The effects of land use on water quality of alpine rivers: A case study in Qilian Mountain, China

Spatiotemporal variations in land use impacts on river water quality in a mountain-to-plain transitional basin in arid region of northern China

Land use, as an integrated representation of natural conditions and human activities, significantly impacts river water quality. Understanding the spatial and temporal variability of these influences offers valuable insights for improving water quality through the implementation of best management practices. This study examined the impact of land use on river water quality in the Dahei River Basin, a typical mountain-to-plain basin located in the arid region of northern China, which is also the last first-order tributary of Upper Yellow River. Hierarchical clustering analysis was employed to analyze the spatial distribution characteristics of river water quality and redundancy analysis was used to explore the impacts of land use on water quality in upstream buffer zones with radii from 500 m to 14,000 m. The results indicate that river water quality conditions in the mountainous region are much better than in the plain region. In both the dry and wet seasons, land use significantly affects water quality variation, particularly at the 8000 m buffer zone, although the mechanisms differ. In the wet season, the non-point source pollution from storm runoff erosion dominates the positive correlations between water pollution levels and the areas of cropland and urban regions, while for the dry season such positive correlations may come from elevated soil electrolyte levels due to groundwater irrigation and point source pollution from urban activities. For land use types that show a negative correlation with water pollutant levels, the stronger correlation observed in grasslands compared to forests region may be attributed to grasslands' better adaptation to arid conditions. The findings from this study enhance our understanding of the spatiotemporal variations in land use impacts on river water quality and can provide guidance for land use planning at the basin scale in arid regions.

Land use types, basin characteristics and water quality together shape riverine phytoplankton community composition and diversity

Exploring the combined effects of basin characteristics, land use types, and human activities on phytoplankton biomass, community composition and diversity is important for developing effective river protection strategies. In the present study, 182 phytoplankton samples were collected in the Hanjian and Danjiang River basins and the explanation rate of the above factors was analyzed. Water quality was the primary factor affecting riverine phytoplankton biomass, with an explanation rate to Chl a reaching 59.8%. Water quality was also the primary factor affecting phytoplankton diversity but the contribution of land use types and basin characteristics was also high. In addition to affecting phytoplankton communities and diversity by affecting water quality, diverse land use can increase the taxa of algae discharged through soil erosion processes. Elevation and slope were the main basin characteristics regulating phytoplankton community and diversity because they can determine the retention time of phytoplankton in rivers. The results also showed that land use types were the primary factor affecting the critical relative abundance of extinction (a), competition coefficient (k), environmental taxa capacity (N), but water quality was the primary factor affecting Shannon index, Simpson index, and Pielou index. This difference indicated that index a, k, and N could reflect specific characteristics of phytoplankton diversity that were not reflected by the latter indices. Our results implied that land use types and basin characteristics affected the discharge of exotic algal taxa, retention time, and other factors, thereby influencing the composition and diversity of riverine phytoplankton communities.

Enhancing river water quality in different seasons through management of landscape patterns at various spatial scales

Landscape patterns have a great effect on river water quality. However, the strategies for enhancing water quality through landscape pattern management remain unclear. In this study, we aimed to provide effective guidance for water quality management by quantifying the key spatial scales and landscape metrics that influence the seasonal variations in water quality and establishing threshold relationships between these metrics and abrupt variations in water quality in the Chaohu Lake basin, China. Results discovered that water quality was poorer in summer and better in spring, with degraded water conditions primarily concentrated in the middle and lower reaches of the watershed. The 100 m riparian zone buffer scale landscape pattern was identified as the key scale affecting water quality in the summer, which accounted for 51.3% of the overall water quality variation. Furthermore, abrupt threshold analysis indicated that summer water quality could be effectively improved by maintaining the proportion and largest patch index of construction land within the 100 m riparian buffer below 22.0%. At the sub-basin scale, landscape pattern-based water quality management was most effective in spring, explaining 43.6% of the variation in water quality. Setting the largest patch index of construction land at the sub-basin scale below 43.0% and increasing the proportion of forest cover above 36.0% can also alleviate water pollution issues. These findings emphasize the importance of incorporating landscape patterns across scales into environment management decisions, providing a scientific basis for effective watershed water quality management.

