Quantitatively distinguishing the impact of solar photovoltaics programs on vegetation in dryland using satellite imagery

Author:

Xia Zilong12ORCID,Li Yingjie34,Zhang Wei12,Guo Shanchuan12,Zheng Lilin5ORCID,Jia Nan6,Chen Ruishan7,Guo Xiaona7ORCID,Du Peijun12

Affiliation:

1. Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science Nanjing University Nanjing Jiangsu PR China

2. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing Jiangsu PR China

3. Natural Capital Project, Woods Institute for the Environment Stanford University Stanford California USA

4. Doerr School of Sustainability Stanford University Stanford California USA

5. Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences East China Normal University Shanghai PR China

6. Center for Systems Integration and Sustainability, part of College of Agriculture and Natural Resources Michigan State University East Lansing Michigan USA

7. School of Design Shanghai Jiaotong University Shanghai PR China

Abstract

AbstractGlobal drylands are experiencing booming development of centralized photovoltaics (PV), which aims to address the dual challenges posed by climate change and energy transformation. In dryland areas with large‐scale deployment of solar PV infrastructure, vegetation was reported to experience drastic changes. However, the long‐term dynamic changes and driving mechanisms have not been thoroughly studied yet. Quantitatively distinguishing the disturbances of climate change and PV plant deployment on vegetation change is the key to understanding the environmental impact of clean energy development and formulating adaptive ecological recovery measures. To understand this, we selected the Gonghe solar power project in northern China, one of the largest dryland PV plants in the world, as a case study. Specifically, satellite‐derived Normalized Difference Vegetation Index (NDVI) and meteorological data from ground stations were used to analyze the changing patterns of vegetation growth and climatic factors. The relative contributions of climatic factors and PV plant deployment to NDVI change were quantified by multiple regression analysis. The results indicated that vegetation has increased gradually since 2000, with the rate of vegetation recovery doubled during the PV expansion period. From 2013 to 2020, climate change was the main driver of increased vegetation (56%), followed by the expansion of solar PV infrastructures (44%). Vegetation inside PV arrays increased 1.4 times faster than outside, mainly because the PV panels improve the efficiency of rainwater utilization in summer and reduce the negative impact of excessive sunlight in the growing season. In addition, vegetation management practices like grazing can further enhance carbon sequestration and create sustainable livelihood opportunities, achieving sustainable economic, social, and ecological development. The novelty of the study lies in the proposed framework to quantify the impact of solar PV programs on vegetation in dryland allowing easy interpretations of vegetation dynamics under clean energy development and climate change, which provide scientific references for clean energy planning and ecological recovery in arid areas.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Wiley

Subject

Soil Science,General Environmental Science,Development,Environmental Chemistry

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