Search Results (2,083)

Negative air ions (NAIs) are key ecological indicators of atmospheric cleanliness and forest ecosystem service functions, particularly in the context of forest wellness and ecotourism. However, long-term, high-frequency observations of NAIs across broad spatial scales remain scarce, limiting our understanding of its regional spatiotemporal dynamics and environmental controls. Here, we present a six-year (2018–2023) continuous, hourly monitoring dataset of NAI concentrations from 60 fixed forest sites across Zhejiang Province, a typical subtropical humid region in southeastern China. The provincial mean NAI concentration over the study period was 1672 ions·cm⁻³, with a pronounced “high around the periphery, low in the center” spatial pattern, with the mountainous southwestern areas consistently showing the highest concentrations and the central Jinqu Basin the lowest. On diurnal scales, NAIs exhibited a bimodal pattern with primary peaks at 7:00 and secondary peaks at 16:00, rather than a simple daytime–nighttime dichotomy. Seasonal dynamics showed significantly higher NAI in summer than in autumn and winter; however, the summer–winter difference was only ~25%, much smaller than the ratios reported for temperate regions. Interannually, NAI concentrations increased from 2018 to 2023 (average annual increase of 158 ions·cm⁻³), peaking during the 2020–2022 period, when anthropogenic emissions were substantially reduced. Using linear mixed-effects models, we identified relative humidity as the dominant positive driver of NAI variability, followed by wind speed as a negative modulator, and precipitation playing a minor role. These findings reveal the multi-scale spatiotemporal dynamics of NAIs in subtropical forests and underscore the overriding control of humidity over ion persistence. Our study provides a robust regional benchmark for background NAI levels in humid subtropical climates and offers direct scientific support for forest-based health resource planning and air quality assessment. Full article

Natural lakes in urbanizing regions face compounding climatic and anthropogenic pressures. Despite their socio-ecological importance, the dual vulnerability of these urban lakes to both long-term areal shrinkage and the shifting frequencies of extreme water events remains a critical research gap, often overlooked in favor of large, remote lake systems. We investigated surface area dynamics, extreme events, and climatic attribution of 7320 natural lakes across China’s five major urban agglomerations (Jing-Jin-Ji, Yangtze River Delta, Greater Bay Area, Chengdu-Chongqing, and Middle Yangtze) from 2001 to 2023. Using a satellite area product, we assessed long-term trends via Seasonal-Trend decomposition by Loess (STL). Regional climate shifts were detected via multi-scale Standardized Precipitation–Evapotranspiration Index (SPEI) breakpoint analysis, and climate attribution was performed by correlating detrended lake areas with SPEI. Results show 59.4% of lakes exhibit significant trends, with shrinkage (50%) vastly outpacing expansion (9.4%), most severely in Jing-Jin-Ji (−0.28%/year). Despite all agglomerations transitioning toward wetter conditions (2008–2013), extreme event responses diverged markedly regionally. Climate-driven lakes (14.5%) displayed stronger shrinkage and greater sensitivity to extremes than lakes with low climate sensitivity, particularly in Jing-Jin-Ji and Chengdu-Chongqing. These findings reveal pronounced spatial heterogeneity in urban lake vulnerability, providing an evidence base for sensitivity-stratified management strategies. Full article

Rainfall variability strongly influences both flood and drought hazards, especially in climatic transition zones where precipitation is highly seasonal and spatially heterogeneous. This study assessed long-term changes in rainfall patterns and compound flood–drought hazard in the Huaihe River Basin, China, using ERA5-Land-derived daily precipitation series at 174 spatial sampling locations during 1950–2025. Rainfall pattern indicators, flood-related rainfall extremes, and SPI-3-based drought indicators were calculated to characterize rainfall amount, frequency, intensity, dry–wet persistence, heavy rainfall events, and meteorological drought conditions. The Mann–Kendall test and Sen’s slope estimator were used to detect long-term trends, and a compound flood–drought hazard classification framework was developed based on a flood-related rainfall hazard index (FHI) and a drought-related hazard index (DHI). The results showed that annual total precipitation, wet days, and consecutive wet days decreased significantly, indicating reduced rainfall occurrence and wet spell persistence. Flood-related rainfall indicators generally showed decreasing tendencies, with more evident declines in persistent multi-day extremes than in single-day rainfall. In contrast, mean SPI-3 showed a significant drying tendency, although drought frequency, severe drought frequency, and drought intensity did not exhibit significant monotonic trends. Spatially, rainfall pattern, flood-related, and drought-related indicators showed clear heterogeneity across the basin. The compound hazard classification identified flood-dominated and drought-dominated areas as the two major hazard types, each accounting for 31.03% of the spatial sampling locations, while low compound hazard and compound flood–drought hazard areas each accounted for 18.97%. These findings indicate that flood- and drought-related hazards coexist but vary spatially across the Huaihe River Basin. The proposed framework provides preliminary rainfall-based information for differentiated flood–drought hazard assessment, climate-adaptive water resources planning, and the sustainable management of water resources in regions facing spatially heterogeneous hydroclimatic hazards. Full article