Increasing human activity shifts the key spatial scale of landscape patterns on water quality from sub-basins to riparian zones

The relationship between landscape patterns and water quality has been extensively studied, yet the understanding of how human activity modulates the spatial scale effects of landscape patterns on water quality remains limited. Here, we investigated the water quality and landscape patterns of three rivers in the Poyang Lake Basin, China, subjected to different intensities of human activity, and analyzed the extent to which water quality parameters were influenced by human activity to unravel the spatial scale effects and identify critical landscape metrics that significantly influence water quality. The results showed that the influence of riparian zone landscape patterns on water quality progressively exceeded that of sub-basin landscape patterns as the intensity of human activity increased. For water quality parameters that were minimally affected by human activity, the influence of sub-basin landscape patterns slightly exceeded that of riparian zone landscape patterns at different intensities of human activity (differences were 0.63 %, 4.25 % and 7.65 %, respectively). Conversely, for water quality parameters significantly affected by human activity, the landscape patterns of the riparian zone had a significantly greater influence than the sub-basin landscape patterns (differences were 5.90 %, 13.00 % and 17.86 %, respectively). Furthermore, the discrepancy between the influence of riparian zone and sub-basin landscape patterns on water quality increased with increasing intensity of human activity, while the overall influence of landscape patterns on water quality showed a decreasing trend (decreasing from 60.35 % to 39.10 %). In addition, the proportions of construction land, farmland, and forestland, and the fragmentation of grassland, were identified as critical landscape metrics that significantly influenced water quality at different intensities of human activity. This study revealed that different intensities of human activity were key factors influencing the spatial scale effects of landscape patterns on water quality.

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.

Landscape fragmentation of built-up land significantly impact on water quality in the Yellow River Basin

Urbanization development often leads to significant changes in the extent in area and fragmentation of built-up land landscape pattern (BLLP) in river basins, which greatly impact the processes of rainfall runoff and pollutant migration. Understanding the spatial scale effects and driving mechanisms of BLLP changes on water quality in large river basins is a challenging research topic and an international frontier in the interdisciplinary fields of geography and environment. This study analyzes the spatial variations of BLLP and water quality throughout the Yellow River Basin (YRB) during the rainy seasons from 2019 to 2021 (4 h scale). Utilized the random forest model to quantitatively separates the contributions of rainfall processes to surface runoff and water pollution, revealing the scale effects and non-linear driving mechanisms of BLLP impacts on water environment changes. The results indicate that: 1) The YRB exhibits great spatial heterogeneity in terms of both BLLP and water quality, with places with lower water quality displaying bigger areas and higher degrees of BLLP fragmentation. 2) The patch density and built-up land area (PD.B and CA.B) have a major impact on changes in water quality in the YRB, with notable impacts noted in circular buffer zones with radii of 20 km and 5 km, respectively. 3) PD.B is sensitive to water quality in the YRB, explaining 39.1%-49.5% of the variance under different rainfall conditions, and exhibits a significant non-linear relationship, with an impact threshold of 0.38 (n/100 ha). The study suggests that for large-scale regions like the YRB, the degree of BLLP fragmentation is more likely to lead to degradation of water environmental quality compared to its area. BLLP fragmentation due to higher PD.B and CA.B disrupts the original ecosystem and hydrological connectivity, resulting in poorer retention and filtration of pollutants carried by rainfall runoff, while increasing the export of other pollutants. However, once urbanization surpasses a certain threshold, the BLLP fragmentation can enhance water quality by reducing the impermeable surface connectivity, as they are no longer impacted by expanding areas. To achieve ecologically sustainable development, it is necessary to apply rational landscape management and water resource management policies that consider the dual process of how BLLP fragmentation affects the water environment.

