Terraced farmland is a unique agricultural landscape and high-quality farmland resource in mountainous areas, with great production and ecological functions, which makes it a valuable livelihood asset for rural households. As a type of farmland resource, the high-quality of terraced farmland originates from the substantial investment of labor force and materials in land improvement processes such as terracing projects, which results in higher "landesque capital". The economic essence of landesque capital is land appreciation. In recent years, the phenomenon of farmland asset devaluation has been widespread in mountainous areas, yet how the landesque capital value of terraced farmland change remains unclear. Therefore, based on land capital theory, this study clarifies the definition of the landesque capital value of terraced farmland, constructing a comprehensive diagnostic framework from the dual perspectives of land economic productivity and land marginalization. Using data from national rural household surveys and literature synthesis in China's mountainous areas, the study reveals the trends and regional differences of landesque capital value. The findings demonstrate that in recent decades, the landesque capital of terraced farmland in China has devalued, with the trend being particularly pronounced in the eastern region. From 1996 to 2020, the differential rent reflecting the landesque capital value of terraced farmland decreased from 793.2 yuan per ha to 441.88 yuan per ha (a 44.29% drop), based on 1995 constant prices. The grain yield increase effect of terraced farmland relative to sloped farmland has been declining, with the rocky mountainous areas in Northern China showing a more significant downward trend than the Loess Plateau region. The economic benefits derived from the landesque capital of terraced farmland are increasingly unable to cover the costs of maintaining their unique functions. Therefore, it is recommended to actively explore optimal utilization approachs for existing terraced farmland while cautiously implementing new terracing projects in China's mountainous areas.

Border areas have emerged as an important region for global land use change (LUC) due to geopolitical-economic factors. The borderlands of southwestern China, which shares borders with Vietnam, Laos, and Myanmar, serves as the forefront of China's southward expansion of the "Economic Corridor of mainland Southeast Asia". Since the 1980s, China has instituted over 40 geopolitical-economic mechanisms with Vietnam, Laos, and Myanmar, profoundly influencing LUC in borderlands. In this paper, we combine GLC_FCS30 land use data and GDELT news media data to quantitatively assess the impact of geopolitical-economic relations on LUC in the borderlands. The results show that: (1) since 1985, there has been a general expansion of construction land in the borderlands of Southwest China, with cropland reclamation coexisting with abandonment and the conversion of farmland to forests and grasslands. Cropland and forested land have slightly declined along the Vietnam and Myanmar borders, while the Laos border has witnessed a significant retreat of cropland near forests. (2) The geopolitical-economic relations between China and the other Southeast Asian countries have a significant positive impact on the changes of agricultural and construction land in the borderlands, and a significant negative correlation with the changes of forest land; the analysis of the mechanism reflects the fact that the infrastructure construction and the population are the intermediary variables driving the changes of the border land use, and that the intermediary effect is obvious, but the transmission mechanism is heterogeneous for different land use types. (3) With the development of geopolitical-economic relations, the disparity between the scale of agricultural land and construction land in the borderlands of Myanmar, Laos, and Vietnam and that of China is diminishing, and the index of land use similarity on both sides of the borders is increasing to varying degrees. The agricultural land in the China-Myanmar and China-Vietnam borderlands is changing in the direction of the borderlands, while that of the China-Laos borderlands is developing along the border lines. This study offers research perspectives and methodological insights for exploring the human-land relationship in borderlands and fosters the development of border geography.

A comprehensive understanding of the impacts of human activities on the living environment is crucial for achieving harmonious coexistence between humans and nature during modernization on the Qinghai-Xizang Plateau. However, existing research on the dynamics and quantitative relationships between human activities and the living environment of plateaus remains insufficient. We develop an assessment framework to evaluate these impacts based on human activities, ecological conditions, and human settlement data. The spatiotemporal features of human activities and the living environment on the plateau from 2000 to 2020 were then analyzed via models such as the coupling coordination model, geographical detector model, and four-quadrant analysis model; we further identify key factors affecting the living environment and assess the overall impact of human activities. We found that human activity across the plateau has remained relatively low but has increased by 15.41% over the past two decades, primarily in the northern Xizang Plateau and eastern Qinghai-Xizang Plateau. The spatial patterns of the plateau's living environment quality improved from northwest to southeast; 61.14% of the regions remained stable, whereas 18.47% exhibited slight improvements. The coupling coordination between human activity intensity and living environment quality has consistently improved, with areas classified as highly and moderately coordinated increasing by more than 9%. Precipitation and urban-rural construction activities were identified as the primary influencing factors for living environment quality. The impacts of human activities on the plateau's living environment are characterized primarily by coordinated development (40.44%) and development conflicts (38.35%), with smaller areas exhibiting environmental enhancement or synchronous degradation. These findings provide critical insights and a theoretical basis for safeguarding environmental security and promoting high-quality regional development on the plateau.

