2125 © 2021 The Authors Journal of Water and Climate Change | 12.5 | 2021

Evaluation and spatial-temporal evolution of water resources carrying capacity in Basin Zhenghua Deng, Liqi Dai, Bing Deng and Xiaoyong Tian

ABSTRACT

A three-dimensional rating index system for water resources system–water environment system– Zhenghua Deng (corresponding author) Liqi Dai socioeconomic system is constructed based on data from Dongting Lake Eco-environment Xiaoyong Tian Hunan Institute of Science and Technology, Monitoring Center, Hunan Provincial Water Resources Bulletin, and Hunan Statistical Yearbook. The , water resources carrying capacity (WRCC) of Dongting Lake Basin from 2009 to 2018 is evaluated by the E-mail: [email protected] TOPSIS model combined with analytic hierarchy process (AHP) and entropy weight, and then the Zhenghua Deng temporal evolution and spatial distribution characteristics of the WRCC of the Dongting Lake Basin are Bing Deng Key Laboratory of Dongting Lake Aquatic Eco- analyzed. The results show that: (1) The WRCC in the Dongting Lake Basin decreases from a good level to Environmental Control and Restoration of Hunan a reasonable level during the period. Among them, the WRCC of the Ouchi River, Hudu River, and Songzi Province, , River Basins decreases significantly. (2) There are obvious spatial differences in the WRCC of the China

Dongting Lake Basin in 2018, the WRCC order is , West Dongting Lake, Zijiang River, South Bing Deng Changsha University of Science & Technology, Dongting Lake, Yuanshui River, Xiangjiang River, East Dongting Lake, Songzi River, Hudu River, Ouchi Changsha, River, with scores of 0.586, 0.526, 0.472, 0.448, 0.416, 0.397, 0.393, 0.313, 0.306, and 0.304, respectively. China Finally, some policy recommendations for improving the WRCC of the Dongting Lake Basin are proposed. Key words | combination weight, Dongting Lake Basin, TOPSIS, water resources carrying capacity

HIGHLIGHTS

• According to the definition of water resources carrying capacity, its index evaluation system has been established. • The paper combines entropy method and TOPSIS method to comprehensively evaluate the change of water resources carrying capacity of Dongting Lake Basin during the last 10 years. • The countermeasures for coordinated development of water resources and society in the Dongting Lake Basin are proposed.

INTRODUCTION

Water is one of the important resources for the survival and important factors restricting the sustainable development development of human society. With the growth of popu- of society and the economy (Zuo & Zhang ). Water lation and development of the economy, water shortage resources carrying capacity (WRCC) is an important indi- and the deterioration of the water environment are becom- cator to characterize the state of regional water resources. ing increasingly serious and are gradually turning into Scientific measurement of regional WRCC is not only a necessary prerequisite for carrying out water resource regu- This is an Open Access article distributed under the terms of the Creative lation, but also an important basis for sustainable economic Commons Attribution Licence (CC BY 4.0), which permits copying,  adaptation and redistribution, provided the original work is properly cited and social development in the region (Song & Zhan ; (http://creativecommons.org/licenses/by/4.0/). Yang et al. , ). Comprehensive evaluation of regional

doi: 10.2166/wcc.2021.210

Downloaded from http://iwaponline.com/jwcc/article-pdf/12/5/2125/923265/jwc0122125.pdf by guest on 29 September 2021 2126 Z. Deng et al. | Evaluation of water resources carrying capacity Journal of Water and Climate Change | 12.5 | 2021

