Search Results (53)

Groundwater is a critical water source in the semi-arid West Liao River Basin (WLRB). Based on daily observations from 117 monitoring wells distributed across the basin during 2019–2024, this study analyzed interannual and seasonal groundwater-level dynamics and identified areas of relative groundwater stress using groundwater level elevation (WLE) and depth to water (DTW). The Mann–Kendall test, Sen’s slope estimator, ordinary kriging, and a composite risk index were applied to quantify temporal trends, map spatial patterns, and classify groundwater risk. Regional WLE showed weak interannual variability but a distinct seasonal cycle, with positive anomalies from January to April and negative anomalies from June to September. At the well scale, 51 wells (43.59%) exhibited significant increases, whereas 36 wells (30.77%) showed significant decreases. Sen’s slope ranged from −2.75 to 0.61 m/year, indicating that the strongest local changes were associated with groundwater-level decline. Spatially, WLE was generally higher in the southwest and lower toward the northeast. Areas with WLE decline were concentrated in the central-western and southern sectors, whereas relative WLE increases occurred in parts of the northern and eastern sectors. The low-, medium-, and high-risk classes included 39, 38, and 39 wells, accounting for 33.62%, 32.76%, and 33.62% of the wells retained for the risk assessment, respectively. High-risk wells clustered in the central-western and southern areas, while low-risk wells dominated the northern and eastern sectors. These results highlight the importance of well-scale monitoring for identifying priority areas of groundwater stress. The proposed framework provides a practical basis for screening priority monitoring areas and supporting spatially differentiated groundwater management in semi-arid basins. However, this study is limited by the relatively short monitoring period (2019–2024) and the lack of quantitative driver attribution; therefore, the findings reflect recent groundwater dynamics rather than long-term secular trends. Full article

Polycyclic aromatic hydrocarbons (PAHs) in farmland soils pose potential ecological and human health risks, yet their contamination characteristics and source-related risks in farmland soils across different river basins in China remain insufficiently understood. This present study analyzed 84 farmland soil samples from northeast (primarily the middle and lower reaches of the Songhua River and Liao River basin), central (primarily the middle reaches of the Yellow River basin and Dongting Lake system), northwest (primarily the middle and upper reaches of the Yellow River and Yarlung Zangbo River basin), and southern (primarily the upper reaches of the Pearl River and Yangtze River basin) China in order to assess the contamination characteristics, sources, ecological risks, and human health risks associated with 16 US EPA priority PAHs in the samples. The findings suggest that the 16 aggregate PAHs’ concentrations in Chinese farmland soils varied from 63.9 to 9637.7 μg/kg, with an average of 1919.3 μg/kg. A gradual decline was observed from north to south, with dibenz[a,h]anthracene (DahA) accounting for the highest proportion at 14.3%. Correlation analysis, principal component analysis, and positive matrix factorization jointly indicated that fossil fuel combustion, high-temperature combustion, and traffic-related emissions were the main PAH inputs to farmland soils. The results of the ecological risk assessment indicated that the northeastern region exhibited the highest PAH ecological risk, with 41.2% of sample plots demonstrating severe PAH contamination. Conversely, the southern region exhibited the lowest PAH ecological risk, with 73.9% of the sample plots demonstrating no ecological risk. The human health risk assessment found that non-carcinogenic risks for both children and adults were within safe limits, while carcinogenic risks for both groups were relatively high. DahA was identified as the primary carcinogen, accounting for 45.9% and 70.3% of the total carcinogenic risk for children and adults, respectively. Oral ingestion was the primary route of exposure. This study provides an integrated basin-scale assessment of PAH contamination and source-related risks in Chinese farmland soils, supporting targeted management of PAH inputs in agricultural environments. Full article

Intensive monoculture exacerbates soil compaction and sodification in the West Liao River Plain. This study evaluated legacy effects of diversified 3-year rotations on sodic soil health (ESP > 15%, ECe < 4 dS m⁻¹) during two subsequent maize seasons. Rotations incorporating salt-tolerant forages and deep-rooted crops (sugar beet–Echinochloa–sorghum and Echinochloa–tall fescue–silage corn) significantly reduced bulk density (8.6–13.1%) and exchangeable sodium percentage (up to 14.1 percentage points) relative to continuous monoculture. Treatments with maximum desalination (22.6% reduction) enhanced fungal α-diversity by 98.0%, while forage-dominated systems enriched Acidobacteriota by 35.2%, shifting bacterial communities toward oligotrophic dominance. Structural equation modeling confirmed that rotation effects on enzyme activity were mediated through reduced bulk density and ESP. These systems provide effective biological models for sustainable maize cultivation in sodic soils via synergistic physical-chemical-biological amelioration. Full article