The origin of civilization marks a milestone in the development of human society. Here, we review the symbols of civilization, analyze the origin and formation of civilizations in high-altitude regions, and preliminarily summarize the meaning of high-altitude civilization and its regional evolution process. The results show that: (1) With prehistoric human colonization of high-altitude regions, 2500 m above sea level, high-altitude civilization formed through the development of agriculture and animal husbandry, social stratification, and the emergence of kingdoms and kingship. (2) The Kingdom of Aksum (Ethiopian Plateau), Tiwanaku and Wari (Andean Altiplano), and Zhang Zhung and Yarlung (Tibetan Plateau) indicate the formation of high-altitude civilization since 80 CE. (3) In high-altitude civilizations, the harsh natural environment and human adaptation were prerequisites; agriculture and nomadism were the basis of origin; external communication and control of trade were the drivers of development; and the emergence of kingdoms and royal states were signs of formation. However, our understanding of high-altitude civilization is still limited by the number of archaeological sites and excavated materials. We expect that future studies will promote understanding of key issues, such as the timing of civilization formation, social responses to climate change, and the role of high-altitude civilizations in global civilization exchange.

The changes in the natural-artificial dualistic water cycle system have triggered the inconsistency of hydrometeorological time series. Continuing to use traditional frequency calculation methods would affect the accuracy of water resource planning and flood-drought management decisions, underscoring the need for (in)consistency testing before performing hydrological calculations. To address the misjudgement issues of current methods, this study proposes a hydrological (in)consistency testing method (CT) based on correlation coefficients. The CT method applies a discrete wavelet transform to extract high-frequency pure random components from the original time series, then calculates the correlation coefficients between these components and the original time series to determine (in)consistency. Statistical experiments indicate that the CT method significantly reduces false positive rates compared with traditional methods like the Bartels test. Its accuracy and stability improve as the time series length increases, making it especially effective at identifying inconsistent time series. These promising results confirm that the CT method is a valuable tool in (in)consistency test, ensuring robust and reliable outcomes. A case study of the surface water resources amount modulus coefficient time series of 10 major river basins in China (1956-2020) shows that surface water resources in the Southeastern, Yangtze, Huaihe, Pearl, and Southwestern river basins are consistent. In contrast, the Songhua, Haihe, Yellow, Liaohe, and Northwestern river basins display pronounced inconsistency characteristics. Existing studies, based on external driving factors such as climate change and human activities, have validated the inconsistency of hydrological time series in regions like the Songhua River Basin, indirectly confirming the effectiveness of the CT method. For consistent time series, consistent hydrological frequency analysis can be directly applied, whereas for inconsistent time series, researchers should analyze the characteristics of inconsistent components or conduct inconsistent hydrological frequency calculations. These approaches aim to predict and plan for potential risks, thereby providing robust support for scientific water resource management decisions.

This study systematically investigates the impact of elevated atmospheric CO₂ on streamflow at the global scale, using control experiments from the TRENDY project, a coordinated ensemble of global dynamic vegetation models. These models incorporate key processes such as vegetation growth, carbon uptake, and water use under changing CO₂ conditions. Our analysis reveals that the majority of global dynamic vegetation models simulate an increase in streamflow under elevated CO₂, driven by vegetation-mediated mechanisms such as reduced stomatal conductance. This effect is particularly pronounced in tropical, cold, and temperate regions. To evaluate the reliability of these modeled responses, we further employed an observational-based approach that isolates CO₂-vegetation-induced streamflow changes using a fully differential method. This method was applied to 1116 catchments that are minimally impacted by human activities. These observational results were then compared with the modeled outputs. Our findings show that most global dynamic vegetation models consistently project increased streamflow under elevated CO₂ levels, which tend to overestimate the magnitude of this increase, especially in temperate forest and cold forest regions as well. Notably, nine out of the fourteen models exhibit an average absolute overestimation exceeding 20% in these catchments. These findings point to notable discrepancies between model simulations and observation-based estimates. They highlight the need to improve and validate global dynamic vegetation models, especially regarding their responses to atmospheric CO₂ changes. Enhancing the reliability of such models is essential for accurate assessments of future water resources and climate change impacts.

