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Land-use change significantly contributes to carbon emission. Analyzing this relationship fosters exploration of low-carbon, efficient land-use patterns at regional levels. Using ArcGIS 10.5 and the PLUS model, this study investigated land transfer trends across six counties and one district in the Malian River Basin between 2000 and 2020. It quantified carbon emissions from land use and performed spatial distribution analysis using land-use and socio-economic data. The study demonstrates the following: (1) Between 2010 and 2020, significant land-use changes occurred in the Malian River Basin with 72,919.49 km² of land undergoing transformation. Notably, the farmland-to-forest and grassland conversion project in Qingyang City was a major factor contributing to the shift from arable land to forest and grassland. (2) Natural factors influencing land conversion in the Loess Plateau region primarily include precipitation and elevation. Conversely, social factors such as population density, road networks, and local government establishments in districts and counties are pivotal in driving land-use changes within the Malian River Basin. (3) Carbon emissions vary significantly among different land-use types, with building land, cropland, unutilized land, watershed, grassland, and forest land showing descending emissions. The rapid expansion of building land notably increases carbon emissions in the study region, while forest land, a significant carbon sink, absorbs approximately 88% of total carbon emissions. (4) Districts and counties in the study area exhibit varying levels of carbon emissions, with Ning County, Xifeng District, Huan County, Qingcheng County, Zhengning County, Heshui County, and Huachi County listed in descending order. Regions with higher carbon emissions typically host abundant energy resources and significant energy production and consumption activities. Variations in carbon emission levels are largely influenced by resource availability and development priorities. Variations in resource levels and developmental focus are pivotal in explaining differences in carbon emission levels. Thus, it is crucial to explore the dynamic interplay between land-use carbon emission efficiency and land evolution in the Malian River Basin. This research will support ecological management and sustainable economic development in the Yellow River Basin, while also contributing to the achievement of the “double carbon” goals. Full article

The loessial tableland is a unique landform type on the Loess Plateau in China. Long-term soil erosion has led to the retreat of gullies and the rapid reduction of fertile arable land, which has further decreased agricultural production. In this study, we chose the Malian River basin to analyze the temporal and spatial variation of its runoff and sediment load, as well as the potential causes. The annual runoff and sediment load at six hydrological stations in the study area were collected for the period between 1960 and 2016. The Mann−Kendall and Pettitt tests were respectively applied to detect temporal variations and abrupt changes in the runoff and sediment loads. The results showed that an abrupt change in the runoff and sediment loads occurred in 2003. The average annual runoff in the Malian River was 4.42 × 10⁸ m³ yr⁻¹ from 1960 to 2002, and decreased to 3.32 × 10⁸ m³ yr⁻¹ in 2003–2016. The average annual sediment load was 1.27 × 10⁸ t yr⁻¹ in 1960–2002, and decreased to 0.65 × 10⁸ t yr⁻¹ in 2003–2016. The spatial patterns in the sediment load suggested that the Hongde sub-basin contributed a higher sediment count to the Malian River, which may require additional attention for soil and water conservation in the future. Anthropogenic activities significantly affected runoff and sediment load reduction according to the double-mass curve method, accounting for 90.7% and 78.7%, respectively, whereas rainfall changes were 9.3% and 21.3%, respectively. As such, the present study analyzed the loessial tableland runoff and sediment load characteristics of the Malian River basin for soil and water erosion management. Full article

In the published article [1], the authors realized some errors in the second affiliation and thus wish to make the revisions as below: Change the Affiliation 2 “Chinese Academy of Sciences, Beijing 100049, China” to “University of Chinese Academy of Sciences, Beijing 100049, China” [...] Full article

The Malian River Basin is the Longdong grain elevator and a new oil and energy base of East Gansu Province. Limited water resources programming utilization is a key for the development of the socio-economic and energy industry, as well as the improvement of the ecological environment. An analytical framework for assessing socioeconomic development, rational allocation of water resources, and guiding policy development is proposed in this study. A decision tree method was used in the risk analysis and was improved by introducing the expert advisory probabilistic method into the sensitivity analysis to reduce cognitive bias. A large-system multi-objective model was developed to solve the problem of the rational allocation of available water resources and for benefit maximization among water users. The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) method was used to generate a solution. The water supply amount within the basin was 8.69 × 10⁸ m³ and the water shortage rate was 15.90%. The optimization model method had better distribution results than the weights method without new water supply. Through the model method results, the water saving potential was found and the related policies were proposed. The framework and methods can further provide a reference for both the planning of water resources and the formulation of regulatory policies and will greatly alleviate water crises in semi-arid areas. Full article