Weirs are often constructed on mountainous rivers because of their low construction costs and their ability to provide irrigation and facilitate landscaping, yet there is little research on how fish habitat quality in mountainous rivers responds to weir distribution. This study categorized the distribution characteristics of weirs on typical reaches according to their sinuosity and calculated the corresponding habitat suitability index (HSI) and weighted usable area (WUA) under various discharge conditions using a coupled MIKE21 and habitat suitability model. Then, the relationship between the distribution characteristics of weirs and the quality of fish habitats under different discharge conditions was analyzed. The results show that weirs in mountainous rivers can affect the habitat suitability of the rivers, but this effect is closely related to discharge conditions and layout mainly because the key hydraulic factors that determine habitat quality for different sinuous reaches vary under different discharge conditions. This study found that in high-sinuosity rivers with high discharge conditions, water depth is the key factor determining the quality of fish habitats, so weirs can improve habitat quality by improving the suitability of downstream water depth. However, in other conditions, velocity is the key factor determining habitat quality, in which case weirs cannot improve habitat quality and can even degrade it. Therefore, other methods of improving velocity are needed to enhance habitat quality. The results of this study provide a reference for the protection of fish habitats in mountainous river channels and the determination of suitable locations for weir construction.
Integrated assessment of the water environment has become widespread in many rivers, lakes, and reservoirs; however, aquatic organisms in freshwater are often overlooked in this process. Zooplankton, as primary consumers, are sensitive and responsive to changes in the water environment. Water and zooplankton samples were collected on-site at Shanxi Reservoir quarterly to determine 12 water environmental indicators and to quantify the abundance of zooplankton of Cladocera, Copepoda and Rotifera by using the ZooScan zooplankton image-scanning analysis system, combined with OLYMPUS BX51 using machine learning recognition classification. The aim was to explore the relationship between water environmental factors and zooplankton through their spatial and temporal heterogeneity. Through principal component analysis, redundancy analysis and cluster analysis, variations in the factors driving zooplankton population growth in different seasons could be identified. At the same time, different taxa of zooplankton can form clusters with related water environmental factors during the abundant water period in summer and the dry water period in winter. Based on long-term monitoring, zooplankton can be used as a comprehensive indicator for water environment and water ecological health evaluation, as well as providing scientific support for regional water resources deployment and management.
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