A comparative analysis of the brGDGTs distribution, their variations with altitude, and the dispersion in the surface sediments of the Kelan River in the southern Altai Mountains and the adjacent topsoil (all samples were collected in July 2018), indicates that the brGDGTs of the river sediments are primarily derived from autochthonous sources, rather than from allochthonous inputs. The MBT'_5ME index, which is calculated based on brGDGTs and is widely used for temperature reconstruction, shows a variation of only 0.07 in the surface sediments of the Kelan River over a vertical altitudinal gradient of 1735 m (from 702 m to 2437 m). The variation of MBT'_5ME, represents a temperature variation of no more than 2.5 ℃ and is significantly smaller than the actual air temperature variation (around 11.1 ℃), indicating that the MBT'_5ME index in the surface sediments of the Kelan River cannot be used for air temperature reconstruction and is more likely to represent the temperature changes of the river water itself. Since meltwater from ice and snow is a significant water source for the Kelan River, the autochthonous brGDGTs in surface sediments of the river are likely to be strongly influenced by it. Therefore, we propose that in high-altitude or high-latitude regions, the temperature changes in geological archive caused by ice and snow meltwater can directly affect the distribution of autochthonous brGDGTs. This, in turn, impacts the reliability of "air temperature" reconstructions based on brGDGTs indices. This understanding highlights the importance of fully considering the impact of meltwater on sedimentary environment when using brGDGTs for paleotemperature reconstructions, and it provides valuable insights for future brGDGTs-based research in high-altitude or high-latitude regions.

The loess in arid-semiarid regions is facing soil erosion under climate change and human activities. Quantitative assessment of surface erosion in loess region is of great significance for understanding environmental change and achieving sustainable development goal. There is a large area covered by loess in Tajikistan with serious soil loss, but the study is relatively less. Utilizing remote sensing data produced by Landsat 8 and Random Forest algorithm, based on the field investigation and Google Earth Engine (GEE) platform, this study identified the loess accumulation area in Tajikistan, quantitatively studied the temporal and spatial characteristics of surface erosion rate in Tajikistan's loess regions. The loess in Tajikistan is mainly distributed in Afghan-Tajik Basin, along Zarafshan River, and lowlands north of Alai Mountains, covering an area of approximately 37400 km². The RUSLE model was used to evaluate the surface erosion rate in the loess regions of Tajikistan from 1901 to 2023, in which the area of weak erosion accounted for the most 44.96%, 16.68% of the area was near the tolerable erosion rate (250-750 t·km^-2·a^-1 ), and the area of intense erosion or above accounted for 14.25%. Geomorphology has a significant effect on the surface erosion intensity. Erosion rate of loess in plain area is lower, while that of mountain area is higher. The average soil erosion rate from 1901 to 2023 was 1690.99 t·km^-2·a^-1, showing a fluctuating upward trend, and the erosion rate increased by 708.77 t·km^-2·a^-1. The areas with weak and slight erosion are decreasing, while the areas with stronger erosion are increasing. By comparing different loess sedimentary regions in the Northern Hemisphere, it is found that the modern soil erosion rates in the Loess Plateau of China and the Great Plain of the United States are decreasing significantly after the implementation of ecological restoration and soil conservation projects. Therefore, in the case of increasing surface erosion in the loess regions of Tajikistan, appropriate soil and water conservation policies should be formulated and implemented in the study area and other arid-semiarid regions, taking into account both the restoration of the natural environment and the needs of human production and life, so as to achieve the Sustainable Development Goals.

