三峡库区支流库湾水体富营养化演变特征研究

支流库湾水体富营养化是三峡水库蓄水带来的主要水环境影响特征之一。根据对不同历史蓄水期间三峡库区各支流库湾的水质变化特征及富营养化状态分析表明:三峡水库从试验性蓄水阶段进入常态调度运行后,支流库湾的水动力条件被进一步削弱,入河污染物扩散能力大幅度降低,库湾水质逐渐变差,各支流库湾普遍表现为中、富营养级水平,年内整体表现为春季高于秋季。从三峡库区支流库湾水体富营养化演变特征来看,库湾水动力条件由河流态改变为湖库态是其发生水体富营养化的主驱动力因素,陆域营养盐输入是库湾水体富营养化演变的物质基础     

Landscape features control river's confluences water quality and tributary fish composition

Rivers networks represent hierarchical dendritic habitats within terrestrial landscapes and differences in connectivity and land use influence dispersal, and consequently biodiversity patterns. We, therefore, measured variation in water chemistry and fish abundance and related these to a number of landscape characteristics (e.g., wetland, urban, wooded, and agricultural) in the River Klarälven and its 30 permanently flowing tributaries. We hypothesized that these environmental attributes would differ between tributary and main stem habitat and that these differences would be driven by landscape attributes including land use. We found considerable intertributary variation in temperature and nutrient levels, and between the tributaries and the main stem. Generally, water temperature was lower in the tributaries, whereas nutrient levels were higher in the tributaries. The lower water temperature has implications for coldwater fishes, and we found two fishes, burbot and lamprey, associated with coldwater tributaries. We also found an inverse relationship between water quality and anthropogenic land use. Protecting tributaries with low anthropogenic impact will likely become increasingly important with ongoing global warming as they can function as thermal refugia for coldwater fishes. Hence, this study underscores the need to evaluate water courses at regional scales to identify spatial refuges and ensure connectivity.     

Machine-learning modeling of hourly potential thermal refuge area: A case study from the Sainte-Marguerite River (Quebec,Canada)

To understand the temporal and spatial variability of thermal refuges, this study focused on modeling potential thermal refuge area (PTRA) at a sub-daily time-step in two tributary confluences of the Sainte-Marguerite River (Canada) during the summers of 2020 and 2021. Aquatic ectotherm species, such as Atlantic salmon (Salmo salar), seek these refuges to avoid heat stress during high summer river temperatures. To investigate the temporal variability of these PTRA, we employed inverse weighted distance interpolation to delineate the hourly area available at both confluences. We then analyzed the impact of the atypical low flow conditions of summer 2021 on the diel cycle of PTRA extremes using the coefficient of variation and the generalized additive model (GAM). Finally, we used four supervised machine-learning regression models and three to five hydrometeorological predictors to estimate hourly PTRA availability: multivariate adaptive splines regression (MARS), GAM, support vector machine regression (SVM), and random forest regression (RF). The results showed that tree-based and kernel-based regression models, RF and SVM, outperformed GAM and MARS. RF had the highest accuracy at both sites, with a relative root mean square error and Nash–Sutcliffe efficiency coefficient (Nash) of 13% and 93%, respectively. Our study discovered that under warm conditions in August 2021, small perennial tributary inflows in combination with low mainstem discharge could create high and constant PTRA at confluences, potentially providing vital thermal refuges for cold-water taxa. These refuges may be especially important at the local level, within a specific stretch or section of the river. Given the decreasing availability of thermal refuges for salmonids, it is crucial to monitor stream temperatures at small spatial and temporal scales using data-driven techniques in order to understand stream temperature heterogeneity at tributary confluences.