Search Results (1,017)

With urbanization transforming from scale expansion to high-quality development and the increasing prominence of the ecological environment constraints of drainage basins, systematically identifying the mechanism of action of non-point source pollution from a high-quality development perspective is significant for coordinating urban development and environmental protection. Based on remote sensing data on atmospheric pollution and multi-source spatial big data such as nighttime light (NTL), LandScan population, point of interest (POI), and land use data from 2013 to 2025, this study applies methods including deposition flux analysis, deep learning fusion, bivariate spatial autocorrelation, and geographically weighted regression (GWR) to empirically analyze the spatiotemporal evolution characteristics, spatial correlation, and local impacts of high-quality urban development on non-point source pollution in the Chenghai drainage basin. We find that, firstly, non-point source pollution and high-quality urban development in the Chenghai drainage basin both present significant stage-specific and spatial heterogeneity. In other words, the two are not mutually independent spatial elements in space; instead, they are closely and significantly correlated, with their correlation types showing obvious spatial agglomeration characteristics. Secondly, the impact of high-quality urban development on non-point source pollution evolves in stages. It gradually shifts from a whole-region, homogeneous, strongly positive driving force to spatial differentiation. Specifically, from 2013 to 2017, the whole-region regression coefficients are generally greater than 0.5, meaning that urban development represents a strong, whole-region driving force promoting pollution. However, after 2017, this impact evolves into a stable spatial differentiation pattern. It mainly shows that the northern urban core area, where coefficients are greater than 0.5, maintains a continuous strong positive driving force. Meanwhile, the peripheral area, where coefficients are generally lower than 0, creates a negative inhibition effect. Based on the above rules, further analysis shows that the impact of high-quality urban development on non-point source pollution is absolutely not a simple linear relationship. Instead, it is a result of the coupling effect of multiple factors, including development stage, spatial location, and governance level. Therefore, to positively affect the ecological environment through high-quality development, model transformation and precise governance are essential. The findings of this study deepen our understanding of the transformation of urban development models and the response mechanism of non-point source pollution. They also provide a scientific basis and decision support for promoting the coordinated governance of high-quality urban development and non-point source pollution by region and stage in plateau lake drainage basins, as well as for improving the sustainable development of drainage basins. Full article

The automatic extraction of seismic reflection events is fundamental to seismic interpretation and structural identification in oil and gas exploration, particularly for large-scale regional surveys and preliminary basin-scale assessments. Although the B-COSFIRE (Bar-Combination of Shifted Filter Responses) method has demonstrated strong capability in detecting ridge-like structures, its application in large-scale seismic processing is limited by high computational cost and complex filter bank configuration. Conventional edge detectors such as the Canny operator are computationally efficient but often produce fragmented and noise-sensitive results in low signal-to-noise ratio (SNR) seismic data because they rely solely on local gradient information and ignore the spatial continuity of geological horizons. To overcome these limitations, this study proposes a lightweight and computationally efficient framework for rapid seismic event extraction. The method simplifies the B-COSFIRE architecture by replacing its configurable filter bank with a Difference-of-Gaussian (DoG) operator, which enhances ridge-like reflection features while suppressing background interference through a center–surround mechanism. Furthermore, a Spatial Consistency Constraint (SCC) module is introduced to enforce lateral continuity using directional morphological closing operations. This strategy reconstructs disrupted reflection segments and converts isolated detection responses into spatially coherent linear structures. Adaptive thresholding and skeletonization are then applied to obtain single-pixel-wide reflection contours suitable for geological interpretation and regional structural analysis. The proposed method was evaluated using both synthetic seismic models (Ricker wavelet convolution with Gaussian noise, σ = 0.15) and real post-stack seismic profiles characterized by low SNR conditions. Experimental results demonstrate that the proposed method achieves a Precision of 0.9527, Recall of 1.0000, and F1-score of 0.9758 on synthetic data, outperforming both the standard Canny detector (F1: 0.8972) and B-COSFIRE (F1: 0.7311). The Continuity Index reaches 261.00 pixels, substantially higher than Canny (223.67 pixels) and B-COSFIRE (66.86 pixels). Notably, B-COSFIRE exhibits a severely imbalanced detection profile (Precision: 0.5762, Recall: 1.000), indicating excessive false positives that undermine its practical utility. The proposed method additionally achieves the lowest runtime (0.024 s per profile), representing a 44× speedup over B-COSFIRE (1.039 s), while requiring no training data. Overall, the proposed framework provides a practical and efficient solution for automated seismic event extraction. With only a small number of geologically interpretable parameters and strong robustness across different datasets, the method is well-suited for large-scale seismic data processing and preliminary structural assessment in underexplored regions, enabling rapid first-pass evaluation of extensive survey areas before detailed interpretation and reservoir characterization. These characteristics make the method particularly suitable for computer-assisted interpretation workflows in industrial oil and gas exploration. Unlike prior approaches that treat seismic event extraction as a generic edge detection problem, the proposed framework explicitly encodes geological prior knowledge—specifically, the lateral continuity of stratigraphic interfaces—as a morphological constraint, bridging the gap between image processing methodology and geophysical interpretation requirements. Full article

