Search Results (285)

Our study addresses how large-scale hydrological alterations shape zooplankton biodiversity in floodplain ecosystems, which are highly sensitive to changes in river connectivity. Following the operation of the Gabčíkovo hydroelectric power plant in the Danube inland delta, we examined the long-term responses of crustacean zooplankton communities, as these organisms are key indicators of hydromorphological disturbance. Based on previous evidence that river regulation often reduces habitat heterogeneity, we hypothesized that hydrological alterations in the Danube riverscape would promote increasing taxonomic and functional homogenization within sites, while simultaneously enhancing differentiation between sites over the past three decades. A total of 121 planktonic crustacean species were recorded across six monitored sites between 1991 and 2020, comprising 49 copepods and 72 cladocerans. Communities showed rising species richness, especially during the first decade of the hydropower plant’s operation. While overall richness increased, dam-induced hydromorphological changes triggered habitat-specific community shifts. In the main channel and adjacent parapotamal arm, taxonomic and functional homogenization occurred, dominated by resilient tychoplanktonic species with a gathering or secondary filter-feeding strategy. In contrast, isolated side arms experienced gradual eutrophication, favoring euplanktonic and primary filter-feeding taxa. The observed taxonomic and functional convergence within both habitat groups reflects the loss of connectivity and the cessation of artificial flooding. Full article

Increasing demand for land and resources in Himalayan catchments is altering hydrological processes and threatening freshwater ecosystems. Sediment mobilization and nutrient fluxes, especially during monsoon rainfall events, are intensifying the degradation of water bodies. This study investigates land cover change and its effects on nutrient dynamics in the Phewa Lake catchment, Nepal. Landsat imagery from 1990 to 2021, processed through Google Earth Engine, was used to map land changes. Nutrient loading for the two time periods was estimated with the InVEST model. Surface soils were sampled across the catchment to analyze nitrogen and phosphorus distribution, while their particle-bound transport to the lake was assessed through riverbed sediments and the suspended sediments collected during monsoon rainfalls. Pre-monsoon water quality was examined to evaluate eutrophication levels across different lake zones. Results reveal forest recovery in the upper catchment, but agricultural land in the lower catchment is being rapidly converted to urban areas. While forest recovery has enhanced sediment retention, nutrient inputs to the lake, particularly nitrogen and phosphorus, have increased. Fertilizer leaching and untreated sewage emerge as key sources in rural and urban areas, respectively. Seasonal constraints of the dataset may underestimate the overall extent of water quality deterioration, as indicated by high nutrient loads in monsoon suspended sediments. Overall, this study highlights the dual effect of land cover change: forest regrowth coincides with rising nutrient discharge. Without timely interventions, growing urban populations in the region may face worsening water quality challenges. Full article

Arctic warming is expected to alter permafrost landscapes and shift tundra ecosystems from greenhouse gas sinks to sources. We quantified plant biomass and necromass, carbon stocks, and microbial activity across five Low-Arctic tundra sites in the Yana–Indigirka Lowland (Chokurdakh, NE Siberia) during the 2024 growing season. Above- and below-ground plant biomass was measured by harvest adjacent to 50 × 50 m permanent plots; total C and N were determined by dry combustion on an elemental analyzer. Total organic carbon (TOC) stocks were calculated by horizon from TOC (%), bulk density, and thickness. Microbial basal respiration (BR), substrate-induced respiration (SIR), microbial biomass C (MBC), and the metabolic quotient (qCO₂) were assessed in litter/organic (O), peat (T), and mineral gley horizons. Mean above-ground biomass was 15.8 ± 1.5 t ha⁻¹; total living biomass averaged 43.1 ± 1.6 t ha⁻¹. Below-ground biomass exceeded above-ground by 1.73×. Carbon in above-ground, below-ground, and necromass pools averaged 7.8, 12.2, and 12.5 t C ha⁻¹, respectively. Surface organic horizons dominated ecosystem C storage: litter–peat stocks ranged from 234 to 449 t C ha⁻¹, whereas 0–30 cm mineral layers held 18–50 t C ha⁻¹; total (surface + 0–30 cm) stocks spanned 258–511 t C ha⁻¹ among sites. Key contributors to biomass and C storage were deciduous shrubs (Salix pulchra, Betula nana), bryophytes (notably Aulacomnium palustre), and the graminoids (Eriophorum vaginatum). BR and MBC were highest in O and T horizons (BR up to 21.9 μg C g⁻¹ h⁻¹; MBC up to 70,628 μg C g⁻¹) and declined sharply in mineral soil; qCO₂ decreased from O to mineral horizons, indicating more efficient C use at depth. These in situ data show that Low-Arctic tundra C stocks are concentrated in surface organic layers while microbial communities remain responsive to warming, implying high sensitivity of carbon turnover to thaw and hydrologic change. The dataset supports model parameterization and remote sensing of shrub–tussock tundra carbon dynamics. Full article