Riverine bacterial communities are more shaped by species sorting in intensive urban and agricultural watersheds

Bacterial communities play a crucial role in maintaining the stability of river ecosystems and driving biogeochemical cycling, exhibiting high sensitivity to environmental change. However, understanding the spatial scale effects and assembly mechanisms of riverine bacterial communities under distinct anthropogenic disturbances remains a challenge. Here, we investigated bacterial communities across three distinct watersheds [i.e., intensive urban (UW), intensive agricultural (AW), and natural (NW)] in both dry and wet seasons. We explored biogeographic patterns of bacterial communities and the influence of landscape patterns at multi-spatial scales and water chemistry on bacterial communities. Results showed that α diversity was significantly lower in UW and AW compared to NW, particularly in the dry season. A gradient of β diversity with NW > UW > AW was observed across both seasons (p < 0.05). Pseudomonadota, Bacteroidota, and Actinobacteriota were the most abundant phyla across all watersheds, with specific taxa enriched in each watershed (i.e., the class Actinobacteria was significant enrichment in UW and AW, and Clostridia in NW). The influence of landscape patterns on bacterial communities was significantly lower in human-disturbed watersheds, particularly in UW, where this influence also varied slightly from near riparian buffers to sub-watershed. Homogeneous selection and drift jointly dominated the bacterial community assembly across all watersheds, with homogeneous selection exhibiting a greater influence in UW and AW. Landscape patterns explained less variance in bacterial communities in UW and AW than in NW, and more variance was explained by water chemistry (particularly in UW). These suggest that the stronger influence of species sorting in UW and AW was driven by more allochthonous inputs of water chemistry (greater environmental stress). These findings provide a theoretical foundation for a deeper understanding of riverine bacterial community structure, spatial scale effects, and ecological management under different anthropogenic activities.

Dams alter the control pattern of watershed land use to riverine nutrient distribution: Comparison of three major rivers under different hydropower development levels in Southwestern China

Land use plays a critical role in managing water quality in a watershed, as it governs the import and distribution of nutrients. In addition to the land use, some rivers in Southwest China are encountering a new environmental stressor of damming, which is being driven by the national strategy of hydropower development. However, the coupling effect of land use and dams on nutrients remains poorly understood, challenging the effective management of riverine water quality. Therefore, this study examined the nutrients in the Nu, Yarlung Tsangpo (YT), and Lancang (LC) Rivers, which have no dam, 1 dam, and 11 dams, respectively, during different regulatory periods (spring and fall) to identify variations in nutrient control patterns influenced by land use and dams. The findings suggested that an increase in hydropower development contributed to a notable shift in nutrient patterns from land use regulation towards dam regulation and coupling effects. Land use dominated the nutrient variations of the Nu (27.4 %-32.8 %) and low hydropower development YT (25.2 %-30.9 %) Rivers during both seasons, but the primary contributors to the nutrient variations of the high hydropower development LC River were dams (17.9 %-41.6 %) and coupling effects (16.5 %-29.0 %). Dams transform nutrient levels and compositions through internal reservoir cycling, decoupling land use and nutrients. Partial least-squares structural equation model analysis further suggested that the coupling effects of the LC River were seasonal-specific, which was primarily attributed to hydrological variations that affected their interactions. During spring, the reservoir underwent a drainage mode characterized by high-level nutrients in the bottom water. Combined with the import of riverine nutrients, it exacerbated the increase of nutrients (synergistic effect). In contrast, the reservoir transitioned into a storage mode where it intercepted nutrients from the upstream and watershed during the fall, leading to a reduction in the previously observed increasing trend and an increase in nutrient variability (antagonism effect).

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.

