Impact of land use on water quality in buffer zones at different scales in the Poyang Lake, middle reaches of the Yangtze River basin

Rapid COD Sensing in Complex Surface Water Using Physicochemical-Informed Spectral Transformer with UV-Vis-SWNIR Spectroscopy

Water, as a finite and vital resource, necessitates water quality monitoring to ensure its sustainable use. A key aspect of this process is the accurate measurement of critical parameters such as chemical oxygen demand (COD). However, current spectroscopic methods struggle with accurately and consistently measuring COD in large-scale, complex water environments due to an insufficient understanding of water spectra and limited generalizability. To address these limitations, we introduce the physicochemical-informed spectral Transformer (PIST) model, combined with ultraviolet-visible-shortwave-near-infrared (UV-vis-SWNIR) spectroscopy for water quality sensing. To the best of our knowledge, this is the first approach to combine Transformer with spectroscopy for water quality sensing. PIST integrates a physicochemical-informed block to incorporate existing physical and chemical information into the spectral encoding for domain adaptation, along with a feature embedding block for comprehensive spectral features extraction. We validated PIST using an actual surface water spectral data set with extensive geographic coverage including the Yangtze River and Poyang Lake. PIST demonstrated notable performance in COD sensing within complex water environments, achieving an impressive R2 value of 0.9008 and reducing root mean squared error (RMSE) by 45.20% and 29.38% compared to benchmark models such as support vector regression (SVR) and convolutional neural network (CNN). These results emphasize PIST's accuracy and generalizability, marking a significant advancement in multidisciplinary approaches that combine spectroscopy with deep learning for rapid water quality sensing.

Effect of riverfront utilization transitions on riparian water quality in the middle-lower Yangtze River

The Yangtze River Protection Strategy aims to enhance water quality and mitigate environmental risks associated with riverfront utilization. This study targets a 2000-km stretch of the middle and lower Yangtze River, where we conducted field investigations and sampled at 76 locations. We investigated the relationship between riverfront utilization and riparian water quality, and proposed zoned management strategies. Our findings reveal that the riverfront development utilization rate decreased by 0.5 % from 2017 to 2022, with the transitions towards living-oriented utilization from production-oriented uses. The impact of riverfront utilization on water quality differs by type: living-oriented riverfronts significantly elevate NH3-N levels, while production-oriented riverfronts notably increase TP levels. Regarding heavy metal pollutants, life-oriented riverfronts have a minimal impact, whereas production-oriented riverfronts significantly affect Zn concentrations. A strong positive correlation between changes in riverfront utilization rate and Zn levels suggests a primary influence from industrial sources. Based on these results, we have delineated four types of environmental management zoning for riverfront, pinpointed 29.0 % of critical riverfront segments, and outlined corresponding management measures. This research provides practical insights for advancing the scientific management of riverfront utilization along the Yangtze River and enhancing riparian water quality.

Advancing methodologies for assessing the impact of land use changes on water quality: a comprehensive review and recommendations

With increasing scholarly focus on the ramifications of land use changes on water quality, although substantial research has been undertaken, the findings demonstrate pronounced spatial variability and the heterogeneity of research methodologies. To address this critical gap, this review offers a rigorous evaluation of the strengths and limitations of current research methodologies, providing targeted recommendations for refinement. It systematically assesses the existing body of literature concerning the influence of land use changes on water quality, with particular emphasis on the spatial heterogeneity of research results and the uniformity of employed methodologies. Despite variations in geographical contexts and research subjects, the methodological paradigms remain largely consistent, typically encompassing the acquisition and analysis of water quality and land use data, the delineation of buffer zones, and the application of correlation and regression analyses. However, these approaches encounter limitations in addressing regional disparities, nonlinear interactions, and real-time monitoring complexities. The review advocates for methodological advancements, such as the integration of automated monitoring systems and IoT technologies, alongside the fusion of deep learning algorithms with remote sensing techniques, to enhance both the precision and efficiency of data collection. Furthermore, it recommends the standardization of buffer zone delineation, the reinforcement of foundational water quality assessments, and the utilization of catchment-scale analyses to more accurately capture the influence of land use changes on water quality. Future inquiries should prioritize the development of interdisciplinary ecological models to elucidate the interaction and feedback mechanisms between land use, water quality, and climate change.