WRCC helps grasp the interactive relationship between factors affecting the resource carrying capacity through the water resources and economic development, and provides principal component score. Yuan et al. () applied the theoretical support and a realistic basis for coordinating improved fuzzy comprehensive evaluation method to evalu- economic, social, and environmental development ate the WRCC in Jiangyin City. He et al. () used the (Simanjuntak et al. ). TOPSIS comprehensive evaluation method to study and ana- Research on WRCC is relatively abundant, mainly focus- lyze the dynamic changes and spatial differences of the ing on the definition, the evaluation index system, and WRCC of the River Economic Belt from 2007 to evaluation methods of WRCC. At present, there is still no 2016. Lin et al. () applied the TOPSIS model based on consensus on the definition of WRCC. Hui et al. () the entropy weight method, analysis, and evaluation of the believed that WRCC is the water system’s largest supporting WRCC in Kubuqi desert area from 2013 to 2018, and put capacity for socioeconomic development in the region forward suggestions for improvement. during certain development stages, and emphasize the sup- The above research shows that WRCC has gradually porting role of water resources for social and economic become a research hotspot in regional economics and econ- development. Xia () believed that WRCC is the ability omic geography. In general, existing studies have produced to support population size and sustainable socioeconomic good research on the evaluation of WRCC, which has cre- development, and reflects the mutual relationship between ated strong progress concerning WRCC. However, existing water resources and social economy, which is more scienti- studies still have the following limitations. First, most of fic and reasonable. As for the evaluation index system, a the research areas for WRCC are local areas, such as the three-dimensional evaluation index system is often con- western, central, and northeastern provinces, as well as structed based on water resources–social economy– specific urban groups like the Yangtze River Delta in ecological environment (Li et al. ). A five-dimensional China. There are few studies on the comprehensive evalu- rating index system about driving force–pressure–status– ation of WRCC based on river basins. Second, the index influence–response (DPSIR) is used to evaluate WRCC system needs to be further improved. Most existing (Chen et al. ; Zhu & Wang ; Li et al. ; Weng studies adopt socioeconomic and water resource indicators et al. ). An evaluation index system from the perspec- (Rijiberman & van de Venb ; Wu et al. ), and tives of quantity–quality–watershed-flow comprehensively there is no consideration of water environment indicators evaluated the WRCC of the Beijing–Tianjin–Hebei area that affect WRCC. Third, most of the existing literature uses (Yu et al. ). In terms of quantitative research of subjective weighting such as the principal component analysis WRCC, the commonly used evaluation methods are method or objective weighting such as the entropy weighting mainly the conventional trend method, principal com- method, which may lead to insufficient accuracy of the evalu- ponent analysis method, fuzzy comprehensive evaluation ation results of WRCC. method, and system dynamics method. Cui et al. () Based on the current research work, this paper takes the adopted set pair analysis and the improved entropy weight Dongting Lake Basin as the research area. Considering method to determine the objective weight of indicators, water environment indictors’ impact on WRCC, the paper making the evaluation results more real and accurate. Qu & applies the water environment monitoring data of each Fan () used the conventional trend method to study basin monitoring point of the Ecological Environment the WRCC of the Hei River Basin as well as analyzing the Monitoring Center of Dongting Lake, and selects indicators supplyanddemandrelationshipofwaterresourcesinthe from the three subsystems of water resources, water environ- basin under different schemes. Some authors used the ment, and social economy, and then constructs a system dynamics method to establish a comprehensive assess- comprehensive evaluation index system of the WRCC. ment model of water resources in Yiwu and Xi’an (Feng et al. Finally, the program takes the TOPSIS model combined ; Haddeland et al. ). Li et al. () used the principal with composite weighting based on the improved analytic component analysis method to comprehensively evaluate the hierarchy process (AHP) and entropy value method to deter- resource carrying capacity of Zhengzhou and found the main mine the comprehensive weight of each indicator, and the

Downloaded from http://iwaponline.com/jwcc/article-pdf/12/5/2125/923265/jwc0122125.pdf by guest on 29 September 2021 2127 Z. Deng et al. | Evaluation of water resources carrying capacity Journal of Water and Climate Change | 12.5 | 2021

temporal and spatial dynamic changes of WRCC in the and Hunan Dongting Lake Ecological Environment Dongting Lake Basin from 2009 to 2018 are evaluated. Monitoring Center obtained water resources data and socio- The remainder of this paper is organized as follows. The economic data. Ten representative Dongting Lake Basin next section introduces the study area and data source, fol- monitoring stations (Figure 1) were screened to obtain the lowed by a section describing the research methods. Then, water environment data, and included: S1 Songzi River’s a section presents the empirical research results and the Xinjiangkou; S2 Hudu River’s Mituo Temple; S3 Oujichi final section discusses the research findings and concludes River’s Butler Shop; S4 Xiangjiang’s Zhuting Town; S5 the study. Zijiang’s Pingkou; S6 Yuanshui’s Guanyin Temple; S7 Shi- menxinguan of Lishui; S8 Yueyang Tower in the east of Dongting Lake; S9 Xiaohezui in the west of Dongting STUDY AREA AND DATA SOURCE Lake; and S10 Hengling Lake on the south bank of Dongt- ing Lake. Study areas

