Search Results (187)

Post-hemorrhagic hydrocephalus (PHH) is a serious neurological sequela of severe intraventricular hemorrhage (IVH) in premature infants and remains one of the leading indications for ventriculoperitoneal (VP) shunt placement. Evaluating possible VP shunt-related complications can be challenging because clinical manifestations are often nonspecific, neuroimaging may initially appear unchanged, and microbiological cultures may remain negative. We report the case of a 19-month-old male born at 28 weeks’ gestation who developed Grade IV germinal matrix/intraventricular hemorrhage with bilateral intraparenchymal extension, early periventricular cystic leukomalacia, and post-hemorrhagic communicating hydrocephalus requiring multiple cerebrospinal fluid diversion procedures culminating in long-term VP shunt dependence. His medical history was notable for recurrent neonatal meningitis, secondary epilepsy with previous episodes of status epilepticus, secondary adrenal insufficiency, and severe global developmental delay. He presented with fever, recurrent coffee-ground vomiting, abdominal distension, progressive lethargy, reduced responsiveness, and localized erythematous swelling over the cranial VP shunt reservoir, raising concern for possible shunt-related pathology. During hospitalization, he deteriorated with status epilepticus and respiratory failure, with clinical concern for increased intracranial pressure, requiring admission to the Pediatric Intensive Care Unit (PICU). Laboratory investigations demonstrated leukocytosis, elevated C-reactive protein, cerebrospinal fluid pleocytosis, markedly elevated CSF protein, and CSF glucose of 2.0 mmol/L, for which a paired serum glucose value was unavailable, while repeated blood, urine, wound, and CSF cultures remained negative. Initial computed tomography (CT) demonstrated no significant interval change in the chronic hydrocephalus despite progressive neurological deterioration; however, serial neuroimaging later revealed progressive bilateral extra-axial fluid collections with radiological features suggestive of an evolving subacute subdural hemorrhage. The patient was managed with empirical broad-spectrum intravenous antibiotics, aggressive seizure control, stress-dose corticosteroids, respiratory support, and continuous multidisciplinary monitoring. His neurological and respiratory status subsequently improved, and he returned to his pre-admission neurological baseline before discharge with planned further evaluation at a tertiary pediatric neurosurgical center. This case highlights the diagnostic uncertainty surrounding acute neurological deterioration in a child with shunt-dependent PHH. VP shunt-related infection or malfunction remained important but unconfirmed diagnostic considerations, alongside competing or potentially overlapping contributors including status epilepticus, evolving extra-axial collections, respiratory infection, and endocrine or metabolic decompensation. No single etiology was definitively established. The case emphasizes the importance of serial neurological assessment, consideration of alternative diagnoses, repeat neuroimaging, and multidisciplinary evaluation when initial investigations do not establish the cause of deterioration. Full article

Quantifying groundwater storage in karst aquifers remains challenging because of their heterogeneous structure and the scarcity of direct observations. This study proposes a pragmatic approach for characterizing storage and water availability in karst systems at the regional scale using long-term hydrographs from 16 Swiss karst springs and rivers. We distinguish between seasonal storage, associated with recharge events, and low-water storage, which sustains discharge during periods without significant recharge. Seasonal storage was estimated at approximately 30–70 mm for most investigated systems, while total storage reached up to about 140 to 180 mm at some sites, based on recharge–discharge modelling. Low-water storage was estimated to be on the order of 200 mm across most investigated systems, despite differences in hydrogeological settings. Analysis of low-water recession curves showed that most natural springs analyzed in this study followed a similar master recession curve, with low-water conditions defined as beginning at a specific transition discharge of 11.25 L s⁻¹ km⁻². This similarity provides the basis for a regional drought index that estimates the volume of remaining groundwater storage and forecasts discharge several weeks in advance. The results also support a conceptual model in which epikarstic, epiphreatic, and deeper storage compartments attenuate short-term discharge variability while sustaining low-water discharge over prolonged periods. Comparison with non-karst catchments shows that karst hydrogeological systems dampen peak flows but sustain baseflow through distinct storage reservoirs. This approach delivers quantitative indicators to assess drought, manage groundwater, and foresee water shortages in karst regions. Future work will test its validity outside the Swiss dataset. Despite discussed uncertainties in discharge measurements and catchment delineation, results demonstrate that dedicated hydrograph-based analyses can yield robust and transferable insights into karst groundwater storage at regional scales. Full article