Global Greening Major Contributed by Climate Change With More Than Two Times Rate Against the History Period During the 21th Century

Future variations of global vegetation are of paramount importance for the socio-ecological systems. However, up to now, it is still difficult to develop an approach to project the global vegetation considering the spatial heterogeneities from vegetation, climate factors, and models. Therefore, this study first proposes a novel model framework named GGMAOC (grid-by-grid; multi-algorithms; optimal combination) to construct an optimal model using six algorithms (i.e., LR: linear regression; SVR: support vector regression; RF: random forest; CNN: convolutional neural network; and LSTM: long short-term memory; transformer) based on five climatic factors (i.e., Tmp: temperature; Pre: precipitation; ET: evapotranspiration, SM: soil moisture, and CO2). The optimal model is employed to project the future changes in leaf area index (LAI) for the global and four sub-regions: the high-latitude northern hemisphere (NH), the mid-latitude NH, the tropics, and the mid-latitude southern hemisphere. Our results indicate that global LAI will continue to increase, with the greening rate expanding to 2.25 times in high-latitude NH by 2100 against the 1982-2014 period. Moreover, RF shows strong applicability in the global and NH models. In this study, we introduce an innovative model GGMAOC, which provides a new optimal model scheme for environmental and geoscientific research.

Changes in total sulfur of lake sediments from central-eastern China linked to volcanic aerosol and human activity

Investigations into the repercussions of human activities on global climate and the ecological environment have received widespread attention. Over the past century, research has primarily focused on the impact of heavy metals and nutrients on lake ecosystems, along with their links to human activities. However, there is a noticeable dearth in explorations of historical variations in sulfur (S), an element that also has complex adverse effects on the environment and ecosystems. Here, we present an approximately 1800-year record of the total S (TS) content of sediments in Lake Nvshan, central-eastern China. The results provide evidence to indicate that high (low) TS contents in Lake Nvshan sediments are associated with strong (weak) volcanism in the Northern Hemisphere on multi-century scales. We also observed significant enhancement of TS content at 1750 and 1900 CE, which corresponded to a significant increase in the regional population at these times. We thus infer that elevations in TS levels prior to the increase in human activities likely resulted from increased volcanisms that led to greater inputs of sulfate from the stratosphere into the lake. Subsequently, the increases in TS contents could be attributed to intensified human industrial activities. Our findings revealed that volcanically derived sulfates have been supplanted by anthropogenically driven increases in the levels of sulfides as the primary factor influencing sediment TS contents in Lake Nvshan. These findings could elucidate how human activities have steered lake systems away from their natural baseline, thereby augmenting our understanding of their broader environmental impact.

Multi-evidences investigation into spatiotemporal variety, sources tracing, and health risk assessment of surface water nitrogen contamination in China

A comprehensive understanding of nitrogen pollution status, especially the identification of sources and fate of nitrate is essential for effective water quality management at the local scale. However, the nitrogen contamination of surface water across China was poorly understood at the national scale. A dataset related to nitrogen was established based on 111 pieces of literature from 2000 to 2020 in this study. The spatiotemporal variability, source tracing, health risk assessment, and drivers of China's surface water nitrogen pollution were analyzed by integrating multiple methods. These results revealed a significant spatiotemporal heterogeneity in the nitrogen concentration of surface water across China. Spatially, the Haihe River Basin and Yellow River Basin were the basins where surface water was seriously contaminated by nitrogen in China, while the surface water of Southwest Basin was less affected. Temporally, significant differences were observed in the nitrogen content of surface water in the Songhua and Liaohe River Basin, Pearl River Basin, Southeast Basin, and Yellow River Basin. There were 1%, 1%, 12%, and 46% probability exceeding the unacceptable risk level (HI＞1) for children in the Songhua and Liaohe River Basin, Pearl River Basin, Haihe River Basin, and Yellow River Basin, respectively. The primary sources of surface water nitrate in China were found to be domestic sewage and manure (37.7%), soil nitrogen (31.7%), and chemical fertilizer (26.9%), with a limited contribution from atmospheric precipitation (3.7%). Human activities determined the current spatiotemporal distribution of nitrogen contamination in China as well as the future development trend. This research could provide scientifically reasonable recommendations for the containment of surface water nitrogen contamination in China and even globally.

