Analysis of the Coupling Relationship between Water Quality and Economic Development in Hongjiannao Basin, China

Abstract

Hongjiannao is the largest inland lake in China’s deserts. In recent years, the water quality and area of the Hongjiannao Lake have continued to decline, which is closely associated with the economic development in the Hongjiannao basin. To explore the coupling relationship between the water quality and economic development in the Hongjiannao basin, the water quality and economic development index of the basin has been analyzed in terms of the monthly water quality and socio-economic development from 2013 to 2020. The coupling relationship and interaction mechanism between water quality and regional economic development has been studied by coupling coordination degree model. The results show that the water pollution increased and then decreased with the seasons, while the water quality was the worst in the summer. The coordinated degree between the water quality and economic development in Hongjiannao shows an upward trend from 2013 to 2020, which has transformed from the process of lagging economic development to the process of primary coordination, finally to the process of lagging water environment. The coupling relationship between water quality and economic development changed from a state of nearly un-coordination to primary coordination from 2013 to 2016, with economic development lagging behind. The coupling relationship between the two systems changed from barely coordinated to the primary coordinated from 2017 to 2018, with the rapid development of economy and slight decline in water quality. After 2018, those two systems gradually stepped into a virtuous cycle during 2019–2020, but the phenomenon of lagging water quality still existed. Therefore, in order to maintain the stable economic development of resource-based cities, it is necessary to keep improving the current situation of water environment and water shortage in Hongjiannao, which will promote the coordinated and sustainable development of water environment and economy.

1. Introduction

Lakes play an important role in supplying freshwater, conserving water, improving climatic conditions, and maintaining regional ecological health [1,2]. However, since the 1940s, the rapid development of economy began to threaten the lake environment [1,3,4], such as shrinking lake area [5], eutrophication [6], accumulation of organic matter [7], and discharge of heavy metals [8]. The coordinative development of the economy and the lake environment has drawn more and more remarkable attention [9,10,11,12].

To alleviate the deterioration of basin environment and promote the coordinated development of water quality and social economy, the domestic and foreign scholars had put forward the environmental resource constraint theory, sustainable development theory, and coordination degree theory [13]. The theory of coordination degree has been widely used to study the relationship between environmental pollution and economic development [14], and the theory of coordination degree points out that environmental quality will show an obvious downward trend along with economic development in the early stage of economic development; environmental quality will be gradually improved and a virtuous cycle of development will be gradually realized with the economic development reaching a higher level [15,16,17]. The development of the regional economy was the key factor in coordinating and stabilizing the development between water quality of the lakes and social development. A previous study had quantitatively evaluated the environmental and economic coordination of Liaoning Province since 1990, and Liaoning Province had experienced a transformation from dissonance to primary coordination [18]. Many foreign research studies focus on quantitative analysis of sustainable development of resources, environment, society, and economy [19,20,21], Jones et al. studied the effects of climate and land-use changes on the lake environment in Southern Australia from 1840 to 1990, and Tamm T. et al. studied the effects of climate and hydrology on dissolved organic carbon load in Lake Vortsjarv (Estonia). Several researchers applied the coupling coordination model to analyze the relationship between water quality and economic development of the Fuxian lake basin in Yunnan province and the Minjiang river basin in Fujian province [22,23,24,25]. However, there is little information about the relationship of coupling coordination between water quality and economic development of the lake basin in the desert area of northwest China, and there is a lack of research on the internal relationship between pollutants (which could reflect the water quality, such as organic matter, total nitrogen, and total phosphorus) and economic development.

Hongjiannao, which is located in Shenmu County, Shaanxi Province, is the largest freshwater lake in western China [26], which is located in the border area between the Mu Us Desert and the Loess Plateau, and plays an important role in maintaining ecosystem stability. Shenmu County is a typical resource-based city near the Hongjiannao basin and has a population density of about 76 people/km² and a per capita GDP of about 46,100 dollars; its economic level ranks the first among 108 counties in Shaanxi Province and the 9th among 1866 counties in China; its secondary industry accounts for more than 76% and its coal reserves are about 50 billion tons. At the present stage, most studies focused on the changes of water quality, water area, and their influencing factors in Shenmu County under the rapid development of industrial economy [27,28,29,30]. Few studies have described the coupling and coordination relationship between the change of water environmental quality and economic development.

