Karst depressions are common negative topographic landforms formed by the intense dissolution of soluble rocks and are widely developed in Guizhou province. In this work, an inventory of karst depressions in Guizhou was established, and a total of approximately 256,400 karst depressions were extracted and found to be spatially clustered based on multidistance spatial cluster analysis with Ripley's K function. The kernel density (KD) can transform the position data of the depressions into a smooth trend surface, and five different depression concentration areas were established based on the KD values. The results indicated that the karst depressions are clustered and developed in the south and west of Guizhou, while some areas in the southeast, east and north have poorly developed or no clustering. Additionally, the random forest (RF) model was used to rank the importance of factors affecting the distribution of karst depressions, and the results showed that the influence of lithology on the spatial distribution of karst depressions is absolutely dominant, followed by that of fault tectonics and hydrological conditions. The research results will contribute to the resource investigation of karst depressions and provide theoretical support for resource evaluation and sustainable utilization.

Situated in the hinterland of Eurasia, Central Asia is characterized by an arid climate and sparse rainfall. The uneven spatial distribution of water and land resources across the region has pressured economic and social development. An accurate understanding of Central Asia's water resources carrying capacity (WRCC) is vital for enhancing the sustainability of water resources utilization and guiding regional economic and social activities. This study aims to facilitate the sustainability of water resources utilization by evaluating the region's WRCC from the viewpoints of economic and technological conditions and social welfare. A concise yet effective model with relatively fewer parameters was established by adopting water resources data from the Food and Agriculture Organization (FAO) and socioeconomic data from the World Bank. The results indicated that the WRCC of all five Central Asian countries showed an increasing trend with improved water use efficiency from 1995 to 2020. Kazakhstan's WRCC was significantly higher than the other four countries, reaching 54.03 million people in 2020. The water resources carrying index (WRCI) of the five Central Asian countries varied considerably, with the actual population sizes of Turkmenistan and Uzbekistan highly overloaded. Although there has been a decrease in Central Asian countries’ WRCI between 1995 and 2020, water resources utilization problems in the region remain prominent. Based on the water resources carrying capacity evaluation system, to increase available water resources and improve production water use efficiency are key to address these issues. In light of this, this study offers practical and feasible solutions at the policy level: (1) The implementation of signed multilateral agreements on transboundary water resources allocation must proceed through joint governmental efforts. (2) Investments in advancing science and technology need to be increased to improve water use efficiency in irrigation systems. (3) The output of water-intensive crops should be reduced. (4) The industrial structure could be further optimized so that non-agricultural uses are the primary drivers of gross domestic product (GDP) growth.

Effective soil particle size composition can more realistically reflect the particle size sorting process of erosion. To reveal the individual contributions of rainfall intensity and slope to splash erosion, and to distinguish the enrichment ratio of each size and the critical size in splash, loessial soil collected on the Loess Plateau in May 2019 was tested under different rainfall intensities (60, 84, 108, 132, 156 mm h^-1) and slopes (0°, 5°, 10°, 15°, 20°). The results demonstrated that 99% of splash mass was concentrated in 0-0.4 m. Rainfall intensity was the major factor for splash according to the raindrop generation mode by rainfall simulator nozzles. The contributions of rainfall intensity to splash erosion were 82.72% and 93.24%, respectively in upslope and downslope direction. The mass percentages of effective clay and effective silt were positively correlated with rainfall intensity, while the mass percentages of effective very fine sand and effective fine sand were negatively correlated with rainfall intensity. Opposite to effective very fine sand, the mass percentages of effective clay significantly decreased with increasing distance. Rainfall intensity had significant effects on enrichment ratios, positively for effective clay and effective silt and negatively for effective very fine sand and effective fine sand. The critical effective particle size in splash for loessial soil was 50 μm.

Land subsidence is a geohazard phenomenon caused by the lowering of land elevation due to the compression of the sinking land soil body, thus creating an excessive constraint on the safe construction and sustainable development of cities. The use of accurate and efficient means for land subsidence prediction is of remarkable importance for preventing land subsidence and ensuring urban safety. Although the current time-series prediction method can accomplish relatively high accuracy, the predicted settlement points are independent of each other, and the existence of spatial dependence in the data itself is lost. In order to unlock this problem, a spatial convolutional long short-term memory neural network (ConvLSTM) based on the spatio-temporal prediction method for land subsidence is constructed. To this end, a cloud platform is employed to obtain a long time series deformation dataset from May 2017 to November 2021 in the understudied area. A convolutional structure to extract spatial features is utilized in the proposed model, and an LSTM structure is linked to the model for time-series prediction to achieve unified modeling of temporal and spatial correlation, thereby rationally predicting the land subsidence progress trend and distribution. The experimental results reveal that the prediction results of the ConvLSTM model are more accurate than those of the LSTM in about 62% of the understudied area, and the overall mean absolute error (MAE) is reduced by about 7%. The achieved results exhibit better prediction in the subsidence center region, and the spatial distribution characteristics of the subsidence data are effectively captured. The present prediction results are more consistent with the distribution of real subsidence and could provide more accurate and reasonable scientific references for subsidence prevention and control in the Beijing-Tianjin-Hebei region.

