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Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
The development suitability analysis for the Qinghai-Xizang-Plateau: Condition, quality, and risk
Xiaodi Ma1, Chonghao Liu1, Tianjiao Li1
1Chinese Academy of Geological Sciences, Beijing, 100037, China; State Key Laboratory of Deep Earth and Mineral Exploration, Chinese Academy of Geologcial Sciences, Beijing, 100037, China.
Abstract:
The Qinghai-Xizang Plateau (QXP) is a globally unique ecological barrier and a vast repository of natural resources. However, its harsh ecological environment presents a critical challenge in balancing environmental protection with sustainable resource development and economic growth. To fill this gap, this study develops a development suitability index system and evaluation model that includes three key dimensions of development condition, quality, and risk. This approach provides a comprehensive understanding of the spatial distribution patterns of development suitability and identifies the dominant influencing factors. Development suitability on the QXP exhibits significant spatial variability, with higher suitability concentrated in the eastern region, particularly within economic radiation zones centered on provincial capitals. This pattern is primarily attributed to better-developed infrastructure and more intensive human economic activities. Altitude has a unique impact on development suitability, and extreme weather conditions in high-altitude areas pose significant challenges to infrastructure construction, driving up development costs and prolonging project timelines. There is a positive correlation between green development and development suitability, with green innovation and resource recycling significantly enhancing development suitability. Economic growth promotes environmental protection by reducing poverty and advancing environmental protection technologies. This study provides new scientific insights for sustainable development in high-altitude regions and offers a reference for optimizing future policies under the framework of stringent environmental protection requirements.
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