Monthly precipitation distributions provide screening-level hydroclimatic information relevant to regional water-resource assessment that is not captured by annual or seasonal means alone. This study evaluates observed and projected shifts in monthly precipitation distributions across the nine NOAA Climate Regions of the contiguous United States using PRISM observations and NEX-GDDP-CMIP6 projections. Observed changes were assessed using PRISM monthly precipitation for 1941–2020 by comparing 1941–1980 with 1981–2020, with sensitivity tests using 1981–2014 and an alternative bootstrap block length. Future changes were evaluated using five NEX-GDDP-CMIP6 models under four SSP scenarios, relative to each model’s 1981–2014 historical reference. To strengthen the statistical and water-resource interpretation, the analysis additionally evaluates historical CMIP6 performance against PRISM, tests explicit hypotheses using permutation/bootstrap procedures with Benjamini–Hochberg false-discovery-rate control, and introduces a categorical Hydroclimatic Screening Matrix. The selected models reproduced the regional monthly climatological cycle well, with monthly climatology correlations of 0.943–0.969 and monthly climatology Kling–Gupta Efficiency values of 0.834–0.886, although raw monthly time-series skill was lower. Observed PRISM results show robust mean increases in the Northeast, Upper Midwest, and Ohio Valley, while monthly Q95 increased robustly in the Northeast and South. Future projections indicate broad late-century increases in monthly mean and upper-tail precipitation, especially under SSP5-8.5. Statistical testing showed that late-century SSP5-8.5 projected changes fell outside the empirical PRISM historical-change envelope in 14 of 18 region-metric pairs, whereas upper-tail amplification was not FDR-significant across regions. The Hydroclimatic Screening Matrix identifies aligned planning-relevant signals, emerging upper-tail concerns, seasonal-storage follow-up priorities, and directional-uncertainty cases. These results support precipitation-based screening for identifying where detailed hydrologic impact modeling may be warranted, without treating monthly precipitation metrics as direct runoff, recharge, reservoir-operation, or flood-risk estimates. The observational endpoint of 2020 was selected to form two equal 40-year periods, thereby keeping the sample lengths balanced for distributional comparisons. Full article

Deep saline aquifers are among the most promising formations for large-scale carbon capture and storage (CCS); however, reservoir pressure buildup, limited CO₂ dissolution, plume migration, and salt precipitation can reduce storage efficiency and injectivity. This study evaluates the technical and economic performance of engineered CO₂ injection strategies, including intermittent CO₂ injection (ICI), water-alternating-CO₂ (WA–CO₂), carbonated water injection (CWI), and carbonated water-alternating-CO₂ (CWA–CO₂), under low- (180 mD) and high-permeability (1000 mD) saline aquifers and injection rates ranging from 0.01 to 0.5 MTPA. Laboratory-derived relative permeability and CO₂ diffusivity data were incorporated into three-dimensional compositional reservoir simulations, while the most promising strategy was validated using the Sleipner benchmark model. Techno-economic performance was assessed through Monte Carlo uncertainty and sensitivity analyses. The results show that injection strategy, rate, and reservoir permeability strongly influence trapping efficiency and pressure evolution. ICI increased dissolution trapping by up to 20%, enhanced residual trapping by approximately 40%, and reduced average reservoir pressure by up to 10%, although its extended operating period reduced its economic attractiveness. Among the evaluated alternatives, WA–CO₂ provided the best balance between technical and economic performance by enhancing dissolution trapping, improving pressure management and plume control, and maintaining storage costs within 3.6–3.7% of the continuous injection base case. Field-scale validation using the Sleipner model demonstrated improved long-term trapping efficiency and reduced mobile CO₂ and plume extent. Monte Carlo analysis (20,000 realizations) confirmed the economic robustness of the evaluated strategies under the assumed policy framework, identifying Section 45Q tax credit and discount rate as the dominant economic drivers. These findings demonstrate that properly designed WA–CO₂ schemes can significantly improve the technical and economic performance of geological CO₂ storage. Full article