Rural decline is a global issue accompanied by the regional imbalanced development and dysfunction in rural areas. Coordinated interaction among production, living, and ecological functions is essential for the sustainability of rural regional systems. Based on the framework of “element-structure-function”, an indicator system was constructed to explore the evolution characteristics and driving factors of rural regional functions in the farming-pastoral ecotone of northern China (FPENC) using the models of entropy-based TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), revised vertical and horizontal comparison, and GeoDetector. The results indicated a gradual synergy of rural production, living, and ecological functions during the period 2000-2020. Improvements were observed in production and living functions, and higher ecological function was found in Hebei, Inner Mongolia, Liaoning, and Shaanxi. However, conflicts between ecological function and production and living functions were evident in Shanxi, Gansu, and Ningxia. The spatial structure played a dominant role in determining rural production, living, and ecological functions, with ratios of 38%, 56%, and 84%, respectively. Land and industry emerged as the main driving factors influencing the evolution of rural regional functions. Notably, combined interactions of rural permanent population and primary industry output (0.73), grassland area and tertiary industry output (0.58), and forest area and tertiary industry output (0.72) were responsible for the changes observed in rural production, living, and ecological functions, respectively. The findings suggest that achieving coordinated development of rural regional functions can be accomplished by establishing differentiated rural sustainable development strategies that consider the coupling of population, land, and industry in FPENC.

The transpiration-to-evapotranspiration ratio (T/ET) is a crucial indicator of the carbon-water cycle and energy balance. Despite the marked seasonality of warming and greening patterns, the differential responses of T/ET to environmental changes across the seasons remain unclear. To address this, we employed a model-data fusion method, integrating the Priestley-Taylor Jet Propulsion Lab model with observational datasets, to analyze the seasonal trends of T/ET in China’s terrestrial ecosystems from 1981 to 2021. The results showed that T/ET significantly increased in spring, summer, and autumn, with growth rates of 0.0018 a^-1 (p<0.01), 0.0024 a^-1 (p<0.01), and 0.0013 a^-1 (p<0.01), respectively, whereas the winter trends remained statistically insignificant throughout the study period. Leaf area index dynamics were identified as the primary driver of the increase in T/ET during summer, accounting for 79% of the trend. By contrast, climate change was the main contributor to the rising T/ET trends in spring and autumn, accounting for 72% and 77% of the T/ET increase, respectively. Additionally, warming is pivotal for climate-driven changes in T/ET trends. This study elucidated seasonal variations in T/ET responses to environmental factors, offering critical insights for the sustainable management of ecosystems and accurate prediction of future environmental change impacts.

Changes in surface temperature extremes have become a global concern. Based on the daily lowest temperature (TN) and daily highest temperature (TX) data from 2138 weather stations in China from 1961 to 2020, we calculated 14 extreme temperature indices to analyze the characteristics of extreme temperature events. The widespread changes observed in all extreme temperature indices suggest that China experienced significant warming during this period. Specifically, the cold extreme indices, such as cold nights, cold days, frost days, icing days, and the cold spell duration index, decreased significantly by −6.64, −2.67, −2.96, −0.97, and −1.01 days/decade, respectively. In contrast, we observed significant increases in warm extreme indices. The number of warm nights, warm days, summer days, tropical nights, and warm spell duration index increased by 8.44, 5.18, 2.81, 2.50, and 1.66 d/decade, respectively. In addition, the lowest TN, highest TN, lowest TX, and highest TX over the entire period rose by 0.47, 0.22, 0.26, and 0.16°C/decade, respectively. Furthermore, using Pearson’s correlation and wavelet coherence analyses, this study identified a strong association between extreme temperature indices and atmospheric circulation factors, with varying correlation strengths and resonance periods across different time-frequency domains.

The mass elevation effect (MEE) is a thermal effect, in which heating produced by long wave radiation on a mountain surface generates atmospheric uplift, which has a profound impact on the hydrothermal conditions and natural geographical processes in mountainous areas. Based on multi-source remote sensing data and field observations, a spatial downscaling inversion of temperature in the Tianshan Mountains in China was conducted, and the MEE was estimated and a spatio-temporal analysis was conducted. The GeoDetector model (GDM) and a geographically weighted regression (GWR) model were applied to explore the spatial and temporal heterogeneity of the study area. Four key results can be obtained. (1) The temperature pattern is complex and diverse, and the overall temperature presented a pattern of high in the south and east, but low in the north and west. There were clear zonal features of temperature that were negatively correlated with altitude, and the temperature difference between the internal and external areas of the mountains. (2) The warming effect of mountains was prominent, and the temperature at the same altitude increased in steps from west to east and north to south. Geomorphological units, such as large valleys and intermontane basins, weakened the latitudinal zonality and altitudinal dependence of temperature at the same altitude, with the warming effect of mountains in the southern Tianshan Mountains. (3) The dominant factors affecting the overall pattern of the MEE were topography and location, among which the difference between the internal and external areas of the mountains, and the absolute elevation played a prominent role. The interaction between factors had a greater influence on the spatial differentiation of mountain effects than single factors, and there was a strong interaction between terrain and climate, precipitation, the normalized difference vegetation index (NDVI), and other factors. (4) There was a spatial heterogeneity in the direction and intensity of the spatial variation of the MEE. Absolute elevation was significantly positively correlated with the change of MEE, while precipitation and the NDVI were dominated by negative feedback. In general, topography had the largest effect on the macroscopic control of MEE, and coupled with precipitation, the underlying surface, and other factors to form a unique mountain circulation system and climate characteristics, which in turn enhanced the spatial and temporal heterogeneity of the MEE. The results of this study will be useful in the further analysis of the causes of MEE and its ecological effects.