To address severe mine pressure disasters induced by the coupling of mining-induced dynamic stress and impact disturbance during close-distance coal seam mining, this paper takes the No. 8 and No. 9 close-distance coal seams in the 119 mining area of a coal mine in Ningxia, China, as the engineering background. Theoretical analysis and FLAC^3D numerical simulation methods were adopted to systematically study the evolution of overburden structure, the manifestation law of mine pressure caused by mining disturbance, and the dynamic response mechanism of roadway surrounding rock under impact load. The findings demonstrate: ① Based on key block theory and elasticity mechanics theory, the stress transfer mechanism of the complete bearing type overburden rock in close-range coal seams was clarified. The calculation model of floor plastic zone depth and additional stress was derived, and the influence mechanism of the bearing state of interlayer rock strata on the stability of underlying coal seam roadways was revealed. ② Comparative numerical simulations of mining schemes revealed that both schemes formed a “goaf pressure relief-workface-coal pillar” load-bearing configuration with “upward subsidence and downward bulging” basin-shaped settlement. Scheme A exhibited significantly increased stress peaks and interlayer plastic zones due to repeated mining-induced stress, substantially elevating the risk of strong mine pressure manifestation and surrounding rock instability. ③ Under 8 MPa cosine impact load with a vibration frequency of 50 Hz (peak particle vibration velocity of 9.57 m/s), compared with the unsupported roadway, the bolt–cable collaborative support system reduced the peak displacement of surrounding rock by over 35% and decreased the shock wave propagation velocity by more than 40%, effectively suppressing the expansion of plastic zones and the transfer of impact energy, while significantly enhancing the impact resistance of the roadway. This study not only provides a systematic theoretical basis for close-distance coal seam mining and rock burst prevention but also offers scientific guidance and technical reference for surrounding rock control and dynamic disaster prevention of roadways in similar close-distance coal seam mining projects, which is of important engineering value for ensuring the safe and efficient mining of underground coal resources. Full article

