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To clarify the impact of photovoltaic construction in arid areas on the fragile Gobi ecosystem, taking the photovoltaic Gobi base in Hainan Prefecture, Qinghai Province as the research object, based on continuous observation data from February 2023 to February 2024, combined with random forest models and other methods, this study explores the microclimate regulation and the response of carbon and water fluxes as well as the driving mechanism of the carbon cycle. The results show that photovoltaic panels regulate soil temperature in a “peak shaving and valley filling” manner, increasing the moisture content of shallow soil during the growing season. The ecosystem has a stable carbon sink function. NEE has the strongest carbon absorption in August, Re shows a single-peak pattern, and GPP has a “U” shaped pattern. PAR and Rn are the core driving factors of carbon and Carbon–water flux. The multiple linear regression model can explain 64.37% of the NEE variation, providing support for the ecological sustainable management of photovoltaic power stations in arid areas.

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Research on Ecological Response and Carbon Budget Balance Under Microclimate Regulation of Photovoltaic Gobi Base in Hainan Prefecture, Qinghai Province

  • 会议论文

  • 发表日期：

    2026年

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  • Yaning Liu,
  • Quan Quan,
  • Deli Ye,
  • Xiaomei Kou,
  • Qi Li

摘要

To clarify the impact of photovoltaic construction in arid areas on the fragile Gobi ecosystem, taking the photovoltaic Gobi base in Hainan Prefecture, Qinghai Province as the research object, based on continuous observation data from February 2023 to February 2024, combined with random forest models and other methods, this study explores the microclimate regulation and the response of carbon and water fluxes as well as the driving mechanism of the carbon cycle. The results show that photovoltaic panels regulate soil temperature in a “peak shaving and valley filling” manner, increasing the moisture content of shallow soil during the growing season. The ecosystem has a stable carbon sink function. NEE has the strongest carbon absorption in August, Re shows a single-peak pattern, and GPP has a “U” shaped pattern. PAR and Rn are the core driving factors of carbon and Carbon–water flux. The multiple linear regression model can explain 64.37% of the NEE variation, providing support for the ecological sustainable management of photovoltaic power stations in arid areas.