The increasing use of plastics in agriculture has enhanced crop productivity, water-use efficiency, and food supply stability. Nevertheless, the ongoing degradation of agricultural plastics and waste-derived materials has resulted in the widespread occurrence of microplastics (<5 mm) and nanoplastics (<1 μm) in agricultural soils, raising concerns about ecosystem functioning, food safety and human health. This review was conducted using literature obtained primarily from Web of Science, Scopus and PubMed. Publications published between 2019 and 2026 were primarily included. In addition, selected landmark studies published before 2019 were incorporated when they provided foundational concepts, methodological frameworks, or highly cited evidence that remains essential for understanding the sources, fate, and impacts of micro- and nanoplastics in agricultural systems. The review synthesizes recent scientific evidence regarding the sources, environmental fate, biological interactions, and food-chain transfer of micro- and nanoplastics within agricultural and food production systems, tracing their movement from farm to fork. Major contamination pathways include agricultural plastic materials, organic amendments, polymer-coated agrochemicals and atmospheric deposition. Mechanisms governing transport, aging, plant uptake and trophic transfer are also discussed. Current evidence suggests that agricultural soils are among the largest terrestrial reservoirs of micro- and nanoplastics; however, substantial uncertainties remain regarding environmental concentrations, plant uptake under field conditions, and human health risks due to methodological limitations and the lack of standardized analytical protocols. Future research should focus on standardized monitoring methods, enhanced risk assessment frameworks, the development of biodegradable alternatives, and integrated mitigation strategies to reduce plastic contamination. Full article

Reservoir-triggered seismicity (RTS) is commonly associated with stress perturbations induced by reservoir loading and pore-pressure diffusion within fractured rock masses. Shortly after the initial impoundment of the Irapé Hydropower Plant (Minas Gerais, Brazil), a sequence of induced earthquakes was recorded, providing an opportunity to investigate the compatibility between reservoir loading and the observed seismic response. This study presents a first-order hydromechanical assessment integrating finite element modelling, analytical elasticity solutions, and pore-pressure diffusion theory to evaluate the spatial distribution of stress perturbations and the characteristic diffusion times associated with reservoir impoundment. A two-dimensional elastic model was developed to simulate stress redistribution induced by the maximum reservoir load, while a parametric diffusion analysis was performed for representative hydraulic diffusivities and hypocentral depth scenarios between 1 and 6 km. Numerical results showed excellent agreement with the analytical elasticity solution (RMSE = 14.36 kPa, MAE = 11.08 kPa, mean relative error = 1.38%, and R² = 0.999), supporting the reliability of the numerical model. The simulations indicate that vertical stress perturbations decrease from approximately 1.8–2.0 MPa immediately beneath the reservoir to about 0.01–0.1 MPa at kilometer-scale depths, where the recorded seismicity is presumed to occur. The diffusion analysis indicates that pore-pressure propagation to these depths generally requires substantially longer times than the interval between reservoir filling and the onset of seismic activity. Nevertheless, owing to uncertainties in hydraulic diffusivity, fracture connectivity, and hypocentral depth estimates, the diffusion results are interpreted as a first-order sensitivity analysis rather than a site-specific prediction. Overall, the results support the temporal compatibility and physical plausibility of rapid elastic stress redistribution as a potential triggering mechanism, while recognizing that the available geological and seismological data are insufficient to establish a direct causal relationship or demonstrate fault reactivation. Full article

