Search Results (385)

This study investigated the distribution patterns of zooplankton species composition and functional groups, their correlations with aquatic environmental factors, and the mechanisms underlying community stability under the influence of regional barriers in arid areas of Xinjiang, China. The aim was to elucidate the ecological processes driving zooplankton communities in artificial aquatic ecosystems in Central Asia. A systematic survey was conducted on water environmental parameters and zooplankton community structures across 10 artificial water bodies, including the southern foot of the Altai Mountains and both northern and southern slopes of the Tianshan Mountains. The survey encompassed physical and nutrient indicators, and the results revealed significant spatial variation among water bodies across regions. Artificial water bodies in the southern Altai Mountains and northern Tianshan Mountains exhibited substantial fluctuations in temperature, dissolved oxygen (DO), total nitrogen (TN), and total phosphorus (TP). In contrast, water bodies in the southern Tianshan Mountains showed less variation in nutrient indicators. Zooplankton identification results indicated marked differences in zooplankton communities across regions, which were further confirmed by cluster analysis and non-metric multidimensional scaling (NMDS). A total of 19 dominant zooplankton species were identified across the three basins, classified into 6 functional groups. The composition of zooplankton functional groups also varied considerably, which may be closely associated with significant fluctuations in nutrient indicators of aquatic environmental factors across regional barriers. Additionally, there were specific differences in zooplankton diversity among the three basins: the SA region ranged from α-mesosaprobic to polysaprobic and β-mesosaprobic; the NT region was classified as β-mesosaprobic; and the ST region ranged between β-mesosaprobic and lightly polluted. These results may be attributed to differences in regional barriers and glacial meltwater conditions. Canonical Correspondence Analysis (CCA) showed that environmental factors collectively explained 71.1% of the variation in species distribution. Exploring the zooplankton species composition and their relationships with aquatic environmental factors under different regional barriers provides a scientific basis for regional water resource management and environmental protection. Full article

Based on a nonlinear effective stress coefficient calculation method, this study investigates the nonlinear stress sensitivity of permeability in deep shale gas reservoirs through high-temperature, high-pressure experiments on matrix, unpropped fracture, and propped fracture samples. Furthermore, the influence of different effective stress models on production performance in deep shale gas wells was investigated using the PETREL integrated fracturing production simulation module. Results reveal significant nonlinearity in the effective stress behavior of all media, with matrix samples showing much stronger permeability stress sensitivity than fracture samples. Numerical simulations revealed that horizontal well productivity under the nonlinear effective stress model was lower than predictions from the net stress model, providing critical theoretical and technical foundations for the large-scale and efficient development of deep marine shale gas reservoirs in the Sichuan Basin and emphasizing the importance of accurate stress models for production performance forecasting. Full article

The Wufeng–Longmaxi (WF–LMX) shale gas reservoirs at depths > 3500 m in the Lu203–Yang101 well block, southern Sichuan Basin, possess great exploration potential, but their reservoir characteristics and high-production mechanisms remain unclear. In this study, we employed multi-scale analyses—including core geochemistry, X-ray diffraction (XRD), scanning electron microscopy (SEM), low-pressure N₂ adsorption, and nuclear magnetic resonance (NMR)—to characterize the macro- and micro-scale characteristics of these deep shales. By comparing with shallower shales in adjacent areas, we investigated differences in pore structure between deep and shallow shales and the main controlling factors for high gas-well productivity. The results show that the Long 11 sub-member shales are rich in organic matter, with total organic carbon (TOC) content decreasing upward. The mineral composition is dominated by quartz (averaging ~51%), which slightly decreases upward, while clay content increases upward. Porosity ranges from 1% to 7%; the Long11-1-3 sublayers average 4–6%, locally >6%. Gas content correlates closely with TOC and porosity, highest in the Long11-1 sublayer (6–10 m³/t) and decreasing upward, and the central part of the study area has higher gas content than adjacent areas. The micro-pore structure exhibits pronounced stratigraphic differences: the WF Formation top and Long11-1 and Long11-3 sublayers are dominated by connected round or bubble-like organic pores (50–100 nm), whereas the Long11-2 and Long11-4 sublayers contain mainly smaller isolated organic pores (5–50 nm). Compared to shallow shales nearby, the deep shales have a slightly lower proportion of organic pores, smaller pore sizes with more isolated pores, inorganic pores of mainly intraparticle types, and more developed microfractures, confirming that greater burial depth leads to a more complex pore structure. Type I high-quality reservoirs are primarily distributed from the top of the WF Formation to the Long11-3 sublayer, with a thickness of 15.6–38.5 m and a continuous thickness of 13–23 m. The Lu206–Yang101 area has the thickest high-quality reservoir, with a cumulative thickness of Type I + II exceeding 60 m. Shale gas-well high productivity is jointly controlled by multiple factors: an oxygen-depleted, stagnant deep-shelf environment, with deposited organic-rich, biogenic siliceous shales providing the material basis for high yields; abnormally high pore-fluid pressure with preserved abundant large organic pores and increased free gas content; and effective multi-stage massive fracturing connecting a greater reservoir volume, which is the key to achieving high gas-well production. This study provides a scientific basis for evaluating deep marine shale gas reservoirs in southern Sichuan and understanding the enrichment patterns for high productivity. Full article

