverage Rate (R2)
%
+
≥40
[30, 40)
[20, 30)
[10, 20)
<10
River Water Quality Compliance Rate (R3)
%
+
≥90
[80, 90)
[70, 80)
[60, 70)
<60
Source Water Quality Compliance Rate (R4)
%
+
≥95
[80, 95)
[65, 80)
[50, 65)
<50
Rate of Wastewater up to Discharge Standard for Urban (R5)
%
+
≥95
[85, 95)
[75, 85)
[60, 75)
<60
Water Functional Area Compliance Rate (R6)
%
+
≥80
[60, 80)
[40, 60)
[20, 40)
<20
Rate of Water Ecosystem Project Investment to GDP (R7)
%
+
≥1.5
[1, 1.5)
[0.6, 1)
[0.3, 0.6)
<0.3
Rate of Environmental Protection Investment to GDP (R8)
%
+
≥1
[0.8, 1)
[0.5, 0.8)
[0.3, 0.5)
<0.3


## 2.2.2. Fuzzy Matter-Element Extension Assessment Model and Deficiency

The concept of extenics was first proposed and analyzed by Chinese scholar Cai Wen [49]. Fuzzy matter-element extension model is an evaluation model based on matter-element analysis theory and extenics, selecting matter-element features to be evaluated as evaluation indexes, and using the measured data to calculate the correlation of the object to be evaluated. The fuzzy matter-element expansion assessment model holds that all objects can be represented by name, characteristics, and measures, which creates a new idea of evaluating things and has been successfully applied in many projects’ evaluation [50].In the evaluation method with the fuzzy matter-element extension, the selection of weights is very important and directly affects the final evaluation result. The traditional fuzzy matter-element expansion assessment model usually uses subjective weighting methods such as expert grading and Analytical Hierarchy Process (AHP). The expert grading method is a method of assigning weight values by expert assessment of the importance of each indicator, and the AHP is a method of subjectively determining weights based on the assessment of relative importance of different indicators [51, 52]. However, the evaluation of the urban water ecosystem health by using these traditional weighting methods has certain limitations and disadvantages. On the one hand, these subjective weighting methods have much discretionary subjectivity, which will cause weight values to be influenced by human factors, resulting in inaccuracy in the evaluation results. On the other hand, the evaluation indexes of urban water ecosystem health are all quantitative indexes with measured data. The weight values of the indexes should be determined based on the objective information of the indicator [44]. It is difficult for the weight obtained by subjective weighting to reflect the real health status accurately and objectively. So, the subjective weighting methods are not suitable for urban water ecosystem health evaluation.