To quantify the spatiotemporal patterns of the water-level variations in the study area, we conducted cluster analysis of the temporally varying measurements across multiple hydrological stations. The temporal trends and change points were analyzed, followed by IHA-RVA quantification of the water-level alterations before and after change points. Cluster analysis demonstrated the following. (1) Hydrological stations segregate into two distinct groups at the Euclidean distance threshold d = 5, and into three clusters at d = 4, confirming the pronounced west–east heterogeneity in the lake. (2) The hydrological alteration degrees exhibit considerable variation across the lake’s sub-lakes (Qili, Muping, South Dongting, East Dongting), with marked heterogeneity persisting even among representative monitoring stations within individual sub-lakes. The water-level regimes in Qili Lake can be partitioned into two distinct periods, before and after the change point, exhibiting the highest hydrological alteration degree across the lake. Representative stations of the other sub-lakes fall into three periods. During the first phase of hydrological alteration, Zhouwenmiao, Jinshi, and Chenglingji exhibit moderate alteration. Throughout the second alteration phase, all the representative stations consistently exhibit moderate alteration, although significant heterogeneity emerges across hydrological indicators among the sub-lakes. (3) Downstream of Yangliutan station, the longitudinal profile exhibits terraced morphology, segmented into three distinct levels by two hydraulic knickpoints. This geomorphic configuration primarily controls both the localized stage reductions and the maintenance of elevated upstream water levels during dry seasons. Confronting the persistent dry-season stage declines at Yingtian Station, enhanced monitoring and conservation of terraced transition zones in South Dongting Lake must be prioritized, with implementation of the zoned control principle for water-level governance and lake management. This study establishes a scientific foundation for the protection and governance of Dongting Lake, thereby advancing sustainable utilization of its water resources. Full article

Understanding the spatiotemporal dynamics of coastal intertidal meta-ecosystems in response to sea-level rise (SLR) is essential for understanding the interactions between terrestrial and aquatic meta-ecosystems. However, given that annual SLR changes are typically measured in millimeters, ecosystems may take decades to exhibit noticeable shifts. As a result, the extent of lateral responses at a single point is constrained by the fragmented temporal and spatial scales. We integrated the tidal inundation gradient of a coastal meta-ecosystem—comprising a high-elevation flat (H), low-elevation flat (L), and mudflat—to quantify the potential application of inferring the spatiotemporal impact of environmental features, using China’s Yangtze Estuary, which is one of the largest and most dynamic estuaries in the world. We employed both flood ratio data and tidal elevation modeling, underscoring the utility of spatial modeling of the role of SLR. Our results show that along the tidal inundation gradient, SLR alters hydrological dynamics, leading to environmental changes such as reduced aboveground biomass, increased plant diversity, decreased total soil, carbon, and nitrogen, and a lower leaf area index (LAI). Furthermore, composite indices combining the enhanced vegetation index (EVI) and the land surface water index (LSWI) were used to characterize the rapid responses of vegetation and soil between sites to predict future ecosystem shifts in environmental properties over time due to SLR. To effectively capture both vegetation characteristics and the soil surface water content, we propose the use of the ratio and difference between the EVI and LSWI as a composite indicator (ELR), which effectively reflects vegetation responses to SLR, with high-elevation sites driven by tides and high ELRs. The EVI-LSWI difference (ELD) was also found to be effective for detecting flood dynamics and vegetation along the tidal inundation gradient. Our findings offer a heuristic scenario of the response of coastal intertidal meta-ecosystems in the Yangtze Estuary to SLR and provide valuable insights for conservation strategies in the context of climate change. Full article

