Determining the Regional Carrying Capacity of the Wuhan City Circle Based on the Improved Ecological Footprint Method

Xiao, Yi; Ou, Yuqi; Qu, Xiaobo; Zhang, Liping; Zhang, Xiang; Xia, Jun

doi:10.1111/1752-1688.12938

Cited by 7 publications

(4 citation statements)

References 42 publications

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“…Wang et al [17] analyzed the changing trend of water resource carrying capacity in Changchun City based on system dynamics and the improved fuzzy comprehensive evaluation method. Xiao et al [18] calculated the water resource carrying capacity of Wuhan according to a modified ecological footprint model. Jia et al [19] analyzed the change in the water resource carrying capacity of Zhengzhou City based on the DPSIR-TOPSIS model.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Carrying Capacity and Obstacle Factors of Water Resources in Longnan City, China, Based on Driving–Pressure–State–Response and Technique for Order Preference by Similarity to an Ideal Solution Models

Dang

Zhao

Kang

et al. 2023

Water

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Measuring the carrying capacity of water resources and identifying obstacle factors are critical prerequisites for the rational allocation of regional water resources and the high-quality development of economic society. This study took Longnan City, a typical city in northwest China with abundant water resources but an underdeveloped economy, as the research object. Based on the DPSR (Driving–Pressure–State–Response), an evaluation indicator system was constructed. TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) and an obstacle model were used to calculate the water resource carrying capacity and main obstacle factors of Longnan City from 2009 to 2019. The results showed that the carrying capacity of water resources in Longnan City had steadily improved, and the comprehensive closeness had increased from 0.44 (2009) to 0.60 (2019). From the perspective of the ruler layer, the carrying capacity of the driving force system increased from 0.05 in 2009 to 1.00 in 2019. The capacity of the state system increased during the change, with the highest value (0.85) appearing in 2013 and the lowest value appearing in 2016. All subsystems, except the pressure system, had a load-carrying capacity of 0.60 or more in 2019. The utilization of unconventional water resources, the proportion of eco-environmental water use, the volume of wastewater discharge, and the per capita urban daily water consumption are the primary factors affecting the water resource carrying capacity of Longnan City. Developing unconventional water sources, improving sewage treatment technology, promoting efficient water-saving technology, and strengthening environmental protection is the key to improving the water resources carrying capacity of Longnan City. This research provides the basis for enhancing the carrying capacity of water resources and sustainable urban development in Longnan City and other cities in China and water scarcity cities in other countries.

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Section: Introductionmentioning

confidence: 99%

Analysis of Carrying Capacity and Obstacle Factors of Water Resources in Longnan City, China, Based on Driving–Pressure–State–Response and Technique for Order Preference by Similarity to an Ideal Solution Models

Dang

Zhao

Kang

et al. 2023

Water

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“…The Shannon-Weaver formula was used to calculate the diversity index of the ecological footprint by introducing the economic system development capacity formula into the ecosystem, and different land types were used as indicators to measure the diversity of the ecological and economic system [17], calculated as follows:…”

Section: Ecological Diversity Index and Index Of Development Capacity...mentioning

confidence: 99%

Exploration of Rural Agroforestry–Pastoral Complex Systems Based on Ecological Footprint*—Taking Zhagana in Yiwa Township as an Example

Zhang

Xie

2022

Sustainability

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Since 2010, with the rapid development of tourism in Zhagana, Yiwa township, problems with the agroforestry–pastoral complex system and economic development in Zhagana have come to the fore. In order to investigate the sustainability of the agroforestry–pastoral complex system, the ecological footprint model was used to analyse the sustainable development of the ecosystem in Yiwa township from 2005 to 2020 and the ecological security changes in Zhagana from 2010 to 2020 through examining the ecological footprint intensity, the ecosystem diversity index and the ecosystem development capacity index. The results of the study show that the per capita ecological footprint of Yiwa township showed an overall decreasing trend between 2005 and 2020, and the per capita ecological deficit also showed a decreasing trend. Forest land was the most important component of the ecological footprint per capita, and grassland was the most important component of the ecological carrying capacity per capita. The footprint depth tended to increase and then decrease, and the footprint width tended to decrease, with a gentle increase from 2010. The ecological pressure index showed an overall decreasing trend, and the ecological sustainability index showed a sudden upward fluctuation after 2016. Overall, the ecological economy of Zhagana has some capacity for development, but there is a high level of ecological pressure.

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“…At present, the research mainly focuses on the improvement of the ECC model [20][21][22] and the analysis of spatiotemporal changes and driving forces [23][24][25]. In addition, the research on ECC has expanded from the field of ecology to other fields as well [26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Ecological Carrying Capacity and Identification of Its Influencing Factors Based on Remote Sensing and Geographic Information System: A Case Study of the Yellow River Basin in Shaanxi

Zhu

Mei

et al. 2022

Land

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Ecological carrying capacity (ECC), which requires simple scientific evaluation methods, is an important evaluation index for assessing the sustainability of ecosystems. We integrate an innovative research method. Geographic information systems (GIS) and remote sensing (RS) were used to evaluate the ECC of the Yellow River Basin in Shaanxi (YRBS) and to identify the underlying factors that influence it. A calculation method that combines RS and GIS data to estimate ECC based on net primary productivity (NPP) was established. The Carnegie–Ames–Stanford approach model was applied to estimate NPP. The NPP of each land type was used as an indicator to determine the yield factors. The ECC of the watershed was calculated with the carrying capacities of each land-use type. The geographical detector model was used to study the influencing factors of ECC, which provides a scientific basis for the formulation of ecological management policies in YRBS. The results show that from 2000 to 2010, it first decreased by 45.46%, and then increased by 37.06% in 2020, an overall decrease of 13.49 × 105 wha in 20 years. Precipitation is the dominant factor that affects ECC, while the impact of human activities on ECC was significantly enhanced during the study period. The developed method based on RS data serves as a reference for ecological evaluation in other similar regions.

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Determining the Regional Carrying Capacity of the Wuhan City Circle Based on the Improved Ecological Footprint Method

Cited by 7 publications

References 42 publications

Analysis of Carrying Capacity and Obstacle Factors of Water Resources in Longnan City, China, Based on Driving–Pressure–State–Response and Technique for Order Preference by Similarity to an Ideal Solution Models

Analysis of Carrying Capacity and Obstacle Factors of Water Resources in Longnan City, China, Based on Driving–Pressure–State–Response and Technique for Order Preference by Similarity to an Ideal Solution Models

Exploration of Rural Agroforestry–Pastoral Complex Systems Based on Ecological Footprint*—Taking Zhagana in Yiwa Township as an Example

Evaluation of Ecological Carrying Capacity and Identification of Its Influencing Factors Based on Remote Sensing and Geographic Information System: A Case Study of the Yellow River Basin in Shaanxi

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