Search Results (203)

In order to clarify the effects of the volcanic activity on hydrological, thermal and chemical features of a crater lake, Lake Katanuma, Japan, temperature and electrical conductivity at 25 °C (EC25) of lake water were monitored at two maximum-depth points in 2023−2025. Under closed condition of the lake without river outflow, the lake is characterized by a high acidity of pH = 2 on average and the existence of the surrounding geothermal area. A seasonal variation in the thermal and chemical features of the lake was shown by sporadic vertical profiling (0.1 m pitch) of temperature, EC25 and dissolved oxygen (DO) at the two points. The groundwater flow system around the lake was specified by quantifying the groundwater inflow G_in and groundwater outflow G_out in the lake from the estimate of hydrological and chemical budgets under no precipitation. During the pycnal stratification of May–September, the lake exhibited a four-layer structure with different temperature and EC25 values, probably due to the lower intrusion of groundwater passing through three different pathways. The four-layer structure disappeared due to vertical mixing in October–December and March–April and inverse stratification in January–February. The G_out and G_in values were estimated for three budget periods in the mixing season. Utilizing Darcy’s law for the G_out values as a confined groundwater flow, it is found out that G_out has a linear relationship with lake volume. The relatively high G_in and G_out values estimated are probably caused by the high permeability of lacustrine sand and gravel deposited as bedrock, which furnishes the high adjustability to lake level, i.e., its small variation at ca. 0.5 m in amplitude. Full article

Agricultural nonpoint source pollution mainly causes lake eutrophication in China, largely affected by variations in crop distribution. To analyze the multiscale relationships between the long-term evolution of cropping patterns and lake water quality at the macro scale, this study analyzed nationwide datasets for 2000 and 2020 covering 420 relatively large lakes. We systematically examined the spatial restructuring of six major food and cash crops—wheat, rice, maize, soybean, peanut, and rapeseed—and evaluated their multiscale associations with lake total nitrogen (TN) and total phosphorus (TP) concentrations and how these associations changed over time. The results showed the following: (1) From 2000 to 2020, the spatial distributions of the six major crops underwent substantial restructuring. The dominant production areas of rice, wheat, and maize were maintained or further reinforced, whereas soybean, rapeseed, and peanut exhibited varying degrees of regional redistribution and localized concentration. (2) Lake water quality differed between the flood and non-flood seasons. TN exhibited pronounced seasonal differences between the two study periods, whereas temporal changes in TP were generally limited; both nutrients nevertheless showed marked regional heterogeneity among the five major lake regions. (3) The crop–water quality relationship exhibits significant scale dependence and crop-specific variations. The XGBoost model demonstrated a certain degree of out-of-field (OOF) predictive capability for both TN and TP, with OOF R² values of 0.448 and 0.447, respectively. For TN, the highest OOF R² values were observed in the 1000–2000 m buffer zone in both 2000 and 2020; the optimal prediction scale for TP shifted from 1000–2000 m in 2000 to 2000–5000 m in 2020. SHAP results showed that corn maintained a high and relatively stable predictive importance in the TN model, followed by wheat, peanuts, and rice; in the TP model, corn and rapeseed were the crop predictors with the highest relative SHAP importance. PDP results further indicate that there are generally nonlinear or non-monotonic relationships between different crop coverage proportions and TN and TP. (4) Pronounced spatial heterogeneity was observed across the five lake regions. The Eastern Plain Lake Region was characterized by associations involving multiple crops, whereas maize was the most prominent crop in the Northeast Plain and Mountain Lake Region. In the Inner Mongolia–Xinjiang Plateau Lake Region, maize predominated, with wheat and rapeseed also showing notable importance. In the Tibetan Plateau Lake Region, TN was associated with multiple crops, whereas TP was primarily related to maize and rapeseed. The Yunnan–Guizhou Plateau Lake Region exhibited particularly strong scale-dependent differences. This study provides a nationwide analytical framework for comparing the scale differences and regional variations in the statistical associations between the spatial distribution of crops and lake water quality at the specific crop level. The findings can provide a scientific basis for formulating differentiated agricultural nonpoint source pollution control strategies that are adapted to the evolving characteristics of crop planting structures. Full article