The Dongting Lake Basin is located in the northeast of Hunan RESEARCH METHODS Province, on the south bank of the Jingjiang River in the middle reaches of the Yangtze River, forming a complex inter- Evaluation index system action relationship with the Yangtze River. The Ouchikou, Songzikou, and Taipingkou (referred to as ‘Three Outlets’)to According to the definition of WRCC and the principles of the north divert the Yangtze River water from the Oujichi comprehensiveness, representativeness, comparability, and River, Songzi River, and Hudu River into Dongting. Xiang- data availability of the evaluation index system, this paper jiang, Zijiang, Yuanjiang, and Lishui (referred to as the ‘Four constructs the three-dimensional indicator system of water Rivers’) come from the south and are injected into the Dongt- resources system, water environment system, and social ing Lake and, after being stored in the lake, the water system economic system. The water resource system includes four flows through Yueyang City into the Yangtze River. Dongting indicators: water resources per capita, water production Lake is an important throughput lake in the Yangtze River modulus, river patency, and average annual runoff. The Basin. With the advancement of industrialization, farming water environment system includes total water phosphorus modernization, and urbanization in the lake area, the relation- content (TP), total water nitrogen content (TN), chemical shipbetweentheYangtzeRiverandDongtingLakeevolved oxygen demand (COD), and water dissolved oxygen content after the Three Gorges Project became operational. The (DO). The socioeconomic system includes urban population water resource shortage and worsened water resource environ- density, urbanization rate, regional GDP, 10,000 industrial ment has evolved into the restricted condition of Dongting value-added water consumption and 10,000 agricultural Lake regional economic development. As such, studying the value-added water consumption. Table 1 shows the selection spatiotemporal evolution of the WRCC of the Dongting of specific indicators and their impact on WRCC. Lake Basin is of great significance for solving the contradiction between the supply and demand of water resources. It also promotes the sustainable use of water resources and creates Composite weighting theDongtingLakeeco-economiczoneandthegreendevelop- ment demonstration zone. In order to accurately reflect the weights of the indicators of the water resources system, water environment system, and Data sources socioeconomic system of Dongting Lake Basin’s WRCC, this paper combines with subjective weighting by AHP Based on Dongting Lake Basin from 2008 to 2019, Hunan and objective weighting by entropy weighting method to Statistical Yearbook, Hunan Water Resources Bulletin, determine the weight.

Downloaded from http://iwaponline.com/jwcc/article-pdf/12/5/2125/923265/jwc0122125.pdf by guest on 29 September 2021 2128 Z. Deng et al. | Evaluation of water resources carrying capacity Journal of Water and Climate Change | 12.5 | 2021

Figure 1 | Distribution of Dongting Lake Basin and monitoring points.

AHP was proposed by the American scholar A. L. Saaty corresponding eigenvector of the judgment matrix can (). It introduces the experience and professional knowl- be obtained. edge of decision-makers into the evaluation process to (iii) The third step is the consistency test. When the consist- determine the subjective weight of each evaluation index. ency ratio CR <0.1, it shows that the judgment matrix The specific calculation steps are presented: has passed the consistency test, and after normaliza- tion, the weight of each index is obtained. ¼ (i) the judgment matrix U ((auv)m×m), where auv is the relative importance of index u compared with indicator Compared with the AHP, the entropy weight method v, and its value range is 1–9. can objectively determine its weight based on the infor- (ii) The second step is to calculate the maximum eigenvec- mation provided by each evaluation index, to avoid the tor of the judgment matrix. According to the formula deviation of the results caused by the randomness of subjec-

Uw ¼ λmaxw, the maximum eigenvalue λmax and tive weighting, where the entropy weight can measure the

Downloaded from http://iwaponline.com/jwcc/article-pdf/12/5/2125/923265/jwc0122125.pdf by guest on 29 September 2021 2129 Z. Deng et al. | Evaluation of water resources carrying capacity Journal of Water and Climate Change | 12.5 | 2021

Table 1 | Evaluation index system of water resources carrying capacity of Dongting Lake

Index Target layer Criterion layer Index layer Index description properties

Water resources Water resources C1 Water resources per capita Total water resources/Total population (m³/Per) Benefit carrying capacity system C2 Water production modulus Total water resources/Total area (104 m³/km²) Benefit C3 Rivers fluidity Annual average time of river cut off/day Cost C4 Annual average runoff Statistical data (m³) Benefit Water environment C5 Total phosphorus TP (mg/L) Cost system C6 Total nitrogen TN (mg/L) Cost C7 Chemical oxygen demand COD (mg/L) Cost C8 Dissolved oxygen DO (mg/L) Benefit Social economic C9 Urban population density Urban population/Total area (people/km²) Cost system C10 Urbanization rate Urban population/Total population (%) Benefit C11 Gross domestic product GDP statistical data (/billion yuan) Benefit C12 Water use for generating Industrial water consumption/Industrial value- Cost every 10,000 yuan in added (m³/yuan) industrial value added C13 Water use for generating Agriculture water consumption/Agriculture Cost every 10,000 yuan in value-added (m³/yuan) agriculture value added

degree of disorder of the system, that is, the smaller the information entropy of a set of data is as follows: information entropy of the indicator, the larger the entropy Xn weight, that the indicator is more important, and vice versa. 1 H ¼ f ln f i lnn ij ij The main calculation steps are as follows: j¼1 r (i) Data standardization. Construct the original data matrix: ¼ ij fij Pn (2) Z ¼ (zij) × . Due to the different dimensions and index m n rij attributes of the data, the data will be standardized j¼1 using a standardized method: (iii) fij is the characteristic proportion of the indicator. fi Normalized formula for bene t indicators: Therefore the weight of each indicator is

