Search Results (1,905)

The watersheds of the Senegal River, particularly the Gorgol River, are increasingly affected by hydrological extremes such as floods and soil erosion, pressures that are intensified by ongoing climate change and human activities. This study investigates the hydrological functioning and erosion susceptibility of the Gorgol tributaries to support sustainable watershed management. A multidisciplinary approach was applied, combining spatial analysis of watershed characteristics with hydrological modeling and erosion risk mapping. Key datasets included satellite-derived climate variables, which were validated with ground measurements and integrated with topographic, geological, soil, and land-use data. Climate analysis revealed a pronounced north–south rainfall gradient, with most precipitation occurring between July and September, alongside a +1 °C temperature increase over the past 42 years. Erosion susceptibility was assessed using the Revised Universal Soil Loss Equation, incorporating factors such as rainfall erosivity, soil erodibility, slope parameters, land-cover, and conservation practices. Results indicate that areas in the southern basin and those with fragile soils are most vulnerable, with rainfall erosivity being the primary driver of soil loss. Hydrological study identified flood-prone zones and characterized the regimes. These findings offer a scientific basis for targeted interventions in erosion control and flood risk reduction within the Gorgol basin. Full article

Landscapes in semiarid regions are highly sensitive to climate change and anthropogenic activities, and their evolution directly influences ecosystem services and regional ecological security. Although previous research has examined land use changes, systematic quantitative analyses of long-term evolutionary trends and driving mechanisms, particularly the comprehensive relationships between key hydrological elements and landscape pattern evolution in water-scarce, semiarid watersheds, remain limited. To address the research gap in long-term, multifactor, and hydro–landscape integrated analysis, China’s Tuwei River watershed was selected as the study area in this study, and methods such as landscape pattern indices and gray relational analysis were employed to quantitatively reveal the spatiotemporal evolution of watershed landscape fragmentation from 1980 to 2020 and identify its dominant driving forces. The results revealed that (1) over the 40-year period, the land use structure of the watershed underwent significant restructuring, with developed land expanding by 1282%, cropland and bare land areas decreasing by 14.2% and 32.01%, respectively, and grassland and forestland areas increasing by 24.5% and 14.9%, respectively; (2) land-scape fragmentation continued to intensify, with the landscape fragmentation composite index (FCI) increasing by 37.6%, patch density (PD) continuously increasing, edge density (ED) and landscape shape index (LSI) increasing significantly, and landscape connectivity weakening; (3) natural and socioeconomic factors jointly drove landscape evolution, with temperature and mean annual flow contributing the most among natural factors and the urbanization rate and secondary industry output value serving as the core drivers among socioeconomic factors; and (4) the trend of landscape fragmentation was synchronized with changes in annual rainfall and runoff and exhibited a significant negative correlation with the groundwater level. In summary, through long-term, multifactor comprehensive analysis, the evolution characteristics and driving mechanisms of landscape patterns in the Tuwei River watershed were systematically revealed in this study. These findings not only deepen the understanding of landscape fragmentation processes under the dual pressures of climate change and anthropogenic activities but also provide scientific evidence for the sustainable management of landscapes and associated ecosystems in semiarid watersheds. Full article

River discharge scaling is fundamental to the global hydrological cycle and to water resource assessment. This study investigates the existence of multiple scaling regimes and introduces a novel framework for clustering river discharge using multiscale fractal characteristics. We analyzed daily discharge data from 38 stations across continental Canada over an 80-year period. Multifractal characterization was performed at decadal and long-term scales using three key parameters: the singularity exponent (${\alpha }_0$), multifractal strength ($\alpha$), and asymmetry index (r). K-means clustering in the $\alpha -r$, ${\alpha }_0-r$, and $\alpha -{\alpha }_0$ planes revealed distinct clusters, with the asymmetric parameter (r) emerging as the strongest distinguishing factor. These clusters represent groups of rivers with similar dynamical structures: the $\alpha -r$ clusters categorize discharge based on scaling strength and fluctuation influence. Analysis of the generalized Hurst exponent revealed anti-persistent behavior at most stations, with exceptions at five specific locations. This multifractal clustering approach provides a powerful method for classifying river regimes based on intrinsic characteristics and identifying the physical drivers of discharge fluctuations. Full article

