Yellow River Basin Research Articles

The spatiotemporal evolution and influencing factors of carbon emissions in the Yellow River Basin based on nighttime light data

To achieve sustainable ecological development in the contemporary global economy and technology, addressing carbon emissions is imperative. The issue of carbon emissions and their impact on the environment has been the subject of intense scrutiny and debate among academicians worldwide. This investigation investigates the Yellow River Basin in China, a region with substantial industrial development. It analyses the fluctuations in carbon emissions and their influencing factors from 2010 to 2022 using nighttime light data. The spatial clustering features of carbon emissions in the prefecture-level communities of the Yellow River Basin from 2005 to 2022 are verified by the spatial autocorrelation analysis. The Gini coefficient is employed to examine regional disparities in carbon emissions in three distinct ways: total difference, intra-regional difference, and inter-regional difference. Ultimately, the GTWR model is implemented to evaluate the variables that influence carbon emissions within the Yellow River Basin. The results suggest that the Yellow River Basin is characterized by substantial spatial clustering. Shandong Province and Lvliang City are home to high-high clustering cities, while Gansu Province, Shaanxi Province, and Sichuan Province are home to low-low clustering cities. Carbon emissions are increasing annually. In comparison to the Upper, Middle, and Lower Yellow River regions, the disparities in carbon emissions between the Middle and Lower Yellow River regions are somewhat lesser. Intra-regional differences follow the trend of Upper Yellow River > Middle Yellow River > Lower Yellow River. Economic development, industrial structure, scientific advancement, and education level consistently positively impact carbon emissions in the Yellow River Basin. However, financial development has a sustained inhibiting effect on carbon emissions, and infrastructure development initially promotes but eventually inhibits carbon emissions.

Forecasting and Evaluation of Ecosystem Services Supply-Demand Under SSP-RCP Scenarios in the Henan Segment of the Yellow River Basin, China

Forecasting and Evaluation of Ecosystem Services Supply-Demand Under SSP-RCP Scenarios in the Henan Segment of the Yellow River Basin, China

Spatiotemporal evolution of vegetation phenology and its response to environmental factors in the upper and middle reaches of the Yellow River Basin.

Spatiotemporal evolution of vegetation phenology and its response to environmental factors in the upper and middle reaches of the Yellow River Basin.

Ecological restoration in the Yellow River Basin enhances hydropower potential

Hydropower, an important renewable energy source worldwide, is threatened by reservoir sedimentation. Ecological restoration (ER) can mitigate this by reducing upstream sediment, thereby extending hydropower facilities’ lifespan. However, ER may also reduce runoff, potentially diminishing energy generation and complicating its overall impact on hydropower potential. Here, we examine China’s Yellow River, once the world’s most sediment-laden river, using eco-hydrological and reservoir regulation models to assess how large-scale ER influences the hydropower potential of the Xiaolangdi Reservoir, which controls 92.3% of the basin area. Our results indicate that, excluding upstream reservoirs’ operations and socioeconomic water use, Xiaolangdi could generate a total of ~2.7×1011 kWh of energy before facing diminished flexibility and efficiency caused by the exhaustion of sediment storage—57.3% more than without ER—equating to an additional ~100 billion kWh. This enhancement in hydropower potential primarily arises from the extended lifespan, despite a 6.9% reduction in average annual energy generation. These findings advance our understanding of the ecosystem-water-sediment-energy nexus, offering valuable insights for integrated watershed management globally.

Space and temporal evolution and driving force analysis of ecological compensation efficiency in cultivated land--take the nine provinces in the Yellow River Basin as an example.