Lakes on the Tibetan Plateau are sensitive indicators of regional climate change and hydrological variability. Comprehensive analyses of the area, level, and volume of typical lakes across multiple time scales remain limited. In this study, based on the Google Earth Engine platform, we integrated Landsat TM/ETM+/OLI and Sentinel-2 imagery, nine satellite altimetry datasets (Jason-1, Jason-2, Jason-3, Cryosat-2, Sentinel-3A, Sentinel-3B, ICESat, ICESat-2, and GEDI), and four machine learning methods (Lasso, SVM, Random Forest, and XGBoost) to investigate multi-timescale (annual, seasonal, and monthly) variations in lake area, level, and volume of Qinghai Lake, Nam Co, and Bangong Co, from 2000 to 2022. All three lakes showed overall increases in lake area, level, and volume, but with different magnitudes and temporal patterns. Qinghai Lake showed the most pronounced expansion, Nam Co experienced moderate growth, characterized by temporal fluctuations, whereas Bangong Co showed a relatively small but persistent increase. Seasonal analysis showed that lake area expansion was generally strongest in autumn, whereas monthly lake volume peaked in October for Qinghai Lake and Nam Co and in September for Bangong Co. Climate analyses indicated that Qinghai Lake may be mainly influenced by increased precipitation and runoff as well as reduced evaporation, Nam Co may be mainly influenced by precipitation, runoff, and delayed hydrological responses to glacier meltwater, and Bangong Co was likely associated with runoff and cryospheric water supply, while basin characteristics may have also contributed to its long-term hydrological response. These results highlight regional differences in lake responses to climate variability across the Tibetan Plateau. Full article

Arid inland saline lakes are key components of basin ecosystems. As the largest saline lake in Xinjiang and a critical ecological barrier in northwest China, Ebinur Lake’s area dynamics are vital to regional sustainable development. This study integrates Landsat imagery (1992–2024) with meteorological and socio-economic data to investigate optimal water extraction methods, spatio-temporal lake area variations, and driving mechanisms. Multiple methods were employed, including water index comparison, Mann–Kendall test, Pearson correlation, and ridge regression. Results show that: (1) the Normalized Difference Water Index (NDWI) maintains high, stable classification accuracy across years and months, making it suitable for long-term monitoring; (2) from 1992 to 2024, lake area demonstrates a significant fluctuating downward trend without abrupt change points, indicating continuous degradation. During the growing season (April–October), it first decreases and then increases, with larger early-season areas, minima in August and September, coinciding with peak agricultural irrigation demand; (3) regarding driving mechanisms, socio-economic factors dominate (approximately 70%), while meteorological factors play a weakly regulatory role (about 30%). Population growth and increased water consumption are the primary drivers, with obvious seasonal differences. Meteorological changes, socio-economic development, and ecological measures jointly influence lake area. Although extreme events (e.g., anomalous precipitation) induce short-term fluctuations, they do not alter the long-term degradation trend dominated by human activities. This study provides methodological support for long-term monitoring of arid saline lakes and scientific evidence for ecological conservation and water resource management in the Ebinur Lake Basin. Full article

The increasing frequency and magnitude of glacial lake outburst floods pose a severe threat to the safety of downstream communities. However, Interference from glacier shadows and mountain shading reduces the accuracy of remote sensing-based glacial lake detection. We propose a two-level nested framework that integrates global spatiotemporal aggregation and local adaptive enhancement. At the global level, the 80th temporal percentile (P80) of multi-temporal AWEI imagery is used to construct a stable water-background composite and suppress short-term seasonal noise. Multi-source physical constraints, including the Normalized Difference Snow Index (NDSI), a DEM-derived slope constraint (slope < 10°), and red-band reflectance thresholds (0.3 < BandRed < 1.6), are applied to suppress interference from land, terrain shadows, snow, and glaciers. At the local scale, an adaptive dynamic segmentation strategy is proposed by establishing an equal-area buffer for each individual lake, where the temporal occurrence frequency of MNDWI is computed to build a stable water probability composite, and the Otsu algorithm is applied to independently derive lake-specific optimal thresholds. Using Landsat imagery and meteorological data from 1990 to 2025, we quantified the spatiotemporal dynamics of typical glacial lakes in the central Himalayas, and explored the driving mechanisms of climate factors on lake area changes. Over the past 35 years, the number and area of lakes have exhibited a pronounced expansion trend under a climatic regime characterized by rising temperatures, increasing precipitation, and decreasing relative humidity. During 1990–2020, lake area variations were primarily governed by strong interactions between temperature and wind speed. Summer variability exerted a more pronounced impact than winter variability. The proposed framework provides an effective approach for glacial lake extraction in the study area and may provide useful technical support for long-term monitoring of alpine lakes. Full article

