Search Results (3,715)

In 2023, Tropical Cyclone Freddy caused severe damage in southern Malawi, flooding much of the lowland area near Lake Chilwa and displacing many residents. This study evaluates long-term, region-specific mitigation strategies to lessen future risks, using a novel approach that combines drone and satellite data, building footprints, and 3D simulations to analyze how building elevation affects flood damage and assess Property-Level Flood Risk Adaptation measures. Results show a significant difference in ground elevation between affected and unaffected buildings, with damaged structures generally at lower levels. The 3D simulation confirmed a water-level rise of approximately 3.0 m caused by Freddy. Scenario analysis indicates that elevating buildings by 2.0, 2.5, and 3.0 m could reduce direct flood exposure and 64%, 76%, and 91% of damage, respectively. These insights can inform the development of targeted regional risk-mitigation strategies through Property-Level Flood Risk Adaptation in high-risk areas. Full article

Although sedimentary zones in Lake Taihu differ in external inputs, hydrodynamic conditions, and sedimentary settings, the spatial differentiation of eukaryotic microbial communities and their assembly mechanisms remain insufficiently understood. This study analyzed sediment cores from four typical sedimentary zones of Lake Taihu: Dapu (DP), Gonghu (GH), the central lake area (HX), and Xuhu (XH). By integrating physicochemical measurements, 18S rRNA gene high-throughput sequencing, redundancy analysis, functional annotation, iCAMP, and co-occurrence network analysis, we characterized the composition, environmental associations, and assembly mechanisms of sedimentary eukaryotic microbial communities. The results showed that eukaryotic microbial communities in Lake Taihu sediments exhibited marked spatial heterogeneity, with dominant taxonomic groups including Chlorophyta, Intramacronucleata, and Diatomea. Alpha diversity was higher in the GH zone and lower in the HX zone, whereas beta diversity showed significant separation among lake zones. NH₄⁺-N, NO₃⁻-N, TN, TP, TOC, D50, MWC, and pH were associated with variation in community composition, but the main associated factors differed among zones. FunGuild annotation showed that annotated fungal functional groups exhibited distinct trophic distribution patterns across sedimentary zones. iCAMP analysis indicated that community assembly was generally dominated by stochastic processes, with dispersal limitation prevailing in the GH zone and ecological drift dominating in the DP, HX, and XH zones. Co-occurrence network analysis further revealed marked differentiation in potential biological associations among sedimentary zones. Overall, this study showed that nutrient conditions and sediment physical properties in different sedimentary environments of Lake Taihu jointly shaped the spatial patterns of eukaryotic microbial communities and their ecological associations, providing baseline information for understanding sedimentary ecological processes in eutrophic shallow lakes. Full article

The Xianglaqu River Basin, a major recharge area of the Xiagacuo endorheic lake basin on the Tibetan Plateau, provides an ideal setting for investigating hydrochemical evolution in alpine arid closed basins. In this study, 27 groundwater, spring-water, and surface-water samples collected from June to August 2023 were analyzed using correlation analysis, Piper diagrams, Gibbs diagrams, and ion-ratio methods. The results show that groundwater, spring water, and most surface water are predominantly of the HCO₃⁻–Ca·Mg type, indicating overall hydrochemical consistency across the basin. However, marked spatial differentiation occurs along the flow system: upstream waters are relatively simple and stable, whereas downstream and terminal surface waters show pronounced increases in Na⁺, Cl⁻, SO₄²⁻, and TDS, and some samples exhibit a tendency toward HCO₃⁻–Na facies. These patterns reflect progressive solute accumulation and terminal enrichment in the closed basin. Hydrochemical evolution is controlled mainly by water–rock interaction, with carbonate weathering as the dominant source of major ions, while silicate weathering, minor local saline-mineral dissolution, cation exchange, and evaporation concentration further influence water chemistry. Overall, the basin is characterized by local weathering release, along-path solute accumulation, and terminal evaporative enrichment. Full article