The efficiency of farmland ecological compensation is a crucial indicator reflecting the effectiveness of input-output implementation in farmland ecological compensation. Investigating the spatial-temporal evolution patterns and driving factors of farmland ecological compensation efficiency holds significant practical value for agricultural ecological protection and high-quality development in the Yellow River Basin. This study employs various methods including the EBM model, GML index, Dagum Gini coefficient decomposition, Markov chain, non-parametric Kernel density estimation, and ArcGIS mapping to measure farmland compensation efficiency, analyze its spatial-temporal evolution patterns, and conduct a driving force analysis using a two-way fixed effects model. Results: (1) Spatial-temporal evolution patterns: Overall, the average farmland ecological compensation efficiency in the Yellow River Basin is relatively low. In terms of temporal trends, the efficiency exhibits a "V"-shaped cyclical fluctuation, gradually rising with a convergence trend. Spatially, farmland ecological compensation efficiency has gone through three stages: low in the center, high in the periphery; high in the center, low in the periphery; and finally, uniform across the entire region. Although cross-level transitions occur, a "leap" transition is difficult to achieve. Regionally, the overall spatial disparity in farmland ecological compensation efficiency in the Yellow River Basin shows a decreasing trend, following an "M"-shaped variation pattern. (2) Driving force analysis: Farmland productivity, agricultural machinery density, and the level of agricultural scale all exhibit positive effects on farmland ecological compensation efficiency, while the level of government agricultural support the degree of agricultural marketization, urbanization, and industrialization all have negative effects. It is necessary to allocate resources efficiently by region, promote coordinated regional development, empower high-quality agriculture through science and technology, innovate agricultural development models, foster government-business collaboration, and diversify strategies to enhance farmland ecological compensation efficiency.

A Deep Learning Framework for Long-Term Soil Moisture-Based Drought Assessment Across the Major Basins in China

Drought is a critical hydrological challenge with ecological and socio-economic impacts, but its long-term variability and drivers remain insufficiently understood. This study proposes a deep learning-based framework to explore drought dynamics and their underlying drivers across China’s major basins over the past four decades. The Long Short-Term Memory network was employed to reconstruct gaps in satellite-derived soil moisture (SM) datasets, achieving high accuracy (R2 = 0.928 and RMSE = 0.020 m3m−3). An advanced explainable artificial intelligence (XAI) approach was applied to unravel the mechanistic relationships between SM and critical hydrometeorological variables. Our results revealed a slight increasing trend in SM value across China’s major basins over the past four decades, with a more pronounced downward trend in cropland that was more sensitive to water resource management. XAI results demonstrated distinct regional disparities: the northern arid regions displayed pronounced seasonality in drought dynamics, whereas the southern humid regions were less influenced by seasonal fluctuations. Surface solar radiation and air temperature were identified as the primary drivers of droughts in the Haihe, Yellow, Southwest, and Pearl River Basins, whereas precipitation is the dominant factor in the Middle and Lower Yangtze River Basins. Collectively, our study offers valuable insights for sustainable water resource management and land-use planning.

Spatiotemporal analysis of habitat quality and driving factors in the middle reaches of the Yellow River Basin.

Habitat quality (HQ) is critical for the sustainable development of regional ecosystems and provides a theoretical basis for environmental protection and land use planning. The middle reaches of the Yellow River, characterized by abundant water resources, severe soil erosion, and high biodiversity conservation value, represent a vital ecological barrier for China's environmental security. This study analyzes land use/land cover changes (LUCC) from 1992 to 2022 using a land use transfer matrix, evaluates HQ with the InVEST model, and identifies the primary driving factors and their complex interactions through the GeoDetector model. Spatial autocorrelation analysis (SAA), including Global Moran's I (GMI), Local Moran's I (LMI), and Getis-Ord Gi*, further uncovers spatial clustering and distribution patterns of HQ, revealing underlying ecological mechanisms. The results indicate that LUCC in the middle reaches of the Yellow River has undergone significant transformations: urbanization and agricultural expansion have exerted negative impacts on HQ, while ecological restoration policies have substantially improved HQ in certain areas. GeoDetector analysis highlights economic development and LUCC as the dominant drivers of HQ, with significant synergistic interactions among factors. SAA confirms the clustering characteristics of HQ, providing robust support for the formulation of more targeted and effective environmental protection strategies. This study recommends strict implementation of conservation boundaries, curbing urban land expansion, optimizing ecological compensation mechanisms, and promoting ecological restoration policies, such as converting farmland to forests or grasslands, to enhance HQ in the region.