Climate and land-use changes are major drivers of hydrological and water quality dynamics in the Great Lakes Basin. This study investigates recent changes in climate, land use, runoff, and total phosphorus (TP) loading in selected illustrative watersheds within the Canadian Lake Erie Basin and Canadian Lake Ontario Basin during 2009–2022. Results suggest that recent warming and hydroclimatic variability have altered hydrological regimes in southern Ontario, including higher winter temperatures and shifts in seasonal runoff. Land-use changes, including the expansion of row crops and urban areas, have further influenced watershed responses. Variations in TP loading were associated with changes in hydroclimatic conditions and land use. These findings highlight the increasing importance of event-driven nutrient transport under changing hydroclimatic conditions and support adaptive watershed management approaches accounting for seasonal runoff variability and event-driven nutrient transport. This study provides insight into the combined impacts of climate and land-use changes on hydrology and nutrient loading in southern Ontario watersheds. The analysis results enhance understanding of water quality dynamics in the Great Lakes region and support the development of more effective, adaptive, and integrated watershed management strategies under future climate and land-use changes. Full article

Small water bodies serve as fundamental units and key conduits for material cycling and hydrological processes at the watershed scale. However, quantitatively identifying the mechanisms driving their area evolution under multi-factor coupling in different scenario simulations remains challenging. This study focused on the small water bodies in the Chaohu Lake Basin. An Otsu algorithm was applied to establish a basin-scale database of small water bodies, while the GeoDetector model was integrated to reveal the spatiotemporal driving mechanisms of multi-factor coupling behind their evolution. Furthermore, a Long Short-Term Memory (LSTM)–Transformer model was modified to simulate future scenarios of small water body area dynamics. The results indicated that, from 1995 to 2024, the area of small water bodies in the Chaohu Lake Basin exhibited a fluctuating decreasing trend (wet season: 186–269 km²; dry season: 110–253 km²). In terms of spatial distribution, the small water bodies exhibited an unbalanced distribution pattern characterized by wide dispersion alongside regional clustering. Results from the GeoDetector model revealed that land use type (q = 0.711) and evapotranspiration (q = 0.526) were the dominant drivers of variations in small water body areas. LSTM–Transformer simulations (R² = 0.92, p < 0.01) suggested that, under temperature, precipitation, and land use change scenarios, the small water body areas in the Chaohu Lake Basin will exhibit distinct seasonal variation characteristics, with scenario-dependent differences in fluctuation amplitude and peak–trough timing. These results offer theoretical support for the protection of small water bodies and integrated water resource management in the Chaohu Lake Basin. 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

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

Dongting Lake, a vital freshwater lake in China with substantial ecological, economic, and social significance, has fractional vegetation coverage (FVC) as a core indicator of regional ecological balance. To characterize the ecosystem’s health and support targeted protection, this study analyzed FVC’s spatio-temporal evolution and associated spatial factors in the Dongting Lake ecological restoration area using 2005–2020 MODIS imagery, integrating the dimidiate pixel model, slope trend analysis, and geographic detector model (noting the latter quantifies spatial explanatory power but not direct ecological causality). Results revealed distinct FVC heterogeneity: 2011 had the poorest vegetation (mean FVC = 0.60), while 2005, 2010, and 2012 showed higher FVC (mean = 0.65); summer exhibited the most vigorous growth due to favorable hydrothermal conditions. Slope was the dominant single factor with the highest spatial explanatory power for FVC (q = 0.50), its distribution strongly associated with soil moisture and erosion. The slope–soil moisture interaction had the strongest joint spatial explanatory power (q = 0.625), reflecting topographic–hydrological synergistic spatial association, implying slope may indirectly modulate vegetation water availability (inferred from spatial correlation, not causality). The slope–DEM interaction (q = 0.534) confirmed combined topographic explanatory effects. Overall, 70.3% of the region saw significant FVC improvement (notably in spring) from 2005 to 2020, with degradation in February, March, and December. Slope emerged as a key factor consistent with interannual and seasonal FVC variations. These findings provide a reliable scientific basis for targeted wetland restoration, emphasizing enhanced vegetation management in summer, autumn, and the growing season. Limitations include: MODIS’s 250 m resolution leading to mixed-pixel effects in fragmented wetlands, limited validation coverage of extreme habitats and single-year verification, and the Geodetector model’s reliance on spatial stratification and factor independence assumptions (deviating from wetland’s continuous factor variation) that preclude causal inference. Full article