Reservoir stimulation is essential in enhanced geothermal systems and unconventional reservoirs where low permeability, inadequate fracture connectivity, or near-wellbore damage restricts commercial injection or production. This review evaluates hydraulic fracturing, thermal stimulation, plasma-pulse stimulation, and selected dynamic stimulation technologies. It compares their physical mechanisms, fracture-network development, reservoir applications, permeability enhancement, operational maturity, deployment challenges, and future perspectives. Hydraulic fracturing remains the most mature method for reservoir-scale fracture creation, fracture conductivity, and reservoir connectivity. In enhanced geothermal systems, however, performance depends on the heat-exchange area, distributed flow, thermal sweep, long-term energy recovery, and induced-seismicity control rather than permeability enhancement alone. Thermal stimulation is integral to geothermal reservoir development. Cold-fluid injection generates thermoelastic stress redistribution, enlarges the fracture aperture, activates natural fractures, promotes thermally assisted fracture propagation, and influences thermal breakthrough. Plasma-pulse stimulation, also termed pulsed-power plasma, electrohydraulic, or shock-wave stimulation, provides a low-water method for near-wellbore permeability enhancement, damage bypass, fracture reactivation, and restimulation. Its broader deployment remains constrained by the limited treatment radius, scale-up uncertainty, energy-transfer efficiency, tool durability, completion integrity, and insufficient field validation. Liquid CO₂ phase-transition, propellant, and explosive stimulation provide additional dynamic-loading options with distinct fracture responses, controllability, safety, and technology readiness. Stimulation technologies should therefore be selected according to the dominant reservoir limitation and evaluated using sustained injectivity or productivity, effective reservoir contact, distributed flow, delayed thermal breakthrough, treatment durability, wellbore integrity, and a controlled geomechanical response. Future progress requires hybrid stimulation, coupled thermal–hydraulic–mechanical–chemical (THMC) modeling, integrated monitoring, adaptive control, physics-informed artificial intelligence, digital twins, standardized field validation, and techno-economic and life-cycle assessments. Full article

Dam failure can trigger cascading consequences involving human safety, economic losses, social disruption, and environmental damage. Accurate assessment of these consequences remains challenging due to uncertainties associated with indicator selection, expert judgment, and consequence classification. To address these issues, this study develops an integrated model for evaluating dam failure consequences under uncertainty. A multidimensional evaluation index system consisting of life loss, economic loss, social impact, and environmental impact is established based on existing studies and expert knowledge. The hesitant cloud model is combined with an improved entropy weight method to represent the hesitancy in expert evaluations and to improve the rationality of indicator weight determination. Furthermore, set pair analysis is introduced to evaluate the uncertain relationships between assessment indicators and consequence levels. The proposed model is applied to a reservoir case in China to verify its applicability. The results indicate that the first cumulative membership value, obtained by cumulatively summing the dam failure consequence grades from “slight” to extremely severe”, that exceeds the confidence level λ is 0.7799, corresponding to the severe consequence level. This result is consistent with the comprehensive evaluation obtained using the cloud matter element method. Compared with the traditional method, the generalized set pair potential avoids the case where the opposition degree (c) equals 0. The proposed approach improves the representation of uncertainty and reduces the influence of unclear boundaries among evaluation levels. This study provides a practical decision support tool for dam failure consequence assessment and reservoir risk management. Full article

