Comparative analysis of water resources carrying capacity based on principal component analysis in Beijing-Tianjin-Hebei region from the perspective of urbanization

Liu, Chuanfeng; Wang, Ruimei; Zhang, Xiling; Cheng, Changlin; Song, Huan; Hu, Yu

doi:10.1063/1.4971934

Cited by 7 publications

(6 citation statements)

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“…The principal component scores were calculated with the variance contribution rate as the weight, and the composite score, F, was obtained afterward [42]. The comprehensive scores of monitoring stations in the Xin'anjiang River are shown in Table 3.…”

Section: Composite Scorementioning

confidence: 99%

Using Principal Components Analysis and IDW Interpolation to Determine Spatial and Temporal Changes of Surface Water Quality of Xin’anjiang River in Huangshan, China

Yang

Zhao

Wang

et al. 2020

IJERPH

213

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This study was aimed at assessing the spatial and temporal distribution of surface water quality variables of the Xin’anjiang River (Huangshan). For this purpose, 960 water samples were collected monthly along the Xin’anjiang River from 2008 to 2017. Twenty-four water quality indicators, according to the environmental quality standards for surface water (GB 3838-2002), were detected to evaluate the water quality of the Xin’anjiang River over the past 10 years. Principal component analysis (PCA) was used to comprehensively evaluate the water quality across eight monitoring stations and analyze the sources of water pollution. The results showed that all samples could be analyzed by three main components, which accounted for 87.24% of the total variance. PCA technology identified important water quality parameters and revealed that nutrient pollution and organic pollution are major latent factors which influence the water quality of Xin’anjiang River. It also showed that agricultural activities, erosion, domestic, and industrial discharges are fundamental causes of water pollution in the study area. It is of great significance for water quality safety management and pollution control of the Xin’anjiang River. Meanwhile, the inverse distance weighted (IDW) method was used to interpolate the PCA comprehensive score. Based on this, the temporal and spatial structure and changing characteristics of water quality in the Xin’anjiang River were analyzed. We found that the overall water quality of Xin’anjiang River (Huangshan) was stable from 2008 to 2017, but the pollution of the Pukou sampling point was of great concern. The results of IDW helped us to identify key areas requiring control in the Xin’anjiang River, which pointed the way for further delicacy management of the river. This study proved that the combination of PCA and IDW interpolation is an effective tool for determining surface water quality. It was of great significance for the control of water pollution in Xin’anjiang River and the reduction of eutrophication pressure in Thousand Island Lake.

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Section: Composite Scorementioning

confidence: 99%

Using Principal Components Analysis and IDW Interpolation to Determine Spatial and Temporal Changes of Surface Water Quality of Xin’anjiang River in Huangshan, China

Yang

Zhao

Wang

et al. 2020

IJERPH

213

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“…Most of the indicators are based on the pressure-state-response (PSR) framework [36], less on indicators for scientific and technological innovation. Measurement is mainly performed using principal component analysis [37], improved analytic hierarchy process [38], fuzzy comprehensive evaluation [39,40], grey relational analysis [41], data envelopment analysis (DEA) [42], system dynamics [6,43], technique for order preference by similarity to ideal solution (TOPSIS) [44,35] and back propagation (BP) neural network [45]. However, there are few ways to measure the degree of interaction between subsystems in the water resources sustainability system, and most scholars have undertaken their research on water resources in the Yangtze River Economic Belt from nine provinces and two municipalities, while the research from the urban level is quite rare in this regard.…”

Section: Literature Reviewmentioning

confidence: 99%

Urban Water Inclusive Sustainability: Evidence from 38 Cities in the Yangtze River Economic Belt in China