Phytoplankton are the primary producers in freshwater lake ecosystems and play a fundamental role in maintaining the structure and function of lacustrine food webs. Baiyangdian Lake, located at the core of Xiong’an New Area, is vital for regional aquatic ecological security. However, systematic data on phytoplankton community dynamics throughout the phytoplankton critical growing season are scarce. In this study, we conducted a monthly investigation of phytoplankton communities in Baiyangdian Lake from April to October 2025, analyzing community composition, abundance, and diversity patterns. A total of 152 phytoplankton taxa across 8 major algal groups were identified, with Chlorophyta, Bacillariophyta, and Cyanobacteria being the dominant groups. Phytoplankton abundance exhibited distinct seasonal variation, peaking in August and reaching its lowest in October. The Shannon–Wiener diversity index (H′) and Pielou evenness index (J′) were generally at favorable levels, indicating a relatively stable community structure. The mean phytoplankton density across all sampling sites during the growing season was 8.70 × 10⁶ cells/L, categorizing the lake as having “no obvious bloom” according to standard bloom severity classifications. The overall trophic state of Baiyangdian Lake during the study period was mesotrophic. These findings provide fundamental baseline data and scientific support for the management of algal bloom risks and the long-term conservation of the lake’s aquatic ecosystem. Full article

Water contamination by phenolic endocrine-disrupting chemicals (EDCs) is a global environmental concern. Yet, the occurrence of phenolic EDCs in artificial water diversion systems remains poorly understood. Thus, the Eastern Route of the South-to-North Water Diversion Project, the world’s longest water diversion project, was chosen as the study area to investigate the spatiotemporal distribution of alkylphenols (APs) and bisphenol A (BPA), typical phenolic EDCs, and to evaluate their risks. During the diversion operation, higher mean ΣAP concentrations were observed in lakes of Nansi and Dongping relative to the Luoma Lake–Dongping Lake and Yangtze–Luoma Lake diversion channels. The AP composition in the two lakes was also different from that in the two channels. These findings demonstrated that the canal water was not a key source of AP contamination in the lakes, highlighting the importance of local wastewater inputs. The spatial distribution of ΣAP and BPA concentrations in the lakes was mainly affected by the riverine inputs. For ecological risks, 4-n-nonylphenol (4-n-NP) exhibited moderate ecological risks at 81.3% of sampling sites in Dongping Lake and 68.8% of those in Luoma Lake, highlighting the need for heightened attention in future studies. Even under the high exposure scenario, 4-n-NP and BPA would not produce health risks to residents through water intakes. Overall, surface water resources of the Eastern Route Project were confirmed to be safe for human consumption. Full article

Most remote-sensing studies of cyanobacterial blooms have focused on bloom onset, peak intensity, and spatial extent, while the post-bloom recovery stage has received far less attention. Yet this stage is directly relevant to water-quality recovery and to the timing of management response. In this study, we developed an event-based remote-sensing framework to quantify post-bloom recovery using satellite-derived chlorophyll-a as the core indicator, and applied it to Lake Taihu and Lake Dianchi over the period 2000–2022. FAI-derived bloom-area time series were used to identify bloom days and event termination, while satellite-derived chlorophyll-a was used to determine the post-bloom recovery date relative to an event-specific background threshold. Recovery duration was defined as the period from bloom termination to the first return of chlorophyll-a below an event-specific background threshold. Based on this framework, we quantified recovery duration, event frequency, representative recovery trajectories, and recovery-rate metrics, and then examined their controls using statistical comparison, nonlinear modeling, grouped contribution analysis, and path-based validation. The two lakes showed distinct recovery regimes. Lake Taihu had 82 recovery events, with a mean recovery duration of 8.82 days and a median of 6 days, whereas Lake Dianchi had 28 events, with a mean duration of 25.32 days and a median of 22 days. Events lasting more than 20 days accounted for 9.76% of cases in Taihu but 57.14% in Dianchi. By the recovery date, normalized chlorophyll-a and bloom area had decreased to 44.5% and 12.1% of their peak values in Taihu, compared with 20.4% and 4.9% in Dianchi, respectively. Driver analysis indicated that recovery duration was influenced mainly by phase-specific meteorological forcing and lake background, rather than by bloom magnitude alone. Trigger-stage meteorology, lake identity, and transition-stage meteorology contributed 31.53%, 27.58%, and 19.40% of the grouped explanatory signal, together accounting for about 78.5%. These results show that post-bloom recovery can be quantified as an event-scale remote-sensing metric and compared across lakes. The framework extends remote sensing from bloom detection to recovery assessment and provides a basis for lake-specific post-bloom monitoring and management. Full article