Response of water quality in major tributaries to the difference of multi-scale landscape indicators in Dongting Lake basin, China

River water quality has been increasingly deteriorated because of the influence of natural process and anthropogenic activities. Quantifying the influence of landscape metrics, namely topography and land use pattern, which encompass land use composition and landscape configuration, across different spatial and seasonal scales that reflect natural process and anthropogenic activities, is highly beneficial for water quality protection. In this study, we focused on investigating the effects of topography, landscape configuration and land use composition on water quality at different spatial scales, including 1-km buffer and sub-watershed, and seasonal scales, including wet and dry season, based on the monthly water quality data in 2016 of Dongting Lake in China. Multivariate statistical analysis of redundancy analysis and partial redundancy analysis was used to quantify the contributions of these factors under different scales. Our results showed that among the three environmental groups, topography made the greatest pure contribution to water quality, accounting for 11.4 to 30.9% of the variation. This was followed by landscape configuration, which accounted for 9.4 to 23.0%, and land use composition, which accounted for 5.9 to 15.7%. More specifically, water body made the greatest contribution to the water quality variation during dry season at both spatial scales, contributing 16.6 to 17.2% of the variation. In contrast, edge density was the primary interpreter of the variability in water quality during wet season at both spatial scales, accounting for 9.9 to 11.1% of the variation. The spatial variability in the influence of landscape metrics on water quality was not markedly distinct. However, these metrics have a minimal impact difference on water quality at the buffer scale and the sub-watershed scale. Moreover, the contribution of landscape configuration varied the most from the buffer to sub-watershed scales, indicating its importance for the spatial scale difference in water quality. The findings of this study offer useful insights into enhancing water quality through improved handling of landscape metrics.

Historical and dispersal processes drive community assembly of multiple aquatic taxa in glacierized catchments in the Qinghai-Tibet plateau

Understanding the relative role of dispersal dynamics and niche constraints is not only a core task in community ecology, but also becomes an important prerequisite for bioassessment. Despite the recent progress in our knowledge of community assembly in space and time, patterns and processes underlying biotic communities in alpine glacierized catchments remain mostly ignored. To fill this knowledge gap, we combined the recently proposed dispersal-niche continuum index (DNCI) with traditional constrained ordinations and idealized patterns of species distributions to unravel community assembly mechanisms of different key groups of primary producers and consumers (i.e., phytoplankton, epiphytic algae, zooplankton, macroinvertebrates, and fishes) in rivers in the Qinghai-Tibet Plateau, the World's Third Pole. We tested whether organismal groups with contrasting body sizes differed in their assembly processes, and discussed their applicability in bioassessment in alpine zones. We found that community structure of alpine river biotas was always predominantly explained in terms of dispersal dynamics and historical biogeography. These patterns are most likely the result of differences in species-specific functional attributes, the stochastic colonization-extinction dynamics driven by multi-year glacier disturbances and the repeated hydrodynamic separation among alpine catchments after the rising of the Qilian mountains. Additionally, we found that the strength of dispersal dynamics and niche constraints was partially mediated by organismal body sizes, with dispersal processes being more influential for microscopic primary producers. Finding that zooplankton and macroinvertebrate communities followed clumped species replacement structures (i.e., Clementsian gradients) supports the notion that environmental filtering also contributes to the structure of high-altitude animal communities in glacierized catchments. In terms of the applied fields, we argue that freshwater bioassessment in glacierized catchments can benefit from incorporating the metacommunity perspective and applying novel approaches to (i) detect the optimal spatial scale for species sorting and (ii) identify and eliminate the species that are sensitive to dispersal-related processes.

Research progress in water quality prediction based on deep learning technology: a review

Water, an invaluable and non-renewable resource, plays an indispensable role in human survival and societal development. Accurate forecasting of water quality involves early identification of future pollutant concentrations and water quality indices, enabling evidence-based decision-making and targeted environmental interventions. The emergence of advanced computational technologies, particularly deep learning, has garnered considerable interest among researchers for applications in water quality prediction because of its robust data analytics capabilities. This article comprehensively reviews the deployment of deep learning methodologies in water quality forecasting, encompassing single-model and mixed-model approaches. Additionally, we delineate optimization strategies, data fusion techniques, and other factors influencing the efficacy of deep learning-based water quality prediction models, because understanding and mastering these factors are crucial for accurate water quality prediction. Although challenges such as data scarcity, long-term prediction accuracy, and limited deployments of large-scale models persist, future research aims to address these limitations by refining prediction algorithms, leveraging high-dimensional datasets, evaluating model performance, and broadening large-scale model application. These efforts contribute to precise water resource management and environmental conservation.