Characterized by its distinct river-lake topology and watershed geomorphology features, the Endorheic Qiangtang Basin is an essential component of the Qinghai-Xizang Plateau (QXP). However, the shortage of high-precision watershed and river system data has hindered a thorough understanding of the hydrological structure and fluvial geomorphology characteristics in this region. With the application of an innovative extraction method, a high-precision watershed and river system dataset within the Endorheic Qiangtang Basin is developed. This dataset enables an analysis of the spatial distribution of endorheic rivers and associated geomorphological features in this region. Furthermore, the spatial correlations between the endorheic river development and watershed geomorphology, climate conditions, and hydrological inputs are systematically examined. The results show that the Endorheic Qiangtang Basin comprises approximately 430 independent sub-watersheds and 1373 endorheic rivers with catchment areas exceeding 50 km². The average length of endorheic rivers is 32.62 km and the erosion base levels predominately concentrate between 4000 and 5000 m in elevation. Based on sub-watersheds as statistical units, the average drainage density is calculated as 0.10 km/km², and the average weighted river longitudinal gradient is 5.56‰. The river longitudinal profiles predominantly display slightly concave to nearly linear shapes throughout the study area. Compared to climate conditions and hydrological inputs, watershed area and geomorphological attributes exert a more significant influence on river development in the Endorheic Qiangtang Basin. A larger watershed area is beneficial to the development of larger river networks and concave river longitudinal profiles, and watersheds with greater elevation drop and gradient have steeper river longitudinal profiles. This study provides insights into the spatial distribution, development characteristics, and influencing factors of the endorheic rivers on the QXP. The findings provide basic data and regularity characteristics of river geomorphology, contributing to further research on earth surface processes of the Qinghai-Xizang Plateau under the background of climate change.

The joint operation of cascade reservoir systems significantly influences river sediment dynamics and geomorphological changes, particularly in downstream hubs that are critical for understanding riverbed channel evolution. This study focuses on a 108 km stretch of the Hanjiang River downstream of the Xinglong Hydraulic Hub, analyzing runoff, sediment, and topographic data from 1977 to 2023. We investigate the characteristics of riverbed scouring/deposition intensity, bar-pool distribution, cross-sectional morphology, flow conditions from normal to low-water levels, and autumn flood processes. The results reveal that: (1) Following the joint operation of the South-to-North Water Diversion Project and the Xinglong Hydraulic Hub, with reductions in runoff and sediment transport of 11.42%-15.40% and 69.2%-73.9%, the proportion of flow levels between 500 m³/s and 800 m³/s at Xinglong Station increased from 21.10% (1980-2013) to 43.12% (2014-2023). (2) From 1977 to 2023, the total erosion volumes in the low-water and bankfull channels from Xinglong to Xiantao reaches were 1.24×10⁸ m³ and 1.57×10⁸ m³, with 78.52% of the riverbed scouring concentrated in the low-water channel. (3) From 1977 to 2016, the riverbed exhibited a "uniform scouring of bars and deep-water channel" pattern, which shifted to a "deep-water channel scouring and lower-bar deposition" pattern from 2016 to 2023, indicating that navigation projects have stabilized the lower-bars and deep-water channel. (4) During 2014-2023, flow conditions from normal to low-water levels showed a decreasing trend downstream of the Xinglong Hydraulic Hub, influenced by riverbed scouring, navigation engineering, and flow processes. This resulted in a synchronous reduction in the differential between normal and low-water levels near the dam and the riverbed in deep-water channel. (5) The decrease in sediment content transport is the primary driver of riverbed scouring in the low-water channel from Xinglong to Xiantao reaches, followed by waterway management project, with runoff having the least impact. During 2016-2023, the contributions of these factors to riverbed scouring were 63.33%, 25.79%, and 10.88%, respectively. Additionally, the relative increase in autumn flood intensity has intensified riverbed scouring. This study enhances our understanding of how the operation of large-scale hydraulic hubs and waterway management projects impact downstream riverbed evolution and water level fluctuations.