The Western Liao River Basin is one of the cradles of Chinese civilization and is recognized as China’s third mother river, following the Yellow River and the Yangtze River. This study focuses on traditional settlements in the Western Liao River Basin and evaluates their spatial perception elements using the IPA (Importance–Satisfaction Analysis) method. By enriching research on the spatial perception evaluation of traditional settlements, this work provides guidance for the protection and inheritance of traditional settlements in the Western Liao River Basin. Based on a field survey of the current spatial conditions of these traditional settlements, an evaluation system for spatial perception elements is proposed. Using SPSS software, the importance and satisfaction scores of each evaluated element are determined. Using the IPA method, this study classified 18 spatial perception factors of traditional settlements in the West Liao River Basin into four categories: strengths, potential overkill, low priority, and urgent improvement. Differentiated conservation and optimization strategies were proposed based on these findings. The study also reveals that local residents’ spatial perception is an active construction process rooted in daily life and cultural practices, exhibiting characteristics of “place dependence” and “path orientation.” Elements rated as high in importance but low in satisfaction reflect residents’ cultural anxiety and sense of spatial loss. The study emphasizes that the conservation of traditional settlements should shift from expert-led approaches to local collaboration, fully incorporating residents’ cognitive patterns to construct a dynamic pathway for heritage transmission grounded in daily practices and cultural memory. Full article

In the ecologically fragile West Liao River Basin, characterizing groundwater dynamics is crucial for sustainable water management. Using 2000–2016 groundwater level data, this study applies Seasonal-Trend decomposition using Loess (STL) and change-point detection to analyse trends. Driving factors are quantified via random forest combined with SHapley Additive exPlanations (SHAP) analysis, and a novel STL–Long Short-Term Memory (STL-LSTM) hybrid model is developed for forecasting. Key findings include: (1) Groundwater levels declined persistently, with a significant change point in 2009. The post-2009 decline rate accelerated to −0.749 m/yr, a 55.7% increase. (2) Statistical attribution reveals that soil moisture (43.5%) and climatic factors (29.0%) are the primary predictors of groundwater variability. The dominance of soil moisture highlights the key role of agricultural irrigation, which strongly modifies soil water dynamics during the growing season. (3) The STL-LSTM model achieves optimal predictive performance (R² = 0.8805, RMSE = 0.7081 m), demonstrating enhanced accuracy for non-stationary sequences. This integrated framework combines trend diagnosis, driver interpretation, and hybrid modelling, offering scientific support for precise groundwater management in semi-arid agricultural basins. Full article

In order to explore the co-evolutionary relationship between the functions of microbial communities and the chemical composition of groundwater in a hyporheic zone affected by groundwater exploitation along riverbank, we have taken the Huangjia water source area on the Liao River main stream in Shenyang as an example. DNA was extracted from microorganisms in the hyporheic zone affected by groundwater exploitation along the riverbank, and we conducted high-throughput sequencing to select the dominant bacterial strains from the indigenous bacteria. They are classified as the Proteobacteria phylum, the Actinobacteria phylum, the Firmicutes phylum, the Bacteroidetes phylum, the Chloroflexi phylum, and the Acidobacteria phylum. The dominant bacteria have a good correlation with Fe, Mn, and environmental factors (such as DO—dissolved oxygen, Eh—oxidation-reduction potential, etc.) in the hyporheic zone. The functions and activities of the superior bacterial strains exhibit a feature of co-evolution with the water’s chemical environment, which has certain response characteristics to redox zoning. Studying the co-evolution relationship between the microbial community structure and function in the hyporheic zone and the chemical composition of the groundwater can provide a microbiological theoretical basis for the redox zonation. It also offers reference for understanding the process of Fe and Mn migration and transformation in the hyporheic zone under the hydrodynamic conditions of groundwater exploitation along the riverbank. Full article