Distribution characteristics of microorganisms in sediments of Dagu River and their biological indicator function for evaluating eco-environmental quality of rural river

The microorganisms in sediments play a crucial role in biogeochemical cycle processes, and numerous studies have shown that microbial community is closely related to environmental factors. However, the usability of sediment microorganisms to evaluate the eco-environment quality of rural rivers has not been adequately explored. This study investigated the distribution characteristics and response of sediment microorganisms to environmental parameters and benthic organisms. Based on the environmental parameters and benthic community indices, the 12 stations were divided into high-polluted group A, moderate-polluted group B and low-polluted group C. Station DG01 and DG02 in group A had the highest level of As and Ni pollution and nutrient concentration, and DG09 in group A had the lowest benthic diversity. Correspondingly, group A had the lowest abundance of Proteobacteria, which has a higher requirement for the environment than Planctomycetes. Group B had the highest sulfide level (97.45 mg/kg), and bacteria (Thiobacillus, Sulfurisoma and Sulfuritalea) with genes involved in sulfur cycling were more enriched in this group. Group C had the lowest level of total nitrogen (243.36 mg/kg), and Rhodanobacteraceae in Xanthomonadales might be a key bioindicator for low nitrogen. In addition, Chlorophyta was found to be more susceptible to heavy metals, and moreover co-occurrence networks showed that microeukaryotes were more sensitive to heavy metal pollution compared to benthic animals and prokaryotes. Therefore, this study suggested that benthic microorganisms especially microeukaryotes could be used as good indicators for evaluating the eco-environmental quality of rural rivers.

Spatial characteristics of hydrochemistry and stable isotopes in river and groundwater, and runoff components in the Shule River Basin, Northeastern of Tibet Plateau

Water resources play a crucial role in constraining the high-quality development of the arid, necessitating an in-depth investigation and understanding of hydrological processes, hydrochemical characteristics, and their influencing factors amidst climate change. This study meticulously examined and analyzed the hydrochemistry and stable isotope composition (δ18O and δD) of river and groundwater within the Shule River Basin (SRB). Results showed that both river (mean: 8.01) and groundwater (mean: 7.92) had alkaline pH values, while average total dissolved solids were measured at 709.25 mg/L in river and 861.88 mg/L in groundwater, indicating predominance of fresh water sources. HCO3-, SO42-, Na+ and Ca2+ were the most abundant ions, influenced by evaporation-crystallization processes and rock weathering. The dominated hydrochemical facies in both river and groundwater were Ca-HCO3 type in the upper (UR) and the middle reaches (MR), while Ca-Mg-Cl type in the lower reaches (LR). The local meteoric water line (LMWL) was defined as δD = 8.01δ18O + 18.48 (R2 = 0.98, n = 163; P < 0 0.001). The more negative δ18O and δD values in river and groundwater were plotted nearby and lower right of the LMWL, implying that the important recharge source of those waters is from precipitation. The relationship between river δ18O and elevation showed an increase of 0.14‰/100 m in the UR, but a negative correlation with a rate of -0.47‰/100 m in the MR and LR. Precipitation, groundwater, baseflow and meltwater accounted for 62.5%, 19.8%, 11.9% and 5.8% of the UR river, respectively, during the observed period, according to the end-member mixing analysis. These runoff components displayed distinct seasonal variations, primarily driven by precipitation during the early and groundwater/baseflow during the rapid and end-stage ablation periods. The observed alterations in hydrological elements present both opportunities and challenges for water resource management across the SRB, and adaptive measures have been proposed based on our study. These findings provide valuable insights into efficient utilization of water resources from water chemistry and environmental isotopes.