Global extreme hydrological events pose considerable challenges to the sustainable development of human society and river ecology. Land use/cover change (LUCC) is a visible manifestation of human activity and has caused substantial alterations in extreme hydrological regimes across rivers worldwide. The Jinsha River lies upstream of the Yangtze River and its hydrological variability has had profound socioeconomic and environmental effects. In this study, we developed Hydrological Simulation Program-FORTRAN (HSPF) and land-use simulation models of the entire watershed to simulate the effects of LUCC on hydrological extremes and quantify the inter-relationships among them. The main land-use changes between 1995 and 2015 were those associated with cropland, forest land, and grassland. Between 2015 and 2030, it is estimated that the coverage of forest land, grassland, construction land, and unused land will increase by 0.64%, 0.18%, 69.38%, and 45.08%, respectively, whereas that of cropland, water bodies, and snow- and ice-covered areas will decline by 8.02%, 2.63%, and 0.89%, respectively. LUCC has had irregular effects on different hydrological regimes and has most severely altered stream flows. The responses of hydrological extremes to historical land-use change were characterized by spatial variation. Extreme low flows increased by 0.54%-0.59% whereas extreme high flows increased by 0%-0.08% at the lowest outlet. Responses to future land-use change will be amplified by a 0.72%-0.90% reduction in extreme low flows and a 0.08%-0.12% increase in extreme high flows. The hedging effect caused by irregular changes in tributary stream flow was found to alleviate the observed flow in mainstream rivers caused by land-use change. The extreme hydrological regimes were affected mainly by the net swap area transferred from ice and snow area to forest (NSAIF) and thereafter to cultivated land (NSAIC). Extreme low flows were found to be positively correlated with NSAIF and NSAIC, whereas extreme high flows were positively correlated with NSAIC and negatively correlated with NSAIF.

There is a great uncertainty in generation and formation of non-point source (NPS) pollutants, which leads to difficulties in the investigation of monitoring and control. However, accurate calculation of these pollutant loads is closely correlated to control NPS pollutants in agriculture. In addition, the relationships between pollutant load and human activity and physiographic factor remain elusive. In this study, a modified model with the whole process of agricultural NPS pollutant migration was established by introducing factors including rainfall driving, terrain impact, runoff index, leaching index and landscape intercept index for the load calculation. Partial least squares path modeling was applied to explore the interactions between these factors. The simulation results indicated that the average total nitrogen (TN) load intensity was 0.57 t km^-2 and the average total phosphorus (TP) load intensity was 0.01 t km^-2 in Chengdu Plain. The critical effects identified in this study could provide useful guidance to NPS pollution control. These findings further our understanding of the NPS pollution control in agriculture and the formulation of sustainable preventive measures.

Transpiration (Tc) is a critical component of the global water cycle. Soil moisture (SM) and vapor pressure deficit (VPD) are key regulators of Tc, and exploring their contributions to changes in Tc can deepen our understanding of the mechanisms of water cycling in terrestrial ecosystems. However, the driving roles of VPD and SM in Tc changes remain debated because of the coupling of SM and VPD through land-atmosphere interactions which restrict the quantification of the independent effects of SM and VPD on Tc. By decoupling the correlations between SM and VPD using a novel binning approach, this study analyzed the dominant drivers of vegetation transpiration in subtropical China from 2003 to 2018 based on multi-source data, including meteorological reanalysis, remotely sensed soil moisture, transpiration, and land cover data. The results show that Tc first increased and then remained stable with an increase in SM across the study area but changed slightly with increasing VPD. Overall, the relative contribution of SM to the change in Tc was approximately five times that of VPD. The sensitivities of Tc to SM and VPD differed among vegetation types. Although the sensitivity of Tc to SM was greater than that of VPD for all four vegetation types, the thresholds of Tc in response to SM were different, with the lowest threshold (approximately 35%) for the other forests and the highest threshold (approximately 55% ) for short wood vegetation. We infer that this is associated with the differences in ecological strategies. To verify the reliability of our conclusions, we used solar- induced chlorophyll fluorescence (SIF) data as a proxy for Tc based on the tight coupling between photosynthesis and transpiration. Consistent results were obtained by repeating the analyses. The results of this study, in which the impacts of SM and VPD on Tc were decoupled, are beneficial for further understanding the critical processes involved in water cycling in terrestrial ecosystems in response to climate change.