This research evaluates the performance of the Final Run remote sensing precipitation products from the Integrated Multi-satellite Retrievals for GPM (IMERG-F) in complex terrain river basins (2014–2023). Utilizing decade-long daily precipitation data from 2415 manned national-level ground stations, the evaluation employs eight statistical metrics—probability of detection, false alarm ratio, accuracy, critical success index, Pearson correlation coefficient (PCC), root mean square difference, mean difference, and relative difference—to analyze detection accuracy, correlation, and bias on daily, monthly, and annual scales. The main findings include the following: (1) IMERG-F’s daily precipitation detection capability follows a three-tier spatial pattern (northwest to southeast), aligning with the stepped terrain of China. (2) Stronger correlations (PCC = 0.7–0.9) with gauge data emerge in southeastern regions despite higher biases, while northwestern areas show weaker correlations but fewer deviations. (3) IMERG-F overestimates annual rainy days, but slightly underestimates precipitation intensity compared with ground observations. (4) Annual precipitation estimates exceed gauge measurements, particularly in the Songhua and Liao River Basins (18–20% overestimation). Monthly analysis shows fewer errors during rainy seasons versus winter dry periods, with pronounced seasonal variations in northwestern basins. These findings emphasize the need for terrain-aware calibration to improve satellite precipitation monitoring in hydrologically diverse basins, particularly addressing seasonal and spatial error patterns in water resource management applications in northern China. Full article

This study focuses on 120 representative river basins across China, utilizing CMIP6 multi-model climate data and CESM2-LE large ensemble climate data to develop a bias-correction framework for climate models that integrates statistical methods, with the aim of enhancing the spatiotemporal accuracy of climate model outputs. Building on this framework, the study simulates the evolution of hydrological drought characteristics in Chinese river basins during 2071–2100 under the SSP370 scenario and quantifies the relative contributions of internal climate variability (ICV), anthropogenic climate change (ACC), and inter-model uncertainty (IMU) to hydrological drought projections. Results reveal a pronounced south–north divergence in future drought risk. Southern China—especially the middle–lower Yangtze and Pearl River basins—exhibits a >10% increase in drought frequency, with event totals exceeding 30 per 30 years, yet individual droughts remain short and moderate in intensity. Conversely, northern basins—particularly the Songliao and Liao River systems—display pronounced lengthening and intensification of droughts, with mean duration surpassing 12 months and severity indices rising above 38, translating to 20~40% increases relative to the 1985~2014 baseline. Nationwide, ICV emerges as the dominant driver of projected changes: signal-to-noise ratios for frequency, intensity, and duration fall below unity across more than 70% of basins, indicating that unforced variability overshadows the anthropogenic trend. ACC signals only exceed ICV in southeastern coastal regions and parts of the Pearl River basin for intensity and duration. Inter-model spread rivals or exceeds ICV uncertainty in these same humid subtropical basins, underscoring the sensitivity of projections to model structure. Full article

This study aimed to analyse the spatiotemporal evolution of phytoplankton community dynamics and its underlying mechanisms in the Liaoning section of the Liao River Basin in 2010, 2015, and 2020. Phytoplankton species diversity increased significantly, with an increase from three phyla and 31 species in 2010 to six phyla and 74 species in 2020. Concurrent increases in α-diversity indicated continuous improvements in habitat heterogeneity. The community structure shifted from a diatom-dominated assemblage to a green algae–diatom co-dominated configuration, contributing to an enhanced water purification capacity. The upstream agricultural zone (Tieling section) had elevated biomass and low diversity, indicating persistent non-point-source pollution stress. The midstream urban–industrial zone (Shenyang–Anshan section) emerged as a phytoplankton diversity hotspot, likely due to expanding niche availability in response to point-source pollution control. The downstream wetland zone (Panjin section) exhibited significant biomass decline and delayed diversity recovery, shaped by the dual pressures of resource competition and habitat filtering. The driving mechanism of community succession shifted from nutrient-dominated factors (NH₃-N, TN) to redox-sensitive factors (DO, pH). These findings support a ‘zoned–graded–staged’ ecological restoration strategy for the Liao River Basin and inform the use of phytoplankton as bioindicators in watershed monitoring networks. Full article

