An Improved Method for Evaluating Regional Resource Carrying Capacities: A Case Study of the Tarim River Basin in Arid China
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Xinjiang Laboratory of Lake Environment and Resources in Arid Zone, Research Centre for Urban Development of the Silk Road Economic Belt, College of Geography Science and Tourism, Xinjiang Normal University, Urumqi 830054, Xinjiang, China
Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou 510070, China
College of Economic and Management, Huanghuai University, Zhumadian 463000, China
Submission date: 2018-03-14
Final revision date: 2018-05-08
Acceptance date: 2018-05-15
Online publication date: 2019-01-09
Publication date: 2019-03-01
Corresponding author
Changjian Wang   

Guangzhou Institute of Geography, Guangzhou, 510070 Guangzhou, China
Pol. J. Environ. Stud. 2019;28(4):2415-2428
Resource endowment and resource carrying capacity (RCC) are the most important cornerstones of regional sustainable development. By applying a newly established RCC method, namely, the relative resources carrying capacity (RRCC) method, we evaluated the RCC in the Tarim River basin (TRB) in arid China in Xinjiang during 2000-2011. Research results show that the relative resources carrying capacity can be effectively served as indicators of regional resources sustainable development status. Taking Xinjiang as the reference region, the TRB can be characterized as an area with an overloaded population and surplus economy during the whole research period, where land resources are relative advantage resources carrying the regional population growth and economic development and water resources are relative disadvantage resources restricting rapid regional development. Taking TRB as the reference region, 42 counties and cities in TRB performed significant temporal and spatial disparities according to the RRCC based on population and economic perspectives. Based on the spatial-temporal evolution of RRCC, 42 counties and cities in TRB were classified into four matching modes (A, B, C, and D). The spatial-temporal evolution characteristics and mechanisms about the 42 prefectures and cities were examined, and the suitable development strategies for every different mode were recommended.
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