Urban-rural integration is an advanced form resulting from the future evolution of urban-rural relationships. Nevertheless, little research has explored whether urban and rural areas can move from dual segmentation to integrated development from a theoretical or empirical perspective. Based on the research framework of welfare economics, which offers an appealing paradigm to frame the underlying game between cities and villages, this study clarifies the ideal state of urban-rural integration. It then proposes a series of basic assumptions, and constructs a corresponding objective function and its constraints. Moreover, it assesses the possibility of seeing the transmutation from division to integration between urban and rural areas with continuous socio-economic development. The authors argue that the ideal state of urban-rural integration should be a Pareto-driven optimal allocation of urban-rural resources and outputs, and the maximization of social welfare in the entire region. Based on a systematic demonstration using mathematical models, the study proposes that urban and rural areas can enter this ideal integrated development pattern when certain parameter conditions are met. In general, this study demonstrates the theoretical logic and scientific foundations of urban-rural integration, enriches theoretical studies about urban-rural relationships, and provides basic theoretical support for large developing countries to build a coordinated and orderly urban-rural community with a shared future.

Since the Bonn 2011 conference, the “water-energy-food” (WEF) nexus has aroused global concern to promote sustainable development. The WEF nexus is a complex, dynamic, and open system containing interrelated and interdependent elements. However, the nexus studies have mainly focused on natural elements based on massive earth observation data. Human elements (e.g., society, economy, politics, culture) are described insufficiently, because traditional earth observation technologies cannot effectively perceive socioeconomic characteristics, especially human feelings, emotions, and experiences. Thus, it is difficult to simulate the complex WEF nexus. With the development of earth observation sensor technologies and human activity perception methods, geographical big data covering both human activities and natural elements offers a new opportunity for in-depth WEF nexus analysis. This study proposes a five-step framework by leveraging geographical big data mining to dig for the hidden value in the data of various natural and human elements. This framework can enable a thorough and comprehensive analysis of the WEF nexus. Some application examples of the framework, major challenges, and possible solutions are discussed. Geographical big data mining is a promising approach to enhance the analysis of the WEF nexus, strengthen the coordinated management of resources and sectors, and facilitate the progress toward sustainable development.

Accurately identifying the dominant factor of karst ecosystem services (ESs) is a prerequisite for the rocky desertification control. However, the explanatory power of environmental factors on the spatial distribution of ESs is affected by scaling, and the quantitative research on the scale effect still needs to be further strengthened. This study used the geographical detector to access the explanatory power of environmental factors on soil erosion and water yield at different spatial resolutions, and then explored its differences in three geomorphological-type areas. Results showed that slope and vegetation coverage were the dominant factors of soil erosion, and the interactive explanatory power between the two factors was stronger. Affected by the universality of topographic relief and landscape fragmentation in the study area, the explanatory power of slope and land use type on soil erosion was optimal at low resolution. Precipitation, elevation, and land use type were the dominant factors for the spatial heterogeneity of water yield, and the interaction between precipitation and land use type explained more than 95% of water yield. The spatial variability of elevation in different geomorphological-type areas affected its optimal explanatory power, specifically, in the terrace and hill-type areas, the spatial variability of elevation was weak, its explanatory power was optimal at high resolution. While in the mountain-type areas, the spatial variability of elevation was strong, and its explanatory power was optimal at low resolution. This study quantitatively identified the optimal explanatory power of ES variables through multi-scale analysis, which aims to provide a way and basis for accurate identification of the dominant factors of karst mountain ESs and zoning optimization.

Social upgrading does not inherently follow economic upgrading; rather, they present a complex interplay. This paper, focusing on China, utilizes the coupling coordination degree and a panel regression model to shed light on the intricate interaction between social upgrading and economic upgrading. It is found that the coupling coordination degree of social and economic upgrading in China has improved from 0.33 to 0.49 since the mid-1990s, undergoing a shift from a stage of slight imbalance to low-level coordination. However, significant regional disparities are present in terms of economic upgrading, social upgrading, and their coupling coordination degree. Developed areas exhibit a higher degree of coupling coordination compared to less developed regions, indicating a connection between the coupling coordination degree and the level of economic growth. Economic globalization, public governance, and the legal environment positively impact the coupling coordination between social and economic upgrading, while economic privatization and corporate violations of law exert negative effects. The paper concludes with policy discussions for enhancing the coupling coordination between social and economic upgrading.

China's mariculture provides more than 60% of the world’s mariculture products and plays an important role in the world’s aquaculture and food supply. Research on changes in the spatial distribution pattern of China’s mariculture, however, remains lacking. To accurately reflect the changes in the spatial pattern of mariculture in China, in this study, we used multitemporal optical and synthetic aperture radar remote sensing images to enhance the characteristics of mariculture and extracted the spatial distribution data for mariculture in China in 2000, 2010, and 2020. Accordingly, we explored the distribution pattern and changes in mariculture in China. We found that, in 2020, China’s mariculture exhibited a distribution pattern of more in the north and less in the south. With the Yangtze River estuary as the boundary, the proportion of mariculture in northern China was 70.9%, and that in southern China was only 29.1%. This difference did not exist in 2000, but it emerged because of the rapid development of mariculture in northern China from 2010 to 2020. In addition, by superimposing the mariculture data with shoreline and water depth data, we found that more than 90% of China’s mariculture area was located in the sea area within 20 km of the shoreline and that more than 80% of the mariculture area was located in the sea area with water depths of less than 20 m. In addition, the spatial distribution of mariculture in China developed from near the shore and moved outward from shallow to deep water areas. We examined the driving factors that influence changes in the spatial distribution of mariculture in China. We argue that technological advancements in mariculture, as well as the intensive concentration of mariculture near the shore, policy constraints and incentives, and economic development, collaborate to shape the current pattern of mariculture development in China.