The exploitation of mineral resources often necessitates groundwater drainage, which may impact surrounding ecosystems, particularly vegetation. In this study, the effects of passive drainage in the Kornica-Popówka chalk mine in eastern Poland were analyzed using Sentinel-2 satellite images and the NDVI vegetation index. Groundwater monitoring wells were used to delineate the extent of the depression cone, representing areas of potentially altered hydrological conditions. NDVI values were analyzed across multiple time points between 2023 and 2024 to assess the condition of vegetation both inside and outside the depression cone. The results indicate no significant difference in NDVI values during the 2023–2024 study period for this specific chalk mine case between areas affected and unaffected by the depression cone, suggesting that vegetation in this region is not experiencing stress due to lowered groundwater levels. This outcome highlights the influence of other environmental factors, such as rainfall and land use, and suggests that the local geological structure allows plants to maintain sufficient access to water despite hydrological alterations. This study confirms the utility of integrating remote sensing with hydrogeological data in environmental monitoring and underlines the need for continued observation to assess long-term trends in vegetation response to mining-related groundwater changes. Full article

To quantitatively evaluate the hydrological regime dynamics in West Dongting Lake over the past seven decades, this study utilizes daily average water level series (1955–2024) from key control stations (Nanzui and Xiaohezui) to analyze variations in water level and discharge through change-point detection methods, adopting the water level difference between Xiaohezui and Nanzui as a pivotal indicator of hydrological changes; the IHA–RVA framework is then applied to comprehensively assess the degree of alteration in hydrological indicators before and after identifying change points, demonstrating the following: (1) declining trends in water level/discharge at both stations—primarily attributable to reduced inflows from the Songzi and Hudu Rivers—underwent abrupt shifts in 1983 and 2003, while the water level difference displayed an increasing trend with a change point in 1991; (2) the overall degree of hydrologic alteration (DHA) was moderate, with enhanced variability during T2 (2003–2024) relative to T1 (1983–2003), notably for discharge at Nanzui and water level at Xiaohezui; (3) reduced discharge in the Songzi and Hudu Rivers primarily drives the decreased outflow from West Dongting Lake. In the Li and Yuan basins during period T1, anthropogenic factors dominated runoff alterations. During T2, anthropogenic contributions accounted for 76.27% and 48.67% of runoff changes, respectively, resulting in reduced runoff volumes under equivalent precipitation inputs. (4) Under fixed water level differences, a significant positive correlation exists between discharges at Xiaohezui and Nanzui stations. Greater discharge flows downstream through the flow channel adjacent to NZ at West Dongting Lake’s outlet. Collectively, these findings establish a technical foundation for assessing the impact of hydrological regimes and aquatic ecological security in Dongting Lake, thereby advancing sustainable water resource utilization across the basin. Full article