1 H rij ¼ zij min (zij)=max (zij) min (zij) ¼ i Wi Pm (3) m Hi i¼1 Normalized formula for cost indicators: (iv) Upon determining the weights of the indicators, we established an indicator weighted criterion matrix using rij ¼ max (zij) zij=max (zij) min (zij) (1) the following formula:

¼ The normalization matrix R (rij)m×n is obtained, where Y ¼ rij × Wi (4) rij is the normalized value of the i-th index at the j-th moni- toring point; and max (zij) and min (zij) represent the TOPSIS model maximum and minimum values of the i-th target at the j-th

observation point. Technique for order preference by similarity to an ideal sol- (ii) Calculation indicator weights. According to the defi- ution (TOPSIS) is one of the methods for comprehensive nition of information entropy in information theory, the evaluation of multi-objective decision-making. The basic

Downloaded from http://iwaponline.com/jwcc/article-pdf/12/5/2125/923265/jwc0122125.pdf by guest on 29 September 2021 2130 Z. Deng et al. | Evaluation of water resources carrying capacity Journal of Water and Climate Change | 12.5 | 2021

idea is to detect the relative distance between the evaluation the research results of many scholars, the final calculation index and the optimal and the worst solutions. To sort, the result T is divided into five levels representing severe over- concept is clear and operable, and it can be used for hori- load, overload, reasonable, good, and high quality of zontal and vertical comparative analysis. Specific WRCC, as shown in Table 2. evaluation steps are as follows:

(i) Calculate relative distance. We calculated the ideal sol- ution Y þand the negative solution Y of the indicator EMPIRICAL RESEARCH RESULTS weighted criterion assessment value using formula (5): Calculation results þ Y ¼{ max yi1, max yi2 ...max yim} (5) Y ¼{ min yi1, min yi2 ...min yim} According to the calculation steps of combination weight- ing, the weights of each index are calculated by formulas (1)–(4). The specific results are shown in Table 3. The distance from the i-th index to the optimal solution According to the calculation results of the combined Y þ is recorded as Dþ. The distance from the i-th index to the j weights, using formulas (5) and (6), the evaluation results negative ideal solution Y is recorded as D, and the calcu- j of the WRCC of each basin can be calculated as shown in lation formula is as follows: Table 4. vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u uXm þ ¼ t 2 Dj ( max yij yij) Analysis of temporal evolution of water resources i¼1 carrying capacity in Dongting Lake Basin vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u uXm ¼ t 2 During the inspection period, the average WRCC of the Dj ( min yij yij) (6) i¼1 entire basin of Dongting Lake decreased from 0.472 in 2009 to 0.415 in 2018 (Figure 2). Among them, the WRCC of the Dongting Lake district decreased from 0.509 in (ii) Calculate the relative closeness of each assessment þ 2009 to 0.456, from a good level to a reasonable level, show- indicator value vector to the ideal solution Y using ing a steady decline in general. The average value of Three formula (7): Outlets Basin declined from 0.413 in 2009 to 0.305 in

2018, the evaluation level of the WRCC going from a reason- Dj T j ¼ þ (7) able stage to an overloaded state (Figure 3). The value of the Dj þ Dj WRCC of the Xiangjiang Basin increased from 0.291 in 2009 to 0.397 in 2018, and its evaluation level increased from

The value range of Tj is [0–1]. When T is larger, it is severe overload to an overload state (Figure 4). The closer to the ideal solution, and the WRCC is higher. WRCC basically showed a steady downward trend When T is smaller, the distance from the ideal solution is (Figure 4). According to Figures 2–4, the time evolution of farther, and the WRCC is lower. As such, the status of the WRCC of the Dongting Lake Basin can be divided WRCC must be evaluated. Comprehensively referring to into two stages.