Investigation of the interactions and influencing factors of the Water-Land-Energy-Carbon system in the Yellow River Basin

The survival and advancement of human society are fundamentally dependent on the availability and sustainable management of water, land, and energy resources. The development and utilisation of various energy sources and a considerable number of natural resources lead to carbon emissions. A complex interplay exists between water, land, energy, and carbon, and their correlation lies at the core of the regional "natural-social-economic" system, which is crucial for human existence and advancement. Despite its importance, research on the water-land-energy‑carbon (WLEC) nexus is limited. In this study, we employed an innovative combination of the comprehensive assessment index, coupled coordination degree, panel vector autoregressive, and random forest models to investigate the spatiotemporal evolution, internal dynamic interactions, and external influencing factors of the WLEC system in the Yellow River Basin (YRB) from 2007 to 2021. The findings revealed that the degree of coupled coordination in the WLEC system of the YRB exhibited an overall steady upward trend. The spatial agglomeration effect was continuously enhanced, and regional disparities increased. Complex interaction mechanisms exist within the water, land, energy, and carbon subsystems in the YRB. Population size, land relief, and sunshine are the prevailing factors influencing the degree of coupling coordination in the WLEC. Addressing the trade-off relationship among the subsystems of the WLEC system is a key aspect of optimising its correlation relationship. This study provides a scientific basis and relevant suggestions for achieving the Double-Carbon Goal, promoting ecological protection and high-quality development in the YRB.

Antibiotic resistome dynamics in agricultural river systems: Elucidating transmission mechanisms and associated risk to water security

Usage of antibiotics in agriculture has increased dramatically recently, significantly raising the influx of antibiotic resistance genes (ARGs) into river systems through organic manure runoff, seriously threatening water security. However, the dynamics, transmission mechanisms, and potential water security risk of ARGs, as well as their response to land use spatial scale and seasonal variations in agricultural river systems remain unclear. To address these challenges, this work employed metagenomic technique to systematically evaluate the pollution and dissemination of ARGs in overlying water and sediment within a typical agricultural catchment in China. The results demonstrated significant differences between overlying water and sediment ARGs. Overlying water dominated by multidrug ARGs exhibited higher diversity, whereas sediment predominantly containing sulfonamide ARGs had higher abundance. The dynamics of ARGs in overlying water were more responsive to seasonal variations compared to sediment due to greater changes in hydrodynamics and nutrient conditions. The profiles of ARGs in overlying water were largely regulated by microbiota, whereas mobile genetic elements (MGEs) were the main forces driving the dissemination of ARGs in sediment. The variation in dissemination mechanisms led to different resistance risks, with sediment presenting a higher resistance risk than overlying water. Furthermore, Mantel test was applied to discover the impact of land use spatial scale and composition on the transmission of ARGs in river systems. The findings showed that cultivated land within 5 km of the riverbank was the key influencing factor. Cultivated land exacerbated ARGs spread by increasing MGEs abundance and nutrient concentrations, resulting in the abundance of ARGs in high-cultivated sites being twice that in low-cultivated sites, and raising the regional water security risk, with a more pronounced effect in sediment. These findings contribute to a better understanding of ARGs dissemination in agricultural watersheds, providing a basis for implementing effective resistance control measures and ensuring water security.

Anthropogenic impact of rare earth elements on groundwater and surface water in the watershed of the largest freshwater lake in China

Limited knowledge exists regarding the potential risks associated with anthropogenic release of rare earth elements (REEs) in the environment. This study aimed to investigate REE signatures in the watershed Poyang Lake, the largest freshwater lake in China. Samples of surface water, wastewater, and groundwater were collected from five rivers discharging into the lake. Results revealed wastewater from wastewater treatment plants contained total REE concentrations from 231 to 904 μg/L, exceeding those found in surface water (0.4 to 1.3 μg/L) and groundwater (0.5 to 416 μg/L). Samples with elevated REE were found in Ca-Mg-Cl/SO4 type waters and exhibited an 18OD deviation from local meteoric water line. Wastewater exhibited a higher positive Gd anomaly compared to surface water and groundwater, attributed to anthropogenic input of Gd (Gdanth). The determined Gdanth concentration ranged from 0.04 to 0.21 μg/L, and from 0.06 to 0.37 μg/L, accounting for 4 % to 21 % and 49 % to 84 % of total Gd concentrations in groundwater and surface water, respectively. Gdanth concentration in wastewater (0.19 to 0.43 μg/L) remained constant in effluent after wastewater treatment. Surface water displayed relatively complex normalized REE patterns influenced by anthropogenic activities and natural processes (weathering and complexation), while groundwater exhibited heavy REEs enrichment, due to carbonate solution complexation. Additionally, Gdanth concentration showed a positive correlation with ΣREE, Pb, Ni, and Co concentrations in groundwater, indicating a good pollution tracing potential. Health risk assessment using the hazard quotient (HQ) suggested higher HQGd values in groundwater compared to surface water. Residents in the eastern part of Poyang Lake were found to face higher risks associated with Gd in groundwater compared to the western part, with infants and children at greater risk than adult males and females. These findings offer valuable insights into environmental behavior and health risks of REEs in aquatic systems impacted by human activities.