In this study, based on water quality and economic development in the Hongjiannao basin from 2013 to 2020, the temporal evolution characteristics of the water environment in Hongjiannao were analyzed via SPSS one-way variance analysis and Daniel and Mann–Kendall trend test. Then, the coupling coordination relationship between water quality and regional socio-economic development was explored in terms of the comprehensive index method and coupling coordination degree model. Those findings will compensate the data of the coupling and coordination relationship between water quality and economic development in the Hongjianao basin. Meanwhile, this investigation aims to find the node where the water environment quality could be enhanced with the economic development kept stably increasing in order to keep sustainable development of the regional economy.

2. Methods and Materials

2.1. Study Area

Hongjiannao is located in Shenmu City, Shaanxi Province, China (Figure 1). The geographical coordinates are 39°04′–39°08′ in the north latitude and 109°49′–109°56′ in the east longitude. The current area of Hongjiannao Lake is around 41.8 square kilometers, the altitude of Hongjiannao is around 1100 m, the climate property of Hongjiannao is the continental monsoon, the average of annual rainfall is around 346.8 mm, and the average of water depth is 8.2 m, and there are many kinds of aquatic life (Nitraria tangutorum, Salix cheilophila, etc.) [27]. With the rapid development of industry and tourism economy, the underground water supply of Hongjiannao has been damaged due to coal mining, while the water quality of Hongjiannao has been affected by the discharge of domestic sewage and mineralized mine wastewater [18].

2.2. Data Description

The water quality monitoring station of Hongjiannao Lake in Shenmu County was built in August of 2012 (http://www.cma.gov.cn/2011xzt/2013zhuant/20131126/2013112606/201311/t20131126_232560.html, accessed on 3 January 2021). The water quality of Hongjianao Lake had been detected from 2013 to 2020. The water quality cannot be effectively monitored from December to February of the next year due to the long ice sealing period in the winter. There are 10 indexes that have been used to evaluate the water quality (http://hb.yl.gov.cn/, accessed on 15 January 2021), including five-day biochemical oxygen demand (BOD₅), dissolved oxygen (DO), permanganate index (COD_Mn), total phosphorus (TP), total nitrogen (TN), ammonia nitrogen (NH₄⁺-N), volatile phenol, chemical oxygen demand (COD_Cr), petroleum, and anionic surfactant. All those indexes were detected according to the Surface Water Environmental Quality Standards (GB 3838-2002) [31].

Shenmu County has entered a stable period of economic development since 2012. There are 12 economic indicators that have been selected to evaluate the economic structure and economic benefits, and the date of economy was acquired from the Yulin Statistical Yearbook (2013–2020) and the Shenmu National Economic and Social Development Statistics Bulletin (2013–2020) (http://tjj.yl.gov.cn/, accessed on 10 February 2021).

2.3. Characteristics of Water Quality Evolution

2.3.1. Seasonal Differences of Water Quality

The least significant difference (LSD) method in single factor variance (one-way ANOVA) was used to present the characteristics of water quality with seasons, and the variance analysis was applied to compare the mean values of two or more samples for evaluating the water quality [32].

2.3.2. Interannual Variation Trend of Water Quality

The annual average value of each water quality index was calculated from the monthly data, and the Daniel trend test and Mann–Kendall trend test were used to present the changeable tendency of Hongjiannao [33]. The Daniel trend test is one of the most commonly methods to measure the environmental pollution; due to its low requirement for samples number, it is commonly used in trend analysis of time series. The Mann–Kendall trend test is a nonparametric statistical method, which only requires independent data and is not susceptible to outliers, but it has the disadvantage of not being able to detect specific patterns of trends. These two methods are selected to compare and verify each other, and the water quality change trend is more reasonable. [34].

The City Water Quality Index (CWQI) has been used to evaluate water environmental quality. The smaller the index is, the better the environmental quality is. Firstly, the arithmetic mean of the concentration of each individual index $C(i)$ is calculated. Then, the water quality index for individual indicators is calculated $CWQI(i)$. Finally, the lake water quality index is calculated comprehensively $CWQ{I}_{Lake}$ (https://www.mee.gov.cn/gkml/hbb/bgth/201606/t20160627_356096.htm, accessed on 8 November 2021).

$$CWQI(i)=\frac{C(i)}{C_s(i)}$$

(1)

$$CWQ{I}_{Lake}={\displaystyle \sum _{i=1}^{n}CWQI(i)}$$

(2)

where $CWQI(i)$ is the water quality index of a single index, $C(i)$ is the monitoring value of the $i$ water quality index, $C_s(i)$ is the standard limit of Class III of the $i$ water quality index, $CWQ{I}_{Lake}$ is the lake water quality index, and $n$ is the number of water quality indicators.

