Search Results (3)

Maintaining good water quality in the Lijiang River is a scientific and practical requirement for protecting and restoring the environmental and ecological value of the river. Understanding the influence of non-point source pollution on the water quality of the Lijiang River is important for water quality maintenance. In this study, the pollutant flux in the upper reaches of the Lijiang River was calculated based on water quality monitoring, non-point source pollution, and point source pollution statistics. The Z–Q relation curve method, hydrologic analogy method, and contour map method were used to estimate the flow of the Lijiang River. We then constructed a water quantity–water quality balance model of the upper reaches of the Lijiang River based on an equilibrium equation of water quantity and a modified one-dimensional steady-state model of the river. Water quality changes in the upper reaches were simulated for a wet, normal, and dry season. The simulation errors were all within −30% to 30%, which was in line with the pollution simulation requirements of the Standard for hydrological information and hydrological forecasting (GB/T 22482-2008). The simulated reliability of each water quality indicator is at a high level, based on the calculated Nash–Sutcliffe efficiency coefficient. The overall model simulation results were good. The simulation results show that the impact of non-point source pollution on the water quality of the upper reaches of the Lijiang River was greater than that of point source pollution. The effect of different types of non-point source pollution on the water quality of the Lijiang River was as follows: rural domestic pollution > urban household pollution without centralized treatment > pollution from agricultural cultivation. This study provides technical support for the long-term hydrology and water quality monitoring of the Lijiang River and provides a basis for the reduction in non-point source pollution and the continuous improvement of the water quality in the Lijiang River Basin. Full article

As the climate and the external environment have changed, the environmental factors of the Lijiang River Basin (LRB) have changed, posing new threats to the environmental quality, ecosystem balance, and management and protection of the water environment of the Lijiang River. Water quality indicators and environmental factors vary spatially along the Lijiang River, which runs through urban areas, farmland, and karst areas. However, research on the response of water quality to water environmental factors is still lacking. Within this context, this study considered statistical methods and hydrological, meteorological, and water quality data of the middle and lower reaches of the Lijiang River from 2012 to 2018, expounded on the temporal and spatial change characteristics and evolution trends of water quality indicators; we analyzed the correlation between water quality indicators and environmental factors; we quantitatively assessed the sensitivity and contribution rate of water quality indicators to environmental factors. The results demonstrated that rainfall feedback on the river streamflow was lagging, and upstream precipitation often affected downstream streamflow. The water quality in the upper reaches of Guilin has improved year by year, and pollution levels have increased slightly when flowing through the urban area of Guilin. In spite of this, it still falls within the range of self-purification. River characteristics heavily influence the impact of environmental factors on water quality indicators; in contrast, the effects of different locations along the same river are more similar. Four water quality indicators are negatively correlated with water temperature, pH, and dissolved oxygen (DO). The sensitivities of ammonia nitrogen (NH₄-N) and chemical oxygen demand (COD_Mn) to streamflow increase with the flow direction. The contribution rates of DO-to-total phosphorus (TP) and pH-to-TP are over −6%. Water temperature is the major contributing factor in the Lijiang River, while DO has a higher contribution in tributaries. The external sources affect the concentration of various water quality indicators and the sensitivity of water quality indicators to the external environment. There should be a series of measures implemented to reduce pollution, such as using oxygenation or chemical means to increase pH in Dahe and Yangshuo to control water pollutants. Tourism and particular karst topography make LRB’s calculations unique, but the research method can be applied to other watersheds as well. Full article

Beta diversity partitioning has currently received much attention in research of fish assemblages. However, the main drivers, especially the contribution of spatial and hydrological variables for species composition and beta diversity of fish assemblages are less well studied. To link species composition to multiple abiotic variables (i.e., local environmental variables, hydrological variables, and spatial variables), the relative roles of abiotic variables in shaping fish species composition and beta diversity (i.e., overall turnover, replacement, and nestedness) were investigated in the upstream Lijiang River. Species composition showed significant correlations with environmental, hydrological, and spatial variables, and variation partitioning revealed that the local environmental and spatial variables outperformed hydrological variables, and especially abiotic variables explained a substantial part of the variation in the fish composition (43.2%). The overall species turnover was driven mostly by replacement (87.9% and 93.7% for Sørensen and Jaccard indices, respectively) rather than nestedness. Mantel tests indicated that the overall species turnover (ß_SOR and ß_JAC) and replacement (ß_SIM and ß_JTU) were significantly related to hydrological, environmental, and spatial heterogeneity, whereas nestedness (ß_SNE or ß_JNE) was insignificantly correlated with abiotic variables (P > 0.05). Moreover, the pure effect of spatial variables on overall species turnover (ß_SOR and ß_JAC) and replacement (ß_SIM and ß_JTU), and the pure effect of hydrological variables on replacement (ß_SIM and ß_JTU), were not important (P > 0.05). Our findings demonstrated the relative importance of interactions among environmental, hydrological, and spatial variables in structuring fish assemblages in headwater streams; these fish assemblages tend to be compositionally distinct, rather than nested derivatives of one another. Our results, therefore, indicate that maintaining natural flow dynamics and habitat continuity are of vital importance for conservation of fish assemblages and diversity in headwater streams. Full article