Spatial Association Network and Driving Factors of Agricultural Eco-Efficiency in the Hanjiang River Basin, China

Abstract

Reducing agricultural emissions and promoting carbon sequestration are vital for China to achieve its dual carbon goals. Achieving the green transformation of agricultural watersheds requires a thorough understanding of the internal transmission relationships within the watersheds and the underlying spatial correlation structures. This paper used the SBM-3E model to calculate the agricultural ecological efficiency of 17 prefecture-level cities in the Hanjiang River Basin (HRB) from 2010 to 2020, taking agricultural carbon emissions and a comprehensive non-point source pollution index as the unexpected output. The Gravity model and social network analysis methods were used to analyze the evolution characteristics of the network structure of agricultural ecological efficiency, and the secondary assignment procedure method was used to identify the driving factors from the planting structure, water use structure, and resource endowment. First, from 2010 to 2020, the overall agricultural ecological efficiency in the HRB demonstrates a declining trend, with efficiency values of 12.15, 9.40, and 6.67 in the upper, middle, and lower reaches, respectively. Second, the spatial correlation network density of agricultural ecological efficiency in the HRB is 0.17, with a network efficiency of 0.89. The correlation among units within the basin is relatively low, but stability is high. Moreover, the individual network spillover absorption capacity exhibits heterogeneity, and the status of each subject within the watershed follows a “core-edge” structure. Third, total water consumption and corn cultivation have a positive impact on the agricultural ecological efficiency network in the HRB, whereas agricultural water use and rice cultivation negatively influence the network. We propose policy recommendations to facilitate the advancement of green development in China’s agricultural watersheds and the achievement of the dual carbon goals.

Spatial Network and Influencing Factors of Green Water Use Efficiency in the YREB: Considering carbon emissions and pollution indicators

“…On the one hand, at the level of research scope, there are few studies that take into account the unwanted results brought by carbon emission and pollution indexes in measuring water resource efficiency, especially the lack of separate accounting for the three major water use sectors, namely agriculture, industry, and domestic water use. On the other hand, the spatial econometrics of water efficiency is limited by the research methodology, which only assesses geographical proximity and describes agglomeration characteristics, and cannot observe the dynamic correlation of efficiency values in space (Huang et al, 2021;Zhang et al, 2023). More studies focus on the spatial quantification of non-spatial data, while ignoring the network structure formed by the flow of capital, technology, labor and other factors in the process of spatial and temporal evolution, and are unable to depict the evolution of the spatial correlation network and the analysis of its driving factors.…”

“…During this period, the two homogeneous relationship circles were significantly affected, and the structure of the efficiency network changed from "inverted tower" to "flat", which indicates that the structural relationship of the efficiency network in equilibrium has increased, and the interaction capacity and degree of connection between provinces have deepened. The governance of the "coreperiphery" structure (Zhang et al, 2023) is gradually weakened to form a synergistic development, and the structure of the green water use efficiency network shifted from a balanced synergistic relationship to a "core-periphery" structure after 2010, which is not a reversion to the structure of 2000-2004, but may be due to the closer links between upstream provinces and the middle and lower reaches of the network, which have gradually reduced the fragmented links.…”