Table 2 | Evaluation criteria for water resources carrying capacity of the Dongting Lake Basin

Closeness degree [0,0.3) [0.3,0.4) [0.4,0.5) [0.5,0.6) [0.6,1]

Grade V IV III II I Grade description Severe overload Overload Reasonable Good High quality

Downloaded from http://iwaponline.com/jwcc/article-pdf/12/5/2125/923265/jwc0122125.pdf by guest on 29 September 2021 2131 Z. Deng et al. | Evaluation of water resources carrying capacity Journal of Water and Climate Change | 12.5 | 2021

Table 3 | Evaluation index weight of water resources carrying capacity in Dongting Lake Basin

Indicator 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

C1 0.146 0.121 0.135 0.114 0.118 0.124 0.117 0.104 0.129 0.135 C2 0.089 0.106 0.087 0.084 0.081 0.096 0.088 0.093 0.084 0.082 C3 0.076 0.077 0.081 0.077 0.081 0.073 0.071 0.081 0.087 0.074 C4 0.045 0.061 0.058 0.054 0.072 0.066 0.063 0.068 0.057 0.058 C5 0.048 0.044 0.056 0.053 0.061 0.057 0.046 0.051 0.049 0.053 C6 0.053 0.057 0.049 0.055 0.045 0.042 0.041 0.048 0.056 0.049 C7 0.059 0.047 0.044 0.041 0.058 0.051 0.048 0.045 0.044 0.043 C8 0.036 0.033 0.041 0.047 0.047 0.041 0.043 0.039 0.048 0.046 C9 0.071 0.082 0.088 0.102 0.107 0.113 0.104 0.099 0.106 0.117 C10 0.075 0.091 0.079 0.084 0.078 0.088 0.091 0.091 0.084 0.081 C11 0.105 0.082 0.091 0.104 0.096 0.091 0.105 0.11 0.093 0.098 C12 0.126 0.121 0.102 0.104 0.083 0.094 0.101 0.096 0.095 0.087 C13 0.071 0.078 0.089 0.081 0.073 0.064 0.082 0.075 0.068 0.077

Table 4 | Assessment of water resources carrying capacity of Dongting Lake

Three Outlets Four Rivers Dongting Lake Years Ouchi river Songzi river Hudu river Xiangjiang Zijiang Yuanjiang Lishui East West South

2009 0.421 0.404 0.413 0.291 0.547 0.451 0.664 0.447 0.602 0.477 2010 0.403 0.397 0.392 0.317 0.536 0.437 0.648 0.424 0.587 0.464 2011 0.385 0.376 0.377 0.321 0.488 0.414 0.634 0.398 0.561 0.436 2012 0.352 0.341 0.356 0.335 0.456 0.391 0.591 0.381 0.538 0.384 2013 0.331 0.355 0.359 0.342 0.431 0.377 0.579 0.377 0.541 0.391 2014 0.345 0.332 0.337 0.359 0.419 0.365 0.561 0.361 0.526 0.378 2015 0.321 0.311 0.331 0.376 0.411 0.378 0.574 0.374 0.491 0.417 2016 0.305 0.326 0.311 0.381 0.423 0.385 0.566 0.388 0.509 0.431 2017 0.311 0.307 0.315 0.394 0.447 0.409 0.571 0.401 0.513 0.454 2018 0.303 0.311 0.302 0.397 0.469 0.418 0.582 0.396 0.522 0.448 Mean 0.348 0.346 0.349 0.351 0.463 0.403 0.597 0.395 0.539 0.428 Grade IV IV IV IV III III II IV II III

The first stage is from 2009 to 2014. During this period, COD from industrial wastewater into the lake from the WRCC of the Dongting Lake Basin generally declined. 856,000 tons, 67,000 tons, and 1.1 million tons, respectively, The carrying capacity of water resources decreased from increased to 984,000, 83,000, and 1.316 million tons. Due to 0.472 to 0.398, and the evaluation level dropped from the impact of the operation of the Three Gorges Project, the reasonable to overloaded. The main reason was that the total runoff of Dongting Lake water resources from 213 bil- total GDP of Hunan Province increased from 130.6 billion lion m³ decreased to 198 billion m³. The WRCC of Ouchi to 270.7 billion yuan in 2009–2014, a growth rate of 7.9%. River, Songzi River, and Hudu River decreased from The water consumption per yuan of GDP and the value- 0.421, 0.404, and 0.413 in 2009 to 0.345, 0.332, and 0.337 added industrial water consumption per 10,000 yuan were in 2014, respectively. WRCC level dropped from reasonable 135 m³ and 83 m³. The total discharge of TN, TP, and to overload level. The main reason is the total runoff of

