Search Results (10,477)

Climate change has intensified extreme hydrological risks, particularly in basins characterized by frequent seasonal streamflow interruptions and discontinuous hydrological records, where traditional process-based models exhibit limited capability for adaptive water resource management. This study develops a hybrid SWAT-LSTM framework that integrates SWAT-derived hydrological variables with meteorological factors and applies SHAP interpretability analysis to quantify dominant drivers and identify threshold inflection points of runoff variability. Using the upper and middle reaches of the Huolin River Basin as a case study, the coupled model outperformed the standalone SWAT model during the test period (NSE: 0.876 vs. 0.710; R²: 0.884 vs. 0.736) and more accurately reproduced extreme flood and drought events. Future projections (2026–2100), driven by the optimized FGOALS-g3 climate model under SSP2-4.5 and SSP5-8.5 scenarios, indicate increasing precipitation, accelerated minimum temperature rise, and a non-stationary runoff pattern characterized by a mid-century decline followed by a late-century increase. The SHAP results reveal strengthened meteorological dominance, particularly for precipitation and minimum temperature, while soil moisture, evapotranspiration, and percolation remain key hydrological controls. The upward shift in the minimum temperature threshold reflects strengthened temperature control on runoff dynamics under warming. The proposed framework improves extreme runoff prediction and provides a quantitative basis for climate-adaptive basin management. Full article

This study systematically examines the low-carbon transition challenges faced by the Yellow River Basin, a core strategic energy base in China with a coal-dominated energy system, under the dual carbon goals. Existing studies based on traditional econometric models or single-province analyses are mostly limited to static analysis, failing to simultaneously capture the nonlinear spatiotemporal evolution, cross-regional spillover effects, and long-term changing trends of carbon emissions in the basin. To fill this gap, this study builds an Energy–Economy–Carbon (EEC) analytical framework, and develops an integrated TFT-ASTGCN deep learning framework. Specifically, we employ the Temporal Fusion Transformer (TFT) for high-precision multivariate time-series simulation and peak forecasting, while the Attention-based Spatial–Temporal Graph Convolutional Network (ASTGCN) is used to identify complex spatial dependencies of inter-provincial emissions. The empirical results confirm that: (1) Basin carbon emissions show significant coal-driven carbon lock-in, with initial decoupling between economic growth and emissions. (2) Most provinces will maintain rising emissions under the current development mode, posing severe challenges to carbon peaking. (3) Asymmetric spatial spillover effects are prominent, underscoring cross-regional collaborative governance as a critical pathway for achieving an early and stable carbon peak in the basin. Full article

Whether and how digital financial inclusion (DFI) is associated with ecological efficiency (EE) is a critical issue for the sustainable development of the Yangtze River Economic Belt (YREB). Based on panel data from 2011 to 2023, this study measures EE using the PCA-Super SBM model, and employs panel fixed-effects models and mediation models to systematically examine the association, mechanisms, and regional patterns of DFI with EE in the YREB. The findings are as follows: (1) DFI and EE exhibit notable spatiotemporal co-evolution characteristics, with the DFI index increasing nearly 14-fold and the EE level rising by approximately 21.5% over the study period. (2) DFI shows a statistically significant positive association with EE improvement; this finding remains robust after various robustness checks. (3) The association between DFI and EE is partially mediated through four pathways: capital allocation optimization, green technological innovation, industrial structure upgrading, and environmental regulation strengthening, among which green technological innovation is the most prominent mediating pathway. (4) Numerically, the association strength varies across functional zones, being higher in the ecological barrier zone (EBZ) and the coordinated development zone (CDZ) than in the high-quality development zone (HQDZ); however, differences in coefficients across zones are not statistically significant and should be interpreted cautiously. Based on these findings, this study proposes policy recommendations including establishing a DFI-EE linkage platform, implementing differentiated functional-zone strategies, and strengthening cross-basin collaborative governance, thereby providing a reference for the green transformation of the YREB. Full article

