The “Space-Sky-Ground-Lake” four-dimensional integrated water quality monitoring system in Xiong'an New Area, represents a significant innovation in environmental monitoring. By combining satellite remote sensing, unmanned aerial vehicles (UAVs), unmanned ships, and automatic water quality monitoring stations, the system achieves comprehensive, three-dimensional oversight of Baiyangdian's water quality. Satellite data enables high-resolution spatial analysis and trend assessment, while UAVs and unmanned ships provide real-time data from inaccessible regions. Automated stations continuously track key indicators, enhancing efficiency and accuracy. This intelligent and unmanned monitoring system markedly enhances both monitoring efficiency and data accuracy, offering new directions for the advancement of environmental monitoring, particularly in water quality assessment. Its successful implementation demonstrates that cutting-edge technology can effectively tackle the challenges posed by water quality monitoring in complex environments, thereby providing robust support for ecological protection and governance. As technology evolves, the SSGL framework is poised to drive the environmental monitoring sector toward greater intelligence and efficiency.
Stream temperature is strongly influenced by environmental factors that are increasingly altered by climate change, particularly during river heat periods (RHPs), when thermal stress intensifies. In urban streams, elevated water temperatures pose risks to both ecological conditions and water quality. Riparian vegetation represents one of the few manageable controls, as it can mitigate warming by reducing incoming solar radiation. This study investigates low-flow water temperatures in the Liesingbach river, a small- to medium-sized urban stream in Vienna. Riparian shading was quantified based on solar radiation transmission, and water temperatures were simulated using a calibrated coupled hydraulic and full energy balance model under current and future climate scenarios. The results highlight the importance of integrating thermal processes into urban river restoration. Riparian vegetation reduced peak water temperatures during critical low-flow periods and enhanced ecological resilience, although it could not fully offset long-term warming. Variations in vegetation density resulted in differences in peak temperatures of up to 4.2 °C under current conditions and 5.6 °C under future climate scenarios. Despite these cooling effects, projected temperatures remained high, underscoring the urgency of mitigation measures. The increasing importance of shading under climate change further highlights its value as an adaptation strategy. Overall, the applied modeling framework provides a practical tool for quantifying these effects and supporting urban stream management under warming conditions.
The Agno River Basin in the northern Philippines is a region of significant ecological and economic value; however, baseline data on its fish diversity and distribution are poorly documented, limiting effective river basin management. This study provides the first baseline assessment of water quality and fish assemblages (July 2021 and January 2022) across eight sample stations representing diverse land use in the upper and lower Agno River Basin. Diversity indices and spatio-temporal analyses were applied to characterize patterns in both water quality and fish communities. While most physicochemical parameters complied with national and international water quality standards, elevated electrical conductivity was detected near mining zones, and agricultural areas exhibited increased temperatures and reduced dissolved oxygen levels. Most water quality parameters showed significant variability across stations, seasons and interactions effects (p < 0.001). A total of 23 fish species, representing 13 families were recorded, with Gobiidae (84%) and Cichlidae (11%) accounting for the highest abundance. Pseudogobius javanicus and Rhinogobius bucculentus were the most abundant taxa. Notably, no fish specimens were found at the Baloy station, located downstream of intensive mining activity. Species diversity ranged from low to moderate (Shannon index H′ = 0.29–1.62), with low evenness and high dominance, indicating habitat specialization and uneven resource distribution. Non-metric multidimensional scaling (NMDS) (p > 0.05) and species clustering analysis showed similar species composition across sites. Multivariate analyses, including canonical correspondence analysis (CCA) and redundancy analysis, revealed that temperature showed affinities with fish composition and abundance. However, patterns must be interpreted cautiously due to the lack of statistical support (p > 0.05). The findings provide valuable insights into the current ecological condition of the Agno River Basin and highlight the importance of continuous monitoring and comprehensive evaluation of land-use impacts and aquaculture pressures to inform evidence-based, ecosystem-based river basin management.
Coastal deltas are critical global biodiversity hotspots but face intensifying conflicts between anthropogenic development and ecosystem fragility, particularly in saline-alkali environments. However, quantifying the specific effectiveness of ecological restoration within these sensitive zones remains a challenge, as most assessments overlook soil-specific responses to land use transitions. Using the Yellow River Delta as a representative case, this study integrated the InVEST model with spatial intersection analysis to evaluate habitat quality evolution from 2000 to 2020. Results reveal a spatial polarization: while urbanization degraded inland habitats, the policy-driven conversion of cropland to wetland significantly enhanced coastal zones. Crucially, the intersection analysis demonstrated that habitat quality in protected saline-alkali wetlands improved substantially, significantly outperforming natural succession in unprotected areas. These findings validate the efficacy of active restoration measures (e.g., Suaeda salsa rehabilitation) in reversing degradation in saline contexts and provide a transferable framework for spatial zoning management in complex coastal ecosystems globally.
This study analyzes land use and land cover (LULC) dynamics within the Al-Qusayr watershed, located in the Syrian component of the Upper Orontes Basin. Five Landsat datasets for 1991, 2000, 2009, 2017, and 2024 were analyzed to capture key pre-conflict, conflict, and recovery phases, thereby distinguishing irrigated from rainfed agriculture in this vulnerable semi-arid karst watershed. We applied supervised Support Vector Machine (SVM) classification and a multi-step post-classification correction to refine the results. The accuracy assessment for each period yielded overall accuracies between 91.4% and 94.2%. Five main LULC classes were identified: Agricultural Land (including Farmland and Rainfed/Winter Season), Water (including Water bodies and Wetland), Urban, Unused Land/Natural Vegetation, and Dry Stream. Over the study period, significant shifts occurred. Total agricultural land expanded by 24.6% and urban areas expanded by 74.6%. This growth corresponded with a 53.4% reduction in unused land. A significant conversion from irrigated to rainfed agriculture was observed during the conflict followed by a reversal of this trend after 2017. To provide quantitative context for driver attribution, we integrated CHIRPS precipitation to derive a standardized precipitation anomaly (z-score; 1991–2024) and VIIRS nighttime-light radiance (2014–2024) as an indirect proxy for disruption and recovery conditions, and related these indicators to irrigated and rainfed agricultural changes. Irrigated farmland contraction during the conflict period coincided with negative precipitation z-scores (drought) and reduced nighttime lights, whereas the recovery of irrigated agriculture after 2017 was accompanied by rising nighttime lights despite continued dry conditions, suggesting that improved stability may have contributed to agricultural reactivation. Overall, the Al-Qusayr watershed experienced substantial LULC fluctuations associated with the combined pressures of drought, policy shifts, and conflict. However, the landscape demonstrated notable adaptive capacity, particularly through agricultural resilience. These findings provide a useful baseline for decision-makers targeting sustainable land rehabilitation and resource management.