Downloaded from http://iwaponline.com/jwcc/article-pdf/12/5/2125/923265/jwc0122125.pdf by guest on 29 September 2021 2132 Z. Deng et al. | Evaluation of water resources carrying capacity Journal of Water and Climate Change | 12.5 | 2021

water resources in the Three Outlets Basin decreased from 47.8 billion m³ to 36.3 billion m³, and the river channel drying extensions from 69 to 129 days. The carrying capacity of the water resources in Xiangjiang increased from 0.291 in 2009 to 0.359 in 2014, and the evaluation level has rebounded from a severe overload level to an overload level. The main reason is that the Xiangjiang is the concen- tration area for traditional industries such as metals, steel, coal, food processing, etc. in the Dongting Lake Basin. The total industrial wastewater discharge over the past five years was 83.09 million tons, accounting for about 82% of the total wastewater discharge in the Dongting Lake Basin. Until very recently, people have only gradually rea- Figure 2 | Water resources carrying capacity in Dongting Lake area. lized the importance of environmental protection, and the government has adopted environmental control policies to strictly limit the discharge of industrial sewage, which has made the carrying capacity of water resources in the Xiang- jiang River Basin improve. The second stage is from 2015 to 2018. The WRCC of the Dongting Lake watershed fluctuated in a reasonable scope between 0.398 and 0.415, and the difference between the WRCC of the watersheds of Dongting Lake gradually narrowed. The main reason is the planning and implemen- tation of the Dongting Lake ecological economic zone and the construction of the Chang-Zhu-Tan type experimental area. The government plays a key role in coordinating econ- omic development and environmental protection. It mainly Figure 3 | Water resources carrying capacity in the Three Outlets Basin. implements the policy of adjusting and optimizing the layout of high water-consumption industry such as non-ferrous metal mining and smelting, petrochemicals, papermaking, and power and energy. The special governance policy of the Dongting Lake ecological environment has optimized the socioeconomic system and the water environment system and gradually increased the WRCC of Dongting Lake basin. However, the state of water resources has been affected by the river–lake relationship. The continuous decline of water resources in total supply negatively affects the WRCC.

Spatial distribution analysis of water resources carrying capacity in Dongting Lake Basin

Table 4 shows the WRCC of the Dongting Lake Basin in

Figure 4 | Water resources carrying capacity in the Four Rivers Basins. 2018. The WRCC of the Ouchi River, Songzi River, Hudu

Downloaded from http://iwaponline.com/jwcc/article-pdf/12/5/2125/923265/jwc0122125.pdf by guest on 29 September 2021 2133 Z. Deng et al. | Evaluation of water resources carrying capacity Journal of Water and Climate Change | 12.5 | 2021

River, Xiangjiang, and East Dongting Lake areas are in over- of WRCC. The population density of cities in the Xiangjiang, load level, and their bearing capacity values are 0.303, represented by Changsha, , , and Hen- 0.311, 0.302, 0.397, and 0.396, respectively. Zijiang, Yuan- gyang, has reached 655 per/km, and total GDP has jiang, and areas are at a reasonable reached 1,842.238 billion yuan, accounting for 50% of level, and the carrying capacity values are 0.469, 0.418, Hunan Province. The urbanization development and the and 0.448, respectively. Lishui and West Dongting Lake total value of industrial production are significantly and are at a good level, with carrying capacity values of 0.582 positively related to TN, TP, and COD which negatively and 0.522. The overall ranking of WRCC is Lishui > West affect the carrying capacity of water resources in the Xiang- Dongting Lake > Zijiang > South Dongting Lake > Yuan- jiang. With the decrease of the amount of water entering the jiang > Xiangjiang > East Dongting Lake > Songzi River > East Dongting Lake, the self-purification capacity of the Ouchi River > Hudu River. In order to more intuitively water body decreases. Moreover, the accumulation of pollu- reflect the changes in WRCC of the Dongting Lake Basin tants is obvious, and the average annual range of total in 2009 and 2018, Arc GIS was used to draw a comparison phosphorus is in the range of 0.063–0.127 mg/L, exceeding chart of WRCC levels (Figure 5). the Class III water quality limit value of lakes and reservoirs, The water resources per capita, river patency, water pro- thus placing great pressure on WRCC. duction modulus and average annual runoff in the water resources system of the Three Outlets Basin are 1,873 m³, 286 days/year, 3,348 m³/km2, respectively. The annual aver- DISCUSSION AND CONCLUSION age runoff of 5.7 billion m³ greatly impacts the carrying capacity of the Three Outlets Basin. The TN content in the Based on the construction of a comprehensive evaluation water environment system exceeds the standard, and the index system of the WRCC of the Dongting Lake Basin, value-added agricultural water consumption per 10,000 the entropy-weighted TOPSIS method was used to analyze yuan is 359 m³/10,000 yuan. The contribution rate of agri- the temporal evolution and spatial distribution character- cultural non-point source pollution to the total nitrogen in istics of the WRCC of the Dongting Lake watershed, to the basin exceeds 70% which adversely affects the status investigate the impact of the WRCC of the Dongting Lake

Figure 5 | Distribution of water resources carrying capacity in the Dongting Lake Basin.