Gao

Guo

2021

Sustainability

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The ecological environment of urban water resources in the Yangtze River Economic Belt (YREB) is in a huge challenge; yet, while myriad studies have investigated the carrying capacity or sustainable utilization of Chinese water resources, few to none have looked at the inclusive sustainable development of water resources. In this article, a new concept of urban water inclusive sustainability (UWIS) is firstly proposed, and the conceptual framework of ASFII and a five-dimensional indicator system are developed, integrating availability, sustainability, friendliness, inclusiveness and innovation. The panel data of 38 cities in the YREB are adopted from 2008 to 2018 to measure UWIS and five development indexes by the TOPSIS (technique for order preference by similarity to ideal solution) and entropy method. Moreover, the characteristics of the temporal–spatial evolution of the overall system and subsystems coupling coordination are described using the coupling coordination degree model. Key factors that hinder UWIS are identified through the obstacle degree model. The results indicate that the overall UWIS showed a gradual upward trend at a lower to medium level from 2008 to 2018 and a friendliness > sustainability > inclusiveness > innovation > availability index. The UWIS from high to low is YRDUA (Yangtze River Delta urban agglomeration), MRYRUA (middle reaches of the Yangtze River urban agglomeration) and CCUA (Chengdu–Chongqing urban agglomeration). The 38 cities are in low-level coordination, and their temporal characteristics show a trend of economy > science and technology > water resources > environment > societal system, YRDUA > MRYRUA > CCUA. The spatial differentiation is manifested as high in the east and low in the west. The main obstacles come from 12 factors, such as the water resources utilization rate, etc. The findings of our study will be a scientific reference for the Chinese government to track UWIS and ensure urban water resources security in the YREB.

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“…The use and innovation of evaluation methods is an important part of water resources evaluation, and in recent years many scholars have used different methods of water resources evaluation to explore the extent of development and sustainable use of regional water resources [20]. Liu, Chuanfeng et al used principal component analysis to comparatively assess the carrying capacity of water resources in Hebei, Tianjin and Beijing [21]. Abadi used a system dynamics approach and the Vensim model to model the water resource system downstream of the Karkheh dam in Khuzestan province.…”

Section: Introductionmentioning

confidence: 99%

Index System of Water Resources Development and Utilization Level Based on Water-Saving Society

Dai

Tang

et al. 2022

Water

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The notion of a ‘Water-saving society’ may help China achieve sustainable development and high-quality development. In this paper, the concept of water resources development and utilization level is discussed from the perspective of a water-saving society, and an evaluation index system including 33 indicators is constructed. This paper takes the evaluation of water resources development and utilization level of Jingyu County from 2009 to 2018 as an example to verify the rationality of the indicator system of this study. Additionally, by changing the sensitivity analysis method of indicator weights, the indicators with greater influence on the evaluation results are screened to reduce the uncertainty of too many indicators and low correlation. The results show that the evaluation value of water resources development and utilization level in Jingyu County from 2009 to 2018 was improved from V to II, and the improvement of industrial and domestic water use efficiency and effectiveness improved the water resource problems in the study area. Sensitivity analysis showed that the sensitivity parameters are the degree of water resources development and utilization (8.7%), water consumption per CNY 10,000 of industrial value added (11.2%), water consumption per CNY 10,000 of GDP (9.3%), leakage rate of the urban water supply network (8.4%), per capita water resources (10.1%), per capita COD emissions (9.3%) and urbanization rate (8.2%).

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Comparative analysis of water resources carrying capacity based on principal component analysis in Beijing-Tianjin-Hebei region from the perspective of urbanization

Cited by 7 publications

References 0 publications

Using Principal Components Analysis and IDW Interpolation to Determine Spatial and Temporal Changes of Surface Water Quality of Xin’anjiang River in Huangshan, China

Using Principal Components Analysis and IDW Interpolation to Determine Spatial and Temporal Changes of Surface Water Quality of Xin’anjiang River in Huangshan, China

Urban Water Inclusive Sustainability: Evidence from 38 Cities in the Yangtze River Economic Belt in China

Index System of Water Resources Development and Utilization Level Based on Water-Saving Society

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