The Macao rammed earth wall is a typical representative of cultural heritage in hot-humid regions. However, the spatial differentiation mechanisms of its surface deterioration remain unclear. This study, taking the Old Wall in Macao as a case, combined field investigation with terrestrial laser scanning (TLS) and thermal imaging to systematically reveal the spatial distribution patterns of surface pathologies and their hydrological driving mechanisms. Based on structural separations and deterioration characteristics, the wall was divided into three adjacent sections for comparative analysis. The main conclusions are as follows: (1) Quantitative analysis showed the section with a gentler slope (77%) experienced significant flatness deterioration due to uneven settlement, promoting internal water penetration that triggered severe undercutting (35% of its surface area); (2) The other two sections maintained steep slopes (86%) that promoted surface runoff, which combined with adjacent building drainage led to significant biological colonization (68% in the section most affected by nearby temple drainage); (3) Thermal imaging verified the correlation between water infiltration cores and temperature-flatness anomalies, enabling construction of a coupled “geometry-hydrology-pathology” model that elucidates the complete causal chain from foundation settlement to surface pathology. This study provides a theoretical basis and technical support for the differentiated protection of rammed earth heritage in hot-humid environments. Full article

Lake eutrophication exhibits pronounced spatial heterogeneity at the watershed scale, yet a systematic and quantitative understanding of how landscape characteristics drive these variations remains limited. In this study, a long-term and internally consistent trophic state dataset for the Liangzi Lake Basin was constructed by integrating Landsat imagery from 1990 to 2022 with a semi-analytical water color inversion method. A multi-scale landscape feature system incorporating both land use composition and landscape pattern metrics was developed at the sub-basin level to elucidate the mechanisms by which landscape characteristics influence eutrophication dynamics. The XGBoost model was employed to characterize the nonlinear relationships between landscape attributes and trophic conditions, while the SHAP interpretability approach was applied to quantify the relative contribution of individual landscape components and their interaction pathways. The analytical framework demonstrates that landscape pattern attributes—such as fragmentation, diversity, and connectivity—play essential roles in shaping the spatial variability of eutrophication by modulating hydrological processes, nutrient transport, and ecological buffering capacity. By integrating remote sensing observations with interpretable machine learning, the study reveals the complexity and scale dependence of landscape–water interactions, providing a methodological foundation for advancing the understanding of eutrophication drivers. The findings offer theoretical guidance and practical references for optimizing watershed landscape planning, controlling non-point source pollution, and supporting ecological restoration efforts in lake basins. Full article

Compressed air energy storage in aquifers presents a promising approach for large-scale energy storage, yet its implementation is complicated by geochemical reactions, such as pyrite oxidation, which can impact reservoir integrity and operational efficiency. This study numerically investigates the evolution of reservoir characteristics and geochemical processes during CAESA operations to address these challenges. Using the TOUGHREACT simulator, we developed one-dimensional and two-dimensional reactive transport models based on the Pittsfield aquifer field test parameters to simulate coupled thermal-hydrological–chemical processes under varying injection rates, temperatures, reservoir depths, and operational cycles. The results demonstrate that higher injection rates induce greater near-well pressure buildup and extended thermal zones, while deeper reservoirs exhibit abrupt declines in pressure and gas saturation due to formation constraints. Geochemical analyses reveal that pyrite oxidation dominates, leading to oxygen depletion, groundwater acidification (pH reduction), and secondary mineral precipitation, such as goethite and hematite. These findings underscore the critical interplay between operational parameters and geochemical reactions, highlighting the need for optimized design to ensure long-term stability and efficiency of aquifer-based energy storage systems. Full article

Hydrological droughts represent a growing challenge for northern watersheds in Thailand, where climate change is projected to intensify seasonal water stress and destabilize agricultural productivity and water resource management. This study employed the Composite Hydrological Drought Index (CHDI) to evaluate the spatiotemporal characteristics of future droughts under representative concentration pathway (RCP) scenarios. The findings revealed a pronounced seasonal contrast: under RCP8.5, the CHDI values indicated more severe drought conditions during the dry season and greater flood potential during the wet season. Consequently, the region faces dual hydrological threats: prolonged water deficits and increased flood exposure within the same annual cycle. Drought persistence is expected to intensify, with maximum consecutive drought runs extending up to 10–11 months in future projections. The underlying mechanisms include increased actual evapotranspiration, which accelerates soil moisture depletion, enhanced rainfall variability, which drives the sequencing of floods and droughts, and catchment storage properties, which govern hydrological resilience. These interconnected processes alter the timing and clustering of drought events, concentrating hydrological stress during periods that are sensitive to agriculture. Overall, drought behavior in northern Thailand is projected to intensify in a spatially heterogeneous pattern, emphasizing the need for localized, integrated adaptation measures and flexible water management strategies to mitigate future risks of drought. Full article