2.4. Coupling Model

2.4.1. Construction of Index System

The economic development is reflected by the increase of economic aggregate, the promotion of economic quality, and the improvement and optimization of economic structure [22,35]. There are 12 indicators (as shown in

Table 1. The evaluation indexes for the economic development and water quality in Hongjiannao.

System	Sub-System	Indexes	Weight of Coefficient
Social-economic development	Economic structure	X1	0.0294
		X2	0.0084
		X3	0.0237
		X4	0.0020
	Economic benefit	X5	0.0350
		X6	0.0431
		X7	0.0403
		X8	0.0591
		X9	0.0709
		X10	0.0581
		X11	0.0216
		X12	0.0241
Water environment	Water indexes	Y1	0.0132
		Y2	0.0423
		Y3	0.1058
		Y4	0.1086
		Y5	0.0782
		Y6	0.1856
		Y7	0.1906
		Y8	0.0666
		Y9	0.0848
		Y10	0.1243

Note: X₁ denotes share of primary industry/%, X₂ denotes share of secondary industry/%, X₃ denotes share of tertiary industry/%, X₄ denotes urbanization rate/%, X₅ denotes (GDP)/billion RMB, X₆ denotes local financial revenue/billion RMB, X₇ denotes GDP of industries/billion RMB, X₈ denotes GDP of agriculture and forestry/billion RMB, X₉ denotes increasing rate of GDP/%, X₁₀ denotes total retail sales of consumer goods/thousand RMB, X₁₁ denotes urban per capita disposable income/RMB, X₁₂ denotes rural per capita disposable income/RMB, Y₁ denotes DO/m, Y₂ denotes COD_Mn /mg·L⁻¹, Y₃ denotes BOD₅/ mg·L⁻¹, Y₄ denotes NH₃-N/mg·L⁻¹, Y₅ denotes TN / mg·L⁻¹, Y₆ denotes TP/mg·L⁻¹, Y₇ denotes volatile phenol/mg·L⁻¹, Y₈ denotes COD_Cr/ mg·L⁻¹, Y₉ denotes petroleum/mg·L⁻¹, Y₁₀ denotes anionic surfactant/mg·L⁻¹.

) that are used to present the social-economic development system of Shenmu County.

2.4.2. Water Environment and Economic Development Index

To eliminate the influence of different indexes, the original data are standardized. The corresponding formulas are shown as follows:

The standardized formula for positive index is:

$$r_{ij}=\left(x_{ij}-\min \left\{x_j\right\}\right)/\left(\max \left\{x_j\right\}-\min \left\{x_j\right\}\right)$$

(3)

The standardized formula for negative indicators is:

$$r_{ij}=\left(\max \left\{x_j\right\}-x_{ij}\right)/\left(\max \left\{x_j\right\}-\min \left\{x_j\right\}\right)$$

(4)

In this study, the relative importance of each index was reflected by the sum-variation coefficient [32], which multiplies the standardized value to obtain the water environment index (f_(x)) and the economic development index (g_(x)). x_i (i = 1, 2, 3... m) represents the standardized water quality index, x_j (j = 1, 2, 3... n) is on behalf of the standardized economic development index, and w_i and w_j are the corresponding weights of x_i and x_j, respectively. f(x) and g(x) are obtained by the following formulas:

$$f(x)={\displaystyle \sum _{i=1}^m{w}_i}{x}_i$$

(5)

$$g(x)={\displaystyle \sum _{j=1}^n{w}_j}{x}_j$$

(6)

2.4.3. Coupling Coordination

Coupling degree is a physical concept, which could reflect the mutual influence caused by multiple interactions of two or more systems [33]. In this study, the coupling degree was applied to study the interrelation between water quality and economic development in the Hongjiannao basin, which is indicated by the formula below:

$$C={\left\{\left(f(x)g(x)\right)/{\left(f(x)+g(x)\right)}^2\right\}}^{1/2}$$

(7)