Precipitation is a fundamental element in terrestrial water circulation and ecosystem hydrological balance. The occurrence of concentrated precipitation is closely linked to vegetation growth and soil fertility rather than accumulated or averaged precipitation. Despite its importance, the characteristics of continuous precipitation and its specific effects on vegetation cover remain uncertain. In this study, we formulated a new continuous precipitation index system, including $C{P}_d$ (continuous precipitation days); $AC{P}_t$ (annual continuous precipitation times); $C{P}_a$ (continuous precipitation amount); and $FCP$ (frequency in different ranges of $AC{P}_a$). We utilized daily precipitation data from 467 meteorological stations across China, which were divided into eight vegetation type regions. We observed that the spatial distribution of continuous precipitation differed to varying degrees from accumulated precipitation. The national average of $MAC{P}_a$ for a single event was 16.7 mm, ranging from 3.8 mm in the temperate desert region to 37.1 mm in the tropical monsoon forest and rainforest region. Similarly, the national average of $MC{P}_d$ ($MMC{P}_d$) for a single event was approximately 2.3 or 9 days. At the regional level, the tropical monsoon forest and rainforest region experienced the longest $MMC{P}_d$. Furthermore, the national average of $MAC{P}_t$ occurrences for 1 year was 57.7 times, varying from 29.8 times in the temperate desert region to 77.9 times in the tropical monsoon forest and rainforest region. Vegetation responses to precipitation regimes exhibit significant regional heterogeneity across China. Our analysis reveals that $MAC{P}_t$ and $M{P}_a$ show markedly positive correlations with vegetation growth. In subtropical monsoon climate zones, particularly the Yunnan–Guizhou Plateau and Qinling Mountains, $MAC{P}_t$ demonstrates strong positive correlations (r = 0.6–1.0) with NDVI, where sustained rainfall provides stable moisture availability for vegetation. While a positive correlation between vegetation (NDVI) and mean annual consecutive precipitation is observed in some arid northern regions, in ecosystems such as the Loess Plateau (TG/TM), vegetation growth shows greater dependence on $M{P}_a$, highlighting the crucial role of total precipitation amount in water-limited ecosystems. Notably, extreme precipitation events display dual effects on vegetation dynamics. Prolonged heavy rainfall ($MMC{P}_d$/$MMC{P}_a$) exhibits significant negative impacts on NDVI (r = −1.0 to −0.6) in topographically complex regions, including the Hengduan Mountains and Yangtze River Basin (SE), likely due to induced soil erosion and waterlogging stress. Our findings underscore the importance of incorporating continuous precipitation indices to evaluate and forecast the influence of precipitation on ecosystem stability. This understanding is vital for developing informed conservation and management strategies to address current and future climate challenges. Full article

Natural hydrogen is regarded as a potential resource for the global energy transition, and its accumulation is closely linked to water–rock reactions involving Fe²⁺ bearing minerals and effective sealing conditions. The Liaohe Basin, located on the northeastern margin of the North China Craton within a key metallogenic belt, is surrounded by sedimentary-metamorphic iron deposits and is a potential area for natural hydrogen accumulation. In this study, aeromagnetic and satellite gravity data were integrated to estimate basement depth through gravity interface inversion, followed by three-dimensional magnetic susceptibility and density inversion and structural–mineralization correlation analysis. The results reveal strong basement heterogeneity. Iron-rich anomalous bodies show clustered and belt-like to dome-like distributions, mainly along the transitional zone between deep depressions and basement uplifts. Combined density–magnetic zonation suggests that high-density, high-magnetic units may correspond to iron-rich bodies, whereas high-magnetic, low-density units likely indicate fractured and altered fluid pathways. Based on the measured results of surface hydrogen concentration, it is inferred that the high magnetic anomaly in the uplift transition zone at the edge of the depression might be the coupling area of iron-rich rock bodies and channel zones, which is the priority response area of natural hydrogen in the Liaohe Basin, China. Full article

Sediment accumulation in reservoirs represents a critical challenge for sustainable water resources management in semi-arid regions. In Jordan, accelerated sedimentation threatens the operational capacity of major dams, including the King Talal Dam (KTD), which serves as a key water resource in the Amman–Zarqa Basin (AZB). This study assesses sediment yield and erosion risk at the catchment scale using the Soil and Water Assessment Tool (SWAT) integrated with the Modified Universal Soil Loss Equation (MUSLE). The AZB was subdivided into 31 sub-basins and 586 Hydrological Response Units (HRUs) based on land use, soil characteristics, topography, and slope. The model was calibrated for the period 1993–2002 and validated for 2003–2012 using hydrological and sediment observations from 17 monitoring stations. Long-term simulations covering more than two decades were conducted to quantify spatial and temporal sediment yield patterns across the basin. Results indicate a mean annual sediment yield of 2.79 t ha⁻¹ yr⁻¹, corresponding to approximately 0.59 MCM yr⁻¹ of sediment inflow to the reservoir. These estimates closely agree with bathymetric survey results reported by the Jordan Valley Authority, which indicate sedimentation rates of 2.59 t ha⁻¹ yr⁻¹ (0.55 MCM yr⁻¹). Overall, the model demonstrates strong agreement between observed and simulated sediment loads, confirming its reliability for sediment dynamics assessment. The findings are relevant to Sustainable Development Goals (SDGs) 6 (clean water and sanitation) and 15 (life on land) by informing sustainable watershed and soil erosion management practices. Full article

