Rivers are dynamic, complex integrators of their environment, which makes verification of the beneficial outcomes of restoration challenging. Thermal regime is central to habitat suitability and is often a focus in planning and evaluating the impact of restoration and climate resilience. Among these concerns, high summer stream temperature has frequently been identified as a limiting factor for salmon, steelhead, and trout. Our objective was to demonstrate the utility of combining high resolution thermal observation and modelling to evaluate restoration designed to mitigate stream thermal processes. This was demonstrated on the Middle Fork of the John Day River which is a critically impacted salmonid fishery in northeast Oregon, USA. We employed distributed temperature sensing and energy‐balance modelling to define the thermal regime. Restoration was predicted to result in a 0.7°C reduction of peak daily stream temperatures while increasing night temperatures by 0.9°C. This combined modelling and monitoring approach suggests that the 2012 restoration offered relief for native fish species stressed by excessive stream temperatures. This powerful combination of technology can be used in many projects to make optimal use of restoration investments to achieve durable and quantifiable improvements in habitat.

中文翻译：

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耦合高分辨率监控和建模以验证基于恢复的温度改善

河流是其环境的动态复杂集成者，这使得验证恢复的有益结果具有挑战性。热力状态对于栖息地的适应性至关重要，通常是规划和评估恢复和气候适应力影响的重点。在这些问题中，夏季溪流温度高经常被认为是鲑鱼，硬皮鱼和鳟鱼的限制因素。我们的目标是证明结合高分辨率热观测和建模来评估旨在减轻流热过程的修复效果。这在约翰·戴特河的中叉上得到了证明，这是在美国俄勒冈州东北部受到严重影响的鲑鱼渔业。我们采用了分布式温度感测和能量平衡模型来定义热态。恢复预计会导致每日溪流峰值温度降低0.7°C，而夜间温度升高0.9°C。这种组合的建模和监测方法表明，2012年的恢复为因溪流温度过高而受压的本地鱼类提供了缓解。这种强大的技术组合可以在许多项目中使用，以最优化地利用恢复投资，以实现对栖息地的持久和可量化的改善。