Exploring the spatial structure and impact factors of water use efficiency in China

Cheng, Zhe; He, Junna; Liu, Yinxi; Zhang, Qianxi; Deng, Yu-Feng

doi:10.1016/j.eiar.2023.107258

Cited by 23 publications

(5 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Firstly, the system's implementation should prioritize key problematic areas and basins, undertaking targeted remediation initiatives. Emphasis should be placed on leveraging new technologies to facilitate comprehensive ecological management of rivers and lakes through a combined approach of technology and management [26]. Secondly, the prevalent issue of insufficient supervision is a significant contributor to recurrent environmental issues in rivers and lakes.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

See 1 more Smart Citation

The Implementation Effect of China’s River and Lake Chief System

Song,

Zhao,

Wang

et al. 2024

Water

Self Cite

View full text Add to dashboard Cite

The river and lake chief system offers a valuable policy toolkit to mitigate the degradation of water ecology, thereby bolstering water resource management for sustainable water development in China. To evaluate the effects of implementation and improve policy, this study took Beijing as a typical case and conducted a quantitative assessment using multidimensional data. The findings suggest that while the river and lake chief system in Beijing is effective and has significantly contributed to the ecological management of rivers and lakes, there are also notable regional disparities and urban–rural divergences. In addition, human activities are the main sources of environmental pollution in rivers and lakes, which should be the focus of the river and lake chief system. The river and lake chief system needs to embed more public participation and cooperative governance. This research aids in better understanding China’s river and lake chief system for both researchers and practitioners, facilitating the advancement of the knowledge body of global water policy and governance.

show abstract

Section: Conclusion and Discussionmentioning

confidence: 99%

“…These cities predominantly reside in the semi-arid and arid regions of north and northwest China. Notably, the water scarcity in northern China has emerged as a significant impediment to the nation's economic development [26]. Consequently, Beijing was chosen as the representative case for this study.…”

Section: Study Areamentioning

confidence: 99%

The Implementation Effect of China’s River and Lake Chief System

Song,

Zhao,

Wang

et al. 2024

Water

Self Cite

View full text Add to dashboard Cite

show abstract

“…The S-SBM model combines the advantages of both the super-efficiency and SBM models. It can re-decompose an effective decision-making unit with an efficiency value of one while bringing the UOs into the model to avoid the loss of effective decision-making unit information [23][24][25]. Therefore, this study adopted the S-SBM model, including UOs, to estimate the AEE of counties in Liaoning Province.…”

Section: The S-sbm Modelmentioning

confidence: 99%

Measurement of Agricultural Eco-Efficiency and Analysis of Its Influencing Factors: Insights from 44 Agricultural Counties in Liaoning Province

Zhang,

Jin

2024

Land

View full text Add to dashboard Cite

Agricultural eco-efficiency (AEE) considers economic and environmental benefits and is a key indicator of green agricultural development. To achieve the multiple goals of improving agricultural production efficiency, reducing agricultural environmental damage, and reducing the input of agricultural resources, this study enriches the case study of agricultural production performance evaluation at the county level by measuring the AEE of 44 agricultural counties in Liaoning Province based on panel data and a super-efficient slacks-based measure model including undesired outputs. A two-way fixed-effects model was used to analyze the impact of agricultural development, macro-environment, and policy support on AEE. We found that the average AEE of the counties in Liaoning Province in 2014, 2016, 2018, and 2020 was 0.716, 0.735, 0.749, and 0.813, respectively, indicating a cumulative improvement rate of 13.55%. The average AEE levels gradually improved during the study period. Notably, the development of AEE among the counties was uneven. AEE was distributed in a “block-like” manner, and its local correlation presents a phenomenon of “small agglomeration and large dispersion”. In addition, the level of the agricultural economy, industrialization, and urbanization significantly promoted the improvement of AEE, and the promoting effects varied between different income levels and regions. Therefore, Liaoning Province needs to improve the AEE of each county according to local conditions and narrow the differences in AEE between counties. To continuously improve the level of rural economic development, lead the development of agricultural modernization with new urbanization, and comprehensively improve the overall AEE of counties. The research results are of guiding significance for deepening the study of AEE and can provide decision-making support for optimizing the mode of agricultural production and promoting the green development of regional agriculture.

show abstract

“…Ma et al [31] concluded that the technological progress has a positive impact on WRUE, whereas water costs and environmental pollution reduced the efficiency. For the factors affecting agricultural WRUE, researchers have focused on resource endowment [32], industrial structure [33], soil type [34], water conservancy facilities [35], and the agricultural planting structure [36]. The driving factors of industrial WRUE have been studied.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of the Driving Factors of Water Resources Use Efficiency in China’s Agricultural and Industrial Sectors

Li,

Huang,

Zhou

et al. 2024

Water

View full text Add to dashboard Cite

The efficient use of water resources has become an important topic in China. Research on measurement and driving factors is the foundation for improving water resources use efficiency (WRUE). In this paper, the super-efficiency slacks-based measure (SE-SBM) model is used to measure the WRUE of China from 2005 to 2021. The agricultural carbon emissions and chemical oxygen demand (COD) in industrial wastes are taken as undesirable by-products. The driving factors of WRUE are discussed with use of the Tobit regression model. The results show that China’s agricultural WRUE ranges from 1.185 in Jilin to 0.687 in Ningxia. In the industrial sector, the WRUE ranges from 1.399 in Beijing to Jiangxi 0.212. The economic structure and development level, water resources endowment, government influence and environmental regulation, agricultural planting scale and urbanization rate have impacts on WRUE. Precautionary measures need to be applied to prevent inefficient WRUE caused by the declining share of the industrial sector in the economic structure. More financial support should be focused on water-saving irrigation in agriculture and energy and resource efficiency in industry. The organizational structure and technological advantages of urbanization should also be emphasized in efforts to improve water efficiency.

show abstract

Exploring the spatial structure and impact factors of water use efficiency in China

Cited by 23 publications

References 50 publications

The Implementation Effect of China’s River and Lake Chief System

The Implementation Effect of China’s River and Lake Chief System

Measurement of Agricultural Eco-Efficiency and Analysis of Its Influencing Factors: Insights from 44 Agricultural Counties in Liaoning Province

A Comparative Study of the Driving Factors of Water Resources Use Efficiency in China’s Agricultural and Industrial Sectors

Contact Info

Product

Resources

About