Accurately quantifying vertical sediment transport rates in large seaward rivers is vital for estimating basin-scale water and sediment fluxes and assessing riverbed evolution. Traditional multi-point velocity and suspended sediment concentration (SSC) measurements are costly and slow, hindering long-term online monitoring. Bidirectional flows in tidal reaches further exacerbate this challenge. We propose a physics-constrained support vector machine (SVM) inversion method to estimate vertical sediment transport rates from single-point measurements. Constrained by modified logarithmic velocity and Rouse suspended sediment concentration profiles, it quantitatively relates single-point hydraulic variables to key parameters governing vertical distributions. Lower Yangtze River tidal reach field data validate the hybrid model’s successful reconstruction of vertical distributions. It accurately captures transient sediment responses across maximum flood and ebb. Inverted transport rates match measurements closely (RMSE = 0.085, NSE = 0.969, PBIAS = 2.50%) and exhibit strong cross-site generalization. Sensitivity analysis identifies 0.4 times the water depth above the riverbed as the optimal single-point sensor position. Although currently validated only in the lower Yangtze River, this low-cost, reliable method supports local basin management, flood control, and disaster mitigation by enabling continuous sediment flux monitoring. However, applying it to other river or estuarine systems may require recalibration or retraining to adapt to different local conditions. Full article

Water scarcity in semi-arid closed-basin systems is increasingly driven by hydrological and land transformation processes. This study integrates multi-temporal remote sensing and physicochemical data to examine spatio-environmental drivers of surface water decline in Lake Manyara. Normalized Difference Water Index (NDWI) maps derived from dry-season Landsat imagery (July 2015 and July 2025) were used to quantify surface water dynamics, while supervised Maximum Likelihood land use/land cover (LULC) classification provided a characterized existing spatial context of the study area. Physicochemical parameters derived from recent field observations were evaluated using Carlson’s Trophic State Index (TSI). Results indicate a 31.7% reduction in dry-season surface water extent, from 232.4 km² in 2015 to 158.7 km² in 2025, accompanied by a marked spectral shift toward more negative NDWI values, reflecting extensive lakebed exposure. Agricultural expansion and bare land surfaces were spatially associated with stronger negative NDWI patterns (r ≈ −0.64, p < 0.05). Water quality assessment revealed extreme hypereutrophic conditions (TSI = 98.07), characterized by elevated phosphorus, nitrate, and chlorophyll-a, and high ionic concentrations. The findings demonstrate that hydrological contraction, eutrophication, and catchment land transformation are interconnected processes intensifying water scarcity in semi-arid lake systems. Full article

Riparian areas serve as critical hotspots of biodiversity, and understanding the spatial pattern of species distribution is essential for biodiversity conservation. However, the mechanism underlying species distribution remains an unsolved topic in ecology. To address this knowledge gap, we examined the spatial pattern of riparian herbaceous community structure along a large temperate river (i.e., the Liaohe River) in China, and aimed to determine how the relative roles of climate, local habitat, and spatial factors in shaping plant community structure vary across different geographical regions. Our findings indicate that climate, local habitat, and spatial factors jointly influence herbaceous community structure. Specifically, precipitation and temperature significantly affected species richness in most regions of the Liaohe River basin. Notably, precipitation exhibited a negative relationship with species richness along the West Liaohe River, whereas it showed a positive association along the left tributaries of the Liaohe Mainstream. Spatial factors explained a larger proportion of variations in herbaceous community composition than climate and local habitat along the West Liaohe, East Liaohe, and Taizihe Rivers. Although local habitat explained a small fraction of variations in herbaceous composition in most geographical regions, it emerged as key drivers along the Liaohe Mainstream. In conclusion, the relative roles of climate, local habitat, and spatial factors in structuring riparian herbaceous communities were not determined by spatial extent, but were closely tied to the environmental context, including climate and human disturbance. Full article