Seasonal snow cover in mountainous regions represents a critical natural freshwater reserve for arid and semi-arid areas of Central Asia. This study evaluates the long-term (2000–2024) spatiotemporal dynamics of snow cover in the Arys River basin, located within the Western Tien Shan. The research utilizes daily satellite data from MODIS Terra and Aqua, along with data from the MODSNOW automated processing system. Terra-Aqua composite imagery was employed to minimize cloud cover effects. Satellite-derived estimates were validated against observational data from five meteorological stations of the Republican State Enterprise (RSE) “Kazhydromet”. The results indicate significant interannual variability in snow cover extent: the snow-covered area during the cold season ranged from 16.2% to 54.1%, with a mean value of 34.4%. Trend analysis revealed a weak negative trend, while Sen’s slope estimator showed an average annual reduction in snow cover area of 0.37% per year. The most pronounced decline in snow accumulation was observed in mid-elevation mountain zones. These findings suggest potential increased risks to seasonal water availability in the Arys River basin and, more broadly, across the Syr Darya basin under ongoing climate change conditions. The results provide a scientific basis for quantifying climate impacts and developing adaptation strategies for integrated water resources management in Central Asia. Full article

Climate change is modifying the physical structure and biogeochemical functioning of stratified marine systems, with important consequences for trace element (TE) transport, speciation, and exposure. The Black Sea provides a structurally amplified case because restricted exchange, persistent stratification, a basin-scale redoxcline, and extensive shelf-sediment reservoirs intensify climate–contaminant interactions. This review synthesizes mechanistic evidence to develop a climate-informed interpretive framework for TE redistribution under non-stationary environmental forcing. We examine how warming, deoxygenation, hydrological variability, sediment resuspension, acidification, and episodic events alter TE partitioning across dissolved, particulate, sedimentary, and biotic compartments. The synthesis identifies six major redistribution pathways involving surface-layer retention, river plume and suspended particulate transport, shelf-sediment remobilization, redoxcline dynamics, acidification–ligand effects, and event-driven exposure pulses. Together, these processes show that TE patterns increasingly reflect state-dependent internal redistribution rather than external loading alone. To address this shift, we propose a monitoring and risk-interpretation framework that links climate-sensitive state variables to redistribution pathways, integrates multiple matrices, and supports adaptive assessment through trigger-based monitoring escalation. The Black Sea is treated as a structurally amplified reference system for examining climate-sensitive redistribution pathways in stratified basins, although their expression and relative importance remain dependent on basin-specific structural controls. Full article

The Dongchuan District in Kunming City is located in the transition zone between the Yunnan–Guizhou Plateau and the Sichuan Basin. As a region with a copper mining history of over 2000 years, the district has experienced frequent landslides that pose serious threats to human lives, property, and ecological sustainability. Therefore, it is essential to compile a comprehensive landslide inventory and analyze the relationships between landslide spatial distribution and influencing factors for geological hazard prevention. High-resolution remote sensing imagery was interpreted to establish a landslide inventory, based on which the spatial distribution and geometric characteristics of landslides were systematically analyzed. The results show that a total of 1623 landslides were identified, with a total area of 10.36 km². Landslides predominantly occur at elevations of 1000–2000 m, on slopes of 20–45°, with aspects of 255–285°, and relief between 150 and 400 m, in areas with annual rainfall below 825 mm, within 1000 m of rivers and 3000 m of fault lines, and 1000–5000 m of mines. Four landslide clusters were delineated along the Xiao River Fault, highlighting the significant influence of the fault on the spatial distribution of landslides. Most landslides are longitudinal in planform, with travel distances (L) of 50–450 m and heights (H) from 25 to 350 m, both exhibiting allometric scaling with volume. The mean H/L ratio is 0.56 (corresponding to a mean reach angle of 29°), significantly higher than that in Baoshan City (21°). The results provide insights into landslide initiation mechanisms and spatial distribution patterns on the northern margin of the Yunnan–Guizhou Plateau, offering valuable data for landslide hazard assessment and sustainable regional development. Full article