Identify the seasonal differences in water quality and pollution sources between river-connected and gate-controlled lakes in the Yangtze River basin

The river-connected Dongting Lake (DT) and Poyang Lake (PY), and the gate-controlled Taihu Lake (TH) and Chaohu Lake (CH) are the four important lakes in the Yangtze River Basin. The comprehensive Water Quality Index (WQI), the Eutrophication Integrated Index (TLI(Σ)), and the Positive Matrix Factorization (PMF) model were employed to evaluate water quality and the contribution of pollution sources for these lakes. The results show that WQI for all lakes indicated generally good water quality, with DT scoring 73.52-86.18, the highest among them. During the wet season, the eutrophication degree of river-connected lake was medium, and that of gate-controlled lakes was high. The surface runoff and agricultural non-point sources are the main pollution sources for both types of lakes, but their impact is more pronounced in gate-controlled lakes during the wet season. The study provides evidence support for scientific understanding of water quality problems and management strategies in these areas.

Restore polder and aquaculture enclosure to the lake: Balancing environmental protection and economic growth for sustainable development

The restoration of lakes and their buffer zones is crucial for understanding the intricate interplay between human activities and natural ecosystems resulting from the implementation of environmental policies. In this study, we investigated the ecological restoration of shallow lakes and buffer zones in the Yangtze-Huaihe River Basin, specifically focusing on the removal of polder and aquaculture enclosure areas within the lakes. By examining data from eight shallow lakes and their corresponding buffer zones, encompassing lake morphology, water quality parameters, and land use/land cover (LULC) data spanning from 2008 to 2022, which shed light on the complex relationships involved. During the process of restoring polder and aquaculture enclosure areas, we observed a general decrease in the extent of polders and aquaculture enclosures within the lakes. Notably, the removal of aquaculture enclosures had a more pronounced effect (reduction rate of 83.37 %) compared to the withdrawal of polders (reduction rate of 48.76 %). Linear regression analysis revealed a significant decrease in the concentrations of seven water quality parameters, including COD, CODMn, TN, TP, NH3-N, Chl-a, and F, while pH and DO factors exhibit a distinct increasing trend. The results of redundancy analysis and Pearson correlation analysis demonstrated significant correlations between the area of polders and aquaculture enclosures and the changes in lake water quality. Encouragingly, the withdrawal of polders and the removal of aquaculture enclosures had a positive impact on the lake water quality improvement. In contrast, the LULC in the buffer zones of the lakes experienced a gradual decline owing to land degradation, resulting in a reduction in ecosystem service value (ESV). These results offer valuable support for policymakers in their endeavors to restore lake water quality, mitigate the degradation of buffer zones land, and promote the sustainable development of land and water resources.

Distribution characteristics and microbial synergistic degradation potential of polyethylene and polypropylene in freshwater estuarine sediments

The microbial degradation of polyethylene (PE) and polypropylene (PP) resins in rivers and lakes has emerged as a crucial issue in the management of microplastics. This study revealed that as the flow rate decreased longitudinally, ammonia nitrogen (NH4+-N), heavy fraction of organic carbon (HFOC), and small-size microplastics (< 1 mm) gradually accumulated in the deep and downstream estuarine sediments. Based on their surface morphology and carbonyl index, these sediments were identified as the potential hot zone for PE/PP degradation. Within the identified hot zone, concentrations of PE/PP-degrading genes, enzymes, and bacteria were significantly elevated compared to other zones, exhibiting strong intercorrelations. Analysis of niche differences revealed that the accumulation of NH4+-N and HFOC in the hot zone facilitated the synergistic coexistence of key bacteria responsible for PE/PP degradation within biofilms. The findings of this study offer a novel insight and comprehensive understanding of the distribution characteristics and synergistic degradation potential of PE/PP in natural freshwater environments.