This study develops an objective attribution framework, integrating a two-step K-means clustering procedure with a random forest algorithm, to classify the weather systems responsible for high winds over the mid- and lower reaches of the Yangtze River from 2020 to 2023. The analysis utilizes hourly automatic weather station observations, ERA5 reanalysis, and merged precipitation data. Four dominant HW types are identified: cold-air (CAHWs, 40.3%), tropical-cyclone (TCHWs, 27.9%), convective-system (CSHWs, 22.2%), and a residual “other” category (9.6%). Three main types exhibit distinct spatiotemporal distributions and environmental characteristics. CAHWs occur mainly in spring, autumn, and winter, concentrated in three sub-regions within the terrain channel or above the lake surface. CAHWs are characterized by non-precipitating northerlies associated with deformation frontogenesis and modulated by boundary layer processes, including terrain channeling and surface friction. TCHWs are confined to coastal areas in July and September, primarily controlled by tropical cyclone motion and land-sea distribution. CSHWs peak in afternoons from March to October and can be further divided into precipitating (PCSHWs, 40.3%) and non-precipitating (NPSCHWs, 59.7%) types. NPCSHWs typically occur in precipitation-free zones within 50 km of convective systems producing moderate to heavy rainfall, whereas PCSHWs form in smaller convective systems along the periphery of precipitation regions rather than within heavy-rainfall cores. PCSHWs are associated with higher instability, stronger low-level shear, and weaker inhibition than NPCSHWs, indicating a more organized convective environment. Full article

As a critical decision–support tool for sustainable development in alpine lake watersheds, ecosystem service valuation requires scientifically robust accounting systems to inform environmental management. This study addresses the significant interference caused by multi-source heterogeneity in indicator selection, methodology application, and parameter determination within current valuation systems. We innovatively developed a multi-dimensional accounting framework. Through establishing standardized systems for indicators, methods, and parameters, taking Xingyun Lake as the research area, we systematically elucidated the differential impact mechanisms of accounting elements on valuation outcomes. Empirical results demonstrate that structural differences in indicator systems induce 11.61% of valuation fluctuations. Methodological choices lead to 13.86% of deviations. Insufficient parameter localization generates errors up to 18.48%. The refined framework improved valuation accuracy by 16.22%. This study quantitatively evaluates the influencing factors of ecosystem services and confirms a cascading amplification effect of element sensitivity (parameters > methods > indicators) on valuation outcomes, establishing methodological foundations for alpine lake watershed ecological accounting benchmarks. It has important decision-making reference value for applying ecosystem service function evaluation to sustainable development. Full article

Three locally calibrated Indices of Biotic Integrity (IBIs) based on macroinvertebrates (B-IBI), zooplankton (Z-IBI), and phytoplankton (P-IBI) were developed to characterize relative aquatic ecological condition at impaired sites in Dongjiang Lake, a deep reservoir-type lake in China, during 2021–2023. Using synchronous monitoring data, candidate metrics for the three biotic groups were screened and assembled by integrating taxonomic diversity, community composition, pollution-tolerance attributes, trophic indicators, and functional feeding groups. Metric values were standardized using a linear transformation, and site conditions were classified using a unified five-class grading scheme under the present local calibration framework. A total of 327 taxonomic units (species or morphospecies) were recorded across the three biotic groups, indicating relatively high biodiversity in the study area. Under the present locally calibrated framework, most impaired sites were classified within the moderate-to-good range, with clear interannual variation and spatial heterogeneity. Upstream and downstream sections showed greater fluctuations in IBI classes than the lake area. The macroinvertebrate-based IBI was more sensitive to long-term and cumulative habitat disturbance, whereas the zooplankton- and phytoplankton-based IBIs responded more rapidly to short-term variation in nutrients and water quality. Together, these results indicate that multitaxon IBIs can provide complementary information on relative ecological condition within Dongjiang Lake and may support ecological zoning, pollutant management, and restoration prioritization in similar deep reservoir-type lake systems. Full article