Downloaded from http://iwaponline.com/jwcc/article-pdf/12/5/2125/923265/jwc0122125.pdf by guest on 29 September 2021 2134 Z. Deng et al. | Evaluation of water resources carrying capacity Journal of Water and Climate Change | 12.5 | 2021

watershed factors, and the main research conclusions are as Adjust the agricultural production structure in the Three follows: (1) From 2009 to 2018, the WRCC of the Dongting Outlets Basin, prominent agricultural non-point source pol- Lake basin went from a good level to a reasonable level, lution control, reducing the use of chemical fertilizers and showing a steady decline. The carrying capacity of the pesticides, vigorously promoting high-efficiency, low-toxic, Ouchi River, Hudu River, Songzi River basin, and East low-residue chemical and biological pesticides, piloting Dongting Lake has decreased significantly. (2) Obvious and promoting agricultural water-saving technology demon- differences exist in the spatial distribution of WRCC in the strations. Increasing the concentration of urban and rural Dongting Lake Basin. The WRCC of Lishui, Zijiang, and water pollution treatment and accelerating urban and rural West Dongting Lake is relatively high, whereas that of life with the construction and reconstruction of centralized Xiangjiang, Yuanshui, Ouchi River, Hudu River, Songzi sewage treatment facilities will achieve full coverage of the River, and East Dongting Lake is poor. The spatial distri- construction of sewage treatment facilities in cities, key bution of WRCC in the Dongting Lake basin is in the towns, and villages along the lake. order of Lishui > West Dongting Lake > Zijiang > South Dongting Lake > Yuanjiang > Xiangjiang > East Dongting Lake > Songzi River > Ouchi River > Hudu River. ACKNOWLEDGEMENTS The study of the WRCC of the Dongting Lake Basin pro- vides the policy basis for the construction of the Dongting The authors are grateful to two anonymous reviewers from Lake ecological economic zone and the green development the editorial department of the Journal of Water and demonstration zone in the middle reaches of the Yangtze Climate Change, and Jianxin Xiong, professor of Hunan River. Possible policy measures to improve and enhance Institute of Science and Technology, for their suggestions the water carrying capacity of the Dongting Lake Basin about the manuscript. This research is funded by the include:(1) Strengthen the construction of water conser- Natural Science Foundation of Hunan Province, China, vancy engineering facilities in the Three Outlets Basin. grant number 2019JJ40107; the Natural Science Dredge the Ouchi River, Songzi River, and Hudu River. Foundation of Hunan Province, grant number 2018JJ2157. Increase the amount of water flowing into the Three Outlets Basin and reduce the main river channel cut-off time; implement dredging and dredging projects to restore the DATA AVAILABILITY STATEMENT connectivity and water delivery capacity of the channel, and solve the problems of serious siltation. (2) Use ‘source All relevant data are included in the paper or its Supplemen- reduction–process control–end treatment’ to reduce indus- tary Information. trial, agricultural, and domestic pollution emissions in the Dongting Lake Basin. Guide and optimize the industrial layout of the Xiangjiang River; promote the industrial trans- REFERENCES fer of Xiangjiang River to Industry shifted to Yueyang and cities; strengthen the supervision and management Chen, Y. B., Chen, J. H., Li, C. X. & Feng, Z. Y.  Evaluation of large water industry emissions; promote the transform- index system of water resources carrying capacity of ation and upgrading of petrochemical, steel, and non- Shenzhen City based on DPSIR model. Journal of Hydraulic 07 – ferrous metal industries; strengthen the supervision and gov- Engineering ,98 103. Cui, Y., Feng, P., Jin, J. & Liu, L.  Water resources carrying ernance of sewage discharges of papermaking and capacity evaluation and diagnosis based on set pair analysis petrochemical enterprises in the Dongting Lake area, and and improved the entropy weight method. Entropy 20 (5), encourage key enterprises to implement cleanliness. Recy- 359–368. Feng, L. H., Zhang, X. C. & Luo, G. Y.  Application of system cling of industrial water; carry out special rectification of dynamics in analyzing the carrying capacity of water the water environment of Dongting Lake and repair the resources in Yiwu City, China. Mathematics and Computer in water ecological environment of Dongting Lake Basin. Simulation 79, 269–278.