In the context of climate change, the hydrological processes and water resource system vulnerabilities in inland river basins of arid regions are intensifying. Understanding their evolutionary patterns and driving mechanisms is crucial for sustainable water resource management, agricultural development, and the protection of ecological security. This study focuses on the Kaidu River Basin, systematically analyzing the temporal and spatial variations in hydrological cycle elements in the basin from 1998 to 2023 based on multi-source precipitation data, the SWAT hydrological model, and the glacier degree-day model. The study also identifies the main driving factors using a geographic detector. The results show that the SWAT model performs well (calibration period R² and NSE ≥ 0.75, validation period R² and NSE of 0.75 and 0.70, respectively), indicating reliable simulation results. The surface water resources and the contribution of glacier meltwater to runoff in the basin both show a fluctuating downward trend, while potential evapotranspiration increases. The contribution of glacier meltwater during the ablation season decreased from 69.86% in 2014–2016 to 45.01% in 2017–2021. The hydrological processes exhibit a spatial pattern of “mountain areas generating runoff, non-mountain areas consuming water”. The geographic detector results indicate that precipitation is the decisive factor for the spatial differentiation of hydrological processes (influence degree q = 56.9%), with temperature, potential evapotranspiration, and altitude playing important synergistic roles. Moreover, the explanatory power of multi-factor interactions is much greater than that of individual factors. The findings of this study provide a scientific basis for the optimized allocation of watershed water resources, efficient agricultural irrigation, and the sustainable development of oasis ecosystems under changing environmental conditions, thereby supporting the goals of water security and sustainable development in inland river basins of arid regions. Full article

Nature-based solutions (NbSs) are increasingly recognized as sustainable and cost-effective strategies for mitigating drought impacts. However, robust quantitative evidence on the effectiveness of NbSs for drought mitigation, especially under future climate change scenarios, remains limited. In particular, the extent to which grazing management can reduce agricultural and hydrological droughts over long time horizons is still poorly understood. This study examines the long-term effectiveness of grazing management as a NbS for mitigating drought under historical and future climate conditions in the Ganale Dawa River Basin, Ethiopia. We combined remote sensing, machine learning, and climate projections to simulate soil moisture and runoff using a long short-term memory (LSTM) model. Protected areas were used as proxies for light grazing, while adjacent non-protected areas represented heavy grazing. Agricultural and hydrological droughts were quantified using the standardized soil moisture index (SSMI) and standardized runoff index (SRI), respectively. The results show that light grazing consistently reduced drought severity compared to heavy grazing across all periods. Agricultural drought severity was reduced by up to ~15% under SSP2-4.5 and SSP5-8.5, while hydrological drought severity showed substantially larger reductions, exceeding ~40% in mid- and late-future periods. Differences between grazing regimes widened under stronger climate forcing, indicating that grazing management benefits become more pronounced under future climate stress. These findings demonstrate that grazing management is an effective NbS for enhancing long-term drought resilience. Scaling up sustainable grazing practices could, therefore, serve as a practical climate adaptation strategy for drought-prone basins in Ethiopia and similar regions. Full article

Natural pumice can reduce the self-weight of concrete, but its high porosity, high water absorption, and weak interfacial bonding tend to limit the strength and durability of lightweight aggregate concrete. To address this issue, this study proposes a method for preparing and applying reinforced pumice lightweight aggregates, namely, using nano-SiO₂-modified fly ash to construct a nanocomposite material at the micro-interface for the reinforcement treatment of natural pumice aggregates, and reveals the mechanism by which this treatment enhances the performance of lightweight aggregate concrete. Through aggregate performance tests, compressive strength tests, XRD, SEM, and freeze–thaw cycle tests, the effects of the reinforced pumice aggregate on the performance of lightweight concrete were systematically investigated. The results show that after the reinforcement treatment, the water absorption of the pumice aggregate decreases by 17.6%, and the cylinder compressive strength increases by 34.3%. As the replacement ratio of reinforced pumice increases, both the early-age and later-age compressive strengths of the concrete continuously improve. When all the pumice aggregate is reinforced, the 3 d and 28 d compressive strengths increase by 35.1% and 33.44%, respectively. Meanwhile, the reinforced pumice effectively improves the interfacial bonding between the aggregate and the cement paste, reducing the width of the interfacial transition zone by 32%, enhancing the matrix compactness, and delaying crack propagation. The study demonstrates that the reinforced pumice aggregate possesses favorable characteristics, not only effectively improving the mechanical properties and freeze–thaw resistance of lightweight concrete but also providing a new technical pathway for the high-performance utilization of porous lightweight aggregates, offering a reference for the resource utilization of industrial solid waste and engineering applications in cold regions. Full article