The Upper Blue Nile Basin contributes about 60% of the Nile River’s annual streamflow but faces severe sediment-related challenges driven by intense monsoonal erosion and reservoir siltation. Accurate estimation of suspended sediment concentration (SSC) and sediment load in large, data-scarce watersheds remains difficult due to sparse monitoring and complex supply-limited transport dynamics. This study develops a hybrid machine learning (ML) and process-based approach for the Kessie watershed (65,784 km²), a major sediment source upstream of the GERD. The approach combines Random Forest (RF) based SSC reconstruction from 251 intermittent samples spanning 1995–2011, approximately 70% collected during the wet season (June–October) and 94% concentrated in 2008–2011, covering a wide range of observed streamflow conditions at the time of sampling (120–5897 m³/s), with a two-stage calibration of the WASA-SED model. Using hydrologically informed predictors, the RF algorithm substantially outperformed the bias-corrected traditional sediment rating curve and other ML algorithms, increasing the validation coefficient of determination (R²) from 0.274 to 0.693. The reconstructed daily SSC yielded a mean annual sediment load of 180.7 Mt/yr. The model performed well, particularly at monthly scales for 1995–2011, achieving good to very good performance (NSE up to 0.83/0.71 for streamflow and 0.86/0.63 for sediment load, calibration/validation, respectively) and reproducing dominant hydrological and sediment regimes using duration curves. Mann–Kendall trend analysis (α = 0.05) indicated no statistically significant monotonic trends in annual rainfall (p = 0.90), mean annual streamflow (p = 0.24 observed; p = 0.84 simulated), or mean annual sediment load (p = 0.66 simulated); the reconstructed sediment load series showed a near-significant increasing tendency (p = 0.06) that falls below the accepted significance threshold and should be interpreted with caution given the short 17-year record. This hybrid approach effectively captures monsoon-driven sediment fluxes and provides model-based daily-to-monthly sediment load estimates with quantified uncertainty. It supports improved reservoir sedimentation assessment, erosion-risk evaluation, and transboundary water-resources planning in data-scarce tropical highlands. Full article

Seasonal snowpack and snowmelt are critical regulators of forest ecosystem functioning in temperate, boreal, montane, and alpine regions. Snowpack acts as a temporary water and energy reservoir, while snowmelt determines the seasonal availability of water and influences ecosystem processes during the growing season. Climate change is altering snowfall patterns, snow accumulation, and melt timing, with consequences for forest productivity, resilience, and disturbance dynamics. This review synthesizes current knowledge on snow–forest interactions and identifies major research trends, methodological approaches, and remaining knowledge gaps. The study combines a bibliometric analysis and a qualitative literature review based on publications indexed in the Scopus and Web of Science databases. A total of 695 publications were included in the bibliometric dataset and analyzed to assess temporal trends, geographical patterns, research themes, and the ecological consequences of changing snow dynamics in forests. Representative studies from this dataset were subsequently synthesized to evaluate the influence of snowpack and snowmelt on forest ecosystem functioning, resilience, and sustainability. The reviewed literature shows that snowpack and snowmelt strongly regulate forest water availability, soil thermal conditions, nutrient cycling, vegetation responses, and carbon dynamics. Changes in snow regimes, particularly reduced snow accumulation and earlier melt, can increase the risk of soil freezing, modify moisture conditions, intensify water stress, and affect ecosystem carbon balance. However, the magnitude and direction of these effects depend on forest type, species composition, climate, and landscape characteristics. Forest structure also plays an important role in controlling snow interception, accumulation, persistence, and melt processes. The bibliometric analysis indicates a rapid increase in research interest in snow–forest interactions over the last two decades, with major contributions from the United States, Canada, China, and Northern Europe. Environmental sciences, hydrology, and ecology were the dominant research areas. Despite substantial progress, uncertainties remain regarding long-term ecosystem responses, species-specific vulnerabilities, and the interactions between declining snow cover and other climate-driven disturbances. This review emphasizes that understanding snowpack and snowmelt dynamics is essential for predicting forest ecosystem responses to climate change and for improving sustainable forest management and watershed conservation strategies in snow-dependent regions. Full article