The coupling coordination degree model was also used to characterize the coordinated development between the water quality and economic development. A good coupling and coordination state is not only a benign correlation, but also a guarantee for the stable and sustainable development of each system [35]. Economic development was calculated via the following formulas:

$$T=\alpha f(x)+\beta g(x)$$

(8)

$$D\left[f(x),g(x)\right]=\sqrt{CT}$$

(9)

In the formula, f(x) is the water environment index, while g(x) is the economic development index. C, T, and D represent the coupling degree, comprehensive harmonic index, and coupling coordination degree, respectively. α and β represent the contribution of water environment and economic development, separately. In this study, the water environment and economic development were assumed at the same status for the social development, α = β = 1/2. The classification of coupling-coordination types was shown in

Table 2. The types of coupling coordination between water environment and economy.

Types		Sub-Types		Form	State
Coordination period	0.6 < D ≤ 1	High coordination	0.8 < D ≤ 1	f(x) − g(x) > 0.1	lagging economic development
				g(x) − f(x) > 0.1	Lagging water environment
				0 ≤ |f(x) − g(x)| ≤ 0.1
		Intermediate coordination	0.7 < D ≤ 0.8	f(x) − g(x) > 0.1	lagging economic development
				g(x) − f(x) > 0.1	Lagging water environment
				0 ≤ |f(x) − g(x)| ≤0.1
		Primary coordination	0.6 < D ≤ 0.7	f(x) − g(x) > 0.1	lagging economic development
				g(x) − f(x) > 0.1	Lagging water environment
				0 ≤ |f(x) − g(x)| ≤ 0.1
Transformation period	0.4 < D ≤ 0.6	Barely coordination	0.5 < D ≤ 0.6	f(x) − g(x) > 0.1	lagging economic development
				g(x) − f(x) > 0.1	Lagging water environment
				0 ≤ |f(x) − g(x)| ≤ 0.1
		Nearly un-coordination	0.4 < D ≤ 0.5	f(x) − g(x) > 0.1	lagging economic development
				g(x) − f(x) > 0.1	Lagging water environment
				0 ≤ |f(x) − g(x) | ≤ 0.1
Un-coordination	0 <D ≤ 0.4	Slight un-coordination	0.3 < D ≤ 0.4	f(x) − g(x) > 0.1	lagging economic development
				g(x) − f(x) > 0.1	Lagging water environment
				0 ≤ |f(x) − g(x)| ≤ 0.1
		Intermediate un-coordination	0.2 < D ≤ 0.3	f(x) − g(x) > 0.1	lagging economic development
				g(x) − f(x) > 0.1	Lagging water environment
				0 ≤ |f(x) − g(x)| ≤ 0.1
		Serious un-coordination	0 < D ≤ 0.2	f(x) − g(x) > 0.1	lagging economic development
				g(x) − f(x) > 0.1	Lagging water environment
				0 ≤ |f(x) − g(x) | ≤ 0.1

.

3. Results and Analysis

3.1. Variation of Water Quality

3.1.1. The Seasonal Variations in Water Quality

The water quality indexes of Hongjiannao from 2013 to 2020 are listed in

Table 3. The variation of water indexes in Hongjiannao with seasons.

Season	DO/ mg·L−1	CODMn/ mg·L−1	BOD5/ mg·L−1	NH3-N/ mg·L−1	TN/ mg·L−1	TP/mg·L−1	Volatile Phenol/ mg·L−1	CODCr/ mg·L−1	Petroleum/ mg·L−1	Anionic Surfactant/ mg·L−1
Spring	8.317 a	12.429 a	2.586 a	0.351 a	3.381 a	0.089 a	0.009 a	43.143 a	0.038 a	0.050 a
Summer	7.424 b	12.664 a	3.275 a	0.375 a	3.468 a	0.091 a	0.011 a	45.084 a	0.043 a	0.065 a
Autumn	8.384 c	12.844 a	1.718 b	0.268 a	2.740 a	0.085 a	0.009 a	44.118 a	0.038 a	0.059 a

Note: ^a–c represents significant differences among seasons.