The conservation of traditional villages has shifted from isolated site-by-site protection to regional collaboration, and exploring pathways for their sustainable development has become a key focus of research. Existing research still falls short in areas such as the integration of heritage value into decision-making mechanisms and the establishment of systematic conservation frameworks, leading to prominent issues of isolated conservation and homogeneous development. Taking traditional villages in Yanchuan County, China, as a case study, this research aims to establish a clustered conservation system and achieve a transition towards networked collaborative governance. The study utilised field surveys and literature review to establish a database and systematically catalogue heritage resources; it combined the Analytic Hierarchy Process (AHP) and the Delphi method to construct a value evaluation system and identify distinctive features; and it integrated cluster theory with GIS spatial analysis to construct a clustered conservation framework across three dimensions: classification and grading, symbiotic models, and the overall spatial pattern. The results indicate that: (1) the spatial distribution of villages in Yanchuan County is uneven, and the villages themselves exhibit significant homogeneity in their characteristics; (2) core characteristics include Loess culture, cave dwellings and revolutionary heritage sites, with comprehensive scores ranging from 0.4437 to 0.9116; these are classified into three protection levels, identifying five categories of villages of value. (3) Five major cluster zones were delineated based on resource and spatial characteristics. By integrating river basins and transport corridors, a comprehensive protection framework of ‘one belt, two wings, two centers and five zones’ was established, alongside three types of cluster symbiosis models, thereby achieving regional resource integration and enhancing collaborative efficiency. The cluster-based protection system proposed in this study can effectively address the challenges facing the conservation and development of traditional villages, providing a feasible solution for regional collaborative protection, and holds practical significance for cultural heritage management and sustainable development. Full article

The “Golden Triangle” area of the Kuitun River Basin is a typical arid irrigated region where limited surface-water supply and intensive groundwater abstraction have caused persistent groundwater decline and overexploitation. This study developed a one-way semi-loosely coupled GWAS–GMS/MODFLOW framework for allocation optimization, spatial projection, groundwater simulation, and effectiveness evaluation. An improved NSGA-II-S algorithm was used to optimize multi-source water allocation, and the resulting management-unit outputs were projected into MODFLOW source–sink terms using area-weighted transformation and mass conservation. GWAS satisfactorily reproduced monthly runoff at the Jiangjunmiao station, and GMS/MODFLOW reasonably matched observed groundwater heads at six national monitoring wells (R² = 0.952–0.998; RMSE = 0.15–0.355 m; MAE = 0.12–0.315 m). Three 2030 scenarios were compared: baseline, optimized allocation, and combined pumping restriction with allocation adjustment. Under the baseline scenario, groundwater storage remained in deficit. The optimized allocation scenario expanded the quasi-stable zone (−0.1 to 0.1 m/a), whereas the combined scenario most effectively suppressed severe decline hotspots, reducing the proportion of the −3 to −2 m/a zone from 11.22% to 2.68%. These results indicate that recharge reallocation and pumping restriction play complementary roles in groundwater overexploitation control. The framework provides a quantitative basis for coordinated multi-source water management in arid irrigated basins. Full article

Time-series InSAR is an important means for early identification and monitoring of landslides. However, in complex mountainous areas, it still faces challenges such as significant geometric distortions and complicated deformation mechanisms. To address these issues, this paper proposes a landslide identification and prediction framework that integrates ascending and descending orbits InSAR observations with physics-guided deep learning. Taking Yangbi County, Yunnan Province, as a case study, we combined ascending and descending Sentinel-1A data and employed the SBAS-InSAR method to identify potential landslides, detecting a total of 41 hazardous sites. The cumulative displacement time series of typical landslides were further extracted along the slope aspect to more realistically reflect landslide movement characteristics. On this basis, wavelet decomposition was introduced to separate the displacement series into trend and periodic components. Gray relational analysis was then used to select influencing factors such as precipitation and temperature, and a stepwise prediction model based on LSTM (WT-LSTM) was constructed. The results indicate that the model achieves significantly higher prediction accuracy at characteristic points of the representative landslide (RMSE = 1.16–2.19 mm) compared to standalone LSTM and SVR models. These findings demonstrate its effectiveness and potential applicability in landslide deformation monitoring and prediction in complex mountainous areas, while also providing a useful reference for landslide risk early warning. Full article