Global warming has led to a significant shrinkage of the cryosphere over the Qinghai-Xizang Plateau, affecting the water quality and safety of the river source area. To assess these impacts, 126 river water samples were collected from the Buqu River Basin located at the source of the Yangtze River during June-October of 2021 and 2022. The chemical characteristics and controlling factors of river water were analyzed across different underlying surface basins using methods such as the Piper trilinear diagram, Gibbs diagram, correlation analysis, and the ion ratio assessment. Results indicated that: (1) The total dissolved solids (TDS) values of river water in the study area were higher at the downstream than those of the upstream. The hydrochemical composition differed with varying underlying surface coverages. The Dongkemadi Basin, with a higher proportion of glacier coverage, exhibited Ca²⁺ and HCO₃^- as the primary hydrochemical ions. In contrast, other basins with lower glacier coverage exhibited water chemistry types primarily characterized by HCO₃^-·SO₄^2--Ca²⁺·Mg²⁺and $HC{O}_{3}^{-}$·$S{O}_{4}^{2-}$-Ca²⁺·Mg²⁺·Na⁺. (2) A negative correlation was observed between ion concentration and runoff, likely due to dilution effects. (3) The Gibbs diagram indicated that rock weathering was the primary factor influencing ionic concentration in river water samples. Based on the ion ratio analysis, the Buqu Basin was concluded to be mainly influenced by the weathering of silicate rocks, with contributions from carbonate rocks and sulfuric acid interactions. Furthermore, the railway station basin was mainly influenced by evaporite and carbonate rocks, while the river water in the upstream Dongkemadi Glacier basin was predominantly affected by carbonate rocks. (4) The forward geochemical model calculations revealed that the carbonate rocks accounted for 73.2% of the cation sources in the Dongkemadi Basin, followed by silicate and evaporite rocks, with precipitation showing the least influence. (5) The ionic concentrations of river water at the outlets of the Buqu and Dongkemadi basins exhibited a significant negative correlation with temperature. This indicates that in the context of global warming, changes in glacier permafrost may affect the chemical composition of river water in the cryosphere watershed, and consequently impact the water quality and safety of the river source area. These findings provide a scientific basis for the protection of the ecological environment and the development and utilization of water resources in the river source area.

The correlation between environmental shifts and agricultural progress during the Neolithic and Bronze Ages has garnered significant attention. The Xingyang basin stands out as a pivotal region in the genesis of Chinese civilization and early agricultural practices. Nevertheless, the connection between the spatiotemporal evolutionary trends in Neolithic to Bronze Age agriculture within the Xingyang basin and alterations in hydrogeomorphic environments remains obscure. This study focuses on reconstructing the historical distribution of lakes in the Xingyang basin at four distinct time points (~8000 BP, ~6000 BP, ~4500 BP, and ~3600 BP), utlizing two dated limnological profiles along with age and elevation data sourced from existing limnological records. Subsequently, in conjunction with available plant flotation data, we investigate the interplay between the sptiotemporal distribution patterns of agriculture and hydrogeomorphic conditions. The results show that: (1) Around 8000 a BP, lakes within the Xingyang basin were abundant, peaking approximately 6000 a BP. Subsequently, there was a significant reduction in lake size around 4500 a BP, with further diminishment and fragmengtation into smaller bodies of water by 3600 a BP. (2) During the Neolithic and Bronze Ages, the Xingyang basin adopted an agricultural framework centered on foxtail millet (Setaria italica), broomcorn millet (Panicum miliaceum) and rice (Oryza sativa). Millet-based agriculture prevailed in the surrounding hilly regions throughout the Neolithic and Bronze Ages, while the alluvial plains witneessed a mixed millet-rice cultivation. Nevertheless, transitional zones between the alluvial plains and adjacent hills experienced shifts in crop structure, alternating between millet agriculture and mixed cultivation of millet and rice across different periods. Integration of paleoclimate reconstruction data from neighboring areas reveals that the Yangshao culture era witnessed the most extensive distribution of Holocene lakes in the Xingyang basin. Notably, rice cultivation extended beyond the plains to encompass mountainous regions and certain loess terraces in proximity to the plains, representing the broadest dissemination of rice during the Neolithic-Bronze Ages. The hydrogeomorphic conditions during the Neolithic and Bronze Ages exerted discernible influence on regional agricultural evolution.