Downloaded from http://iwaponline.com/jwcc/article-pdf/12/5/2125/923265/jwc0122125.pdf by guest on 29 September 2021 2135 Z. Deng et al. | Evaluation of water resources carrying capacity Journal of Water and Climate Change | 12.5 | 2021

Haddeland, I., Heinke, J., Biemans, H., Eisner, S., Florke, M., Song, X. M. & Zhan, C. S.  Assessment of water resources Hanasaki, N., Konzmann, M., Ludwig, F., Masaki, Y., carrying capacity in Tianjin City of China. Water Resource Schewe, J., Stacke, T., Tessler, Z. D., Wada, Y. & Wisser, D. Management 25, 857–873.  Global water resources affected by human interventions Weng, X. R., Long, X., Ye, Y. & Peng, F.  Study on water and climate change. Proceedings of the National Academy of resource carrying capacity of Chongqing City by DPSIR Sciences of the United States of America 111, 3251–3256. coupling model. Journal of Water Resources Research 2, He, G., Xia, Y. L. & Qin, Y.  Evaluation and spatial-temporal 189–201. dynamic change of water resources carrying capacity in the Wu, L., Su, X. L. & Ma, X. Y.  Integrated modeling framework Yangtze River economic belt. Research of Soil and Water for evaluating and predicting the water resources carrying Conservation 26 (1), 287–291. capacity in a continental river basin of Northwest China. Hui, Y. H., Jiang, X. H. & Huang, Q.  Study on the evaluation Cleaner Production 204, 366–379. index system of water resources carrying capacity. Bulletin of Xia, J.  Measurement of water resources security: research and Soil and Water Conservation 1,30–34. challenges of water resources carrying capacity. Haihe Water Li, Y. Z., Liu, Y. & Yan, X. P.  Research on evaluation index Resources 1 (02), 5–7. system of watershed ecological security based on DPSIR Yang, J., Lei, K. & Meng, W.  Assessment of water resources model. Journal of Peking University (Natural Science) carrying capacity for sustainable development based on a 48 (06), 971–981. system dynamics model: a case study of Tieling City, China. Li, G. W., Han, M., Liu, L., Zhao, X. X. & Yu, J.  Evaluation of Water Resource Management 29, 885–899. Zhengzhou City’s water resources carrying capacity based on Yang,Z.,Song,J.,Cheng,D.,Xiu,J.,Li,Q.&Amahad,M.I. principal component analysis. Regional Research and  Comprehensive evaluation and scenario simulation Development 33 (3), 139–142. forthewaterresourcescarryingcapacityinXi’an city, Lin, L. Z., Li, D. & Lin, Z.  Evaluation of water resources China. Journal of Environmental Management 230 (5), carrying capacity in Kubuqi Desert Area based on entropy 221–233. weight and TOPSIS model. Journal of Huazhong Normal Yu, H. Z., Li, L. J. & Li, J. Y.  Evaluation of water resources University (Natural Sciences) 07 (07), 1–15. carrying capacity in the Beijing-Tianjin-Hebei Region based Qu, Y. G. & Fan, S. Y.  Analysis and calculation of water on quantity-quality-water bodies-flow. Resources Science resources carrying capacity in Heihe River Basin and 42 (2), 358–371. countermeasures. China Desert 01,2–9. Yuan, Y. M., Sha, X. J., Liu, Y. Q., Gao, Y. H. & Liu, J.  Rijiberman, M. A. & van de Venb, F. H. M.  Different Application of improved fuzzy comprehensive evaluation approaches to assessment of design and management of method in water resources carrying capacity evaluation. sustainable urban water systems. Environment Impact Water Resources Protection 33 (01), 52–56. Assessment Review 20, 333–345. Zhu, Y. Z. & Wang, G. S.  Assessment of water resources Satty, A. L.  How to make a decision: the analytical hierarchy carrying-capacity with multi-criteria scenario analysis process. European Journal of Operational Research 48,9–26. method: a case study in Zhangye region. Geographical Simanjuntak, E. R. P., Sumabrata, J., Simarmata, H. A. & Zubair, Research 5, 732–740. A.  Analysis of water carrying capacity in cibinong urban Zuo, Q. T. & Zhang, X. Y.  Research on dynamic bearing development. IOP Conference Series: Earth and capacity of water resources under climate change. Journal of Environmental Science 436, 012003. Hydraulic Engineering 46 (04), 387–395.

First received 25 July 2020; accepted in revised form 25 January 2021. Available online 19 March 2021

Downloaded from http://iwaponline.com/jwcc/article-pdf/12/5/2125/923265/jwc0122125.pdf by guest on 29 September 2021