A significant portion of Europe is prone to flooding, including severe events occurring over very small areas. Recent flood hazard mapping methods can cover large regions, but often fail to capture processes driven by small streams or direct rainfall. This study presents the authors’ experience in the application of a fully hydrodynamic model over an entire territory, with direct rainfall input (rain-on-grid approach at the basin scale). The case study is the Neto River basin in Calabria (Italy), covering approximately 1000 km², a region that represents an ideal natural laboratory for investigating flash flood processes in Europe. Simulations were carried out using the TUFLOW 2D commercial modelling tool. A key objective is to demonstrate that the Chicago hyetograph enables a constant return period across the entire domain. Additionally, specific procedures are proposed to represent numerous minor crossings (e.g., small bridges, culverts, and road and railway underpasses) and dam outlets without refining the computational grid or abandoning the Shallow Water Equations (SWE). This approach allows identification of major river floods, flash floods, runoff-related hydraulic effects, and pluvial flooding. Results show that the fully hydrodynamic rain-on-grid model is highly effective for flood hazard mapping, with strong agreement between simulations and observed events, confirming its predictive reliability and enabling high-resolution, comprehensive territorial analysis. Full article

Wetlands are ecosystems with critical functions. However, the accelerated progression of global urbanization and human activities, including agricultural encroachment, has resulted in a notable decline in wetland areas and the degradation of wetland quality worldwide. Consequently, wetland restoration has become a central focus of wetland research. Plant community characteristics are among the simplest and most frequently used indicators for evaluating wetland restoration progress and are a crucial factor in maintaining the health and stability of wetland ecosystems. Therefore, this study aimed to investigate the plant community characteristics of restored wetlands with different durations of abandonment in the lower Tumen River Basin, which is expected to provide guidance for promoting the restoration of abandoned farmlands in this region. We hypothesize that species diversity decreases with increasing abandonment age, plant community composition converges toward that of natural wetlands over time, and beta diversity declines due to increasing biotic homogenization during succession. We established a chronosequence of abandoned wetlands in the lower Tumen River Basin, with sites abandoned for approximately 5, 15, and 30 years. And we use natural wetlands and paddy fields as references. With natural succession, the dominant plant species in the restored wetlands transitioned from annuals/biennials to perennials. The aboveground biomass initially increased and subsequently decreased. A gradual decline in species diversity was observed along with a further reduction in beta diversity, and the species turnover component consistently exceeded the richness difference component. The pronounced biotic homogenization among communities indicates that achieving a stable state comparable to that of natural wetlands may require considerably more time or may not be attainable solely through natural succession. Full article

Sub-sag 21 in the eastern Yangjiang Sag, Pearl River Mouth Basin, South China, contains a thick lacustrine source-rock interval within the lower Wenchang Formation and is a major exploration target on the northern margin of the South China Sea. However, the timing of deposition during the early to middle Eocene remains poorly constrained, and the applicability of quantitative palaeoclimate reconstruction methods in low-latitude lacustrine basins requires further evaluation. In this study, we analyzed mudstones from the lower Wenchang Formation in Well E1. Using cyclostratigraphic constraints, we applied AstroGeoFit to construct an astronomically tuned age model, and combined palynological coexistence analysis with geochemical weathering proxies and linear–regression calibration to quantitatively reconstruct and cross-validate mean annual temperature and mean annual precipitation. Within this time-calibrated framework, we further quantified organic-carbon burial to evaluate the relationship between palaeoclimate evolution and organic-matter enrichment. The AstroGeoFit results indicate that the top of the lower Wenchang Formation in Well E1 is constrained to 44.563 Ma, and that the studied succession spans 50.249–44.563 Ma. Palynological coexistence analysis identifies three palaeoclimate phases within this interval. Method evaluation shows that the temperature reconstruction based on major-element geochemistry agrees well with the pollen-based temperature record, whereas one precipitation reconstruction based on weathering proxies shows the most robust agreement and stability relative to the pollen-based precipitation record. Reconstructed mean annual temperature ranges from 10.77 to 22.20 °C, and reconstructed mean annual precipitation ranges from 1188.27 to 1871.89 mm. Correlation analyses on the tuned timescale show that precipitation is more strongly associated than temperature with organic-matter accumulation parameters, including total organic carbon and organic carbon accumulation rate, indicating that organic carbon burial in the eastern Yangjiang Sag lake basin was mainly controlled by hydrological forcing. During the Early Eocene Climatic Optimum, carbon burial in low-latitude lakes was, therefore, not a simple response to elevated temperature, but instead reflected the integrated effects of precipitation, runoff, stratification, material supply, transport, and preservation. The evolutionary sequence further suggests that early high productivity was diluted by rapid sedimentation, reducing total organic carbon; subsequent cooling, lake deepening, and strengthened stratification enhanced organic matter preservation; and finally, tectonic subsidence together with regional humidification promoted the development and long-term preservation of high-quality lacustrine source rocks. Full article