Taking the Yellow River Basin (YRB) as an example, this study explores the non-stationary drought evolution features in large river basins under climate change. This study utilized precipitation and multiple climate factor data to establish the non-stationary standardized precipitation index (NSPI) through the GAMLSS model. Combined with the run theory, Copula function and a cascaded RF-LSTM machine learning model, the drought characteristics and retrospective predictive patterns were systematically assessed. The results show that: (1) The Arctic Oscillation, the Pacific Decadal Oscillation, the Southern Oscillation and the North Pacific Index are the primary climate drivers of non-stationary precipitation variation in the YRB, with the former three being selected most frequently and NPI additionally influencing April–June and September, and their effects are both different and lagging. Compared with the traditional SPI, the NSPI assigned higher drought grades and greater severity to typical drought years (e.g., the 1974 event was rated D3 with a severity of 17.935 by NSPI versus D2 with 11.733 by SPI), and thus better captured non-stationary drought evolution. (2) The duration of droughts exhibited a decreasing trend that was not statistically significant (p > 0.05), whereas drought intensity and severity decreased significantly (p < 0.05); the peak severity showed a significant upward trend (p = 0.0078). Spatially, the northwest of the Loess Plateau was a compound core area with high severity, high frequency and long duration of droughts, while the upper reaches were mainly characterized by low severity, short duration and sudden droughts. (3) The drought risk in the YRB shows a higher frequency in the lower reaches and a lower frequency in the upper reaches. The middle and lower reaches were high-risk areas, with shorter AND-type joint exceedance return periods for moderate drought (2.46–5.83 years) and severe drought (3.77–9.15 years). The upper reaches were low-risk areas, with longer return periods reaching up to 5.83 years for moderate drought and 9.15 years for severe drought. The study shows that the NSPI, considering the driving of multiple climate factors, can more effectively identify and assess non-stationary drought risks, providing a scientific basis for drought prevention and control in river basins. Full article

Flooding triggered by intense precipitation is a significant natural hazard affecting Mediterranean regions, where complex terrain, rapid hydrological response and increasing urbanization can amplify flood impacts. This study assesses flood susceptibility in two representative Mediterranean River catchments: the Koiliaris in Crete, Greece, and the Pediaios in Cyprus. A compact Flood Hazard Index (FHI) was developed by integrating the Topographic Wetness Index (TWI), Curve Number (CN), and R20 heavy rain frequency index, representing the principal geomorphological, hydrological and climatological controls of flood generation. Spatial datasets including EU-DEM elevation data, CORINE land cover, European soil databases, and Copernicus CERRA precipitation reanalysis were combined within a GIS-based multi-criteria framework using Analytic Hierarchy Process weighting. The resulting FHI maps identify high flood susceptibility along river corridors, low-lying accumulation zones, and urbanized areas. In the Koiliaris basin, 34% of the area fell within the high and very high susceptibility classes, mainly in downstream alluvial zones, whereas in the Pediaios basin, 29% of the area fell within the high and very high susceptibility classes, concentrated around the urbanized Nicosia corridor. The analysis of historical flood events provided a qualitative consistency assessment of the FHI patterns, acknowledging that the absence of spatially explicit flood-inundation footprints limits quantitative validation. Full article