Distribution Pattern and Assembly Process of Fungal Communities Along Altitude Gradient in Sediments of the Yellow River Basin

Microorganisms have a profound impact on the stability and ecological health of aquatic environments. Fungi, as important components of river ecosystems, play critical roles as decomposers and symbionts. A comprehensive understanding of the mechanisms underlying fungal community assembly is essential for the effective conservation and management of river ecosystems. However, the distribution patterns and assembly process of fungal communities along elevation gradients in river sediments remain poorly understood. In this study, ITS amplicon sequencing, a neutral community model, and a null model were employed to analyze the distribution patterns and assembly processes of fungal communities in sediments along the altitudinal gradient of the Yellow River. The results indicated that Ascomycota (47.79%) and Basidiomycota (15.68%) were identified as the dominant phyla in the sediments, collectively accounting for 63.47% of the total relative abundance of the community. In the three different altitudinal gradients, the fungal community diversity (Shannon) showed a gradually decreasing trend with increasing altitude. The co-line networks of fungal communities exhibited positive interactions and had more complex and compact networks in the sediments of the Tibetan Plateau area (YRA). Environmental factors in the sediments played an important role in shaping the structure of fungal communities, with lead (Pb), total nitrogen (TN), silt, and total organic carbon (TOC) being the main factors driving changes in community structure, contributing 15.5%, 12.3%, 10.7%, and 10.2%, respectively. In the community assembly process, deterministic processes were found to dominate, with homogenizing selection contributing the most (69.66%). These research results help us understand the distribution patterns of fungal communities along altitudinal gradients and the mechanisms of community assembly, and also provide a scientific basis for biodiversity conservation and the rational use of biological resources.

Trade-off and synergy relationships and regional regulation of multifunctional cultivated land in the Yellow River Basin

Exploring the multifunctional trade-off and synergy relationship of cultivated land is of great significance for protecting cultivated land resources, ensuring food security, maintaining ecological security, and promoting high-quality development in the Yellow River Basin. Based on the selection of 379 counties with concentrated distribution of cultivated land, this study comprehensively evaluates the three-dimensional functional level of “production-society-ecology” of cultivated land from 2010 to 2020. The coupling coordination degree model, land system function trade-off degree model, and K-means clustering analysis method are used to analyze the trade-off and synergy relationship between cultivated land functions and divide the functional zones in the Yellow River Basin. 1) In the last 10 years, the levels of cultivated land production, social, and ecological functions in the Yellow River Basin are in the range of 0.01–0.47, 0.04 to 0.23, and 0.03 to 0.23, respectively. The production function is at a stable level, while the overall level of social and ecological functions has slightly improved. 2) The level of multifunctional coupling and coordination of cultivated land ranges from 0.22 to 0.65. Only 31.13% of counties have a high coupling degree between multiple functions. The production-ecological function in the upstream regions show a coordinated development trend. The social-ecological function in the midstream regions is well coordinated, and the production-social function and production-ecological function in downstream regions towards collaborative development. 3) According to the dominant functional types and the characteristics of multifunctional coupling and coordination, the cultivated land of Yellow River Basin is divided into 7 multifunctional zones, involving 149 with multifunctional advantage zones, 19 with P-S functional composite zones, 21 with P-E functional composite zones, 21 with S-E functional composite zones, 74 with social functional dominant zones, 29 with ecological functional dominant zones, 44 with grain functional dominant zones, and 22 with remediation key zones. The results can provide decision support for differentiated management of cultivated land in the Yellow River Basin and mutual promotion between functions.