Flood risk transfer analysis based on the "Source-Sink" theory and its impact on ecological environment: A case study of the Poyang Lake Basin, China

Driven by climate change, the frequent occurrence of regional destructive floods poses a grave threat to socio-economic systems and ecological environments. Previous flood risk studies have disregarded risk transfer within a region, resulting in inadequate flood risk assessment and ineffective disaster prevention and mitigation outcomes. Therefore, this study introduced the "Source-Sink" theory into flood disaster field to constructing flood risk transfer model. Flood risk assessment and transfer was conducted in the Poyang Lake Basin, China, where the impacts of the initial and transfer statuses on ecosystem service values were quantified. The results showed that the flood risk in the Poyang Lake Basin was relatively low, with high spatial distribution characteristics in the central-north areas but low in the surrounding areas. High-risk zones were mainly distributed southwest of the Poyang Lake. The lower-risk zones exhibited a contiguous distribution and were surrounded by higher-risk zones. Following the completion of the flood risk transfer, high-risk zones increased significantly; but there were a few zones where the risk was transferred to other zones, thereby lowering their risks. Flood risk transfer occurs primarily in low- and medium-risk zones, with high-risk zones being the most important growth targets. The change in risk transfer was most evident in the area surrounding Poyang Lake, while that in the Upper Gan River Basin was lower and less sensitive to the transfer effect. Accounting for flood disaster risk, the ecosystem service values of the Poyang Lake Basin decreased by 8.18 %, with the most significant impacts observed in the surrounding environment and southwest Poyang Lake. After the completion of the flood risk transfer, the ecosystem service value in the Poyang Lake Basin declined by 24.66 %. This study provides a reference point for flood risk management and sustainable regional development that account for risk transfer.

Evaluation and monitoring of the water quality of an Argentinian urban river applying multivariate statistics

In this work, we present the water quality assessment of an urban river, the San Luis River, located in San Luis Province, Argentina. The San Luis River flows through two developing cities; hence, urban anthropic activities affect its water quality. The river was sampled spatially and temporally, evaluating ten physicochemical variables on each water sample. These data were used to calculate a Simplified Index of Water Quality in order to estimate river water quality and infer possible contamination sources. Data were statistically analyzed with the opensource software R, 4.1.0 version. Principal component analysis, cluster analysis, correlation matrices, and heatmap analysis were performed. Results indicated that water quality decreases in areas where anthropogenic activities take place. Robust inferential statistical analysis was performed, employing an alternative of multivariate analysis of variance (MANOVA), MANOVA.wide function. The most statistically relevant physicochemical variables associated with water quality decrease were used to develop a multiple linear regression model to estimate organic matter, reducing the variables necessary for continuous monitoring of the river and, hence, reducing costs. Given the limited information available in the region about the characteristics and recovery of this specific river category, the model developed is of vital importance since it can quickly detect anthropic alterations and contribute to the environmental management of the rivers. This model was also used to estimate organic matter at sites located in other similar rivers, obtaining satisfactory results.

The multiscale nexus among land use-land cover changes and water quality in the Suquía River Basin, a semi-arid region of Argentina

Agricultural intensification and urban sprawl have led to significant alterations in riverscapes, and one of the critical consequences is the deterioration of water quality with significant implications for public health. Therefore, the objectives of this study were the assessment of the water quality of the Suquía River, the assessment of LULC change at different spatial scales, and the analysis of the potential seasonal correlation among LULC change and Water Quality Index (WQI). The Sample Sites (SS) 1 and 2 before Cordoba city had the highest WQI values while from SS3 the WQI decreased, with the lowest WQI close to the wastewater treatment plant (SS7) after Cordoba city. From SS8 in a agricultural context, the WQI increases but does not reach the original values. In light of analysis carried out, the correlation between water quality variables and the different LULC classes at the local and regional scales demonstrated that WQI is negatively affected by agricultural and urban activities, while natural classes impacted positively. The spatialization of the results can help strongly in assessing and managing the diffusion of point and non-point pollution along the riverscape. The knowledge gained from this research can play a crucial role in water resources management, which supports the provision of river ecosystem services essential for the well-being of local populations.