## 2.2.3. Improved Fuzzy Matter-Element Extension Assessment Model

The improved fuzzy matter-element extension assessment model introduces the variable weight theory to determine the weight value of each evaluation index, so as to reduce the subjectivity. The variable weight theory is an integrated weighting method based on the theory of factor space, which is applicable to the calculation of the weight of the quantitative index [53, 54]. The fuzzy matter-element extension assessment model combines the extenics and fuzzy matter-element concept to calculate relationship degrees. The degree of the relationship is used to diagnose the health state of the urban water ecosystem. The steps of the improved fuzzy matter-element extension assessment method are as follows.(1) Determination of the Matter-Element Matrix of Urban Water Ecosystem Health and the Classical Domain. Everything can be described in terms of three elements: name (N), characteristics (C), and measures (x). The core content of extenics is the combination set including name (N), characteristics (C), and measures (x). Assume that an the evaluation matter-element N is described by n characteristics C
1
,
C
2
,
…
,
C
n with measured values x
1
,
x
2
,
…
,
x
n. When all values in the complex elements R
n are fuzzy, they are called compound fuzzy matter-elements. The composite matrix R of the urban water ecosystem health evaluation in Zhengzhou is defined:(1)
R
=
M
1
M
2
⋯
M
j
⋯
M
10
C
1
x
11
x
12
⋯
x
1
j
⋯
x
1,10
C
2
x
21
x
22
⋯
x
2
j
⋯
x
2,10
⋮
⋮
⋮
⋮
C
i
x
i
1
x
i
2
⋯
x
i
j
⋯
x
i
,
10
C
20
x
m
1
x
m
2
⋯
x
m
j
⋯
x
20,10whereM indicates the sample of evaluation index system.The classical domain can be found:(2)
R
o
p
=
N
o
p
,
C
i
,
X
o
i
p
=
c
1
x
o
p
1
c
2
x
o
p
2
N
o
p
⋮
⋮
c
20
x
o
p
20
=
c
1
a
o
p
1
,
b
o
p
1
c
2
a
o
p
2
,
b
o
p
2
N
o
p
⋮
⋮
c
20
a
o
p
20
,
b
o
p
20whereN
o
P represents health level of the evaluation object N; X
o
i
P represents the critical threshold a
o
i
p
,
b
o
i
p of the i index corresponding to the rank p, namely, the classical domain. The classical domain matrix of urban water ecological health evaluation in Zhengzhou is defined.(3)
R
=
N
,
C
,
X
=
c
1
≤
3
3,5
5,8
8,10
>
10
c
2
≤
30
30,40
40,50
5,60
>
60
N
⋮
⋮
c
20
≥
1
0.8,1
0.5,0.8
0.3,0.5
<
0.3(2) Determination of the Evaluation Matter-Element
N
0
(4)
R
=
c
1
x
1
c
2
x
2
N
0
⋮
⋮
c
20
x
20whereN
0 is the health state of water ecosystem in Zhengzhou and x
i represents the measured value of c
i.(3) Determination of Correlation Function. To reflect the health state of the water ecosystem in Zhengzhou, the correlation function is established according to matter-element theory. The dimensions of the evaluation factors in water ecological health are different. For the positive indicators, larger value indexes are better; for the negative indicators, smaller value indexes are better. This leads to differences in the form of the correlation function. We define the new threshold value between “very sick” and “sick” and the new threshold value between “healthy” and “sub-healthy” in Table 2 as a
i and b
i (i
=
1,2
,
…
,
20), respectively.(5)
k
x
i
=
x
i
-
a
i
b
i
-
a
i
x
i
i
s
p
o
s
i
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
∈
a
i
,
b
i
1
x
i
i
s
p
o
s
i
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
≥
b
i
0
x
i
i
s
p
o
s
i
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
≤
a
i
(6)
k
x
i
=
b
i
-
x
i
b
i
-
a
i
x
i
i
s
n
e
g
a
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
∈
a
i
,
b
i
0
x
i
i
s
n
e
g
a
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
≥
b
i
1
x
i
i
s
n
e
g
a
t
i
v
e
i
n
d
i
c
a
t
o
r
a
n
d
x
i
≤
a
iThen relation degree matrixM
k is as follows.(7)
M
k
=
m
1
m
2
⋮
m
20(4) Determination of the Variable Weights. The variable weight theory is used to calculate weight values of different indexes. It is necessary to build the variable weight comprehensive operation model, before the calculation of the weight [39]. Assume that W
=
w
1
,
w
2
,
⋯
,
w
n is factor weight variable, X
=
x
1
,
x
2
,
⋯
,
x
n is factor state variable, and S
(
X
)
=
S
1
(
X
)
,
S
2
(
X
)
,
⋯
,
S
n
(
X
) is state variable weight vector.Then the variable weight vectorW
(
X
)
=
W
1
(
X
)
,
W
2
(
X
)
,
⋯
,
W
n
(
X
) can be represented by the Hadamard product of W and S
(
X
).The main steps are(8)
S
i
X
=
e
x
i
-
x
¯
(9)
w
i
X
=
e
x
p
α
d
i
m
a
x
-
d
i
m
i
n
∑
i
=
1
n
e
x
p
α
d
i
m
a
x
-
d
i
m
i
n
(10)
W
i
X
=
w
i
S
i
X
∑
i
=
1
n
w
i
S
i
Xwhered
i
m
a
x
=
m
a
x
x
i
-
a
i
p
,
b
i
p
-
x
i
;
d
i
m
i
n
=
m
i
n
x
i
-
a
i
p
,
b
i
p
-
x
i,α
=
-
1.(5) Determination of
W
H
I
(11)
W
H
I
P
=
∑
i
=
1
8
k
i
P
W
i
P
∑
i
=
1
8
W
i
P
(12)
W
H
I
S
=
∑
i
=
1
4
k
i
S
W
i
S
∑
i
=
1
4
W
i
S
(13)
W
H
I
R
=
∑
i
=
1
8
k
i
R
W
i
R
∑
i
=
1
4
W
i
R
(14)
W
H
I
=
W
i
T
•
M
kwhereW
H
I
P represents the pressure subsystem integrated index; k
i
P and W
i
P represent the relation degree and weight of pressure subsystem indicator, respectively; W
H
I
S and W
H
I
R represent state subsystem integrated index and response subsystem integrated index, respectively; and W
H
I is the urban water ecosystem health integrated index.(6) Criterion of
W
H
I
. The health state threshold of W
H
I can be obtained by using improved fuzzy matter-element assessment method to calculate converted health level threshold value of each index. The urban water ecosystem health state can also be divided into five grades as shown in Table 3.Table 3
Classification of urban water ecosystem health.
Assessment level
very sick
sick
unhealthy
sub-healthy
healthy
W
H
I
0
(0,0.335)
[0.335,0.671)
[0.671,1)
1