Sikkim, located in the northeastern Himalaya, is highly vulnerable to natural hazards and increasing depletion of surface and subsurface water resources, particularly springs and lakes. In South Sikkim, several lakes exhibit rapid drainage behavior, among which Nagi Lake shows near-complete water loss shortly after rainfall, indicating the presence of subsurface leakage pathways. This study investigates shallow subsurface moisture dynamics and identifies potential seepage-prone zones beneath the Nagi Lake basin using geoelectrical methods. Electrical resistivity profiling was conducted along seven survey lines during the non-rainy season (October–November 2025) to minimize the influence of transient rainfall-induced moisture variations. Profiling was carried out using the Wenner method, achieving investigation depths of approximately 6.5–9 m. Additionally, Vertical Electrical Sounding (VES) using the Schlumberger configuration was performed at selected locations to examine deeper subsurface conditions. Resistivity results indicate that profiles L1, L2, L3, L4, and L7 contain relatively higher moisture restricted to the upper ~5 m, whereas profiles L5 and L6 exhibit persistently low resistivity values from the surface to depths of ~9 m, suggesting sustained subsurface moisture accumulation. The downward extension of low-resistivity zones along L5 and L6 indicates possible preferential seepage pathways or localized subsurface water storage. VES results further reveal a higher density of subsurface anomalies below ~14 m in these areas. These low-resistivity anomalies are interpreted as potential subsurface flow pathways. Although confirmation of active seepage requires additional hydrological or time-lapse investigations, the findings provide important baseline geophysical insights for lake rejuvenation. Full article

Environmental DNA (eDNA) metabarcoding has become a powerful, non-invasive method for detecting aquatic organisms. However, optimal sampling strategies for benthic taxa in lentic ecosystems remain unclear. This study evaluated the effectiveness of eDNA metabarcoding in detecting freshwater Unionidae mussels in lake water columns and examined their spatial and seasonal distribution patterns. We validated a mini-barcode primer targeting the mitochondrial 16S rDNA of unionid mussels through controlled laboratory experiments and field tests, confirming reliable amplification and accurate taxonomic assignment of freshwater bivalve DNA. Field surveys were conducted in four lakes within the Nakdong River basin, where eDNA samples were collected from littoral zones and from surface, mid-, and bottom layers of central lake areas during autumn and winter. Metabarcoding analysis identified 79 amplicon sequence variants (ASVs) representing four unionid taxa, with Cristaria plicata and Sinanodonta lauta comprising the majority of reads and ASVs. Overall, the number of Unionidae eDNA reads showed no significant seasonal differences, but there was notable spatial variation among sampling locations. Read numbers were significantly lower in littoral zones compared to central lake areas, with no significant differences detected among depth layers within the central zones. Species-specific analyses revealed contrasting spatial patterns: C. plicata had higher read abundance in mid- and bottom layers, while S. lauta was more frequently detected in surface and littoral samples. These findings suggest that the distribution of freshwater mussel eDNA in lakes is primarily influenced by spatial factors related to habitat preference and hydrodynamic mixing, rather than by seasonal variation during stable periods. This study offers practical insights for designing effective eDNA sampling strategies for benthic invertebrates in lentic ecosystems. Full article