Hydrological regime is widely recognized as the primary driver shaping riparian vegetation, yet its mechanistic links with taxonomic, functional, and ecosystem diversity under dam-regulated conditions remain insufficiently quantified. In this study, we quantified flow regime characteristics in the Three Gorges Reservoir (TGR). We identified five statistically distinct flow regime types using hierarchical clustering based on magnitude, duration, frequency, average flooding intensity, and rate of change. Significant differences among the five flow regime types were observed using one-way ANOVA with Tukey HSD post hoc tests (p < 0.05), particularly in magnitude, duration, flooding intensity, and rate of change, while flooding frequency showed no significant variation. Species richness was negatively associated with flooding duration but positively associated with hydrological conditions of milder flow regime types, especially during early and late growing seasons (April and September). Functional diversity increased along the flow regime gradient and exhibited a significant positive association with species richness. After statistical re-evaluation, only linear relationships were retained (p < 0.05). The results demonstrate that flow regime is a more reliable predictor of riparian vegetation zonation and functional diversity than flooding duration alone, emphasizing the role of hydrological variability in shaping ecosystem functioning within large regulated reservoirs. Full article

The operation of the Three Gorges Dam (TGD) has profoundly influenced sediment dynamics in the Three Gorges Reservoir (TGR), yet the long-term evolution of runoff–sediment interactions remains insufficiently quantified. Based on long-term hydrological data (1970–2023), this study analyzed the characteristics of runoff and sediment load and evaluated the impacts of the TGD on their relationship within the reservoir area. Results showed that TGD operation significantly altered sediment transport patterns and reshaped the runoff–sediment relationship, although these effects were constrained by temporal variations in upstream water and sediment supply. From 2003 to 2012, sediment transport regulation reached 11.7%, 50.9%, and 80.5% at Qingxichang, Wanxian, and Yichang stations, respectively, while regulation of the runoff–sediment relationship was 20.0% and 50.0% at Qingxichang and Wanxian. During 2013–2023, under the influence of cascade reservoirs in the upper Yangtze River, sediment regulation changed to 8.3%, 60.3%, and 75.2% at the three stations, with runoff–sediment regulation degrees of 21.7% and 54.2% at Qingxichang and Wanxian. The regulation effect displayed a clear spatial gradient, intensifying downstream along the reservoir. These findings demonstrate the dual role of TGD and upstream cascade reservoirs in shaping runoff–sediment dynamics, providing new insights into sediment management and ecological protection in large regulated rivers. Full article

A state factor model of bottomland hardwood swamp formation is applied to a lower coastal plain river in North Carolina, U.S., to explain variations in wetland hydrological, ecological, geomorphological, and soil characteristics. Swamps and wetlands are a function of the interacting influences of the state factors of climate, topography, hydrology, vegetation, fauna, soils, geomorphic setting, and time. Five classifications of swamp and related environments were applied to the study area, with the categories present determined based on fieldwork. For each classification, the implicit, embedded state factors were identified from the classification scheme itself. Relevant environmental gradients for the study area were identified, and a spatial adjacency graph for the study area was developed for each classification. The ability of the environmental gradients to explain the spatial complexity of the pattern was assessed using spatial adjacency graph (SAG) analysis. All the classification criteria are associated with the proposed state factors. SAG analysis shows overdetermination, indicating that known gradients of causal factors are sufficient to explain the overall pattern of spatial contiguity and that single-factor models of change are not sufficient at the local scale. Results confirm studies showing that responses to sea-level and other changes are spatially patchy. Full article

Zeolite is a popular soil amendment capable of improving physical and chemical properties of soils. This study investigates how zeolite concentration affects the hydrological connectivity of sandy loam soil. Soil samples with different zeolite concentrations C_z (0, 1, 1.5, 2.5, 5, 10, 15, and 30%) were analyzed for changes in water dynamics through Fast Field Cycling Nuclear Magnetic Resonance (FFC-NMR) relaxometry. FFC-NMR data revealed that the investigated zeolite can modify the pore size distribution in a wide range (1–15%) of C_z, as the zeolite particle size distribution has a percentage of coarse particles (56%) appreciably higher than that of the original soil (37%). Moreover, a concentration of 1% produces a more relevant increase in the soil’s meso- and macropores, while for C_z > 1.5%, the change in pore size distribution is damped by the increase in water retention that occurs upon increasing zeolite concentration. The analysis also demonstrated that C_z = 1% is sufficient to achieve the highest values of both structural and functional connectivity indexes. In conclusion, for sandy loam soil, adding a zeolite concentration of 1% is sufficient to improve the soil’s physical characteristics, with significant effects on soil hydrological behavior, and can be considered a valid practice to manage the addition of a water resource to the soil. Full article

