Detecting farmland green production efficiency considering Sustainable Development Goals (SDGs) in the Yellow River Basin: Dynamics, drivers, and challenges

Abstract

Pursuing sustainable growth of Farmland Green Production Efficiency (FGPE) is crucial for achieving multiple Sustainable Development Goals (SDGs), particularly SDG2 (Zero Hunger), SDG 12 (Responsible Consumption and Production), SDG13 (Climate Action), and SDG 15 (Life on Land) in ecologically fragile basins. However, the dynamics, drivers, and challenges of FGPE remain underexplored within the SDGs framework, especially at finer spatial scale and across coupled “society-economy-policy-climate” (SEPC) drivers. This study develops an FGPE assessment framework through SDGs lens, utilizing “elements-processes-functions-drivers” paradigm and data from 447 counties in the Yellow River Basin (YRB) from 2000 to 2022. We apply super-efficiency Slacks-Based Measure and Malmquist-Luenberger (SBM-ML), spatial correlation analysis, and geographically and temporally weighted regression models to assess FGPE growth challenges. Results reveal a “U-shaped” trend in the number of high-FGPE counties, with a rapid increase after 2016. Specifically, FGPE across the YRB increased by 97.6 % from 2000 to 2022, though spatial correlation declined by 44.7 %, indicating weakening spatial spillover effect. Despite the overall progress, the YRB still faces multiple challenges, including uneven regional development, weakening spatial correlation, climate sensitivity, economic structural shift, and weak policy effect. The findings highlight that FGPE improvement align with key SDGs targets, including enhancing food security (SDG 2), promoting sustainable production (SDG 12), increasing climate resilience (SDG 13), and conserving land ecosystems (SDG 15). Region-specific strategies are recommended: enhancing climate resilience and ecological conservation in the upper reaches, promoting technological diffusion via urban-industrial transformation in the middle reaches, and advancing green agricultural technologies with more local financial support in the lower reaches.

Keywords

Farmland Green Production Efficiency (FGPE) / Sustainable Development Goals (SDGs) / Spatial-temporal evolution dynamics / Society-economy-policy-climate (SEPC) coupled drivers / Key challenges / Yellow River Basin (YRB)

Data availability statement

Data are available upon request from the authors.

CRediT authorship contribution statement

Chaoqing Chai: Writing - review & editing, Writing - original draft, Visualization, Validation, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Yuanyuan Li: Writing - review & editing, Writing - original draft, Visualization, Validation, Software, Formal analysis, Data curation, Conceptualization. Ronghao Wen: Software, Methodology, Investigation, Formal analysis, Data curation. Hui Zhang: Writing - review & editing, Software, Formal analysis, Conceptualization. Bangbang Zhang: Writing - review & editing, Validation, Supervision, Resources, Project administration, Investigation, Funding acquisition, Conceptualization. Peixue Xing: Validation, Investigation, Formal analysis, Data curation. Ying Sun: Validation, Investigation, Formal analysis, Data curation. Huadong Zhu: Validation, Investigation, Formal analysis, Data curation. Guanghui Hou: Validation, Investigation, Formal analysis, Data curation. Haoyang Wang: Investigation, Data curation. Wenhao Niu: Investigation, Data curation. Weiwei Zheng: Funding acquisition. Xiangbin Kong: Resources, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grants No. 42171267 and 42201291), the Innovation Capability Support Program of Shaanxi in China - Youth Science and Technology Star Project (Grant No. 2024ZC-KJXX-052), the Social Science Foundation of Shaanxi Province (Grant No. 2023R032), and the Northwest A&F University Doctoral Candidates’ Independent Innovation Research Project Funding (Grant No. 2025KYCXZ28).

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.geosus.2026.100418.

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