The increasing frequency of recent droughts has an adverse effect on the ecosystem of the Mongolian Plateau. The growth condition of NPP is considered an indicator of the ecological function. Therefore, identifying the relationship between NPP and drought can assist in the prevention of drought-associated disasters and the conservation of the ecological environment of the Mongolian Plateau. This study used the Carnegie-Ames-Stanford Approach (CASA) model to simulate the NPP capacity of the Mongolian Plateau between 1982 and 2015, as well as drought indicators (drought probability, vulnerability, and risk) to explore the drought risk of NPP. The findings pointed to an overall increase in NPP with regional variances; however, the NPP rate in Inner Mongolia was considerably higher than that in Mongolia. The standardized precipitation evapotranspiration index (SPEI) showed an overall downward trend, with Inner Mongolia experiencing a substantially lower rate of decline than Mongolia. The areas most likely to experience drought were primarily in the center and north while the areas with the highest drought vulnerability were primarily in the northeast, center, and southeast. Mongolia showed a higher probability of drought compared to Inner Mongolia. Drought-prone regions of the Mongolian Plateau increased during the 21st century while drought-vulnerable areas increased and shifted from north to south. Alpine grasslands and coniferous forests were least vulnerable to drought, while other vegetation types experienced temporal variation. In the 21st century, the primary determinants of drought risk shifted from precipitation and the normalized difference vegetation index (NDVI) to temperature and relative humidity.

Exploring the coupling coordinated level of rural population-land-industry (PLI) and its underlying driving mechanism contributes to the scientific decision-making on rural sustainable development. This study assessed the coupling coordinated level of PLI based on an improved evaluation index system and then revealed the regional differentiation and driving mechanism in China’s rural areas in 2020. The results showed that the rural PLI coupling coordinated degree was 0.4694, and thus was in the stage of approximate incoordination. In addition, China’s rural PLI coupling coordinated degree formed a spatially heterogeneous pattern with high levels in the northeast, eastern and central regions, and the intragroup difference contributed more than 80% to the total difference. The rural PLI coupling coordinated level was influenced by the combined effects of rural kernel and peripheral systems, but the rural kernel system mostly determined the differentiation. In the future, rural areas should first exploit population quality improvement projects, land consolidation projects and industrial integration development strategies to promote benign mutual feedback of PLI. Second, driving factors should be comprehensively regulated by implementing a “one village, one product” strategy, breaking the urban-rural dual system, improving agricultural machinery subsidies policy, and promoting urban-rural integrated development.

Glaciers are considered to be ‘climate-sensitive indicators’ and ‘solid reservoirs’, and their changes significantly impact regional water security. The mass balance (MB) from 2011 to 2020 of the Qiyi Glacier in the northeast Tibetan Plateau is presented based on field observations. The glacier showed a persistent negative balance over 9 years of in-situ observations, with a mean MB of −0.51 m w.e. yr⁻¹. The distributed energy-mass balance model was used for glacier MB reconstruction from 1980 to 2020. The daily meteorological data used in the model were from HAR v2 reanalysis data, with automatic weather stations located in the middle and upper parts of the glacier used for deviation correction. The average MB over the past 40 years of the Qiyi Glacier was −0.36 m w.e. yr⁻¹ with the mass losses since the beginning of the 21st century, being greater than those in the past. The glacier runoff shows a significant increasing trend, contributing ~81% of the downstream river runoff. The albedo disparity indicates that the net shortwave radiation is much higher in the ablation zone than in the accumulation zone, accelerating ablation-area expansion and glacier mass depletion. The MB of the Qiyi Glacier is more sensitive to temperature and incoming shortwave radiation variation than precipitation. The MB presented a non-linear reaction to the temperature and incoming shortwave radiation. Under future climate warming, the Qiyi Glacier will be increasingly likely to deviate from the equilibrium state, thereby exacerbating regional water balance risks. It is found that the mass losses of eastern glaciers are higher than those of western glaciers, indicating significant spatial heterogeneity that may be attributable to the lower altitude and smaller area distribution of the eastern glaciers.