. As shown, the content of DO was the lowest in the summer, while the dosage of BOD₅, ammonia nitrogen, total nitrogen, total phosphorus, volatile phenol, chemical oxygen demand, petroleum, and anionic surfactant were the highest in the summer, which means that the water quality of Hongjiannao in the summer was the worst throughout the year. Meanwhile, there was no significant variation for the other indexes of water quality with the seasons (p < 0.05). Hence, the water quality of Hongjiannao in the summer was significantly worse than that in the other three seasons.

3.1.2. The Annual Variation of Water Quality

The annual variation of water quality in Hongjiannao was shown in Figure 2 in terms of DO, BOD₅, TN, TP, and others. From 2013 to 2020, the DO, BOD₅, and TP had a fluctuating downward tendency; the changeable tendency of DO was proportional with that of BOD₅. From 2013 to 2016, the content of TN and TP behaved a significant increasing tendency, and the maximum of TN and TP reached 4.18 and 0.24 mg/L, respectively. Meanwhile, from 2014 to 2016, the level of BOD₅ and DO increased first and then decreased. Thus, the water quality in Hongjiannao Lake gradually deteriorated with the acceleration of eutrophication before 2016. After 2016, the content of DO, BOD₅, TN, and TP had a significant decreasing tendency over years, signifying the improvement of the water quality. This phenomenon was closely related to the regulation of the government for the water environment since 2017. Meanwhile, the decline of the coal economy of Shenmu city was another reason for the improvement in water quality of Hongjiannao Lake since 2015. Moreover, the content of DO kept declining and the dosage of TP became gradually stable since 2020, while the level of BOD₅ began to increase again. Thus, the pollution extent of Hongjiannao Lake is still serious.

The analytical results of the Daniel trend test and the Mann–Kendall trend test were shown in

Table 4. The results of Daniel test and Mann–Kendall test.

	DO /mg·L−1	CODMn /mg·L−1	BOD5 /mg·L−1	NH3-N /mg·L−1	TN /mg·L−1	TP /mg·L−1	Volatile Phenol /mg·L−1	CODCr /mg·L−1	Petroleum Ether/mg·L−1	Anionic Surfactant/mg·L−1
Value of Daniel test	−0.167	−0.667	−0.595	−0.809 **	0.048	−0.095	−0.643 *	0.214	−0.155	−1.107 **
Value of Mann–Kendall test	−0.371	−1.608	−1.361	−2.103 *	0.000	−0.619	−1.361	0.124	−0.742	−2.969 **
Changeable tendency	Down	Down	Down	Down	Up	Down	Down	Up	Down	Down

Note: * means the correlation value was higher than 0.05; ** means the correlation value was higher than 0.01.

in terms of 10 indexes of water quality, and the variation of those indexes had a similar tendency. From 2013 to 2020, the content of TN and COD kept increasing, whereas the other indexes continued to decrease to different extents, especially for the ammonia nitrogen and anionic surfactant. The pollution of water quality in Hongjiannao increased first, and then decreased with the years (Figure 2).

The $CWQ{I}_{Lake}$ value of Hongjiannao can be obtained via Formula (1) (Figure 3). From 2013 to 2020, the water quality showed an increasing trend first, and then decreased. Combined with Figure 2, the contents of total nitrogen and total phosphorus in 2015~2016 were 3.4~6.9 times of the Class Ⅲ standard limit in the “Surface Water Environmental Quality Standard” (GB3838-2002) [31], which is also the main reason for the high CWQI level. Shenmu County began to comprehensively implement the river chief system (http://www.sxsm.gov.cn/zwgk/jcxxgk/zfwj/szbf/12370.htm, accessed on 12 February 2022) after 2016, the local government closed and integrated small coal mines with less than 450,000 tons in the Hongjiannao Valley, which effectively improved the water quality. In 2020, the content of total nitrogen and total phosphorus was 1.1–1.8 times of the Class Ⅲ standard limit, indicating the water environment quality was significantly improved.

