The role of riparian vegetation density, channel orientation and water velocity in determining river temperature dynamics

Integrating process‐based flow and temperature models to assess riparian forests and temperature amelioration in salmon streams

“…Early studies mainly relied on empirical water temperature and meteorological observations that were used to estimate heat fluxes and make comparisons between shaded and exposed sites (Garner et al, ; Hannah et al, ; Malcolm et al, ; Malcolm, Hannah, Donaghy, Soulsby, & Youngson, ). More recently, Garner et al (, ) developed a high‐resolution energy flux model incorporating flow routing that was capable of identifying the processes underlying observed patterns of river temperature variability in relation to channel shading. This investigation further extends these earlier studies by modelling energy exchange and river temperature in an integrated, physically based study that incorporates hydrological, hydraulic, and energy budget modules in a single modelling framework.…”

“…Riparian woodland reduces incoming short‐wave radiation, which dominates energy inputs to river systems during summer months (e.g., Hannah, Malcolm, Soulsby, & Youngson, ). However, the effectiveness of riparian shading varies depending on other controls such as channel orientation, canopy density, and within‐reach residence times (Garner, Malcolm, Sadler, & Hannah, ).…”

“…However, this and other regression‐based modelling studies (e.g., Hrachowitz Soulsby, Imholt, Malcolm, & Tetzlaff, ) have been unable to adequately characterize the magnitude of the shading effect between river reaches with different characteristics, given the complexity of processes involved. A more detailed understanding of the effects of riparian shading can be obtained through integration of field‐based measurements of energy exchange processes under different riparian land use (e.g., Dugdale, Malcolm, Kantola, & Hannah, ; Garner, Malcolm, Sadler, & Hannah, ; Hannah et al, ) and process‐based river temperature models (Garner et al, , ). These models can be further extended to include hydrological processes within a coupled hydrological energy balance modelling framework (see Dugdale et al, , for a review).…”

Influence of landscape and hydrological factors on stream–air temperature relationships at regional scale

“…The influence of the riparian vegetation shading on TS was highlighted by several studies (Chang & Psaris, 2013;Dugdale et al, 2018;Garner, Malcolm, et al, 2017;Hrachowitz et al, 2010; F.L. Loicq et al, 2018).…”

“…The Tw variability, described by metrics of flow magnitude, frequency, duration, timing, and rate of change, on various timescales (Jones & Schmidt, 2018), is influenced by complex processes related to atmospheric, hydrogeological, geomorphic, and landscape characteristics and anthropogenic pressures, which could interact at multiple spatial scales (Caissie, 2006;Hannah & Garner, 2015). Numerous studies have highlighted the importance of riparian forest and groundwater inflows in moderating Tw variability (Dugdale, Malcolm, Kantola, & Hannah, 2018;Garner, Malcolm, Sadler, & Hannah, 2017;Kelleher et al, 2012;Lalot et al, 2015;Loicq, Moatar, Jullian, Dugdale, & Hannah, 2018). Identifying the main controlling factors of Tw variability remains an important task to target streams sensitive to climate change and to develop mitigation action to preserve aquatic ecosystems (Jackson et al, 2018).…”