Resources and Environment in the Yangtze Basin
Resources and Environment in the Yangtze Basin (issn: 10048227) is a scopus indexed journal since 1996 upto now. This journal is sponsored by Bureau of Science and Technology for Resources and Environment of Chinese Academy of Sciences (CAS) and the Wuhan Documentation and Information Center of CAS and published by Science Press. It is committed to publishing high-quality, original research on the all topics of environmental science and environmental engineering.
Aim and Scope
Resources and Environment in the Yangtze Basin (ISSN: 10048227)
Environmental Science,
Environmental Engineering,
Nature and Landscape Conservation,
Water Science, resource and Technology,
Ecology, Management, Monitoring, Policy and Law.
Submission Deadline
Volume -
42
, Issue
01
20 Jan 2026
Volume -
not available
, Issue
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Resources and Environment in the Yangtze Basin
The Impact of Socialized Service Supply on Economic Benefits and Green Production of Large-scale Farmers
Farmland scale management (FSM) is an essential strategy to establish an appropriate management scale for agricultural production, enhance smallholder farmer production efficiency, and improve the utilization rate of farmland. The Chinese government promotes farmland transfer as a tool to establish modern and moderate-scale agriculture. However, farmers remain unable to afford agricultural services and inputs required for appropriate FSM after farmland is transferred-in. This paper aims to examine the impact of agricultural socialized services (ASSs) on the FSM behavior of smallholder farme
Carbon Emission Differences, Influence Mechanisms and Carbon Peak Projections in Yangtze River Delta Region
The Yangtze River Delta is the most populous and economically active region in China. Studying the reduction in CO2 emissions in this region is of great significance in achieving the goal of “peak carbon and carbon neutrality” in China. In this study, the Tapio decoupling and extended STIRPAT models were used to study the differences in provincial CO2 emissions characteristics and influencing factors in the Yangtze River Delta from 2001 to 2019. The results show that the growth rate of CO2 emissions was slower than that of economic development, which means that CO2 emissions and
Spatial and Temporal Distribution and Influencing Factors of Four Major Chinese Carps Larvae Fish Resources in Lower Reaches of Yangtze River
Hydrodynamic characteristics of spawning grounds are important factors affecting the spawning of four major Chinese carps (Mylopharyngodon piceus, Ctenopharyngodon idella, Hypophthalmichthys molitrix, and Aristichthys nobilis). To investigate the relationship between the preferred hydrodynamic characteristics of spawning sites and the response of fish spawning behavior, we monitored the flow field of spawning sites during ecological operation of the Three Gorges Dam (i.e., man-made flood regulation) in 2014 and 2015. We used the data to explore the correlation between vort
Network Characteristics and Influencing Factors of Spatial Correlation of Carbon Emissions in China
Railway carbon emissions reduction is of great significance. In this study, carbon emission efficiency in railway transportation in China’s 31 provinces is measured for 2006–2019 based on an unexpected output slack-based measure (SBM) model. A gravity matrix of the spatial correlation network for carbon emission efficiency is constructed using the modified gravity model, the spatial network structure is explored using social network analysis, and the factors influencing the spatial network are analyzed using the quadratic assignment procedure (QAP) model. Based on the results, s
Remote Sensing Assessment of the Water Conservation Function of Ecological System in Dabieshan Mountain Area of Hubei Province
Water conservation is an essential indicator of the hydrological regulation capacity of terrestrial ecosystems. At the regional scale, the water conservation capacity of an ecosystem is typically assessed using the water balance model (WBM). However, the estimation of the runoff depth relies heavily on rainfall data and the ecosystem runoff coefficient look-up table, which introduces uncertainties in the assessment results. To address this issue, this study constructed a new method for quantifying the spatiotemporal distribution pattern of runoff depth based on the ecosystem type and region