Aqueous precipitation and crystallization are central to impurity removal, product formation, and resource recovery in mineral and chemical processing, but robust inline monitoring remains challenging because supersaturation is not measured directly and conductivity signals are affected by temperature, composition drift, bubbles, solids, polarization, and fouling. Electrical conductivity (EC) is attractive as a low-cost, rugged process analytical tool, yet its usefulness depends on mechanistic interpretation: EC reflects charge-carrier concentration and mobility rather than supersaturation itself. This review organizes the literature into a layered framework covering (i) measurement integrity and deployment, (ii) bulk-signal extraction in multiphase media, (iii) estimation of latent variables such as dissolved concentration or supersaturation proxies, and (iv) control readiness based on conductivity-derived targets. Frequency-aware conductivity extraction, event-anchored verification, and observer-based estimation are treated as optional, complementary modules. A Ca-carbonate/CaCO₃ system is used as an illustrative case because its coupling among conductivity, pH/speciation, supersaturation, and precipitation is especially transparent, although the framework is intended for broader processing systems, including complex liquors and slurries. Opportunities are also highlighted for nanomaterials to improve both precipitation control and EC information content. Full article

This study established a refined, distributed SWAT modeling framework that integrates elevation-band and snowmelt modules to reconstruct the alpine hydrological and sediment cycles of the Koshi River Basin (KRB) over the period 1990–2024, with climate scenarios constructed using the delta change approach. The KRB, a major transboundary watershed traversing China, Nepal, and India, was selected owing to its critical hydro-climatic role under the destabilizing “Asian Water Tower”; it generates substantial sediment yield, hosts the densest concentration of hydropower potential within the Ganges system, and spans an extreme vertical gradient from Mount Everest to the southern alluvial plains. Results reveal accelerated warming at a rate of 0.21 °C per decade and an overall warming–wetting trend, punctuated by an abrupt interdecadal shift around 2015. Precipitation dominated interannual streamflow variability, with enhanced rainfall triggering basin-wide sediment surges that overwhelmed the natural buffering capacity of the land surface. Conversely, rising temperatures intensified actual evapotranspiration, markedly depleting soil water and reducing total water yield and monsoon runoff, although sustained snow and glacier melt effectively elevated the dry-season low-flow baseline. The integrated climate forcing reshaped the disparity between hydrological extremes, imposing severe seasonal eco-hydrological stress that manifested as a pre-monsoon deficit in terrestrial green water and acute summer sediment outbursts for aquatic habitats. Furthermore, the flood regime exhibited an altered distribution, with mid-to-high frequency floods enhanced while low-frequency extreme flood peaks declined. The hydro-sedimentological regime consequently exhibits pronounced nonlinear responses to climate change, providing a critical, threshold-based scientific foundation for adaptive transboundary water resource management. Full article

Climate change is expected to significantly alter hydrological regimes in high-altitude tropical basins, where water availability strongly depends on precipitation variability and groundwater processes. The Ramis River basin, a major tributary of Lake Titicaca in the Peruvian Altiplano, is particularly vulnerable to hydroclimatic variability due to its dependence on seasonal water resources. This study evaluates the impacts of climate change on runoff, groundwater recharge, percolation, and renewable water resources using the SWAT hydrological model calibrated and validated for the period 1981–2024. Future projections were developed using the MPI-ESM-MR and ACCESS1-0 global climate models under RCP 4.5 and RCP 8.5 scenarios for the period 2025–2100, applying bias correction through CMhyd. The results indicate a strong sensitivity of basin hydrology to climate forcing. Under the MPI-ESM-MR model, runoff decreases by up to 68% under RCP 4.5, while extreme increases exceeding 130% are projected under RCP 8.5. In contrast, ACCESS1-0 shows moderate reductions in most scenarios. Renewable water resources exhibit a general declining trend (−23% to −41%), suggesting increasing water scarcity conditions. Additionally, the Standardized Precipitation Index (SPI) reveals a higher frequency and persistence of drought events toward the end of the century, particularly under high-emission scenarios. Overall, the findings indicate that the Ramis River basin may face a dual hydroclimatic risk characterized by reduced water availability and increased hydrological extremes. These results highlight the need to integrate climate projections into water resource management and to implement adaptive strategies to reduce future water vulnerability in high-Andean basins. Full article