Validating the potential of multi-frequency synthetic aperture radar (SAR) data for multi-layer and profile soil moisture (SM) estimation modeling, we conducted an airborne multi-frequency SAR joint observation experiment (AMFSEX) over the Liao River Basin in China. The experiment simultaneously acquired airborne high spatial resolution quad-polarization (quad-pol) SAR data at five frequencies, including the Ka-, X-, C-, S-, and L-band. A preliminary “vegetation–soil” parameter estimation model based on the multi-frequency SAR data was established. Theoretical penetration depths of the multi-frequency SAR data were analyzed using the Dobson empirical model and the Hallikainen modified model. On this basis, a water cloud model (WCM) constrained by multi-polarization weighted and penetration depth weighted parameters was used to analyze the estimation accuracy of the multi-layer and profile SM (0–50 cm depth) under different vegetation types (grassland, farmland, and woodland). Overall, the estimation error (root mean square error, RMSE) of the surface SM (0–5 cm depth) ranged from 0.058 cm³/cm³ to 0.079 cm³/cm³, and increased with radar frequency. For multi-layer and profile SM (3 cm, 5 cm, 10 cm, 20 cm, 30 cm, 40 cm, 50 cm depth), the RMSE ranged from 0.040 cm³/cm³ to 0.069 cm³/cm³. Finally, a multi-input multi-output regression model (Gaussian process regression) was used to simultaneously estimate the multi-layer and profile SM. For surface SM, the overall RMSE was approximately 0.040 cm³/cm³. For multi-layer and profile SM, the overall RMSE ranged from 0.031 cm³/cm³ to 0.064 cm³/cm³. The estimation accuracy achieved by coupling the multi-source data (multi-frequency SAR data, multispectral data, and soil parameters) was superior to that obtained using the SAR data alone. The optimal SM penetration depth varied across different vegetation cover types, generally falling within the range of 10–30 cm, which holds true for both the scattering model and the regression model. This study provides methodological guidance for the development of multi-layer and profile SM estimation models based on the multi-frequency SAR data. Full article

Photochemical degradation is a major removal pathway for pharmaceutical pollutants in water, and dissolved organic matter (DOM) in water is an important factor affecting this process. This study investigates the differential effects of seasonally-varied dissolved organic matter (DOM) from Songhua River and Liao River on the photodegradation of pharmaceutical pollutants, using levofloxacin (LFX), sulfamethoxazole (SMZ), and ibuprofen (IBP) as target compounds. The results demonstrated that summer and autumn DOM inhibited the photodegradation of LFX and SMZ through light screening and dynamic quenching effects, with inhibition rates of 35.1% and 55.5%, respectively, whereas winter DOM enhanced degradation through photo-oxidation mechanisms. DOM from Songhua River and Liao River significantly promoted the photodegradation of IBP. Quenching experiments showed differences in the contributions of photochemically reactive intermediates (PPRIs) to the photodegradation of different target pollutants, with hydroxyl radicals (•OH) dominating LFX photodegradation (48.79% contribution), excited triplet states of DOM (³DOM*) dominating SMZ photodegradation (85.20% contribution), and singlet oxygen (¹O₂) dominating IBP photodegradation (79.89% contribution). The photodegradation pathways were elucidated by measuring the photodegradation by-products of the target pollutants: LFX mainly underwent piperazine ring cleavage and oxidative decarboxylation, SMZ underwent isoxazole ring opening and deamination during photodegradation, and IBP underwent photodecarboxylation and oxidation reactions. Under the influence of the DOM from the Songhua River and Liao River, the generation of multiple photodegradation by-products led to an increasing trend in the acute toxicity of target pollutants to luminescent bacteria. This investigation elucidates the dual regulatory mechanisms of natural aquatic DOM on both photo-induced degradation pathways and toxicity evolution dynamics of pharmaceutical contaminants, which is of great significance for understanding the photochemical transformation behavior and risk assessment of pharmaceutical pollutants in aquatic environments. Full article

Understanding vegetation’s drought response helps predict ecosystem adaptations to climate change and offers scientific insights for managing extreme climate events. Using RS technology, this study systematically investigates the response mechanisms of vegetation to drought and their spatiotemporal variations in the ecologically sensitive semi-arid area and the national grain security zone—West Liao River Basin, China. The findings reveal that (1) from 2000 to 2018, NDVI exhibited a fluctuating upward trend, and drought trends remained pronounced in certain areas and seasons; (2) growing-season droughts impaired productivity, while winter droughts reduced soil moisture, with arid-zone vegetation being most vulnerable; (3) grasslands responded rapidly to drought, forests slowly via deep roots, and croplands suffered most during critical growth phases; and (4) drought-adapted western forests/shrubs recovered best, while eastern croplands required targeted measures like resilient crops and water management. The results of this study not only provide a scientific basis for ecological management in the West Liao River Basin but also offer valuable insights for vegetation and water resource management in other arid and semi-arid regions globally. This research holds significant importance for addressing climate change and achieving regional sustainable development. Full article