Water resources are a crucial component of the water-energy-food (WEF) nexus, making it essential to analyze the pressures faced by the WEF nexus from a water resource perspective. However, few studies have examined how China's interprovincial trade affects local WEF nexus water consumption and pressure from a regional trade viewpoint. This study first accounted for provincial WEF water use inventories and then used multi-regional input-output modeling and SSP-RCP multi-scenario analysis to assess consumption-driven water use, external water pressure contributions and pathways, and future changes in embodied water use in provincial WEF nexus. The results show that the blue water footprint embedded in domestic trade within the national WEF nexus accounts for 43% of water use in the energy and food sectors and 25% of total water withdrawals. Guangdong, Zhejiang, Jiangsu, Henan, and Beijing are the five provincial-level regions (hereafter province) with the highest embodied water flow. With regard to external impacts on water resources, the external contribution to Shanxi's water pressure is primarily driven by the energy sector, while in other provinces, it is predominantly driven by the food sector. Among provinces facing high water pressure, Inner Mongolia, Xinjiang, Gansu, Hebei, Ningxia, and Liaoning have external contributions ranging from 30% to 50%. In most of the cases, water consumption in the energy sector is higher for high-risk provinces than for low-risk ones, while the opposite is true for the food sector. By 2030 and 2050, in various scenarios, the implicit water flow in most provinces will be 1.3 to 1.6 times higher than the baseline, with an increasing trend in high-risk water pressure pathways, especially in the energy sector. This study underscores the primary modes of water pressure transmission in interprovincial trade and explores two-way mitigation measures on both the supply and consumption sides. Indigenous water conservation measures and more rational trade structures in high water-scarce provinces are essential for the integrated management of water resources and the sustainable supply and production of critical resources.

With the advent of the remote sensing big data era, the approach to extracting remote sensing information has shifted from single-image processing to an integrated method that combines spatio-temporal-spectral fusion. In other words, this method emphasizes a "large-scale and fine-grained" processing strategy. At the large-scale level, the complexity of the geographical environment presents challenges for remote sensing imaging, such as "same spectrum, different objects" and "same object, different spectra". Proper zoning can effectively reduce the heterogeneity within regional units, thereby improving the accuracy of remote sensing image classification. At the fine-grained level, remote sensing imaging captures subtle changes in surface features, but the inherent "macro pattern, micro complexity" of geographical environments, lacking top-down global regulation, often leads to significant uncertainty and cognitive biases when relying solely on bottom-up classification from remote sensing data. To address this, the paper proposes a multi-scale remote sensing geographical zoning framework designed to resolve the differences in scale and representation between geographical patterns and remote sensing imaging across macro, meso, and micro levels. Through application examples at these three levels, the study demonstrates that appropriate zoning not only enhances the accuracy of remote sensing information extraction but also enriches the variety of extracted attributes, thereby improving the precision of industry-specific remote sensing applications.

Forests play a key role in maintaining the carbon balance of terrestrial ecosystems, protecting biodiversity, and conserving soil and water. Monitoring forest cover and dynamics is one of the crucial tasks under the "UN Decade on Ecosystem Restoration" and the "UN Sustainable Development Goals". Because of the significant differences in the ecological effects of woody and herbaceous vegetation in forests, distinguishing the area fraction between tree and grass is important. However, it is challenging to quantify the slow and cumulative increase in tree cover during forest recovery. Using China's National Forest Inventory (NFI) as a reference, this study compares 14 types of remote sensing data to analyze the most effective ones in depicting China's forest cover and its changes, including 8 types of hard classification data on land cover and 6 types of tree cover. Results show that high variability existed among various types of forest data in spatial distribution. High uncertainty regions in detecting forest cover among all the 14 datasets were concentrated in regions with tree cover less than 30%, such as western China and the North China Plain. The coefficients of variation in about 96% of pixels in these regions were greater than 0.56. Compared to hard classification data, tree cover data is more consistent with China's NFI. Only a weak gain in China's forests since 2000 is detected by the hard classification data, whereas both NFI and tree cover data indicated significant gains. Among the tree cover data we compared, GLOBMAP data agreed best with provincial-level NFI in detecting forest change (k = 0.78). The findings suggest that tree cover data is able to serve as a reliable data in depicting forest recovery.