This study developed a Photovoltaic–Reservoir Water Quality Impact Model (PVRWQIM) based on triangular fuzzy number theory (TFN) to address data sparsity and measurement uncertainty in conventional water quality assessment. The model consists of two components: a TFN-based exceedance-risk module for quantifying the likelihood of water quality parameters exceeding predefined risk thresholds, and a transitional TFN module for evaluating changes in exceedance risk before and after floating photovoltaic (FPV) construction. The model was applied to Junshan Reservoir in Jiangxi Province, China, using 15 observations each from before and after FPV construction. The results indicate the following: (i) Before construction, the exceedance probabilities for water temperature (T), dissolved oxygen (DO), permanganate index (COD_Mn), total phosphorus (TP), total nitrogen (TN), chlorophyll a (Chla), and cyanobacterial density (CD) were 16.7%, 16.1%, 31.3%, 33.7%, 33.3%, 32.7%, and 31.3%, respectively. After construction, the exceedance probabilities for T, DO, COD_Mn, TP, and TN increased to 93.1%, 89.7%, 82.5%, 83.5%, and 83.3%, respectively (p < 0.01), while the probabilities of exceedance for Chla and CD decreased to 14.8% and 14.2%, respectively (p < 0.05). (ii) T and DO are the primary threat factors triggered by FPV construction, with a probability of increased ecological risk of approximately 90%. (iii) The model reveals a statistical correlation pattern: the probability of reduced ecological risk for CD and Chla is 62%, while the probability of increased ecological risk for COD_Mn, TP, and TN is 77%. The two sets of indicators exhibit opposite trends, suggesting that FPV shading may directly suppress algae growth while simultaneously weakening self-purification capacity indirectly through cooling and reduced water flow, thereby contributing to nutrient accumulation. It should be noted that, based on limited observational data, this study reveals correlations rather than proven causal mechanisms; the aforementioned causal interpretations require further validation through controlled experiments or mechanistic models in the future. (iv) The proposed PVRWQIM provides a practical tool for quantifying reservoir water quality risks under sparse data and measurement uncertainty and can support environmental assessment of similar FPV projects. Full article

Circulating tumor DNA (ctDNA) was initially conceived as a minimally invasive surrogate for interrogating cancer biology; however, three decades of evidence have demonstrated that plasma is not a passive reservoir of tumor-derived material, but rather a dynamic and biologically heterogeneous milieu in which multiple competing genomic signals coexist. This review explores the level of interpretive rigor required to translate ctDNA detection into clinically actionable precision oncology. Clonal hematopoiesis of indeterminate potential (CHIP) is discussed not as an occasional confounder, but as an intrinsic source of biological background noise, underscoring the critical importance of matched leukocyte sequencing to discriminate tumor-derived alterations from hematopoietic variants, particularly in older individuals and in patients previously exposed to cytotoxic therapies. The widespread assumption that variant allele frequency (VAF) directly reflects tumor burden is critically re-evaluated through the mathematical relationships linking VAF to tumor fraction, local copy-number architecture, and mutation multiplicity. Within this framework, estimation of cancer cell fraction (CCF) and probabilistic discrimination between clonal and subclonal events are examined, including the emergence of reversion mutations as molecular evidence of therapy-driven evolutionary adaptation. The review also addresses the central paradox of ultra-sensitive sequencing technologies: although unique molecular identifiers and duplex sequencing can extend analytical sensitivity below 0.01% VAF, sensitivity in the absence of contextual specificity risks conflating technical artifacts and biologically insignificant alterations with clinically meaningful disease. Equal emphasis is placed on pre-analytical variables, highlighting how sample collection, stabilization, and processing protocols define the upper limit of downstream analytical reliability. Beyond single-nucleotide variants, fragmentomic and methylation-based approaches are presented as complementary orthogonal dimensions capable of revealing tumor-associated signals even when mutational evidence is limited or absent. Longitudinal ctDNA assessment is argued to provide substantially greater biological and clinical insight than isolated static measurements, while robust clinical reporting is shown to depend on transparent disclosure of assay limitations, residual uncertainty related to CHIP, and structured bidirectional communication between molecular laboratories and treating clinicians. Ultimately, the transition from a biomarker-centered model toward an integrated systems-based framework, combining genomics, epigenomics, fragmentomics, and evolutionary modeling, emerges as the defining challenge for the next generation of liquid biopsy in precision oncology. Full article