Deep brines represent important sources of strategic resources such as lithium and potassium, characterized by low exploration costs and high utilization rates. The Triassic strata in the Sichuan Basin contain abundant lithium- and potassium-rich brines, and understanding their origin is essential for exploring similar deposits. This study integrated field sampling and published data to systematically analyze the brines through hydrochemical testing, statistical methods, and water–rock reaction experiments, providing a comprehensive genetic interpretation based on hydrochemical features, element correlations, and characteristic coefficients. The results indicated that the brines are of the Cl–Na type, and both the sodium–chloride and chloride–bromide coefficients are consistent with a marine origin. Evapo-concentration was identified as the main controlling factor for ion enrichment, with subordinate influence from atmospheric precipitation. The common source of Ca²⁺ and Mg²⁺ likely includes the widespread marine carbonate rocks and/or the alteration of Ca–Mg-bearing silicate minerals (e.g., in green bean rocks or detrital layers) during brine–rock interaction. The desulfation coefficient indicated that lithium enrichment depends on a closed reducing environment, while potassium enrichment shows minimal correlation with brine confinement. Leaching experiments confirmed that green bean rocks serve as a key effective source rock for lithium and potassium, with elemental leaching efficiency positively correlated with fluid salinity. Based on these findings, a “dual-recharge” genetic model is proposed: paleo-marine brines undergoing deep circulation and meteoric water infiltrating along tectonic fractures collectively leached lithium and potassium from the green bean rocks, providing abundant lithium and potassium to the deep brines. This study refines the metallogenic mechanism of lithium- and potassium-rich brines in the Triassic Sichuan Basin and provides guidance for regional brine mineral exploration. Full article

Water dynamics and nutrients are widely recognized as the main triggers of phytoplankton blooms. These factors may control the stability of marine ecosystems. Penzhina Bay and the Shelikhov Gulf are famous for their high tidal dynamics in comparison with the basins of the World Ocean and for being the feeding places of Bowhead whales. Here, we study the dynamics and thermohaline structure of water; nutrients; isotopic signatures of δ¹⁵N–$\mathrm{N}{\mathrm{O}}_3^{-}$ and δ¹⁸O–$\mathrm{N}{\mathrm{O}}_3^{-}$; as well as chlorophyll a in Penzhina Bay, the Shelikhov Gulf, and the Penzhina River to understand the features of an ecosystem with intense tidal dynamics in the subpolar region. This work is based on data obtained in three cruises of the R/V “Akademik Oparin” in the period from 2023 to 2025, with speed boat observations in the Penzhina River from May to October, including the flooding peak in June. The observations covered cases with tides from 7 to 13.4 m in height. The interaction between tides and river runoff was observed to supply dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphorus (DIP) from the sea and dissolved silicate (DSi) from the river. The “white nights” in July, combined with the increased supply of nutrients, are good conditions for phytoplankton blooms, and as a result, the concentration of chlorophyll a in the study area was observed to be up to 39 µg/L. High primary production supports the food chain, and this is probably the main reason why Bowhead whales come to feed in the summer. The DIN/DIP ratio indicates DIN as a limiting factor in most of Penzhina Bay and throughout the Shelikhov Gulf. At the same time, the DSi/DIP ratio at a significant distance from the mouth of the Penzhina River is close to 0, indicating unfavorable conditions for diatoms. The DSi limit can cause the blooming of dinoflagellates, which sometimes occurs in this region. Full article