Megacities serve as global centers for economic, cultural, and high-tech industries. The structural features and population agglomerations are typical traits of urbanization, yet little is known about the morphological features and expansion patterns of megacities worldwide. Here we examined the spatiotemporal variations of urban land in megalopolises from 2000 to 2020 using the Urban Expansion Intensity Differentiation Index. The fractal features and expansion patterns of megacities were analyzed using the Area-Radius Multidimensional Scaling Model. Urban land use efficiency was then evaluated based on the linear relationship between urban land area and population. We found that Southeast Asia and China were the hotspots of urban expansion in megacities from 2000 to 2020, with urban land areas expanding by 3148.32 km² and 5996.26 km², respectively. The morphological features and expansion patterns of megacities exhibited a growing trend towards intensification and compactness, with the average radial dimension increasing from 1.54 to 1.56. The annual decrease in fractal dimensions indicated the integration of inner urban areas. North America and Europe megacities showed a low urban land use efficiency, with a ratio of urban land area to population ranging from 0.89 to 4.11 in 2020. Conversely, South Asia and Africa megacities exhibited a high urban land use efficiency, with the ratios between 0.23 and 0.87. Our results provide information for promoting efficient urban land utilization and sustainable cities. It is proposed to control the scale of urban expansion and to promote balanced development between inner and outer urban areas for achieving resilient and sustainable urban development.

Settlements are excellent spatiotemporal indicators for studying historical human activities and environmental change. This paper discusses the spatial and temporal changes of sites on the Ordos Plateau in China since the Neolithic Age, based on an analysis of spatiotemporal distribution characteristics of the human settlements. The frequency of human settlements on the Ordos Plateau presented a phased fluctuation process, and the sizes were mainly small and medium. The spatial distribution of human settlements was fractal, and the D value of the aggregation dimension was generally small, indicating that the spatial distribution of the sites was agglomerated. Affected by the desert, the sites were mainly distributed in the south and east of the Ordos Plateau. The spatiotemporal distribution pattern of human settlements in the Ordos Plateau resulted from the combined action of natural and human factors, especially climate change. Moreover, local livelihood patterns significantly affected the frequency of human settlements. The number of human settlements in the farming period was large, and the distribution was concentrated. In contrast, the number of sites in the nomadic period was small and scattered. The central government’s policies and the conflicts between farming and nomadic groups further affected the spatiotemporal distribution of human settlements. This study may contribute to a better understanding of historical environmental change and human-land relationships in the Ordos Plateau.

The Yellow River Basin (YRB) is a vital ecological zone in China owing to its sensitive and fragile environment. Under the long-term influence of climate changes and artificial factors, the relationship between precipitation, vegetation, and surface water in the YRB has changed drastically, ultimately affecting the water resources and environmental management. Therefore, we applied multivariate statistical analysis to investigate the precipitation, normalized difference vegetation index (NDVI), and surface water changes in the YRB from 2000 to 2021. Furthermore, we attempted to clarify the ecological effects of precipitation by explaining the relationship between precipitation and vegetation in terms of the time-lag relationship using the Integrated Multi-satellite Retrievals for Global Precipitation Measurement algorithm, Moderate Resolution Imaging Spectroradiometer, and hydrological databases. Precipitation, vegetation, and area of surface water in the YRB showed increasing trends from 2000-2021 (e.g., 7.215 mm/yr, 0.004 NDVI/yr, and 0.932 km²/yr, respectively). The water level in the upper reaches of the YRB showed a downward trend, whereas that in the middle and lower reaches exhibited an upward trend. Changes in precipitation had a positive effect on vegetation and surface water in the YRB, with correlation coefficients of 0.63 and 0.51, respectively. The responses of NDVI and surface water elevation to precipitation were heterogeneous and delayed, with the majority showing a lag time of approximately ≤ 16 days. Moreover, the lag times of Longyangxia Lake and Ngoring-Co Lake were 0 and 8 days, respectively. We showed that precipitation variability can effectively explain vegetation improvement and increases in surface water elevation, while providing a proven scenario for predicting the surface water and vegetation productivity under the influence of climate change.

The Qinghai-Tibet Plateau (QTP), also known as the Third Pole of the Earth, is a vital ecological security barrier for China. It is a tremendously sensitive region affected by the impacts of global climate change. The escalating intensity of climate change has presented profound challenges to its ecosystem functions and stability. This study first analyzes the spatiotemporal variations of the QTP ecosystem patterns and the key functions of the Plateau including water conservation, soil conservation, and windbreak and sand fixation from 2000 to 2020. It clarifies the regional differences in ecosystem functions and their importance, further evaluates the stability of ecosystem functions, and lays a scientific foundation for an ecological civilization on the Plateau by implementing conservation and restoration projects. The main results show that: (1) From 2000 to 2020, the wetland area in the QTP increased, while the grassland area significantly decreased. There were improvements in water conservation and windbreak and sand fixation capacities, with annual rates of change being 3.57 m³·ha^-1·a^-1 and 0.23 t·ha^-1·a^-1, respectively. However, the overall soil conservation trend declined during the same period, with an annual change rate of -0.16 t·ha^-1·a^-1. (2) The core areas of water conservation, soil conservation, and windbreak and sand fixation on the QTP accounted for 12.7%, 13.9%, and 14.2% of the total area, respectively. The core water conservation areas are mainly the southeastern QTP, Sanjiangyuan, and Naqu, while the core windbreak and sand fixation areas were concentrated in the central and western parts of the Plateau. The core soil conservation areas surrounded the entire interior of the Plateau. (3) From 2000 to 2020, the water conservation, soil conservation, and windbreak sand-fixation function on the QTP had higher stability in the southeastern and central parts, while stability was lower in the western region. Considering the stability assessment and ecological protection and restoration practices, the QTP can be divided into three major categories and 16 ecological functional zones. Differentiated ecological protection and restoration efforts can be implemented based on the different core ecosystem functions and zoning.