3.2. Coupling Coordination Analysis

3.2.1. Comprehensive Index Analysis

Figure 4 presents the dynamic change of the water quality and economic development in terms of f(x), g(x), and the level of coupling coordination. In detail, the water environment index showed a downward trend from 2013 to 2014; it increased rapidly to a stable level from 2014 to 2016; then, the water quality declined sharply from 2016 to 2019; and finally, it began to grow again in 2020. The changeable tendency of f(x) was consistent with the water quality over years. The economical level, scale, and structure kept rapidly increasing before 2015, and then they were on a downward trajectory due to the decline of the coal economy. Thus, the value of g(x) rose steadily with the years. Moreover the level of f(x) was lower than that of the g(x) during the early stage, and then gradually exceeded that of the g(x) during the later stage, which indicated that the economic development led to a significant impact on the water quality in Hongjiannao basin.

3.2.2. Change in Coupling Coordination Degree and Classification of Coupling Coordination Types

The coupling coordination index got a yielding point from 2016 to 2019 (Figure 4). Before the yielding point, the g_(x) and f_(x) behaved in a synchronous increasing trend from 2013 to 2016; thus, the degree of coupling coordination continued to increase during this period. After the yielding point, the level of g(x) kept declining from 2016 to 2019, while the content of f(x) continued to increase; therefore, the degree of coupling coordination began to decline. However, the level of coupling coordination has increased again since 2019.

As presented in

Table 5. The types of coupling coordination between water environment and economy in Hongjiannao basin.

Year	Coupling Coordination	Types
2013	0.473	Transformation period	Nearly un-coordination—lagging economic development
2014	0.603	Coordination period	Primary coordination—lagging economic development
2015	0.623	Coordination period	Primary coordination—lagging economic development
2016	0.671	Coordination period	Primary coordination—lagging economic development
2017	0.575	Transformation period	Barely coordination—lagging economic development
2018	0.623	Coordination period	Primary coupling
2019	0.591	Transformation period	Barely coordination—lagging water environment
2020	0.624	Coordination period	Primary coupling—lagging water environment

, the degree of coupling coordination between the water quality and economic development showed an increasing trend with time. In 2013, the type of coupling coordination was at a transition period with the degree of coupling coordination at 0.473, which was ascribed to the lagging of the economic development. The average of coupling coordination was at 0.632 from 2014 to 2016, which was in the primary coordination stage. Being affected by the domestic economic downturn and falling coal prices, the economic development index declined with the enhancement in the water quality. From 2016 to 2019, with the acceleration of industrialization and urbanization, the socio-economic development level of the basin has been growing continuously. During this period, the discharge of industrial sewage and domestic sewage increased, the water environment was seriously polluted, and the water quality began to decline. In 2019, the water environmental quality index lagged behind, which began to restrict the coordinated and stable development of those two subsystems. The coupling coordination type decreased from the coordination period to the transition period, and the coupling coordination degree decreased from 0.671 to 0.591. From 2019 to 2020, the water environment index and economic development index began to increase synchronously, the coupling coordination degree increased to 0.624, and the coordination type entered the coordination period again.

4. Discussion

4.1. Analysis of Seasonal Variation of Water Quality in Hongjiannao Lake

According to the data of water quality with seasons in Hongjiannao from 2013 to 2020, the water quality of Hongjiannao Lake in the summer was the worst, which behaved significantly different with that in the spring; the content of TN, TP, and COD was significantly higher than the discharge standard. The reasons for the degraded water quality in the summer are as follows: (1) The Zhasak River and Manggaitu River are the main water replenishments for the Hongjiannao Lake, which accounts for more than 50% of the total water resources. The pollutants contained in the Zhasak River and Manggaitu River were seriously brought into Hongjiannao Lake in the summer; (2) the pesticides and fertilizers are widely used in the upstream and surrounding crops in the summer, especially for nitrogen fertilizer, those pollutants will enter the Hongjiannao Lake via the surface runoff. (3) Especially in recent years, the phenomenon of extreme high temperature in the summer occurs frequently, and microorganisms and organic matter proliferate in the lake, causing serious pollution to the water body. (4) With the economic development of Shenmu City, the urbanization construction did not keep the synchronous development with the environmental protection governance. The previous investigation also confirmed this phenomenon [30].

4.2. Interannual Variation Analysis of Hongjiannao Water Quality

In recent years, the area of Hongjiannao Lake continued to shrink. The pH of lake kept increasing, and even reached 9.5. The content of TN, TP, and other indexes were below the IV standard. The high level of pollution in Hongjiannao from 2013 to 2015 was mainly attributed to the discharge of chemical substances from the coal factory [18]. And then, the water quality of Hongjiannao continued to increase from 2016 to 2020. During this period, the improvement of water quality is closely related with the government regulation, which was confirmed by the previous study [11].