Deep shale gas reservoirs in the southern Sichuan Basin (Weiyuan area) exhibit strong heterogeneity and complex pore-fracture networks. Traditional reservoir evaluation methods struggle to accurately capture their microscale pore characteristics and fracability, thereby restricting efficient development and precise sweet spot prediction. Therefore, integrating digital core technology with geological analysis is essential to systematically quantify key reservoir parameters, including microscale pore structure, mineral composition, and brittleness characteristics. To clarify the controlling factors of high-quality deep shale gas reservoirs in the Weiyuan area and assess their exploration and development potential, we performed digital core analysis at micron to nanometer scales. Three-dimensional digital core models of representative deep shale gas wells were constructed. Integrating mineral composition, geochemical characteristics, and pore space features, we discuss the geological conditions for deep shale gas accumulation and the fracability of horizontal wells, and we delineate favorable shale reservoir zones. The results show that digital core technology enables quantitative and visual characterization of each sublayer of the Longmaxi Formation shale reservoir, including mineral types, laminae types, pore-throat structures, and organic matter distribution. From the Long 11-1 sublayer to the Long 11-4 sublayer, the pore-throat radius, total pore volume, total throat volume, connected pore-throat percentage, and coordination number all gradually decrease. In the eastern Weiyuan area, the siliceous components in deep shale gas reservoirs at the base of the Longmaxi Formation are primarily of both biogenic and terrigenous origin. Due to local variations in the sedimentary environment, terrigenous input contributes significantly to the total siliceous content in this region. Although the Long 11-1 sublayer of the Longmaxi Formation is lithologically classified as mud shale, its particle size and mineral composition more closely resemble those of clayey siltstone or argillaceous sandstone, suggesting considerable potential for reservoir space development. Typical wells in the eastern Weiyuan area exhibit distinct lithological characteristics, including coarser grain sizes, stronger hydrodynamic conditions during deposition, and abundant terrigenous clastic supply. The rigid framework formed by silt- to sand-sized particles effectively mitigates compaction, thereby facilitating the preservation of intergranular pores and microfractures. High organic matter abundance, appropriate thermal maturity, and a considerable thickness of high-quality shale ensured sufficient hydrocarbon supply. The main types of natural fractures are intergranular and grain-edge fractures formed by differences in sedimentary grain size, and bedding-parallel fractures generated by hydrocarbon generation overpressure. Based on reservoir mineral composition, pore characteristics, areal porosity, and pore size distribution identified via digital core analysis, the bottom 0–3 m of the Long 11-1 sublayer is determined to be the optimal target interval. By delineating the microscopic characteristics of the shale reservoir and predicting rock mechanical parameters, a fracability evaluation index was established from digital core simulations. This guides the selection of target layers in deep shale gas reservoirs and optimizes hydraulic fracturing design. Full article

Accurately assessing dynamic water resource carrying capacity (WRCC) is essential and challenging, particularly in regions like the Gansu sections of the Yellow River Basin (GSYRB), a core water source protection zone in the arid northwest of China, due to its pressing challenge of balancing water resources for socioeconomic needs and ecological security. This study proposes a novel integrated computational assessment framework named SD-VIKOR to address the complexities arising from nonlinear interactions within the “water resources–socioeconomic–ecological environment” (W–S–E) system. The core of this framework is the tight coupling of a system dynamics (SD) simulation model with a VIKOR multi-criteria evaluation module, where indicator weights are objectively–subjectively determined via an Analytic Hierarchy Process (AHP)–entropy weight method. This integrated SD-VIKOR engine enables dynamic, scenario-based WRCC trajectory simulation. To move beyond simulation and enable mechanistic insight, the framework further incorporates a diagnostic suite: a Geodetector module quantifies dominant drivers and their interactions; an obstacle degree model pinpoints key limiting factors; and a coupling coordination degree model evaluates subsystem synergies. Together, they form a closed-loop “dynamic simulation → multi-criteria assessment → driving mechanism analysis and constraint diagnosis → subsystem coordination analysis” workflow. Applied to the GSYRB from 2012 to 2030 under five development scenarios, the framework demonstrated high efficacy. It successfully captured path-dependent WRCC evolution, revealing that the ecological-priority scenario (B2), which shifts system drivers from economic-scale expansion to resource-efficiency and environmental governance, yielded optimal WRCC and the highest system coordination. In contrast, business-as-usual and single-minded economic expansion scenarios underperformed. Six key obstacle factors were quantitatively identified, linking WRCC constraints to natural endowments, economic patterns, and domestic demand. The results reveal pronounced spatial–temporal heterogeneity in WRCC across the GSYRB, with socioeconomic development, water resource use efficiency, and ecological conditions acting as the primary joint drivers of WRCC evolution. Critically, several key indicators are identified as persistent constraints on regional water sustainability. In contrast to conventional static evaluations, the integrated framework captures the complex dynamics and multi-subsystem interactions governing WRCC, offering a more robust diagnostic of resource–environment systems. These insights provide a transferable analytical basis for designing sustainable water management strategies in arid river basins. Full article