Coastal construction projects often require excavation below the water table, where tidal variability and urban infrastructure generate complex groundwater conditions. This study presents a numerical simulation of water table dynamics in a coastal urban area of Mazatlán, México, influenced by tidal forcing, a lake, and an impermeable seawall. Six critical scenarios were modeled using MODFLOW 6 and ModelMuse interface, covering the period from November 2023 to April 2024. The scenarios correspond to astronomical tide events during the new moon phase, when maximum and minimum tide levels occurred within 24 h. These conditions are related to the highest piezometric levels observed in field. Model calibration was based on 18 field observations collected at 09:00, 12:00, and 15:00 across the selected dates. Model outputs closely matched the field observations, with a root mean square error (RMSE) of 0.056 m, and a mean absolute error (MAE) of 0.049 m. Although the differences are minimal, they reflect short-term variability and limited fluctuation during calibration. However, the full monitoring period showed groundwater levels ranging from −0.10 to 0.53 m above mean sea level (masl), emphasizing the importance of understanding short-term dynamics. This modeling approach supports construction planning, helping to anticipate risks and promote better and informed construction practices. Full article

Lake color is an intuitive indicator reflecting the ecological and physicochemical status of lakes and is of great value for both ecological monitoring and environmental assessment. However, the types, spatiotemporal variations, and driving mechanisms of global lake color phenology remain unclear. In this study, we systematically analyzed the color phenology of 975 global lakes based on Landsat remote sensing data from 1984 to 2021. The results indicate that lake color phenology can be categorized into six types, including the perennial green type, evergreen type, and seasonal patterns (spring green, summer green, autumn green, and winter green). Approximately 43.9% of the lakes are classified as the evergreen type, mainly concentrated in the Southern Hemisphere. Further research reveals notable spatial differences in the change in lake color phenology: about 69.4% of lakes in the Southern Hemisphere exhibit relatively stable phenological patterns (frequency of changes within the study area ≤ 2), while approximately 64.4% in the Northern Hemisphere show phenological variations. This dynamic disparity is closely related to lake attributes (area, water depth, elevation) as well as external climatic and watershed conditions (precipitation, wind speed, vegetation). Our findings contribute to developing the interannual patterns of lake color into a novel ecological indicator, thereby advancing the dynamic monitoring and assessment of global lake status. Full article

Glacial lakes in the Third Pole are critically important for climate change and ecological environments. Classifying different types of glacial lakes has become increasingly crucial for dynamic lake monitoring and glacial lake outburst flood (GLOF) assessment. However, automatic identification of glacial lake types still faces numerous challenges. This study developed an automatic classification scheme for glacial lakes by integrating the longest glacier centerline with glacier retreat zones and glacial meltwater flow paths. The scheme comprehensively considers the spatial relationship between glacial lakes and their parent glaciers, as well as dam properties, enabling accurate derivation of key parameters for each glacial lake, including lake type, number of supply glaciers, total area, and the length of inflow channels from parent glaciers. Applying the proposed rule-based classification scheme to 1429 glacial lakes, integrated from eight glacial lake inventories, revealed that the Parlung Zangbo Basin (PLZB) contains 13 supraglacial lakes, 41 ice-contact lakes, 521 glacier-proximal lakes, 235 glacier-distal lakes, and 619 non-glacially fed lakes. The classification scheme is sensitive to changes in glacier extent and can accurately identify non-glacially fed lakes within 10 km of glaciers. Furthermore, this study refined the classification of non-contact glacier-fed lakes into “glacier-proximal” and “glacier-distal” categories, providing a more detailed basis for assessing dam stability and glacial influence, thereby contributing to future large-scale susceptibility assessments of GLOF events. Full article