Study on the dynamic prediction and optimum regulation scheme of water resource carrying capacity in the yellow river basin

The dynamic change in regional water resource carrying capacity (WRCC) is an important factor in formulating an optimal water resource allocation scheme. To accurately predict the dynamic change in WRCC and formulate the optimal regulation scheme in a river basin, this paper proposes a diagnostic index system of WRCC based on the mutual feeding mechanism of economic-society, water resources and eco-environment. The multi-methods including support vector machine (SV) and system dynamics (SD), back propagation neural network (BP), etc., were used to construct a quantitative dynamic prediction model for the WRCC. The orthogonal test (OT) method is used to optimize the WRCC regulation scheme. Through simulation, the WRCC in the sub-regions of the Yellow River Basin in 2030, 2035 and 2050 under different scenarios are obtained. The study results show that the WRCC in the upper, middle and lower reaches of the Yellow River Basin are overloaded or seriously overloaded before the operation of the Western Line of South-to-North Water Transfer Project (WLSNWTP). Six key driving indexes (unconventional water utilization, water flow into the sea, irrigation water use, irrigation area, industrial added value and water consumption of 10 thousand Yuan (CNY) industrial added value) are selected to carry out orthogonal tests, and the optimal WRCC regulation scheme is obtained in different level years. The present study results have an important reference value for efficient water resource utilization and eco-society development in the Yellow River Basin.

Influencing Mechanisms of Changes to Agricultural Water Use in the Yellow River Basin: The Case of Wuwei City, China

Agricultural water use is a crucial component of the water supply and demand balance in the Yellow River Basin, accounting for an average of 75% of the total water usage annually. Understanding the mechanisms influencing the evolution of agricultural water use in various cities within the Yellow River Basin is of significant practical importance for maintaining a stable water balance and promoting high-quality agricultural development in the region. The factors affecting the evolution of agricultural water use are categorized into seven major groups: water resource endowment, water use conditions, hydraulic construction, among others. These encompass 21 quantitative indicators such as total water resources, grain sowing area and agricultural production policy indicators (APPI), which can either drive or inhibit agricultural water use. By comparing and analyzing the influencing factors selected in different studies, and considering the differences between various methods, the comprehensive contribution rates of these factors are calculated to identify the driving and inhibiting factors affecting the trend of agricultural water use in the Yellow River Basin. The study reveals that different time periods and cities have distinct driving and inhibiting indicators for agricultural water use. Overall, time series analysis shows that the GDP of the primary agricultural economy ([Formula: see text] is often a driving indicator of agricultural water use, while annual precipitation (AP), water-saving irrigation machinery (WSIM) in agricultural modernization, and APPI are often inhibiting indicators. The findings provide a basis and guidance for formulating effective water resource management strategies and agricultural development policies.

Impacts of Cascade Reservoirs on Adjacent Climate and Land Use Change in the Upper Yellow River, China

The Yellow River (YR), China’s second-largest river, is rich in water resources, particularly in its upper reaches, which are characterized by mountainous canyons and considerable hydropower potential. Since the 1950s, 24 reservoirs have been constructed along a 918 km stretch of the upper Yellow River (UYR), creating the highest concentration of cascade reservoirs. This development has had significant ecological impacts on the surrounding environment. This study examines the relationship between reservoir attributes and climate factors to evaluate the environmental effects of reservoirs in the UYR. (1) Following reservoir construction, the average annual temperature and precipitation increased by 3–10%, though seasonal and spatial distributions varied. Temperature increases were most pronounced in winter, while precipitation decreased in some regions during spring and summer, although the overall trend remained positive. (2) The ecosystem experienced significant post-construction changes, including reductions in arable land, grassland, and unused land, while water bodies, construction land, and forests expanded. Consequently, the ecosystem within the reservoir area now accounts for 5.2–12.5% of the total area of the region. (3) Temperature and precipitation were closely linked to reservoir attributes, with storage volume (CAP) and long-term average flow (DIS) significantly affecting precipitation, while surface area (AREA) and normal storage level (FSL) had a greater influence on temperature. In conclusion, the dual impacts of reservoir construction on local climate and land use highlight the complex environmental mechanisms involved, providing valuable insights for future reservoir development and ecological protection in the Yellow River Basin and similar regions.