## 2.3. Data Collection

The indicator data from 2006 to 2007 was collected. Among them, the indicators data ofP
1
~
P
4, R
7
~
R
8 in this paper are all from the Zhengzhou Statistical Yearbook (2007–2016) [55]. The indicators data of P
5
~
P
8, S
1
~
S
4, R
1
~
R
6 are all from the Henan Water Resources Bulletin (2007–2016) [37].


## 3. Results and Discussion

### 3.1. Comprehensive Evaluation of Water Ecosystem in Zhengzhou

TheW
H
I for Zhengzhou was calculated using (1)-(14). The health states were evaluated and the results were provided in Figure 3. Figure 3 shows that the water ecosystem of Zhengzhou was in an unhealthy state from 2006 to 2017 and the health status of the water ecosystem in Zhengzhou City steadily increased in the study years; the W
H
I value increased from 0.4224 in 2007 to 0.5866 in 2016. This indicates that the health status of the water ecosystem in Zhengzhou gradually improved over 10 years.Figure 3
W
H
I trends from 2007 to 2016 in Zhengzhou.


### 3.2. Comprehensive Evaluation of Subsystem

#### 3.2.1. Evaluation of Pressure Subsystem

Figure3 shows the trends of the W
H
I
P in the pressure subsystem of water ecosystem health evaluation. The pressure subsystem remained in a sub-healthy state from 2006 to 2017. The W
H
I
P showed only a small increase in 2013 and 2015, while the health status declined during the other years. This indicates that the pressure on water ecosystem health in Zhengzhou may increase and the pressure subsystem may trend toward an unhealthy status over time. The pressures affecting the health status of Zhengzhou’s water ecosystem mainly originated from the urbanization rate (P2), water consumption of the eco-environment (P6), household water consumption (P7), and sewage discharge (P8).Figure4 shows the change trends of the main indicators. Specifically, the main reason for this was the increase in the urbanization rate (P2), one of the indicators in the pressure subsystem. The value increased in the area from 2007 (61.3%) to 2016 (71.02%); the health status of this indicator was in a sick state after 2000. The constant increase of urbanization rate reduced the per capita water resources and per capita green area, thus significantly pressuring the urban water ecosystem. At the same time, the water consumption in the eco-environment (P6) in Zhengzhou City increased, reaching 134 million m3 in 2016. This is 13.4 times the value in 2007. The large increase of water consumption in the urban ecological environment exerted strong pressure on urban water resources, thus increasing the burden on the urban water ecosystem. This caused the health of the pressure system of the water ecosystem to gradually decline. Household water consumption (P7) was also the main indicator for exerting pressure on the health status of Zhengzhou’s water ecosystem. Household water consumption (P7) increased from 475 million m3 in 2007 to 835 million m3 in 2016; this gradually changed the status from a sub-healthy state to a sick state. In addition, the index value of sewage discharge (P8) in Zhengzhou also increased year-by-year, developing from an unhealthy state to a sick state. The water challenge was primarily driven by the climate and pollution. The increase in sewage discharge led to the pollution of the water ecological environment and increased the pressure on the water ecosystem. This outcome is consistent with previous research related to water ecosystems in China. These studies reported the increases in urbanization, water consumption of eco-environment, and sewage discharge as the main reasons for the increase in water resource pressure [56]. The increase of these indicators caused the health status of the pressure subsystem in Zhengzhou to decline, which significantly affected the health status of the city’s water ecosystem.Figure 4
Trend changes of main impact indexes in pressure subsystem.


