Increasing river temperatures are a threat to cold water species including ecologically and economically important freshwater fish, such as Atlantic salmon. In 2018, ca. 70% of Scottish rivers experienced temperatures which cause thermal stress in juvenile salmon, a situation expected to become increasingly common under climate change. Management of riparian woodlands is proven to protect cold water habitats. However, creation of new riparian woodlands can be costly and logistically challenging. It is therefore important that planting can be prioritized to areas where it is most needed and can be most effective in reducing river temperatures. The effects of riparian woodland on channel shading depend on complex interactions between channel width, orientation, aspect, gradient, tree height and solar geometry. Subsequent effects on river temperature are influenced by water volume and residence time. This study developed a deterministic river temperature model, driven by energy gains from solar radiation that are modified by water volume and residence time. The resulting output is a planting prioritization metric that compares potential warming between scenarios with and without riparian woodland. The prioritization metric has a reach scale spatial resolution, but can be mapped at large spatial scales using information obtained from a digital river network. The results indicate that water volume and residence time, as represented by river order, are a dominant control on the effectiveness of riparian woodland in reducing river temperature. Ignoring these effects could result in a sub-optimal prioritization process and inappropriate resource allocation. Within river order, effectiveness of riparian shading depends on interactions between channel and landscape characteristics. Given the complexity and interacting nature of controls, the use of simple universal planting criteria is not appropriate. Instead, managers should be provided with maps that translate complex models into readily useable tools to prioritize riparian tree planting to mitigate the impacts of high river temperatures.

中文翻译：

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一种确定性河流温度模型，用于优先管理河岸林地以降低夏季最高河流温度

河流温度升高对冷水物种构成威胁，包括对生态和经济具有重要意义的淡水鱼，如大西洋鲑鱼。在 2018 年，大约 苏格兰 70% 的河流经历了导致幼鲑鱼热应激的温度，预计这种情况在气候变化下会变得越来越普遍。管理河岸林地已被证明可以保护冷水栖息地。然而，创建新的河岸林地可能成本高昂且在后勤方面具有挑战性。因此，重要的是可以优先在最需要种植的地区种植，并且可以最有效地降低河流温度。河岸林地对河道阴影的影响取决于河道宽度、方向、坡向、坡度、树高和太阳几何形状之间的复杂相互作用。对河流温度的后续影响受水量和停留时间的影响。这项研究开发了一个确定性的河流温度模型，该模型由太阳辐射的能量增益驱动，这些能量增益受水量和停留时间的影响。由此产生的输出是一个种植优先级指标，用于比较有和没有河岸林地的情景之间的潜在变暖。优先级度量具有到达尺度空间分辨率，但可以使用从数字河流网络获得的信息在大空间尺度上进行映射。结果表明，以河流序为代表的水量和停留时间是河岸林地降低河流温度有效性的主要控制因素。忽略这些影响可能会导致次优的优先排序过程和不适当的资源分配。在河流秩序中，河岸遮荫的有效性取决于河道和景观特征之间的相互作用。鉴于控制的复杂性和相互作用的性质，使用简单的通用种植标准是不合适的。相反，应该为管理人员提供地图，将复杂的模型转化为易于使用的工具，以优先考虑河岸植树，以减轻河流高温的影响。