Dynamic monitoring and analysis of chlorophyll-a concentrations in global lakes using Sentinel-2 images in Google Earth Engine

Remote estimation of Chlorophyll-a (Chl-a) has long been used to investigate the responses of aquatic ecosystems to global climate change. High-spatiotemporal-resolution Sentinel-2 satellite images make it possible to routinely monitor and trace the spatial distributions of lake Chl-a if reliable retrieval algorithms are available. In this study, Sentinel-2 images and in-situ measured data were used to develop a Chl-a retrieval algorithm based on 13 optical water types (OWTs) with a satisfying performance (R2 = 0.74, RMSE = 0.42 mg/m3, MAE = 0.33 mg/m3, and MAPE = 55.56 %). After removing the disturbance of algal blooms and other factors, the distribution of Chl-a in 3067 of the largest global lakes (≥50 km2) was mapped using the Google Earth Engine (GEE). From 2019 to 2021, the average Chl-a concentration was 16.95 ± 5.95 mg/m3 for the largest global lakes. During the COVID-19 pandemic, global lake-averaged Chl-a concentration reached its lowest value in 2020. From the perspective of spatial distribution, lakes with low Chl-a concentrations were mainly distributed in high-latitude, high-elevation, or economically underdeveloped areas. Among all the potential influencing factors, lake surface temperature had the largest contribution to Chl-a and showed a positive correlation with Chl-a in approximately 92.39 % of the lakes. Conversely, factors such as precipitation and tree cover area around the lake were negatively correlated with Chl-a concentration in nearly 61.44 % of the lakes.

Analysis of water quality influencing factors under multi-source data fusion based on PLS-SEM model: An example of East-Liao River in China

Owing to alterations in the environment and human activities, the quality of surface water is declining. Despite a substantial number of studies on the factors that impact water quality, there is still a need for a better understanding of the major causes of water quality degradation. This study fused multi-source data using partial least squares structural equation modeling to evaluate the effects of weather, soil composition, and geographical features on the water quality of the East Liao River (ELR), Jilin Province, China. The impacts of land-use practices on water quality at different buffer scales were analyzed. The most significant correlation between land use and water quality was observed at a distance of 4 km. The severity of water pollution was significantly influenced by soil type, with a path coefficient of 0.689 (p < 0.001). Conversely, landscape factors exhibited a notable adverse effect, indicated by a path coefficient of -0.608 (p < 0.001). Additionally, meteorological factors exhibited a significant impact, with a path coefficient of 0.463 (p < 0.001). The indirect effects of landscape elements on water quality were also examined. Water quality could be indirectly influenced by landscape through soil factors, as evidenced by a path coefficient of -0.572 (p < 0.01). In this study, new ideas for studying water quality drivers using multi-source data fusion are introduced. Managers can leverage the findings of this study to improve their decision-making and effectively address water quality issues in ELR located in Jilin Province, China.

Assessing habitat quality at Poyang Lake based on InVEST and Geodetector modeling

Poyang Lake is an essential natural wetland in the Yangtze River basin and plays a vital role in maintaining the ecosystem function and ecological security in the middle and lower reaches of the Yangtze River. However, the relative importance and spatial heterogeneity of the impacts of human activities and land use changes on ecological security needs to be further explored. Here, we analyzed the habitat quality level around Poyang Lake in 2022 and explored the factors of habitat quality change from a geographical perspective. The land use structure changes around the Poyang Lake basin from 2000 to 2022 were quantitatively analyzed, and then the relative importance and spatial heterogeneity of each factor on ecological security changes were investigated using geographic probes. The results show that (1) The worst quality habitat (0-0.1) consists mainly of construction land (1624.9 km2) with an area of 1634.64 km2; (2) Construction land continues to increase with the most significant change, and the dynamic land use attitude is 0.47. Grassland and mudflats have the greatest decrease. The increase in cultivated land in different periods is mainly due to the shift of water surface and forest land; (3) The drivers of habitat quality in Poyang Lake were significantly influenced by the interaction of socioeconomic factors. The explanatory power of population density interacting with the total year-end population and population density interacting with administrative area exceeded 0.84. These values were higher than the explanatory power of each individual factor, indicating that habitat quality was primarily associated with population density, total year-end population, and administrative area. These results suggest that human activities contribute to the degradation of wetlands around Poyang Lake. This study has significant reference value for coordinating human-land relationships in Poyang Lake, optimizing land management policy, and improving the sustainable development of cities.