Global warming has intensified the hydrological cycle, resulting in more frequent extreme precipitation events and altered spatiotemporal precipitation patterns in urban areas, thereby increasing the risk of urban flooding and threatening socio-economic and ecological security. This study investigates the characteristics of summer extreme precipitation in the Poyang Lake City Group (PLCG) from 1971 to 2022, utilizing the China Daily Precipitation Dataset and NCEP/NCAR reanalysis data. Nine extreme precipitation indices were examined through linear trend analysis, Mann–Kendall tests, wavelet transforms, and correlation methods to quantify trends, periodicity, and atmospheric drivers. The key findings include: (1) All indices exhibited increasing trends, with RX1Day and R95p exhibiting significant rises (p < 0.05). PRCPTOT, R20, and SDII also increased, indicating heightened precipitation intensity and frequency. (2) R50, RX1Day, and SDII demonstrated east-high-to-west-low spatial gradients, whereas PRCPTOT and R20 peaked in the eastern and western PLCG. More than over 88% of stations recorded rising trends in PRCPTOT and R95p. (3) Abrupt changes occurred during 1993–2009 for PRCPTOT, R50, and SDII. Wavelet analysis revealed dominant periodicities of 26–39 years, linked to atmospheric oscillations. (4) Strong subtropical highs, moisture convergence, and negative OLR anomalies were closely associated with extreme precipitation. Warmer SSTs in the eastern equatorial Pacific amplified precipitation in preceding seasons. This study provides a scientific basis for flood prevention and climate adaptation in the PLCG and highlighting the region’s vulnerability to monsoonal shifts under global warming. Full article

This study presents a novel bivariate-output deep learning framework based on LeNet-5 for the simultaneous prediction of urban flood susceptibility and inundation depth in Seoul, South Korea. Unlike previous studies that relied on single-output models, the proposed approach jointly learns classification and regression targets through a shared feature extraction structure, enhancing consistency and generalization. Among six tested architectures, the Le5SD_CBAM model—integrating a Convolutional Block Attention Module (CBAM)—achieved the best performance, with 83% accuracy, an Area Under the ROC Curve (AUC) of 0.91 for flood susceptibility classification, and a mean absolute error (MAE) of 0.12 m and root mean squared error (RMSE) of 0.18 m for depth estimation. The model’s spatial predictions aligned well with hydrological principles and past flood records, accurately identifying low-lying flood-prone zones and capturing localized inundation patterns influenced by infrastructure and micro-topography. Importantly, it detected spatial mismatches between susceptibility and depth, demonstrating the benefit of joint modeling. Variable importance analysis highlighted elevation as the dominant predictor, while distances to roads, rivers, and drainage systems were also key contributors. In contrast, secondary terrain attributes had limited influence, indicating that urban infrastructure has significantly altered natural flood flow dynamics. Although the model lacks dynamic forcings such as rainfall and upstream inflows, it remains a valuable tool for flood risk mapping in data-scarce settings. The bivariate-output framework improves computational efficiency and internal coherence compared to separate single-task models, supporting its integration into urban flood management and planning systems. Full article

Forest fires, intensified by climate change, threaten tropical ecosystems by accelerating biodiversity loss, releasing carbon emissions, and altering hydrological cycles. Continuous detection of fire-induced forest loss is therefore critical. However, commonly used optical-based methods often face limitations, particularly due to cloud cover and coarse spatial resolution. This study explores the use of C-band Sentinel-1 Synthetic Aperture Radar (SAR) time series, combined with Bayesian Online Changepoint Detection (BOCD), for detecting and continuously monitoring fire-induced vegetation loss in forested areas. Three BOCD variants are evaluated: two single-polarization approaches individually using VV and VH reflectivities, and a dual-polarization approach ($pol$-BOCD) integrating both channels. The analysis focuses on a fire-affected area in Baixo Uraim (Paragominas, Brazil), supported by field-validated reference data. BOCD performance is compared against widely used optical products, including MODIS and VIIRS active fire and burned area data, as well as Sentinel-2-based difference Normalized Burn Ratio (dNBR) assessments. Results indicate that $pol$-BOCD achieves spatial accuracy comparable to dNBR (88.2% agreement), while enabling detections within a delay of three Sentinel-1 acquisitions. These findings highlight the potential of SAR-based BOCD for rapid, cloud-independent monitoring. While SAR enables continuous detection regardless of atmospheric conditions, optical imagery remains essential for characterizing the type and severity of change. Full article