Clarifying the spatiotemporal trade-offs between the supply and demand of ecosystem services is critical for regional ecological security and sustainable development. This paper focused on the West Liao River Basin, a crucial ecological barrier in Inner Mongolia, and quantified the supply and demand of ecosystem services by utilizing the InVEST model. A coupled coordination model is established to evaluate the supply–demand trade-offs, while a decoupling index model is used to analyze the dynamic changes in coordination. The influencing factors on the supply–demand relationship are also explored by using a geographically and temporally weighted regression (GTWR) model. The results from 2005 to 2020 indicated a decrease in carbon storage and an increase in carbon emissions. Water yield, food, and meat supply increased, while their demand decreased. Soil retention supply and demand both increased. Basin-scale coordination improved from low to moderate levels, with significant gains in both coordination and matching degrees. Decoupling indices fluctuated, with the central region showing a significantly higher decoupling index. The GTWR model showed that the spatial and temporal impacts of eight driving factors, including land use, on CD differed significantly, with precipitation having the most significant impact. The research results provided a theoretical basis for the future development of regional ecological restoration and sustainable development policies. Full article

Reservoirs deliver vital ecological services, including water storage and drainage. However, these functions are increasingly compromised by the dual pressures of climate change and human activities. Among the most pressing concerns is reservoir sedimentation, highlighting the urgency of investigating hydrodynamic sediment scouring. This study focuses on the plain reservoirs of Liaoning Province, using the Shifo Temple Reservoir as a case study. An optimized sediment scouring scheme was developed based on the reservoir’s hydrodynamic characteristics to improve water and sediment management. A coupled hydrodynamic and sediment transport (ST) model was constructed to simulate runoff dynamics and sediment distribution within the Liao he River Basin, while the MIKE21 model was applied to simulate the interaction between the hydrodynamics and sediment transport. The study analyzed groundwater dynamics across different runoff scenarios, seasons, and representative years, offering a scientific foundation for optimizing water and sediment allocation strategies. The results demonstrated a strong correlation between simulated and observed data during validation, confirming the accuracy of the hydrodynamic simulations. Utilizing the coupled HD and ST modules, the study proposed a sediment transfer scheme. The analysis revealed that flow rates between 165 and 190 m³/s significantly enhance sediment scouring in the long term (2029–2039) compared to the short term (2024–2029), effectively reducing sedimentation, minimizing deposition length, and lowering silt removal costs. The findings offer critical insights for predicting reservoir evolution and conducting risk assessments, thereby contributing to the sustainable management and ecological restoration of water systems in Liaoning Province. Full article

The evaluation and prediction of ecological benefits are significant for regional resource development planning and path designing. This study established a novel ecological benefits evaluation system by integrating macro-ecosystem structure, Ecosystem service index (ESI), and ecological quality index (EQI). Based on this system, this study evaluated the spatiotemporal characteristics and changing trend of ecological benefits in Song-Liao River Basin (SRB) from 1990 to 2020. The results show that the macro-ecosystem structure in Song-Liao River Basin remains stable, and the ecosystem service and ecological quality generally show a trend of first decline and then increase. The average growth rates of ESI and EQI were 0.6% and 0.4%, respectively, during 1990–2020. The ecological benefits of natural areas with widely distributed forest areas are higher, while those of areas with frequent human activities are lower. The prediction model based on machine learning has achieved good modeling effect, which shows that the ecological benefits of SRB will be on the rise in the future. Based on the evaluation results, we suggest that more environmental protection policies on the basis of maintaining the existing development plan should be promoted to reduce the contradiction between human and nature in the development process. For the abundant natural forests in this area, reasonable forest management should be carried out to improve the carbon-fixation capacity of vegetation, and a Methodology for managing natural forests should be constructed to make full use of the existing carbon sinks. For the new afforestation project being promoted, carbon-sink afforestation projects of CCER (Chinese Certified Emission Reduction) should be promoted to realize the synergy between economic development and environmental protection. Full article