Plateau lake regions face escalating conflicts between food production and ecosystem conservation under rapid urbanization and strict ecological regulation. However, existing evaluations often overlook the positive ecosystem services generated by cultivated land and fail to capture the nonlinear mechanisms shaping eco-efficiency of cultivated land use (ECLU). This study develops an ecosystem service-based framework to assess the ECLU of Kunming, a typical plateau lake-basin city in southwest China, from 2005 to 2022. Ecosystem service value (ESV) is incorporated as a desirable output within a super-efficiency SBM model, and an XGBoost–SHAP approach is applied to identify the intensity, nonlinear thresholds and interaction mechanisms. Results show an average ECLU of 1.12 with a fluctuating downward trend and widening spatial disparities. High-efficiency zones cluster in central–southern regions, while urbanizing cores experience ecological function degradation despite productivity gains. Cultivated land fragmentation is the dominant barrier, with a critical threshold of 31.90 mu, and fertilizer intensity turns detrimental beyond 0.19 t/ha. Urbanization exhibits an inverted-U pattern—initially suppressive (<35%), promotional (35–55%), and suppressive again (>55%)—with the promotion phase weakened by approximately 67% under severe fragmentation. Globally, threshold-based zoning and fragmentation mitigation must precede fertilizer optimization to ensure synergistic benefits. Full article

The combined effects of climate change and socio-economic development have intensified the risk of water supply–demand imbalance in China. To project future trends, this study develops a multi-scenario coupled prediction framework integrating climate, socio-economic, and human activity drivers, combining data-driven and physically based modeling approaches to assess terrestrial water storage imbalance in nine major river basins under six representative SSP–RCP scenarios through the end of the 21st century. Using ISIMIP multi-model runoff outputs along with GDP and population projections, agricultural, industrial, and domestic water demands were estimated. A Water Conflict Index was proposed by integrating the Water Supply–Demand Stress Index and the Standardized Hydrological Runoff Index to identify high-risk basins. Results show that under high-emission scenarios, the WCI in the Yellow River, Hai River, and Northwest Rivers remains high, peaking during 2040–2069, while low-emission scenarios significantly alleviate stress in most basins. Water allocation inequity is mainly driven by insufficient supply in arid northern regions and limited redistribution capacity in resource-rich southern basins. Targeted strategies are recommended for different risk types, including inter-basin water transfer, optimization of water use structure and pricing policies, and the development of resilient management systems, providing scenario-based quantitative support for future water security and policy-making in China. Full article

The construction and operation of reservoirs have made hydrological processes complex, posing challenges to flood modeling. While many hydrological models have incorporated reservoir operation schemes to improve discharge estimation, the influence of reservoir representation on model calibration has not been sufficiently evaluated—an issue that fundamentally affects the spatial reliability of distributed modeling. Additionally, the limited availability of reservoir regulation data impedes dam-inclusive flood simulation. To overcome these limitations, this study proposes a synergistic modeling framework for data-scarce dammed basins. It integrates a satellite-based reservoir operation scheme into a distributed hydrological model and incorporates reservoir processes into the model calibration procedure. The framework was tested using the coupled version of the DRIVE flood model (DRIVE-Dam) in the Nandu River Basin, southern China. Two calibration configurations, with and without dam operation (CWD vs. CWOD), were compared. Results show that reservoir dynamics were effectively reconstructed by combining satellite altimetry with FABDEM topography, successfully supporting the development of the reservoir scheme. Multi-site comparisons indicate that, while CWD slightly improved streamflow estimation (NSE and KGE > 0.75, similar to CWOD) on the calibrated outlet gauge, it enhanced basin-internal process representation, as evidenced by the superior peak discharge and flood event capture with reduced bias, boosting flood detection probability from 0.54 to 0.60 and reducing false alarms from 0.28 to 0.15. The improvements stem from refined parameterization enabled by a physically complete model structure. In contrast, CWOD leads to subdued flood impulses and prolonged recession due to spurious parameters that distort baseflow and runoff response. The proposed methodology provides a practical reference for flood forecasting in dam-regulated basins, demonstrating that reservoir representation enhances model parameterization and underscoring the strong potential of satellite observations for hydrological modeling in data-limited regions. Full article