In meandering river floodplain systems, remote sensing is a valuable tool for assessing connectivity processes relevant to fish ecological functions. This study used the Google Earth Engine platform and multispectral Landsat 7 imagery. A random forest classifier was used to evaluate water types and area changes in oxbow lakes of the Beni River in Bolivia. Water type dynamics were mainly associated with lake age and distance from the main channel. Seasonal variations highlighted the role of wind-driven sediment resuspension and overflow during high discharge conditions. Long-term lake area changes reflected typical oxbow lake evolution as well as alterations caused by the main channel. Multiannual changes showed a notable area decrease during years of low discharge. Relationships between discharge and lake area dynamics allowed the classification of three lake groups with different levels of connectivity and overbank flow influence. The ecological relevance of these groups was evaluated based on fish habitat preferences and migration patterns. Results emphasize the importance of preserving natural hydrologic variability, with flooding associated with increased habitat availability. Overall, this study demonstrates the usefulness of satellite remote sensing for detecting ecohydrological processes and offers insights to preserve ecological functions in data-scarce regions. Full article

Wetlands are a critical component of the global biogeochemical cycle and have great potential for carbon sequestration under the changing climate. However, previous studies have mainly focused on the dynamics of soil organic carbon while paying little attention to the vegetation carbon storage in wetlands. Poyang Lake is the largest freshwater lake in China, where intra-annual and inter-annual variations in water levels significantly affect the vegetation carbon storage in the floodplain wetland. Therefore, we assessed the seasonal distribution and carbon storage of six typical plant communities (Arundinella hirta, Carex cinerascens, Miscanthus lutarioriparius, Persicaria hydropiper, Phalaris arundinacea, and Phragmites australis) in Poyang Lake wetlands from 2019 to 2024 based on field surveys, the literature, and remote sensing data. Then, we used 16 preseason meteorological and hydrological variables for two growing seasons to investigate the impacts of environmental factors on vegetation carbon storage based on four correlation and regression methods (including Pearson and partial correlation, ridge, and elastic net regression). The results show that the C. cinerascens community was the most dominant contributor to vegetation carbon storage, occupying 12.68% to 44.22% of the Poyang Lake wetland area. The vegetation carbon storage in the Poyang Lake wetland was significantly (p < 0.01) higher in spring (87.75 × 10⁴ t to 239.10 × 10⁴ t) than in autumn (77.32 × 10⁴ t to 154.78 × 10⁴ t). Water body area emerged as a key explanatory factor, as it directly constrains the spatial extent available for vegetation colonization and growth by alternating inundation and exposure. In addition, an earlier start or end to floods could both enhance vegetation carbon storage in spring or autumn. However, preseason precipitation and temperature are negative to carbon storage in spring but exhibited opposite effects in autumn. These results assessed the seasonal dynamics of dominant vegetation communities and helped understand the response of the wetland carbon cycle under the changing climate. Full article

Urban lakes, as critical components of urban ecosystems, provide essential ecological services but face water quality deterioration due to rapid urbanization and associated land use changes. This study investigated the temporal and spatial characteristics and evolution mechanisms of water quality in Wuhan city lakes, with a focus on the Great East Lake basin (GELB), a typical urban lake cluster in the middle Yangtze River basin. By integrating monthly water quality monitoring data (2017–2023) with high-resolution land use data (2020), we employed the Water Quality Index (WQI), Spearman correlation analysis, and Redundancy Analysis (RDA) to assess water quality and the impact of land use on major pollutants. The results revealed significant spatial heterogeneity: Sha Lake (SL) exhibited the best water quality, while Yangchun Lake (YCL) and North Lake (NL) showed the worst conditions. Seasonal variations in water quality were observed, influenced by the ecological functions of lakes and surrounding land use. Notably, understanding these seasonal dynamics provides insights into nutrient cycle operations and their effective management under varying climatic conditions. In addition, the correlation between chlorophyll-a concentration and nutrient elements in urban lakes was not consistent, with some lakes showing significant negative correlations. The water quality of urban lakes is influenced by both land use and human management. Land use analysis indicated high impervious surfaces in East Lake (EL), SL, and YCL exacerbated runoff-driven nutrient loads, the nitrogen elevation from agricultural runoff of Yan East Lake (YEL) and NL’s pollution from historical industrial discharge. This study highlights the urgent need for targeted water management strategies to mitigate the impact of urbanization on water quality and provide a scientific basis for effective governance and ecological restoration in rapidly urbanizing areas around the world. By adopting an integrated approach combining water quality assessments with land use data, this research offers valuable insights for sustainable urban lake management. Full article