The Tianshan–Pamir mountain region, serving as the core “water tower” for countries in Central Asia east of the Aral Sea, is a critical bulwark for sustaining downstream socioeconomic systems. However, constrained by complex topography and harsh climatic conditions, this region suffers from a severe scarcity of long-term, continuous hydrological observation data. This study focuses on a typical data-scarce mountainous area, coupling UAV and satellite imagery-based (e.g., Landsat/Sentinel) flow inversion with a hybrid spatial regionalization method—integrating spatial proximity, basin similarity, and regression-based hydrograph reconstruction—to quantitatively estimate long-term discharge time series. The results indicate that, for the validation of instantaneous discharge inversion, the Nash–Sutcliffe efficiency coefficient (NSE) at 29 river cross-sections was consistently greater than 0.80, with the coefficient of determination (R²) reached 0.94 (p < 0.01). Subsequently, for the long-term discharge series reconstructed using the regionalization method, the NSE values at three representative verification sites—each corresponding to a distinct basin type—were 0.88, 0.84, and 0.86, respectively. These findings exhibit higher precision compared to direct temporal upscaling, confirming the reliability of the regionalization method across varying temporal scales. An analysis of monthly discharge trends from 1989 to 2020 revealed a decreasing trend in the discharge of glacier-dominated rivers, with an average rate of change of −2.89 ± 2.54% (p < 0.05); the Pamir Plateau experienced the largest decline (−4.89 ± 6.58%), which is closely linked to large-scale glacial retreat within the basins. Conversely, the discharge of non-glacier-dominated rivers showed an increasing trend, with a multi-year average rate of change of +0.32 ± 8.43% (n.s.), primarily driven by shifts in precipitation and vegetation cover. This research introduces a new approach for hydrological monitoring in data-scarce regions and provides essential data and methodological support for water resource management decisions in arid zones. Full article

Lycium ruthenicum is a typical desert halophyte with strong stress resistance and high medicinal value in the Tarim Basin. Root endophytic microbes play critical roles in host adaptation, nutrient cycling, and secondary metabolite accumulation. To clarify the diversity patterns of root endophytic bacteria and fungi and their relationships with environmental factors and fruit quality, high-throughput sequencing was used to analyze microbial community characteristics of Lycium ruthenicum collected from different habitats in the Tarim Basin. The results showed that rarefaction curves of alpha diversity indices (Chao1, Shannon, Pielou_e) tended to be saturated, indicating sufficient sequencing depth. Principal coordinate analysis (PCoA) revealed significant habitat-driven differentiation in both bacterial and fungal community structures. Community composition analysis showed that the relative abundance of dominant taxa at the phylum and genus levels differed significantly among sampling sites. Co-occurrence network analysis indicated that bacterial and fungal networks exhibited high modularity and were dominated by positive synergistic interactions, with Pseudomonas, Bacillus, Sphingomonas, Alternaria, and Fusarium as key hub genera. Moreover, root endophytic communities were significantly correlated with climatic variables, soil physicochemical properties, and fruit quality traits, including anthocyanin (AC), proanthocyanidin (PA), total flavonoids (TF), and total polyphenols (TP). Several keystone microbial genera were closely associated with the accumulation of functional metabolites in fruits. This study reveals the biogeographic distribution and co-occurrence characteristics of root endophytes in Lycium ruthenicum and provides a theoretical basis for understanding microbe–host–environment interactions and the quality improvement of desert medicinal plants. Full article