#### 3.2.2. Evaluation of State Subsystem

Figure3 shows the trends in the W
H
I
S in the state subsystem of water ecosystem health evaluation. The W
H
I
S of state subsystem showed an upward trend in all years except for 2008 and 2013; the fluctuations also showed an upward trend from 2007 to 2016. We can see that the state subsystem was in an unhealthy state in 2008 and a sub-healthy state in 2009-2014 and then increased to a healthy state in 2014. It remained in a healthy state in the following years. This indicates that the water ecosystem state in Zhengzhou may improve in future years. The main factors contributing to improving the health status of state subsystem were the per capita green area (S3) and flood control rate (S4).Figure5 shows the change trends of their index values. Specifically, the per capital green area (S3) in Zhengzhou City showed a steady growth trend from 2007 to 2016, indicating a gradual increase from an unhealthy state to a healthy state. The increase of green area conveyed certain improvements of the healthy state of the urban water environment system. This promoted the improvement of the healthy state of the water ecosystem in Zhengzhou. The flood control rate (S4) was also a main factor affecting the health status of the urban water ecosystem. In addition to the state being very sick in 2008, the flood control rate in Zhengzhou increased every year and maintained a healthy status after 2012. The increase of flood control rate reflected the achievements of Zhengzhou in urban water planning and flood control and assures a healthier life for urban residents.Figure 5
Trend changes of main impact indexes in state subsystem.


#### 3.2.3. Evaluation of Response Subsystem

Figure3 shows the trends associated with the W
H
I
R in the response subsystem of the water ecosystem health evaluation. The W
H
I
R of response subsystem showed an increasing trend between 2007 and 2016. The health status of response subsystem was unhealthy in 2007. Starting from 2008, the W
H
I
R of the response subsystem increased to sub-healthy level, and the following years it remained in a sub-healthy state. This indicates that the response subsystem trended toward a healthier direction. The water environment protection in Zhengzhou City makes each index of the response subsystem increase. The main factors influencing the response subsystem of Zhengzhou City include sewage treatment rate (R1), source water quality compliance rate (R4), the water functional area compliance rate (R6), and the rate of water ecosystem project investment to GDP (R7).Figure6 shows the changes in the trends of the four index values. The urban sewage treatment rate (R1) has been listed as the main index affecting the health of the urban water ecosystem. The sewage treatment rate increased to 98.2% between 2007 and 2016, changing from a sick state to a health state. Furthermore, the indicator for source water quality compliance rate (R4) increased from 76% in 2007 to 97% in 2010. This has resulted in a healthy state since 2010. The source water quality compliance rate is the key to impacting the quality of urban residents’ living water, which reflects a basic demand of a water eco-city. The continuous improvement of the source water quality compliance rate has somewhat positively impacted the health state in Zhengzhou. Moreover, the water functional area compliance rate (R6) also steadily increased in Zhengzhou, from a sick (40%) state in 2007 to a healthy (80%) state in 2016. The water functional area compliance rate reflects the need for a healthy state for important rivers and lakes. The improvement of the health state of the water functional area compliance rate in Zhengzhou City helps to assure the health of its urban water ecosystem. This means that the construction of ecologically civilized city in Zhengzhou City achieved positive effects. The rate of investment in water ecosystem projects (R7) reached 1% of GDP, which is a 3.2-time increase. This means that the construction of ecologically civilized city in Zhengzhou City achieved positive effects.Figure 6
Trend changes of main impact indexes in response subsystem.


## 3.1. Comprehensive Evaluation of Water Ecosystem in Zhengzhou

TheW
H
I for Zhengzhou was calculated using (1)-(14). The health states were evaluated and the results were provided in Figure 3. Figure 3 shows that the water ecosystem of Zhengzhou was in an unhealthy state from 2006 to 2017 and the health status of the water ecosystem in Zhengzhou City steadily increased in the study years; the W
H
I value increased from 0.4224 in 2007 to 0.5866 in 2016. This indicates that the health status of the water ecosystem in Zhengzhou gradually improved over 10 years.Figure 3
W
H
I trends from 2007 to 2016 in Zhengzhou.