Nickel ferrite (NiFe₂O₄) is one of the most studied inverse-spinel ferrites because it combines moderate saturation magnetization, comparatively high electrical resistivity, chemical stability, and broad synthesis flexibility. Yet the literature shows that the measured structure and magnetism of NiFe₂O₄ are not intrinsic constants; they evolve strongly with dimensionality, size, thickness, strain state, cation distribution, surface spin disorder, and synthesis pathway. This review develops a unified theoretical and literature-based interpretation of how dimensionality reshapes the structural and magnetic behavior of NiFe₂O₄ across bulk ceramics, nanoparticles, one-dimensional nanostructures, polycrystalline thin films, and ultrathin epitaxial films. The review is anchored in the two uploaded nickel ferrite attachments and expanded using internet-sourced journal literature on spinel inversion, surface effects, mechanochemical synthesis, sputtered and pulsed laser deposited thin films, and epitaxial ultrathin-film anomalies. The central novelty of this article is the formulation of a dimensionality-dependent framework in which the observed magnetic response is governed by a competition among three coupled factors: (i) the cation-distribution function, which controls the A–B superexchange balance and therefore the net ferrimagnetic moment; (ii) the microstructural coherence function, which measures how crystallinity, strain, defects, and anti-phase boundaries preserve or degrade exchange continuity; and (iii) the surface/interface spin-order parameter, which quantifies the loss or reconfiguration of magnetic order at free surfaces and buried interfaces. Within this framework, bulk NiFe₂O₄ behaves as a near-equilibrium inverse spinel with relatively stable magnetization, whereas nanoscale NiFe₂O₄ experiences strong spin canting and finite-size suppression due to the growing fraction of disordered surface spins. Thin films introduce a distinct regime in which strain, texture, anti-phase boundaries, substrate mismatch, and growth kinetics determine both anisotropy and magnetization. In ultrathin epitaxial films, off-equilibrium cation redistribution and interface-controlled electronic reconstruction may even generate magnetization values far above bulk expectations. The review also compares major synthesis routes—solid-state reaction, sol–gel, co-precipitation, hydrothermal growth, reactive milling, combustion, pulsed laser deposition, and radio-frequency sputtering—and explains why each route biases the final dimensionality-dependent properties differently. A set of word-style equations is provided to formalize spinel inversion, finite-size suppression, anisotropy scaling, coercivity trends, and superparamagnetic crossover. Beyond summarizing the field, the review proposes a regime map linking dimensionality to characteristic structural defects and magnetic signatures, and it identifies unresolved questions concerning the true origin of enhanced magnetization in ultrathin NiFe₂O₄, the interplay between anti-phase boundaries and strain, and the distinction between intrinsic inversion changes and extrinsic substrate artifacts. The resulting article offers a submission-ready, originality-focused review that positions dimensionality as the master variable governing structure–magnetism correlations in nickel ferrite. Full article

With global warming continuously worsening drought hazards, the Fuhe River Basin urgently requires insight into drought evolution laws to support resilient water resources management. However, traditional univariate indices such as the Standardized Precipitation Index (SPI) and Standardized Soil Moisture Index (SSI) are limited by their inability to capture the coupled meteorological-agricultural drought process and the time-lag effects between precipitation and soil moisture response. Therefore, a multivariate drought index—which integrates both precipitation and soil moisture information—is needed as a core tool for drought early warning and precise regulation. In this study, the calibrated SWAT model was used to simulate monthly soil moisture content in the Fuhe River Basin over the past 60 years. On a 3-month time scale, a Multivariate Standardized Drought Index (MSDI) was established by coupling the Standardized Precipitation Index (SPI) and Standardized Soil Moisture Index (SSI) using the Copula function. The main findings are as follows: (1) The Nash–Sutcliffe efficiency coefficient (NS) of the SWAT (Soil and Water Assessment Tool) model during the validation period reached above 0.70, indicating favorable performance in monthly runoff simulation. (2) The MSDI revealed frequent drought events in two periods, namely 1960–1979 and 2000–2019, demonstrating the periodic fluctuation pattern of droughts in the basin. (3) Wavelet analysis showed that compared with the previous two periods, the frequency of droughts in the basin increased significantly after 2000, with weakened periodic characteristics, intensified extreme drought events, and a further rise in drought risks. This study deepens the understanding of drought dynamics in the Fuhe River Basin and provides a scientific basis for regional sustainable water resource management and the formulation of climate adaptation strategies. Full article