The wandering reach of the Yellow River has long been a pivotal area of research due to its drastic fluctuations in water-sediment dynamics, frequent shifts in the main channel, and complex river regime evolution. Studies on the main-channel morphological evolution in this reach have focused on the analysis of parameters related to the overall oscillation or have only analyzed a certain reach within the wandering reach, with a lack of detailed studies based on the different characteristics of each area. Therefore, taking the Xiaolangdi Reservoir–Gaocun reach as the research area, by constructing a two-dimensional water-sediment dynamic model, the erosion–deposition characteristics of different sub-reaches and the morphological evolution characteristics of key cross-sections were quantified and analyzed. Based on measured hydrological, sediment, and topographic data, the temporal and spatial changes in the bankfull area and fluvial facies coefficient of typical sections before and after the construction of Xiaolangdi Reservoir were analyzed. By interpreting remote sensing images, the spatio-temporal variation characteristics of the migration distance and bending coefficient of different reaches before and after the construction of Xiaolangdi Reservoir were calculated, and the key factors influencing the evolution of river morphology parameters were identified. The results showed that after the Xiaolangdi Reservoir operation, the overall erosion of the Huayuankou–Jiahetan reach is greater than the deposition, and the erosion is more obvious in dry years. The river course direction and control engineering play a significant role in controlling the morphological evolution of the main channel during the process, causing the R2 reach to significantly swing to the north bank and the R3 reach to the south bank. When the sediment transport coefficient values were between 0 and 0.005 kg.s.m⁻⁶, water-sediment had a positive effect on shaping and evolving the main-channel morphology. The long-term low-sand discharge of Xiaolangdi Reservoir and the continuous improvement of river regulation projects are the main reasons for the above changes. The results can provide support for controlling the evolution of the main channel and improving river regulation projects. Full article

Ancient walled cities represent key material evidence for early state formation and human–environment interaction on the northeastern Tibetan Plateau. However, traditional field surveys are often constrained by the vastness and complexity of the plateau environment. This study proposes an improved deep learning framework, AC-YOLOv11, to achieve automated detection of ancient city remains in the Qinghai Lake Basin using 0.8 m GF-2 satellite imagery. By integrating a dual-path attention residual network (AC-SENet) with multi-scale feature fusion, the model enhances sensitivity to faint geomorphic and structural features under conditions of erosion, vegetation cover, and modern disturbance. Training on the newly constructed Qinghai Lake Ancient City Dataset (QHACD) yielded a mean average precision (mAP@0.5) of 82.3% and F1-score of 94.2%. Model application across 7000 km² identified 309 potential sites, of which 74 were verified as highly probable ancient cities, and field investigations confirmed 3 new sites with typical rammed-earth characteristics. Spatial analysis combining digital elevation models and hydrological data shows that 75.7% of all ancient cities are located within 10 km of major rivers or the lake shoreline, primarily between 3500 and 4000 m a.s.l. These results reveal a clear coupling between settlement distribution and environmental constraints in the high-altitude arid zone. The AC-YOLOv11 model demonstrates strong potential for large-scale archaeological prospection and offers a methodological reference for automated heritage mapping on the Qinghai–Tibet Plateau. Full article

Accurate streamflow forecasting is vital for sustainable water resource management but remains challenging due to pronounced spatiotemporal variability. This study evaluates two process-based models, the SWAT (comprehensive) and the GWLF (parsimonious), and a data-driven random forest (RF) model for monthly streamflow simulations in two contrasting Chinese basins: the humid southern basin (SSB) and the semi-arid northern basin (SRB). Using four statistical metrics (NSE, R², MAE, RMSE), we assess model accuracy, robustness in capturing extremes, and sensitivity to hydrological characteristics and data availability. The results reveal consistently superior performance in the SSB across all models, with SWAT demonstrating the highest overall accuracy—especially for peak flows—due to its physically based structure. The GWLF provides acceptable simulations with minimal data requirements, offering a practical alternative in data-limited regions, like the SRB. RF performs well in the SSB under zero-lag conditions but requires hydrologically informed lag structures in the SRB. However, it consistently underestimates high flows due to its lack of physical constraints. The findings underscore that model selection must, therefore, be guided not only by predictive performance but also by the underlying hydrological context, data availability, and the need for physical realism in decision-making. Full article

Microplastic pollution in riverine ecosystems poses critical environmental challenges, yet current modeling approaches inadequately capture the spatial heterogeneity and topological complexity of fluvial systems. This study develops an innovative spatiotemporal graph convolutional network (ST-GCN) framework that integrates hydrological connectivity, flow parameters, and microplastic characteristics for simultaneous migration pathway identification and pollution source tracing. This model constructs multi-scale graph representations encoding system structure and transport dynamics, implements spatial-temporal convolution layers with adaptive attention mechanisms, and employs a backpropagation-based algorithm for inverse source identification. Validation using 18 months of field observations from 45 monitoring nodes across a 127 km river reach demonstrates 87.3% pathway prediction accuracy and 94.3% source localization accuracy (R² = 0.841, p < 0.001), representing substantial improvements over conventional advection–diffusion models. The framework successfully identified three pollution sources during a real contamination incident within 6 h of detection, enabling rapid regulatory intervention. This research advances environmental modeling by demonstrating that graph neural networks effectively capture transport processes in networked hydrological systems, providing practical tools for watershed management and evidence-based pollution control decision-making. Full article