Understanding long-term precipitation variability is essential for assessing the climate’s impact on sensitive ecosystems, particularly in regions of high environmental value, such as the Danube Delta Biosphere Reserve (DDBR). This study examines the temporal dynamics of monthly precipitation in the Danube Delta, Romania, spanning the period from 1965 to 2019. Three approaches were used to analyze climatic variability: Change Point detection (CPD) to identify shifts in precipitation regimes, the De Martonne Index (I_M) to assess aridity trends, and the Standardized Precipitation Index (SPI) to evaluate drought conditions across annual and monthly scales. Using robust monthly precipitation and temperature datasets from the Sulina meteorological station, CPD analysis revealed statistically significant structural breaks in precipitation trends, suggesting periods of altered climate behavior likely associated with broader regional or global climate changes. I_M values indicated mostly hyper-aridity and aridity at monthly and annual scales, respectively. No monotonic trend was found in this index during the analyzed segments, as emphasized by the Mann–Kendall (MK) test. SPI values provided further evidence of variability in the precipitation regime, highlighting a transition toward more extreme hydrological conditions in the region. The combined use of these indices offers a comprehensive view of the evolution of climatic conditions in the Danube Delta. The findings underscore the growing vulnerability of this unique wetland ecosystem to climatic variability, supporting the need for adaptive water management strategies in the face of anticipated future changes. Full article

The efficient and rational development of hydropower in the Lancang–Mekong River Basin can promote green energy transition, reduce carbon emissions, prevent and mitigate flood and drought disasters, and ensure the sustainable development of the entire basin. In this study, based on publicly available hydrometeorological observation data and satellite remote sensing monitoring data from 2001 to 2020, a machine learning model of the Lancang–Mekong Basin was developed to reconstruct the basin’s hydrological processes, and identify the occurrence patterns and influencing mechanisms of water-related hazards. The results show that, against the background of climate change, the Lancang–Mekong Basin is affected by the increasing frequency and intensity of extreme precipitation events. In particular, Rx1day, Rx5day, R10mm, and R95p (extreme precipitation indicators determined by the World Meteorological Organization’s Expert Group on Climate Change Monitoring and Extreme Climate Events) in the northwestern part of the Mekong River Basin show upward trends, with the average maximum daily rainfall increasing by 1.8 mm/year and the total extreme precipitation increasing by 18 mm/year on average. The risks of flood and drought disasters will continue to rise. The flood peak period is mainly concentrated in August and September, with the annual maximum flood peak ranging from 5600 to 8500 m³/s. The Stung Treng Station exhibits longer drought duration, greater severity, and higher peak intensity than the Chiang Saen and Pakse Stations. At the Pakse Station, climate change and hydropower development have altered the non-drought proportion by −12.50% and +15.90%, respectively. For the Chiang Saen Station, the fragmentation degree of the drought index time series under the baseline, naturalized, and hydropower development scenarios is 0.901, 1.16, and 0.775, respectively. These results indicate that hydropower development has effectively reduced the frequency of rapid drought–flood transitions within the basin, thereby alleviating pressure on drought management efforts. The regulatory role of the cascade reservoirs in the Lancang River can mitigate risks posed by climate change, weaken adverse effects, reduce flood peak flows, alleviate hydrological droughts in the dry season, and decrease flash drought–flood transitions in the basin. The research findings can enable basin managers to proactively address climate change, develop science-based technical pathways for hydropower dispatch, and formulate adaptive disaster prevention and mitigation strategies. Full article