Under concurrent global warming and multi-scale climate anomalies, regional precipitation has become more uneven and less stable, and extreme events occur more frequently, amplifying water scarcity and ecological risk. Focusing on mainland China, we analyze nearly 70 years of monthly station precipitation records together with eight climate drivers—the Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), Multivariate ENSO Index (MEI), Arctic Oscillation (AO), surface air pressure (AP), wind speed (WS), relative humidity (RH), and surface solar radiation (SR)—and precipitation outputs from eight CMIP6 models. Using wavelet analysis and partial redundancy analysis, we systematically evaluate the qualitative relationships between climate drivers and precipitation and quantify the contribution of each driver. The results show that seasonal precipitation decreases stepwise from the southeast toward the northwest, and that stability is markedly lower in the northern arid and semi-arid regions than in the humid south, with widespread declines near the boundary between the second and third topographic steps of China. During the cold season, and in the northern arid and semi-arid zones and along the margins of the Tibetan Plateau, precipitation varies mainly with interdecadal swings of North Atlantic sea surface temperature and with the strength of polar and midlatitude circulation, and it is further amplified by variability in near-surface winds; the combined contribution reaches about 32% across the Northeast Plain, the Junggar Basin, and areas north of the Loess Plateau. During the warm season, and in the eastern and southern monsoon regions, precipitation is modulated primarily by tropical Pacific sea surface temperature and convection anomalies and by related changes in the position and strength of the subtropical high, moisture transport pathways, and relative humidity; the combined contribution is about 22% south of the Yangtze River and in adjacent areas. Our findings reveal the spatiotemporal variability of precipitation in China and its responses to multiple climate drivers and their relative contributions, providing a quantitative basis for water allocation and disaster risk management under climate change. Full article

Satellite precipitation products serve as valuable global data sources for hydrological modeling, yet their applicability across different hydrological models remains insufficiently explored. The distributed physics-informed deep learning model (DPDL), as a representative of emerging differentiable, physics-based hydrological models, requires a systematic evaluation of the suitability of multi-source precipitation products within its modeling framework. This study focuses on the Xiangjiang River Basin in southern China, where both a DPDL model and a Soil and Water Assessment Tool (SWAT) model were constructed. In addition, two model training strategies were designed: S1 (fixed parameters) and S2 (product-specific recalibration). Multiple precipitation products were used to drive both hydrological models, and their streamflow simulation performance was evaluated under different training schemes to analyze the compatibility between precipitation products and hydrological modeling frameworks. The results show that: (1) In the Xiangjiang River Basin of southern China, GSMaP demonstrated the best overall performance with a Critical Success Index of 0.70 and a correlation coefficient (Corr) of 0.79; IMERG-F showed acceptable accuracy with a Corr of 0.75 but had a relatively high false alarm rate (FAR) of 0.32; while CMORPH exhibited the most significant systematic underestimation with a relative bias (RBIAS) of −8.48%. (2) The DPDL model more effectively captured watershed hydrological dynamics, achieving a validation period correlation coefficient of 0.82 and a Nash–Sutcliffe efficiency (NSE) of 0.79, outperforming the SWAT model. However, the DPDL model showed a higher RBIAS of +16.69% during the validation period, along with greater overestimation fluctuations during dry periods, revealing inherent limitations of differentiable hydrological models when training samples are limited. (3) The S2 strategy (product-specific recalibration) improved the streamflow simulation accuracy for most precipitation products, with the maximum increase in the NSE coefficient reaching 15.8%. (4) The hydrological utility of satellite products is jointly determined by model architecture and training strategy. For the DPDL model, IMERG-F demonstrated the best overall robustness, while GSMaP achieved the highest accuracy under the S2 strategy. This study aims to provide theoretical support for optimizing differentiable hydrological modeling and to offer new perspectives for evaluating the hydrological utility of satellite precipitation products. Full article