Foraminiferal shell crystals incorporate the chemical signals of their environment during growth. The recorded information is extracted from the crystals via proxies and can be used to reconstruct paleoenvironments, paleoclimates, and the change of the latter. However, the information that is obtained from the biocrystals is often biased, due to structural and chemical modification of the crystals resulting from dissolution, precipitation, recrystallization, and overall, the transformation of the biologically formed crystals into their inorganic analogs. Electron-backscatter diffraction (EBSD) measurements and analysis render a wide range of information regarding crystallographic-structural attributes of the crystals, such as crystal-microstructure, crystal-texture, the misorientation interrelation of adjacent crystals, crystal-twin-generation and many more. We demonstrate in this study that diagenetic overprint of foraminiferal shell Ca-carbonate crystals can be identified by structural-crystallographic characteristics obtained from EBSD measurements. We investigated modern/pristine and fossil Trilobatus sacculifer shells and observed an undisturbed shell surface for both. Despite the latter, we demonstrate here that with an increase in the degree of fossilization and diagenetic overprint, there is an increase in recrystallized calcite in the shells and a decrease in twinned calcite. Twinned calcite is the hallmark of pristine T. sacculifer shells. We show that, with increasing degrees of shell overprint, crystal-microstructure, and crystal-texture, the frequency of the 60°|<001> twin misorientation is modified and propose to use structural-crystallographic attributes determined with EBSD measurements for the identification of recrystallized/overprinted foraminiferal carbonate. We discuss that disclosing low degrees of overprint is of main importance, as minor structure changes of overprinted shells are easily overlooked with SEM imaging. Nonetheless, these are readily identified with EBSD-measurements. Full article

In many orographically complex monsoon basins, rain gauge networks are sparse and lack the long-term continuous records required for reliable precipitation probability analysis. Traditional regional frequency analysis assumes spatially uniform precipitation across the analysis zone, which is inadequate for basins with steep rainfall gradients and strong seasonal variability. Gridded precipitation products (GPPs) provide spatially continuous, long-term records that enable grid-cell-level probability distribution fitting. However, GPPs may exhibit local biases and errors, and statistical evaluation against gauge observations is necessary before application. This study was conducted in the Phetchaburi–Prachuap Khiri Khan River Basin, western Thailand, a region with steep orographic and coastal rainfall gradients. Four GPPs, namely CHIRPS, CHELSA, WorldClim, and PERSIANN-CCS-CDR, were evaluated against gauge observations. The best-performing product, after monthly bias correction, was then used to generate spatially continuous monthly exceedance probability maps using grid-cell gamma distribution fitting. CHELSA showed the best overall performance across all evaluation metrics (correlation coefficient (r) = 0.908, percent bias (PBIAS) = 7.0%, root mean square error (RMSE) = 48.3 mm), passing the Kolmogorov–Smirnov (KS) goodness-of-fit test at all 96 station-months. CHIRPS and WorldClim showed satisfactory overall performance but exhibited localized biases in complex terrain, whereas PERSIANN-CCS-CDR substantially overestimated wet-season rainfall, limiting its suitability for this basin. Spatial precipitation patterns varied markedly between monsoon regimes, shifting from a dominant west-to-east orographic gradient during the southwest monsoon to a less differentiated advective pattern during the northeast monsoon. Furthermore, analysis at the 75% exceedance probability level showed that mean-based effective rainfall overestimated reliable water supply in high-variance months, leading to underestimation of supplemental irrigation demand. The generated maps provide spatially explicit dependable rainfall estimates across the basin, supporting probabilistic agricultural water management at multiple planning scales in orographically complex monsoon basins. Full article