Cities are the key areas for human beings to achieve sustainable development goals in the future. Estuarine cities are a special type of coastal city in urgent need of a clear definition. This paper proposed that estuarine cities are cities developed on the coast where rivers and oceans meet and defined four connotations, including the intersection of rivers and marine water systems, the coordinated development of land and oceans, the location advantages of connecting rivers and seas, and the important fragility of the ecological environment. We used HydroSHEDS, OSM, GPW, and urban socioeconomic statistics and selected 50 estuarine cities with large rivers as representatives to summarize the main geographical basis and socioeconomic characteristics. Cities are primarily found in low-altitude, flat regions with average annual temperatures that mainly vary from 10°C to 25°C, relatively abundant precipitation, and extensive biological resources. There are substantial variations in the socioeconomic features of estuarine cities. We proposed eight development patterns, including open and inclusive city spirit, high-quality livable cities, high-quality development driven by innovation, integration of internal and external communication with ports and cities, construction of an international financial center, ecological environment protection and restoration, active promotion of cultural tourism, and positive international exchanges.

In the context of global warming, escalating water cycles have led to a surge in drought frequency and severity. Yet, multidecadal fluctuations in drought and their multifaceted influencing factors remain inadequately understood. This study examined the multidecadal changes in drought characteristics (frequency, duration, and severity) and their geographical focal points within China’s north-south transitional zone, the Qinling-Daba Mountains (QDM), from 1960 to 2017 using the Standardized Precipitation Evapotranspiration Index (SPEI). In addition, a suite of eight scenarios, correlation analysis, and wavelet coherence were used to identify the meteorological and circulation factors that influenced drought characteristics. The results indicate the following: (1) From 1960 to 2017, the QDM experienced significant interdecadal variations in drought frequency, duration, and severity, the climate was relatively humid before the 1990s, but drought intensified thereafter. Specifically, the 1990s marked the period of the longest drought duration and greatest severity, while the years spanning 2010 to 2017 experienced the highest frequency of drought events. (2) Spatially, the Qinling Mountains, particularly the western Qinling Mountain, exhibited higher drought frequency, duration, and severity than the Daba Mountains. This disparity can be attributed to higher rates of temperature increase and precipitation decrease in the western Qinling Mountain. (3) Interdecadal variations in droughts in the QDM were directly influenced by the synergistic effects of interdecadal fluctuations in air temperature and precipitation. Circulation factors modulate temperature and precipitation through phase transitions, thereby affecting drought dynamics in the QDM. The Atlantic Multidecadal Oscillation emerges as the primary circulation factors influencing temperature changes, with a mid-1990s shift to a positive phase favoring warming. The East Asian Summer Monsoon and El Niño-Southern Oscillation are the main circulation factors affecting precipitation changes, with positive phase transitions associated with reduced precipitation, and vice versa for increased precipitation.

Ecosystem services in urban agglomerations are the environmental conditions under which human survival and development are sustained. Quantitative assessment of ecosystem services and complex interactions can contribute positively to the achievement of the Sustainable Development Goals (SDGs) for urban agglomerations. However, studies on the future contribution of multi-scenario ecosystem services to the SDGS are lacking. We propose novel integrated modeling framework that integrates the CLUES, InVEST, SOM, and GWR approaches to address the complex relationship between ecosystem services over a long “past-present-future” time series. We construct a novel ecosystem service bundle-based approach for measuring urban agglomerations progress towards achieving ecologically relevant sustainable development goals at multiple scales. In the future scenario, the water yield (WY), habitat quality (HQ), and soil conservation (SC) show similar spatial patterns, with comparable spatial grids, while carbon stock (CS) remains predominantly unchanged and the ecological protection scenario (EPS) improves more significantly. The high-synergy regions are mainly distributed in bundle 4, and most of the trade-off regions appear in bundles 1 and 2. Over the last 30 years, all but the water-related SDGs are declining in bundle 1 of the two urban agglomerations, which are 15% higher in the Guangxi Beibu Gulf (GBG) than in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). From 2020 to 2035, the three scenarios demonstrate that the optimization of the SDGs progresses most effectively under the future ecological protection scenario (EPS). In particular, bundles 3 and 4 are significantly improved. This critical new knowledge can be used in sustainable ecosystem management and decision-making in urban agglomerations.

Quantitative assessments of the impacts of climate change and anthropogenic activities on runoff help us to better understand the mechanisms of hydrological processes. This study analyzed the dynamics of mountainous runoff in the upper reaches of the Shiyang River Basin (USRB) and its sub-catchments, and quantified the impacts of climate change and human activities on runoff using the improved double mass curve (IDMC) method, which comprehensively considers the effects of precipitation and evapotranspiration on runoff, instead of only considering precipitation as before. The results indicated that the annual runoff depth in the USRB showed a slightly increased trend from 1961 to 2018, and sub-catchments were increased in the west and decreased in the east. The seasonal distribution pattern of runoff depth in the USRB and its eight sub-catchments all showed the largest in summer, followed by autumn and spring, and the smallest in winter with an increasing trend. Quantitative assessment results using the IDMC method showed that the runoff change in the USRB is more significantly affected by climate change, however, considerable differences are evident in sub-catchments. This study further developed and improved the method of runoff attribution analysis conducted at watershed scale, and these results will contribute to the ecological protection and sustainable utilization of water resources in the USRB and similar regions.