## 3.2. Comprehensive Evaluation of Subsystem

### 3.2.1. Evaluation of Pressure Subsystem

Figure3 shows the trends of the W
H
I
P in the pressure subsystem of water ecosystem health evaluation. The pressure subsystem remained in a sub-healthy state from 2006 to 2017. The W
H
I
P showed only a small increase in 2013 and 2015, while the health status declined during the other years. This indicates that the pressure on water ecosystem health in Zhengzhou may increase and the pressure subsystem may trend toward an unhealthy status over time. The pressures affecting the health status of Zhengzhou’s water ecosystem mainly originated from the urbanization rate (P2), water consumption of the eco-environment (P6), household water consumption (P7), and sewage discharge (P8).Figure4 shows the change trends of the main indicators. Specifically, the main reason for this was the increase in the urbanization rate (P2), one of the indicators in the pressure subsystem. The value increased in the area from 2007 (61.3%) to 2016 (71.02%); the health status of this indicator was in a sick state after 2000. The constant increase of urbanization rate reduced the per capita water resources and per capita green area, thus significantly pressuring the urban water ecosystem. At the same time, the water consumption in the eco-environment (P6) in Zhengzhou City increased, reaching 134 million m3 in 2016. This is 13.4 times the value in 2007. The large increase of water consumption in the urban ecological environment exerted strong pressure on urban water resources, thus increasing the burden on the urban water ecosystem. This caused the health of the pressure system of the water ecosystem to gradually decline. Household water consumption (P7) was also the main indicator for exerting pressure on the health status of Zhengzhou’s water ecosystem. Household water consumption (P7) increased from 475 million m3 in 2007 to 835 million m3 in 2016; this gradually changed the status from a sub-healthy state to a sick state. In addition, the index value of sewage discharge (P8) in Zhengzhou also increased year-by-year, developing from an unhealthy state to a sick state. The water challenge was primarily driven by the climate and pollution. The increase in sewage discharge led to the pollution of the water ecological environment and increased the pressure on the water ecosystem. This outcome is consistent with previous research related to water ecosystems in China. These studies reported the increases in urbanization, water consumption of eco-environment, and sewage discharge as the main reasons for the increase in water resource pressure [56]. The increase of these indicators caused the health status of the pressure subsystem in Zhengzhou to decline, which significantly affected the health status of the city’s water ecosystem.Figure 4
Trend changes of main impact indexes in pressure subsystem.


### 3.2.2. Evaluation of State Subsystem

Figure3 shows the trends in the W
H
I
S in the state subsystem of water ecosystem health evaluation. The W
H
I
S of state subsystem showed an upward trend in all years except for 2008 and 2013; the fluctuations also showed an upward trend from 2007 to 2016. We can see that the state subsystem was in an unhealthy state in 2008 and a sub-healthy state in 2009-2014 and then increased to a healthy state in 2014. It remained in a healthy state in the following years. This indicates that the water ecosystem state in Zhengzhou may improve in future years. The main factors contributing to improving the health status of state subsystem were the per capita green area (S3) and flood control rate (S4).Figure5 shows the change trends of their index values. Specifically, the per capital green area (S3) in Zhengzhou City showed a steady growth trend from 2007 to 2016, indicating a gradual increase from an unhealthy state to a healthy state. The increase of green area conveyed certain improvements of the healthy state of the urban water environment system. This promoted the improvement of the healthy state of the water ecosystem in Zhengzhou. The flood control rate (S4) was also a main factor affecting the health status of the urban water ecosystem. In addition to the state being very sick in 2008, the flood control rate in Zhengzhou increased every year and maintained a healthy status after 2012. The increase of flood control rate reflected the achievements of Zhengzhou in urban water planning and flood control and assures a healthier life for urban residents.Figure 5
Trend changes of main impact indexes in state subsystem.


### 3.2.3. Evaluation of Response Subsystem

Figure3 shows the trends associated with the W
H
I
R in the response subsystem of the water ecosystem health evaluation. The W
H
I
R of response subsystem showed an increasing trend between 2007 and 2016. The health status of response subsystem was unhealthy in 2007. Starting from 2008, the W
H
I
R of the response subsystem increased to sub-healthy level, and the following years it remained in a sub-healthy state. This indicates that the response subsystem trended toward a healthier direction. The water environment protection in Zhengzhou City makes each index of the response subsystem increase. The main factors influencing the response subsystem of Zhengzhou City include sewage treatment rate (R1), source water quality compliance rate (R4), the water functional area compliance rate (R6), and the rate of water ecosystem project investment to GDP (R7).Figure6 shows the changes in the trends of the four index values. The urban sewage treatment rate (R1) has been listed as the main index affecting the health of the urban water ecosystem. The sewage treatment rate increased to 98.2% between 2007 and 2016, changing from a sick state to a health state. Furthermore, the indicator for source water quality compliance rate (R4) increased from 76% in 2007 to 97% in 2010. This has resulted in a healthy state since 2010. The source water quality compliance rate is the key to impacting the quality of urban residents’ living water, which reflects a basic demand of a water eco-city. The continuous improvement of the source water quality compliance rate has somewhat positively impacted the health state in Zhengzhou. Moreover, the water functional area compliance rate (R6) also steadily increased in Zhengzhou, from a sick (40%) state in 2007 to a healthy (80%) state in 2016. The water functional area compliance rate reflects the need for a healthy state for important rivers and lakes. The improvement of the health state of the water functional area compliance rate in Zhengzhou City helps to assure the health of its urban water ecosystem. This means that the construction of ecologically civilized city in Zhengzhou City achieved positive effects. The rate of investment in water ecosystem projects (R7) reached 1% of GDP, which is a 3.2-time increase. This means that the construction of ecologically civilized city in Zhengzhou City achieved positive effects.Figure 6
Trend changes of main impact indexes in response subsystem.