Exploitation of geothermal energy stored in hot dry rocks requires the application of enhanced geothermal system (EGS) technology, which enables artificial enhancement of reservoir permeability and improved heat extraction efficiency. This study addresses the assessment of geothermal potential in the Gorzów Block (NW Poland), an area identified as prospective for a CO₂-enhanced geothermal system (CO₂-EGS). Geological modeling was used as the primary tool to integrate structural, petrophysical, and thermal data in order to reduce exploration uncertainty and identify the most favorable reservoir interval. The workflow included structural interpretation and parameter modeling of key reservoir properties, with particular emphasis on porosity, clay mineral content, permeability, density, and temperature distribution. The results indicate that the optimal reservoir zone is located at depths of 4100–4300 m below ground level within Lower Permian volcanic formations (Autunian). At this depth, reservoir temperature reaches approximately 145 °C. The analyzed rocks exhibit low porosity (0.04), moderate clay content (0.12), very low permeability (0.008 mD), and an average density of 2.59 g/cm³, indicating tight reservoir conditions requiring hydraulic stimulation. The assessment is subject to limitations associated with the availability and spatial distribution of subsurface data, as well as uncertainties inherent in geological and petrophysical modeling of deep formations. Therefore, the identified reservoir interval and estimated parameters should be regarded as a preliminary assessment that requires further verification through additional exploration and reservoir testing. Nevertheless, the study confirms the value of integrated geological modeling for identifying deep geothermal reservoirs and supporting decision-making in EGS site selection. Full article

Reliable estimates of future precipitation are essential for adaptive water management in large river basins. This study presents a machine-learning approach that combines six CMIP6 models to examine precipitation changes in the Yangtze River Basin. ERA5 monthly precipitation for 1979–2025 served as the reanalysis reference. The random forest model incorporated individual model outputs, ensemble statistics, geographic variables, and monthly cyclic terms. It was trained with data from 1979–2009, evaluated for 2010–2014, and then applied to the period 2015–2099 under SSP1-2.6, SSP2-4.5, and SSP5-8.5. Compared with the simple multi-model mean, the proposed method showed better agreement with ERA5 and generally smaller reconstruction errors during the validation period. Annual precipitation is projected to increase under all three pathways, with the largest increase under SSP5-8.5. Precipitation remains concentrated from May to August, while spring totals and intra-annual variability increase more clearly under high-emission conditions. Mean precipitation remains highest in the humid middle and lower reaches, while the magnitude and significance of future trends vary across the basin. Inter-model spread remains greater than the differences among emission pathways and reaches 85.92 mm under SSP5-8.5 during 2071–2099. These results represent uncertainty-aware climate estimates rather than verified forecasts. They can support flood-risk assessment, reservoir planning, and adaptive water management in the Yangtze River Basin. Full article

Radioisotopic techniques provide powerful tools for reconstructing the history of lake sediments, offering critical insights into past environmental changes and human impacts. These techniques have contributed significantly to our understanding of past environmental change and have implications for current environmental management practices. This review comprehensively examines various radiometric dating techniques used for lake sediments, with a focus on natural, cosmogenic, and artificial radionuclides, including ²¹⁰Pb, ¹³⁷Cs, ²⁴¹Am, ⁷Be, ³H, and ¹⁴C. The review highlights the widespread use of radionuclides in establishing sediment chronologies across different time scales, from short-term processes (days to decades) to long-term environmental reconstructions spanning thousands of years. Moreover, applications in limnological research are explored, including sedimentation rate estimation, reconstruction of pollution history of trace elements, nutrients, microplastics, and organic compounds, and assessment of anthropogenic impacts and catchment changes. The integration of radioisotopic methods with multiproxy paleolimnological approaches is emphasized as a powerful framework for reconstructing past environmental and ecological conditions. Despite their effectiveness, radioisotopic methods are exposed to several sources of uncertainty, including dispersion in atmospheric isotope flux, post-depositional processes, reservoir effects, and model assumptions. These challenges highlight the importance of careful methodological selection, site-specific evaluation, and rigorous uncertainty assessment in radioisotopic studies of lake sediments. Future research should emphasize refining sediment age-model calibration using region-specific sedimentation parameters and standardized validation procedures, and integrating radiometric techniques with geochemical, biological, and paleolimnological proxies to improve the reconstruction of environmental change in lacustrine systems. Such developments would enhance the interpretation of historical pollution records, sediment accumulation patterns, eutrophication history, and ecological variability, thereby providing scientifically robust information to support evidence-based lake management, restoration programs, and long-term conservation strategies. Full article