Multi-Objective Optimization of Two Cascade Reservoirs on the Upper Yellow River During Different Intra-Annual Periods

Due to water scarcity in the Yellow River basin, the existing operations for the Longyangxia and Liujiashan cascade reservoirs are insufficient to meet the demands of multiple objectives. This study establishes a coupled coordination model considering hydropower generation, water supply, and storage capacity at different periods during the year. At the same time, the model quantifies the impact of scheduling strategies on multiple objectives and determines the optimal operation for reservoirs at different periods. The results indicate that the scheduling strategy of the Longyangxia reservoir dominates the changes in hydropower generation, water supply, and storage capacity. Specifically, during the ice flood control period, the scenario of continuous release from Longyangxia and continuous storage at Liujiaxia achieves 1.26 billion kWh of hydropower generation, with a water supply shortage rate of 8.67%; During the non-flood period, releasing water from Longyangxia in April and May and storing it in June while Liujiaxia continuously releases water results in 4.68 billion kWh of hydropower generation and a shortage rate of 1.61%. During the flood control period, continuous storage at Longyangxia and controlling the water level of Liujiashan within flood control limits, with storage in September and release in October, achieves 5.65 billion kWh of hydropower generation and a shortage rate of 0%.

Study on the Distribution Range and Influencing Factors of Salix oritrepha Schneid. and Picea crassifolia Kom. in the Watershed of the Yellow River Under Future Climate Models

The watershed of the Yellow River is an important water conservation area in the Yellow River Basin. Its fragile ecological environment, climate change and unreasonable human activities have led to the continuous degradation of plant community structure in the watershed. This study only considers environmental factors, based on MaxEnt, Garp and other niche models and spatial-temporal analysis methods such as Mess and MoD analysis, to explore the suitable areas of Salix oritrepha Schneid. (First published in C.S.Sargent, Pl. Wilson. 3: 113 (1916)) and Picea crassifolia Kom. (First published in Bot. Mater. Gerb. Glavn. Bot. Sada R.S.F.S.R. 4: 177 (1923)) in the watershed of the Yellow River under different emission scenarios in the future. The results show that the MaxEnt model has a good simulation effect. In terms of spatial distribution, the suitable areas of the two species are mainly concentrated in the southeastern part of the Yellow River source area. Compared with the current period (1970–2000), by 2070, the suitable areas of the two species in each scenario showed a distribution of high in the east and low in the west, with an obvious expansion trend in the area and moving to high altitude and high latitude. According to the analysis of Mess and MoD, the annual average temperature (Bio_1) may be the most important variable affecting the future distribution of the two vegetation types.

Future propagation characteristics of meteorological drought to hydrological drought in the Yellow River basin

Future propagation characteristics of meteorological drought to hydrological drought in the Yellow River basin

Terrestrial ecosystem resilience to drought stress and driving mechanisms thereof in the Yellow River Basin, China

Terrestrial ecosystem resilience to drought stress and driving mechanisms thereof in the Yellow River Basin, China

Response mechanisms of eukaryotic plankton community structure to complex environmental conditions in semi-arid river basins, China.

Response mechanisms of eukaryotic plankton community structure to complex environmental conditions in semi-arid river basins, China.

Coevolution and its influencing factors of the water resources–economy–society–environment composite system in the Yellow River basin

Coevolution and its influencing factors of the water resources–economy–society–environment composite system in the Yellow River basin

Late Holocene sediment source changes in the Yellow River basin, China

Late Holocene sediment source changes in the Yellow River basin, China

Assessing technology's influence on cropland green production efficiency in the Yellow River basin, China

Assessing technology's influence on cropland green production efficiency in the Yellow River basin, China