## 3.2.1. Evaluation of Pressure Subsystem

Figure3 shows the trends of the W
H
I
P in the pressure subsystem of water ecosystem health evaluation. The pressure subsystem remained in a sub-healthy state from 2006 to 2017. The W
H
I
P showed only a small increase in 2013 and 2015, while the health status declined during the other years. This indicates that the pressure on water ecosystem health in Zhengzhou may increase and the pressure subsystem may trend toward an unhealthy status over time. The pressures affecting the health status of Zhengzhou’s water ecosystem mainly originated from the urbanization rate (P2), water consumption of the eco-environment (P6), household water consumption (P7), and sewage discharge (P8).Figure4 shows the change trends of the main indicators. Specifically, the main reason for this was the increase in the urbanization rate (P2), one of the indicators in the pressure subsystem. The value increased in the area from 2007 (61.3%) to 2016 (71.02%); the health status of this indicator was in a sick state after 2000. The constant increase of urbanization rate reduced the per capita water resources and per capita green area, thus significantly pressuring the urban water ecosystem. At the same time, the water consumption in the eco-environment (P6) in Zhengzhou City increased, reaching 134 million m3 in 2016. This is 13.4 times the value in 2007. The large increase of water consumption in the urban ecological environment exerted strong pressure on urban water resources, thus increasing the burden on the urban water ecosystem. This caused the health of the pressure system of the water ecosystem to gradually decline. Household water consumption (P7) was also the main indicator for exerting pressure on the health status of Zhengzhou’s water ecosystem. Household water consumption (P7) increased from 475 million m3 in 2007 to 835 million m3 in 2016; this gradually changed the status from a sub-healthy state to a sick state. In addition, the index value of sewage discharge (P8) in Zhengzhou also increased year-by-year, developing from an unhealthy state to a sick state. The water challenge was primarily driven by the climate and pollution. The increase in sewage discharge led to the pollution of the water ecological environment and increased the pressure on the water ecosystem. This outcome is consistent with previous research related to water ecosystems in China. These studies reported the increases in urbanization, water consumption of eco-environment, and sewage discharge as the main reasons for the increase in water resource pressure [56]. The increase of these indicators caused the health status of the pressure subsystem in Zhengzhou to decline, which significantly affected the health status of the city’s water ecosystem.Figure 4
Trend changes of main impact indexes in pressure subsystem.


## 3.2.2. Evaluation of State Subsystem

Figure3 shows the trends in the W
H
I
S in the state subsystem of water ecosystem health evaluation. The W
H
I
S of state subsystem showed an upward trend in all years except for 2008 and 2013; the fluctuations also showed an upward trend from 2007 to 2016. We can see that the state subsystem was in an unhealthy state in 2008 and a sub-healthy state in 2009-2014 and then increased to a healthy state in 2014. It remained in a healthy state in the following years. This indicates that the water ecosystem state in Zhengzhou may improve in future years. The main factors contributing to improving the health status of state subsystem were the per capita green area (S3) and flood control rate (S4).Figure5 shows the change trends of their index values. Specifically, the per capital green area (S3) in Zhengzhou City showed a steady growth trend from 2007 to 2016, indicating a gradual increase from an unhealthy state to a healthy state. The increase of green area conveyed certain improvements of the healthy state of the urban water environment system. This promoted the improvement of the healthy state of the water ecosystem in Zhengzhou. The flood control rate (S4) was also a main factor affecting the health status of the urban water ecosystem. In addition to the state being very sick in 2008, the flood control rate in Zhengzhou increased every year and maintained a healthy status after 2012. The increase of flood control rate reflected the achievements of Zhengzhou in urban water planning and flood control and assures a healthier life for urban residents.Figure 5
Trend changes of main impact indexes in state subsystem.