Lithofacies, as an integrated representation of key reservoir attributes including mineral composition and organic matter enrichment, provides crucial geological and engineering guidance for identifying “dual sweet spots” and designing fracturing strategies in deep shale gas reservoirs. However, reliable lithofacies characterization remains particularly challenging owing to significant reservoir heterogeneity, scarce core data, and imbalanced facies distribution. Conventional manual log interpretation tends to be cost prohibitive and inaccurate, while existing intelligent algorithms suffer from inadequate robustness and suboptimal efficiency, failing to meet demands for both precision and practicality in such complex reservoirs. To address these limitations, this study developed a super-integrated lithofacies identification model termed SRLCL, leveraging well-logging data and lithofacies classifications. The proposed framework synergistically combines multiple modeling advantages while maintaining a balance between data characteristics and optimization effectiveness. Specifically, SRLCL incorporates three key components: Newton-Weighted Oversampling (NWO) to mitigate data scarcity and class imbalance, the Polar Light Optimizer (PLO) to accelerate convergence and enhance optimization performance, and a Stacking ensemble architecture that integrates five heterogeneous algorithms—Support Vector Machine (SVM), Random Forest (RF), Light Gradient Boosting Machine (LightGBM), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM)—to overcome the representational limitations of single-model or homogeneous ensemble approaches. Experimental results indicated that the NWO-PLO-SRLCL model achieved an overall accuracy of 93% in lithofacies identification, exceeding conventional methods by more than 6% while demonstrating remarkable generalization capability and stability. Furthermore, production simulations of fractured horizontal wells based on the lithofacies-controlled geological model showed only a 6.18% deviation from actual cumulative gas production, underscoring how accurate lithofacies identification facilitates development strategy optimization and provides a reliable foundation for efficient deep shale gas development. Full article

The Tarim Basin is currently the largest petroliferous basin in China, with hydrocarbons primarily hosted in Ordovician marine carbonate paleokarst fracture–vug reservoirs—a typical example being the Tahe Oilfield located in the northern structural uplift of the basin. The principle of “the present is the key to the past” serves as a core method for studying paleokarst fracture–vug reservoirs in the Tahe Oilfield. The deep and ultra-deep carbonate fracture–vug reservoirs in the Tahe Oilfield formed under humid tropical to subtropical paleoclimates during the Paleozoic Era, belonging to a humid tropical–subtropical paleoepikarst dynamic system. Modern karst types in China are diverse, providing abundant modern karst analogs for paleokarst research in the Tarim Basin. Carbonate regions in Eastern China can be divided into two major zones from north to south: the arid to semiarid north karst and the humid tropical–subtropical south karst. Karst in Northern China is characterized by large karst spring systems, with fissure–conduit networks as the primary aquifers; in contrast, karst in Southern China features underground river networks dominated by conduits and caves. From the perspective of karst hydrodynamic conditions, the paleokarst environment of deep fracture–vug reservoirs in the Tarim Basin exhibits high similarity to the modern karst environment in Southern China. The development patterns of karst underground rivers and caves in Southern China can be applied to comparative studies of carbonate fracture–vug reservoir structures in the Tarim Basin. Research on modern and paleokarst systems complements and advances each other, jointly promoting the development of karstology from different perspectives. 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

Southern China, despite its humid climate, has increasingly faced severe hydrological droughts (HDs) in recent decades, highlighting the complexity of drought propagation. Most existing studies primarily examined the relationship between drought propagation and climatic factors, whereas quantitative analyses of interactive effects of underlying surface characteristics on drought propagation remain insufficient. This study introduces an integrated framework combining GRACE satellite-derived terrestrial water storage anomalies with topography, land use, geology, and climate data to examine HD formation and its drivers. The results show a clear divergence between meteorological drought (MD) and HD patterns, revealing that underlying surface characteristics, rather than precipitation deficits alone, drive HD spatial patterns. Among drought propagation indicators, intensity has the strongest link to environmental factors, positively correlating with elevation and slope, and negatively with mean annual precipitation and temperature. Forest coverage helps mitigate drought intensification, while karst geology and land use influence propagation timing. HD intensity follows an elevational gradient, with severe droughts in high-altitude areas and mild, frequent droughts in low-lying basins. These insights provide a mechanistic basis for developing early-warning systems and spatially adaptive water management strategies, thereby supporting sustainable drought resilience and promoting long-term water resource sustainability in Southern China. Full article

