Work

Comparison and spatial heterogeneity of eco-efficiency in two major river basins of China: nonlinear mechanism analysis based on spatial machine learning

Year: 2026

Type: article

Abstract: Achieving a synergy between economic expansion and environmental conservation across major watersheds is vital for China’s sustainable trajectory. This study proposes a unified cross-basin framework, using a three-stage super-efficiency Slack-Based Measure (SE-SBM) and Global Malmquist-Luenberger (GML) index to assess the static and dynamic eco-efficiency (EE) of the Yellow River Basin (YRB) and the Yangtze River Economic Belt (YREB). For the analysis of spatiotemporal evolution, kernel density estimation (KDE) and the Dagum Gini coefficient (DGC) are implemented. A Geographically Weighted Random Forest (GWRF) model is introduced to characterize nonlinear associations and spatial heterogeneity among the factors associated with EE. Results reveal that: (1) The adjusted EE of the YRB declined, but it remained superior overall compared to the slightly rising YREB. In terms of space, the YRB shows a stepwise decline, while the YREB presents a concave shape with a lower center. (2) The technical progress (TC) is the primary contributor to GML-based EE growth in the two major river basins. The GWRF model uncovers significant nonlinear threshold effects (e.g., urbanization and environmental regulations) and U-shaped evolutionary characteristics (e.g., industrial structure and financial development). Local feature-importance patterns further indicate distinct spatial structures: a regulation-oriented constraint pattern in the YRB and a market-oriented radiation pattern in the YREB. This multi-method integration provides a novel theoretical perspective and a solid basis for decision-making in formulating cross-basin collaborative policies.

Source: Frontiers in Environmental Science

DOI: 10.3389/fenvs.2026.1937303

Authors: Panpan Liu, Dandan Dong, Fei Zhao, Jing Meng, Guoqu Deng

Institution: Henan University of Science and Technology

Language: English

Topic: Efficiency Analysis Using DEA

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDGs: Clean water and sanitation, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,801