4.3. Coupling Coordination Analysis of Hongjiannao Water Environment and Socio-Economic Development

The degree of coupling coordination between water quality and economic development increased from 0.473 to 0.624 (from 2013 to 2020), indicating that the coupling coordination state changed from the nearly un-coordination state of the transition period to the primary coordination state of the coordination period. The coordinated development pattern between f_(x) and g_(x) is becoming more and more perfect. According to the development process of coupling coordination, Hongjiannao Lake has experienced three main steps: the lagging economic development, the primary coordination, and the lagging water environment.

In the early stage (2013–2016), f(x) and g(x) increased synchronously, while the coupling coordination degree increased from 0.473 to 0.671. At this stage, being affected by the international coal import and coal price decline, Shenmu County’s exhibition economy developed slowly, while the water quality increased. However, due to the low sewage treatment rate of urban sewage treatment plants, the contents of total nitrogen, total phosphorus, and $CWQ{I}_{Lake}$ in Hongjiannao Lake became higher.

In the interim phase (2017–2018), the economy of Shenmu County developed rapidly, the water quality declined to some extent, $CWQ{I}_{Lake}$ increased slightly, and the coupling coordination degree increased from 0.575 to 0.623. It is worth noting that the lagging state of economic development in this stage has changed (compared with the previous stage). In 2018, f_(x) and g_(x) basically reached the same level, meaning those two subsystems tended to be balanced. This is mainly related to the optimization of industrial structure and the improvement of sewage treatment rate in Shenmu County. The proportion of the secondary industry in Shenmu County increased from 67% to 71%, and the industrialization level changed from the intermediate stage to the advanced stage [18,36]. In addition, according to the Chinese government’s implementation of the river chief system (http://www.gov.cn/xinwen/2016–12/11/content_5146628.htm, accessed on 12 February 2022), Shenmu County raised the sewage discharge standard for coal mines, increased the recycling and utilization of mine drainage water, and reduced the discharge of highly mineralized industrial wastewater. The sewage treatment rate has increased from 82.9% to 88.7% (from 2015 to 2018).

During 2019–2020, the economic development of Shenmu County slowed down, and the water quality improved again, $CWQ{I}_{Lake}$ decreased, and the coupling coordination degree increased from 0.591 to 0.624. The industrial structure and sewage treatment rate of the basin were further improved, the high-end coal chemical industry replaced the original high-polluting enterprises, and the proportion of the secondary industry and sewage treatment rate has been increased to 77% and 93.4%, respectively. The economic development with low emission and high efficiency gradually has been achieved preliminarily. However, there are still some problems restricting economic development, such as water shortage [37], the low level of coupling coordination degree, and the gap between the normal situation and the advanced coordination state. Therefore, with the rapid economic development, we need to strengthen the control of water environmental pollution and promote the coordinated and sustainable development of the water environment and economy in the river basin.

5. Conclusions

This paper analyzes the changeable trend of water quality in Hongjiannao basin and investigates the coupling and coordination development status between water quality and economic development, which provides a theoretical basis for the coordinated development of water pollution treatment and economy. The main conclusions were shown as follows:

(1)

The water quality of Hongjiannao in the summer was worse than that in the spring and autumn. And, the water quality of Hongjiannao behaved with an increasing tendency from 2013 to 2020.

(2)

The degree of coupling coordination in Hongjiannao Lake was at the middle level, and its level increased first, and then decreased, and finally raised again. From 2013 to 2020, the development of coupling coordination in Hongjiannao basin expired three steps: the lagging economic development, the primary coordination, and the lagging water environment.

(3)

It can be seen that under the influence of urbanization, industrialization, and extreme hot weather, lake water levels have fallen, pollution is serious, and water resources are stressed. Therefore, governments at all levels should increase investment and management of pollution control, reduce the discharge of untreated sewage into water bodies, and adopt membrane treatment and other technologies to improve the efficiency of recycled water recovery and realize the resource utilization of sewage, especially in China and other developing countries in the world. Economic development promotes the improvement of water quality, and a good water environment also provides a guarantee for sustainable economic development.