Aeolian deposits are globally recognized as sensitive recorders of Quaternary climate and environmental change, exemplified by the continuous loess sequences of the Chinese Loess Plateau in northern China, which document paleoclimatic and paleoenvironmental evolution since the Miocene. However, such deposits have rarely been confirmed in low-latitude inland regions of southern China. Here we present systematic evidence of aeolian deposition in a low-latitude environment, namely at the Xinlipoding (XLPD) Paleolithic site, situated between the Bose and Bubing Basins in Guangxi, southern China. Using optically stimulated luminescence (OSL), geochemical, and grain-size analyses, we investigate 100 cm thick yellow-brown sandy loam exposed on the hillside of the Bubing Basin. OSL dating constrains its accumulation between 25.3 ± 1.5 ka and 2.7 ± 0.1 ka, spanning the Last Glacial Maximum (LGM) to the late Holocene. Geochemical signatures indicate that the sediments were primarily derived from a nearby terrace in the Bose and Bubing Basins. Grain-size end-member modeling further reveals a mixed alluvial-aeolian origin, comprising both windblown and reworked loess. These findings demonstrate that aeolian dust deposition persisted even in the humid subtropical low-latitude regions of China, recording continuous dust input across glacial–interglacial cycles. The XLPD section thus provides a valuable framework for reconstructing late quaternary environmental change and extends the spatial reach of global aeolian deposition into previously underrecognized regions. Importantly, it also offers a crucial paleoenvironmental context for human occupation in the Bubing Basin from the LGM through the late Holocene. Full article

To explore the pollution sources and health risks of heavy metals in the soil of the southern margin of the Tarim Basin, 1231 soil samples were collected and analyzed for pH and eight heavy metals (Cr, Cd, Pb, Zn, Cu, Ni, As, and Hg). The self-organizing map (SOM) and positive matrix factorization (PMF) models were used to analyze the sources of heavy metals in the soil of the southern Tarim Basin, and a Monte Carlo method-based health risk assessment model was used to quantify the human health risks of different sources of pollution. The results showed that the average contents of all elements did not exceed the local soil background values, except Cd and Hg. The content of As in 0.24% samples was higher than the national risk screening value of China, and the content of the other heavy metals was lower than the Chinese national risk screening value. The main sources of heavy metal pollution were natural–traffic–agricultural mixed sources (60.9%), atmospheric dust fall sources (18.4%), and agricultural sources (20.7%). Soil As, Cr, Pb, Zn, Cu, and Ni were mainly influenced by natural–traffic–agricultural mixed sources. Hg was influenced by atmospheric dust fall (55%) and agricultural sources (45%). Cd was mainly influenced by natural–traffic–agricultural mixed sources (61.6%) and agricultural sources (37.8%). The levels of heavy metals in the soil in Yutian County did not pose a non-carcinogenic risk to humans, but they pose an alert carcinogenic risk to children and adults. Cr is identified as the priority pollutant for human health risk control, while the mixed sources from natural, traffic, and agricultural activities are recognized as the primary targets for pollution control. This study provides a reference for the precise prevention and control of soil heavy metal pollution in the southern margin of the Tarim Basin. Full article

The development of the continental crust during the Archean era is one of the key issues of geoscience. Determining the geological nature of the Archean terrane of the southern Liaoning Province (SLP) is fundamental to decipher the tectonic framework of the eastern North China Craton (NCC) from the late Neoarchean to Paleoproterozoic. The Archean assemblage of the SLP is composed of metabasalt, deformed diorite, TTG, and granite. Zircon U-Pb and Lu-Hf data constrain that the metabasalt formed at 2.52 Ga and was metamorphosed at 2.49 Ga. Dioritic rocks, TTG (tonalite-trondhjemite-granodiorite) and granite formed between 2.53 and 2.48 Ga. More than 85% of analyzed zircon grains yield ε_Hf(t) values intermediate between coeval CHUR and depleted mantle (DM). Their single-stage (T_DM) Hf model ages are dominantly between 2.90 and 2.58 Ga with a peak at 2.76–2.66 Ga, suggesting that the Archean assemblages of the SLP were derived from short-lived crustal sources with limited contributions from older materials. Geochemistry and zircon Lu-Hf systems indicate that these metamafic rocks have N-MORB and island arc-like tholeiitic affinities. Similar basaltic associations were identified from the Wutai greenstone belt. Intra-oceanic subduction and back arc basin extension can be ascribed to the generation of associated MORB-like and arc-related basalt. Along with the closure of the SLP back arc basin, an unknown terrane accreted to the south of the Longgang block at the end of the Neoarchean. Full article