Construction land is the leading carrier of human activities such as production and living. Evaluating the construction land suitability (CLS) on the Qinghai-Tibet Plateau (QTP) holds significant implications for harmonizing the relationship between ecological protection and human activity and promoting population and industry layout optimization. However, no relevant studies provide a complete CLS assessment of the QTP. In this study, we developed a model-based CLS evaluation framework coupling of pattern and process to calculate the global CLS on the QTP based on a previously developed CLS evaluation model. Then, using the land-use data of 1990, 2000, 2010, and 2020, we examined the adaptability of existing construction land (ECL) to the CLS assessment result through the adaptability index and vertical gradient index and further analyzed the limitations of maladaptive construction land. Finally, we calculated the potential area of reserve suitable construction land. This article includes four conclusions: (1) The highly suitable, suitable, moderately suitable, marginally suitable, and unsuitable CLS classes cover areas of 0.33×10⁴ km², 10.42×10⁴ km², 18.06× 10⁴ km², 24.12×10⁴ km², and 205.29×10⁴ km², respectively. Only approximately 11% of the study area on the QTP is suitable for large-scale permanent construction land, and approximately 79.50% of the area is unsuitable under current economic and technological conditions. (2) The ECL adaptability index is 85.16%, 85.93%, 85.18%, and 78.01% during 1990-2020, respectively, with an average adaptability index exceeding 80% on the QTP. The ECL distribution generally conforms to construction land suitable space characteristics but with a significant spatial difference. (3) From 1990 to 2020, the maladaptive ECL was dominated by rural settlement land, transport land, and special land, with a rapidly increasing proportion of urban and other construction land. The maladaptive ECL is constrained by both elevation and slope in the southern Qinghai Plateau, the Hengduan Mountains, and the Qilian Mountains. In contrast, elevation is significantly more limiting than slope in the northern Tibet Plateau, the Gangdis Mountains, and the Himalayan Mountains. (4) The potential area of reserve suitable construction land is 12.41×10⁴ km², accounting for 4.81% of the total land area of the QTP, and the per capita area is 9928 m². Regions of Qaidam Basin, Gonghe Basin, and Lhasa-Shannan Valley have the richest and most concentrated land resource of reserve suitable construction land. The research results provide spatial decision support for urban and rural settlement planning and ecological migration on the QTP.

The application of ecosystem services (ES) theories in land consolidation is a confusing issue that has long plagued scholars and government officials. As the upgraded version of traditional land consolidation, comprehensive land consolidation (CLC) emphasizes ecological benefits, but it does not achieve the expected effect during the pilot phase. This study first proposed a theoretical analysis framework based on ES knowledge to answer the three key questions of why, where, and how to implement CLC better. Taking mountainous counties as the study area, we found that ES trade-offs/synergies, bundles, and drivers were significantly affected by scale effects. ES knowledge can play a crucial role in designing multi-scale CLC strategies regarding the objective, zoning, intensity, and mode. Specifically, mitigating the significant trade-offs between recreational opportunities, food production, and other ES is the top priority of CLC. Land consolidation zoning based on the ES bundles analysis is more rational and can provide the scientific premise for designing locally adapted CLC measures. Land consolidation can be classified into high-intensity direct intervention and low-intensity indirect intervention modes, based on the major drivers of ES. These findings help narrow the gap between ES and CLC practices.

Reference crop evapotranspiration (ET₀) is essential for determining crop water requirements and developing irrigation strategies. In this study, ET₀ was calculated via the FAO-56 Penman‒Monteith model, and the spatiotemporal variations in ET₀ over China from 1960 to 2019 were analyzed. We then quantified the contributions of five driving factors (air temperature, wind speed, relative humidity, sunshine hours, and CO₂ concentration) to the ET₀ trends via a detrending experiment. The results revealed that nationwide ET₀ showed no significant (p>0.05) decreasing trend from 1960 to 2019, with a trend of -8.56×10^-2 mm a^-2. The average temperature and wind speed were identified as the dominant factors affecting ET₀ trends at the national scale. The contributions of the driving factors to the ET₀ trends were ranked in the following order: average temperature (21.3%) > wind speed (-15.63%) > sunshine hours (-11.99%) > CO₂ concentration (6.36%) > relative humidity (3.58%). Spatially, the dominant factors influencing the ET₀ trends varied widely. In the southeastern region, average temperature and sunshine hours dominated the trends of ET₀, whereas wind speed and average temperature were the dominant factors in the northwestern region. The findings provide valuable insights into the dominant factors affecting ET₀ trends in China and highlight the importance of considering different driving factors in calculating crop water requirements.