Climate-driven hydrological extremes and anthropogenic interventions are increasingly altering streamflow regimes worldwide. While prior studies have explored climate or regulation effects separately, few have integrated multiple teleconnection indices and reservoir chronologies within a cross-basin comparative framework. This study addresses this gap by assessing long-term streamflow nonstationarity and its drivers at two key stations—Khabarovsk on the Amur River and Datong on the Yangtze River—representing distinct hydroclimatic settings. We utilized monthly discharge records, meteorological data, and large-scale climate indices to apply trend analysis, wavelet transform, percentile-based extreme diagnostics, lagged random forest regression, and slope-based attribution. The results show that Khabarovsk experienced an increase in winter baseflow from 513 to 1335 m³/s and a notable reduction in seasonal discharge contrast, primarily driven by temperature and cold-region reservoir regulation. In contrast, Datong displayed increased discharge extremes, with flood discharges increasing by +71.9 m³/s/year, equivalent to approximately 0.12% of the mean flood discharge annually, and low discharges by +24.2 m³/s/year in recent decades, shaped by both climate variability and large-scale hydropower infrastructure. Random forest models identified temperature and precipitation as short-term drivers, with ENSO-related indices showing lagged impacts on streamflow variability. Attribution analysis indicated that Khabarovsk is primarily shaped by cold-region reservoir operations in conjunction with temperature-driven snowmelt dynamics, while Datong reflects a combined influence of both climate variability and regulation. These insights may provide guidance for climate-responsive reservoir scheduling and basin-specific regulation strategies, supporting the development of integrated frameworks for adaptive water management under climate change. Full article

Freshwater ecosystems—home to roughly 10% of known species—are losing biodiversity to river-morphology alteration, hydraulic infrastructure, and pollution, yet most ecological network (EN) studies focus on terrestrial systems and overlook hydrological connectivity under human disturbance. To address this, we devised and tested a dual EN framework in the Yangtze River Delta’s Ecological Green Integration Demonstration Zone, constructing freshwater and terrestrial networks independently before merging them. Using InVEST Habitat Quality, MSPA, the MCR model, and Linkage Mapper, we delineated sources and corridors: freshwater sources combined NDWI-InVEST indicators with a modified, sluice-weighted resistance surface, producing 78 patches (mean 348.7 ha) clustered around major lakes and 456.4 km of corridors (42.50% primary). Terrestrial sources used NDVI-InVEST with a conventional resistance surface, yielding 100 smaller patches (mean 121.6 ha) dispersed across woodlands and agricultural belts and 658.8 km of corridors (36.45% primary). Unified models typically favor large sources from dominant ecosystems while overlooking small, high-value patches in non-dominant systems, generating corridors that span both freshwater and terrestrial habitats and mismatch species migration patterns. Our dual framework better reflects species migration characteristics, accurately captures dispersal paths, and successfully integrates key agroforestry-complex patches that unified models miss, providing a practical tool for biodiversity protection in disturbed freshwater–terrestrial landscapes. Full article

While water conservancy projects continuously enhance flood control and resource allocation capabilities, the adverse impacts on basin systems, particularly the structural disruption of surface water–groundwater continuity, have become increasingly pronounced. Therefore, establishing quantitative assessment of water system connectivity as a critical foundation for optimizing spatial water distribution, maintaining ecohydrological equilibrium, and enhancing flood–drought regulation efficacy is important. Focusing on the regulated reaches of the Panjiakou, Daheiting, and Taolinkou reservoirs in the Luan River Basin, this study established and integrated a three-dimensional assessment framework that synthesizes hydrological processes, hydraulic structural effects, and human activities as three fundamental drivers, and employed the Analytic Hierarchy Process (AHP) to develop a quantitative connectivity evaluation system. Results indicate that water conservancy projects significantly altered basin connectivity: surface water connectivity decreased by 0.40, while groundwater connectivity experienced a minor reduction (0.25) primarily through reservoir seepage. Consequently, the integrated surface–groundwater system declined by 0.39. Critically, project scale governs surface connectivity attenuation intensity, which substantially exceeds impacts on groundwater systems. The comprehensive assessment system developed in this study provides theoretical and methodological support for diagnosing river connectivity, formulating ecological restoration strategies, and protecting basin ecosystems. Full article