Glacial lake dynamics in high-mountain regions serve as a sensitive proxy for cryospheric responses to climate warming. This study utilizes multi-temporal Sentinel-2 imagery and digital elevation model (DEM) data to quantify glacial lake evolution in the Donglin Tsangpo Watershed, a strategically important section of the China–Nepal Economic Corridor, from 2016 to 2024. The results show a significant expansion in both the number (from 43 to 56) and total area (from 3.97 km² to 4.94 km², +24.43%) of glacial lakes, primarily driven by the rapid emergence of very small lakes (0.02–0.05 km²) and a clear upward shift in elevation distribution, with new lakes forming above 5300 m and extending to elevations exceeding 5500 m. Analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) reveals that this expansion coincided with pronounced positive thermal anomalies, particularly the 2020 extreme warm event (daytime +3.88 °C, nighttime +1.61 °C). Mechanistic analysis using the ERA5-Land reanalysis dataset further demonstrates that persistent positive downward longwave radiation (LW) anomalies (peaking at +10.71 W/m² in 2021) effectively compensated for reduced shortwave input, inhibiting nocturnal refreezing and extending the effective ablation period. Furthermore, a rising liquid-to-solid precipitation ratio and extreme melt-day anomalies (up to +39.36 days) provided intensified hydrothermal inputs, driving the pronounced expansion of glacier-contact lakes despite non-linear interannual responses. This study also estimates individual lake volumes, identifying a transition toward rapid lake development that elevates potential downstream hazard exposure. These findings provide a high-resolution dataset and a robust physical framework for transboundary environmental monitoring and risk assessment in this climate-sensitive region. Full article

Volatile organic compounds (VOCs) emitted by cranberries from three locations were studied using a proton transfer reaction mass spectrometer (PTR-MS). Cranberries were collected from natural wetlands in a protected landscape (Łętowskie Lake and the Kępice area, northern Poland), from an allotment garden near Słupsk (northern Poland), and from a cranberry plantation (Poland). The collected samples showed statistically significant differences between the three studied cranberry sources, with samples from the garden differing significantly from those from plantations and wetlands. The results of multivariate analyses, such as cluster analysis, also indicated differences in the composition of VOCs responsible for cranberry aroma from different sources. Multivariate PCA revealed similarities between the volatile organic compound (VOC) emissions of cranberries from natural wetlands and plantations. Additionally, machine learning was used to classify cranberries collected from different sites. The classification accuracy of the MLP model for a limited number of variables was approximately 97% at the testing and validation level. This paper presents the potential application of PTR-MS to VOC emission studies, along with statistical analysis and machine learning, as an example of a potential tool for sustainable development in the study of edible fruit aromas. Full article

Sentiment expressions related to child maltreatment (CM) in public discourse are influenced by demographic, economic, and cultural factors and individual characteristics. Using 188,429 geotagged CM-related tweets during 2018–2022, we explored public sentiment expression about CM across the contiguous U.S. We applied multiscale geographically weighted regression (MGWR) to examine how contextual factors relate to the percentage of CM-related tweets with negative sentiment at the county level, revealing the spatial heterogeneity and varying geographic scales of these associations. Counties with higher male-to-female ratios and lower education levels tended to express negative sentiment in CM-related tweets, with consistent patterns observed nationwide. Five factors exhibited spatially varying associations by U.S. region, with higher levels of negative sentiment in the following contexts: a lower percentage of residents living in group quarters or a higher percentage of same-sex couples (Eastern and Central); fewer households lacking broadband access (Central); a higher percentage of single-parent households (New England and Southern Mississippi River); and areas where professionals are mandated to report CM (Great Lakes and Southern Appalachian Mountains). This study provides critical insights for policymakers to adjust policies, educators to design focused interventions, and the public to raise CM awareness. The methodology also provides a valuable framework for investigating public discourse on other social issues. Full article