As an important ecological barrier and economic belt in China, the sustainable development of the Yellow River Basin (YRB) is of great significance to national ecological security and regional economic balance. Based on the coupled and coordinated development analysis of the water–soil–energy–carbon (W-L-E-C) system in the provinces of the Yellow River Basin from 2002 to 2022, this study systematically analyzed the interaction relationship among the various factors through WLECNI index assessment, factor identification, and driving factor exploration. Thus, it fully reveals the spatiotemporal evolution law of regional coordinated development and its internal driving mechanism. It is found that the coordinated development of the W-L-E-C system in different provinces of the Yellow River Basin presents significant spatiotemporal differentiation, and its evolution process is influenced by multiple factors. It is found that the coordination of the YRB presents a significant spatial difference, and Inner Mongolia and Shaanxi, as high coordination areas, have achieved significant improvement in coordination, through ecological restoration and clean energy replacement, arable land intensification, and industrial water-saving technology, respectively. Shandong, Henan, and Shanxi in the middle coordination zone have made some achievements in industrial greening and water-saving technology promotion, but they are still restricted by industrial carbon emissions and land resource pressure. The Ningxia and Gansu regions with low coordination are slow to improve their coordination due to water resource overload and inefficient energy utilization. Barrier factor analysis shows that the water resources utilization rate (W4), impervious area (L4), energy consumption per unit GDP (E1), and carbon emissions from energy consumption (C3) are the core factors restricting coordination. Among them, the water quality compliance rate (W5) of Shanxi and Henan is very low, and the impervious area (L4) of Shandong is a prominent problem. The interaction analysis of the driving factors showed that there were significant interactions between water resource use and ecological protection (W-E), land resource and energy use (L-E), and carbon emissions and ecosystem (C-E). Inner Mongolia, Shaanxi, and Shandong achieved coordinated improvement through “scenic energy + ecological restoration”, cultivated land protection, and industrial greening. Shanxi, Henan, and Ningxia are constrained by the “W-L-E-C” complex obstacles. In the future, the Yellow River Basin should implement the following zoning control strategy: for the areas with high coordination, it should focus on consolidating the synergistic advantages of ecological protection and energy development; water-saving technology and energy consumption reduction measures should be promoted in the middle coordination area. In the low coordination area, efforts should be made to solve the problem of resource overload, and the current situation of low resource utilization efficiency should be improved by improving the utilization rate of recycled water and applying photovoltaic sand control technology. This differentiated governance plan will effectively enhance the level of coordinated development across the basin. The research results provide a decision-making framework of “zoning regulation, system optimization and dynamic monitoring” for the sustainable development of the YRB, and provide a scientific basis for achieving high-quality development of the basin.

Straw return (SR) and biochar application (BA) are widely used organic amendments with potential to improve wheat productivity and resource-use efficiency. However, their responses across environmental and field-management conditions remain poorly synthesized. We conducted a global multilevel meta-analysis of 2,242 yield, 1,239 water productivity (WP), and 1,988 partial factor productivity of nitrogen (PFPN) observation pairs from 385 publications. SR increased wheat yield, WP, and PFPN by 8.31%, 8.76%, and 8.28%, respectively, whereas BA increased them by 10.34%, 11.48%, and 9.96%. Subgroup and Random Forest analyses showed that the magnitude of these benefits was mainly associated with soil properties and field management. Lower nitrogen inputs favored the yield and PFPN responses to SR, whereas increasing biochar application rate strengthened yield and PFPN responses to BA. Water supply was an important predictor of WP under both amendments. These results demonstrate that SR and BA can simultaneously enhance wheat productivity and water and nitrogen use. Their agronomic benefits can be further improved by matching amendment practices with local soil fertility, water availability, and nutrient-management conditions.

Unveiling the relationship between the “Water–Carbon–Ecology” (W-C-E) footprints embodied in regional trade and resource flows is crucial for enhancing the synergistic benefits between economic development and environmental protection. This study constructs an association framework based on the Multi-Regional Input–Output (MRIO) model to systematically evaluate the “W-C-E” footprints and resource flow characteristics of the Yangtze River Economic Belt and the Yellow River Basin. By integrating import and export trade data, this study reveals the patterns of resource flows within and outside these regions. This research delineates the connection patterns between the “W-C-E” footprints and resource flows across three dimensions: spatial, sectoral, and environmental–economic factors. The results indicate that the Yangtze River Economic Belt has gained significant economic benefits from regional trade but also bears substantial environmental costs. Import and export trade further exacerbate the imbalance in regional resource flows, with the Yangtze River Economic Belt exporting many embodied resources through high-energy-consuming products, while the Yellow River Basin increases resource input by importing products such as food and tobacco. Sectoral analysis reveals that agriculture, electricity and water supply, and mining are the sectors with the highest net output of “W-C-E” footprints in both regions, whereas services, food and tobacco, and construction are the sectors with the highest net input. The comprehensive framework of this study can be extended to the analysis of resource–environment–economic systems in other regions, providing methodological support for depicting complex human–land system linkage patterns.

Irrigation districts are key operational units where water diversion, agricultural energy inputs, cultivated land use, and food production are directly coupled. However, existing water–energy–food nexus studies have mainly focused on provincial or basin scales, with limited attention to nonlinear associations and regional heterogeneity at the irrigation-district scale. This study examined the spatiotemporal evolution and associated factors of the agricultural water–energy–food (AWEF) coupling coordination degree (CCD) in 40 lower Yellow River irrigation districts from 2000 to 2020. An integrated framework combining the CCD model, XGBoost–SHAP, nonlinear fitting with bootstrap threshold analysis, and GTWR was used to identify leading associated factors, nonlinear transition points, and spatiotemporal heterogeneity. The AWEF CCD showed an overall upward trend from 2000 to 2020, with the mean value increasing from approximately 0.54 in 2000 to 0.77 in 2020. Spatially, the distribution gradually shifted from the lower-value classes of 0.48–0.55 and 0.55–0.62 in the early stage to the higher-value classes of 0.69–0.76 and 0.76–0.84 in the later stage. Population density (PD), nighttime light index (NLI), proportion of cultivated land (PCL) and proportion of water area (WP) were identified as the key associated factors. Their associations with CCD were not uniform across regions. Their relationships with CCD were nonlinear and region-specific: the SHAP contribution of PD changed from positive to negative across thresholds of 432.7–470.8 persons/km², whereas NLI changed from negative to positive at 7.655–8.472; PCL shifted from positive to negative at 0.8157–0.8241, while WP changed from negative to positive at approximately 0.006–0.012. GTWR further revealed spatiotemporal heterogeneity in the local relationships between these factors and CCD. The local coefficients of PD remained negative throughout the study period, whereas those of NLI remained positive but were generally lower during 2010–2020 than during 2000–2009. The local relationships of PCL and WP with CCD varied across regions and stages, with both positive and negative coefficients observed.