Flood hazards are intensifying across Africa due to rapid urban expansion and hydro-climatic variability. This study develops a multi-metric geospatial framework combining extreme value analysis, hydrograph-based metrics, and dependence modelling to quantify flood magnitude, frequency, timing, and joint risk dynamics. Daily precipitation and streamflow reanalysis data (1985–2025) were analyzed for two contrasting Tanzanian catchments: the large Rufiji basin (RU) and the smaller Mirongo catchment (MW). Annual maxima were modelled using the Generalized Extreme Value (GEV) distribution, complemented by flow duration curves, peak-over-threshold detection, and regression-copula dependence analysis. Results reveal strong hydrological contrasts. RU exhibits amplified rare-event growth (design floods from ~2850 to 11,770 m³/s), extended recession persistence (>100 days), low flashiness, and long rainfall-runoff lags (~15 days), indicating storage-dominated behavior. MW shows smaller design floods (~80 to 370 m³/s), higher flashiness, and short lags (~4 days), reflecting rapid, rainfall-driven response. Gaussian copula parameters indicate moderate dependence in both basins (0.32 and 0.34), suggesting that joint dependence alone does not distinguish flood mechanisms without complementary metrics. The proposed framework improves basin-specific flood risk profiling and supports geospatial early-warning system design in data-scarce Sub-Saharan environments. Full article

Climate models suggest that longer dry periods and heavier rainfall events may occur in arid and semiarid regions, which may greatly affect plant growth and propagation in these regions. Numerous studies have documented the relationship between grassland productivity and precipitation. However, the interactive effects of rainfall amount and rainfall frequency on the growth of perennial grasses with rhizomatous propagation, especially on clonal growth, have not yet been studied. In this study, the effects of three rainfall amounts and two rainfall frequencies on the vegetative traits and clonal growth traits of Leymus chinensis, a perennial rhizomatous species, were examined. Rainfall amount and rainfall frequency exhibited a significant interaction only for the root biomass ratio between the 0–20 cm and 20–40 cm soil layers. All traits (including height, aboveground biomass, root biomass, rhizome number, rhizome length, bud bank size, and daughter shoot number) increased markedly with increasing rainfall amount but showed little response to rainfall frequency. Only the root biomass in the 20–40 cm soil layer increased with an extended dry period between two rainfall events, resulting in a lower root biomass ratio between the 0–20 cm and 20–40 cm soil layers under the medium and high rainfall amount treatments. The size of the belowground bud bank was positively correlated with the daughter shoot number as well as the aboveground biomass, and the positive relationship between the bud bank size and daughter shoot number was strengthened with increasing rainfall amount, but was not sensitive to rainfall frequency. However, lower rainfall frequency significantly decreased the rhizome number per plant. These results highlight that summer rainfall amount is more important than rainfall frequency for the population growth of L. chinensis at medium and high rainfall amounts, and that lower rainfall frequency may reduce the long-term clonal growth ability of L. chinensis in the future. Our findings reveal the response mechanisms of L. chinensis productivity to climate change from the novel perspective of bud banks, which provides practical management insights for artificially established L. chinensis grasslands. This study also offers important implications for elucidating the contributions of belowground biomass production to soil carbon sequestration in grassland ecosystems. Full article

Substantial uncertainties remain in climate model simulations of tropical cyclones (TCs), particularly those associated with internal climate variability. While the influence of the El Niño–Southern Oscillation (ENSO) on interannual TC variability is well established, the contribution of the Interdecadal Pacific Oscillation (IPO) to decadal-scale uncertainty is less well constrained. Although models generally reproduce IPO-related variations in tropical cyclone genesis frequency (TCGF) over the eastern North Pacific, large discrepancies persist across the broader North Pacific basin. Clarifying the role of IPO in modulating TCGF uncertainty is therefore essential for improving decadal TC projections. In this study, we analyzed a large ensemble of historical simulations from the MRI-AGCM within the d4PDF (Database for Policy Decision Making for Future Climate Change) framework. Empirical orthogonal function (EOF) analysis is applied to IPO-composited fields to identify the leading modes of intermember (100 members *60 y, 6000 times) simulation uncertainty on a decadal-scale. The results reveal that state-of-the-art models exhibit robust and spatially coherent uncertainty structures in TCGF under different IPO phases. Two leading modes are identified: (1) a South China Sea mode, closely associated with systematic precipitation biases, and (2) a zonal dipole mode between the eastern and western North Pacific, linked to the equatorward propagation of Arctic Oscillation (AO)-related variability. Misrepresentation of AO variability is found to contribute substantially to biases in simulated TCGF patterns. Comparisons with observational datasets further support the proposed mechanisms. These findings highlight the importance of improving the representation of precipitation processes and extratropical–tropical teleconnections in climate models, which is critical for enhancing the reliability of decadal predictions of North Pacific TC activity. Full article