## 3.2.3. Evaluation of Response Subsystem

Figure3 shows the trends associated with the W
H
I
R in the response subsystem of the water ecosystem health evaluation. The W
H
I
R of response subsystem showed an increasing trend between 2007 and 2016. The health status of response subsystem was unhealthy in 2007. Starting from 2008, the W
H
I
R of the response subsystem increased to sub-healthy level, and the following years it remained in a sub-healthy state. This indicates that the response subsystem trended toward a healthier direction. The water environment protection in Zhengzhou City makes each index of the response subsystem increase. The main factors influencing the response subsystem of Zhengzhou City include sewage treatment rate (R1), source water quality compliance rate (R4), the water functional area compliance rate (R6), and the rate of water ecosystem project investment to GDP (R7).Figure6 shows the changes in the trends of the four index values. The urban sewage treatment rate (R1) has been listed as the main index affecting the health of the urban water ecosystem. The sewage treatment rate increased to 98.2% between 2007 and 2016, changing from a sick state to a health state. Furthermore, the indicator for source water quality compliance rate (R4) increased from 76% in 2007 to 97% in 2010. This has resulted in a healthy state since 2010. The source water quality compliance rate is the key to impacting the quality of urban residents’ living water, which reflects a basic demand of a water eco-city. The continuous improvement of the source water quality compliance rate has somewhat positively impacted the health state in Zhengzhou. Moreover, the water functional area compliance rate (R6) also steadily increased in Zhengzhou, from a sick (40%) state in 2007 to a healthy (80%) state in 2016. The water functional area compliance rate reflects the need for a healthy state for important rivers and lakes. The improvement of the health state of the water functional area compliance rate in Zhengzhou City helps to assure the health of its urban water ecosystem. This means that the construction of ecologically civilized city in Zhengzhou City achieved positive effects. The rate of investment in water ecosystem projects (R7) reached 1% of GDP, which is a 3.2-time increase. This means that the construction of ecologically civilized city in Zhengzhou City achieved positive effects.Figure 6
Trend changes of main impact indexes in response subsystem.


## 4. Conclusion and Suggestion

Many dimensions are involved in evaluating the health of urban water ecosystems. An index system was established to represent Zhengzhou ecosystem health based on a PSR model. The system includes three subsystems: the pressure subsystem, the state subsystem, and the response subsystem. The variable weight comprehensive model is used to determine the weight of the index. The health status of the water ecosystem in Zhengzhou City was evaluated for a 10-year period (2007-2016) by using the improved FMEAM. Overall, the water ecosystem health situation in Zhengzhou has improved; however, its water ecosystem was still in an unhealthy state from 2007 to 2016. The pressure subsystem showed a slight downward trend and remained in a sub-healthy state from 2007 to 2016. The state subsystem showed an upward trend in all years except for 2008 and 2013, and response subsystem’ health state showed an increasing trend during this period. The results of the evaluation are consistent with the actual situation.Zhengzhou’sW
H
I increased during this period, moving toward a healthier direction, but the overall level of the water ecosystem remained low. The social and economic development in Zhengzhou gradually increased the pressure on water resource. In order to improve the health state of the Zhengzhou water ecosystem, the following countermeasures are put forward:(1) We need to build water-saving society in Zhengzhou and to consider the rational use of water resources to reduce pressure on water resources.(2) We need to use water resources more rationally and improve the efficiency of water resources to reduce household water consumption and water consumption of eco-environment.(3) We can increase the capacity to control water pollution discharge by building more sewage treatment plants and by strengthening water ecology-based environmental protection.The finding in this research can provide reference for the urban water ecosystem management. In addition, the methods used in this research can also be available for assessing ecosystem health, river health, water security, and other areas. It is worth noting that the urban water ecosystem is an important part of an ecologically civilized city and the healthy water ecosystem is an important guarantee for an ecologically civilized city. How to make an effective assessment of ecologically civilized city’s construction effect and how to analyze the relationship between the urban water ecosystem and ecologically civilized city are the focus of future work.



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*Source: 7502342-2019-01-29.xml*