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

Luca Fabris* (Corresponding Author), Iain Archibald Malcolm, Willem Bastiaan Buddendorf, Chris Soulsby

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


The importance of riparian tree cover in reducing energy inputs to streams is increasingly recognized in schemes to mitigate climate change effects and protect freshwater ecosystems. Assessing different riparian management strategies requires catchment-scale understanding of how different planting scenarios would affect the stream energy balance, coupled with a quantitative assessment of spatial patterns of streamflow generation. Here, we use the physically based MIKE SHE model to integrate simulations of catchment-scale run-off generation and in-stream hydraulics with a heat transfer model. This was calibrated to model the spatio-temporal distribution of hourly stream water temperature during warm low flow periods in a Scottish salmon stream. The model was explored as a "proof of concept" for a tool to investigate the effects of riparian management on high stream water temperatures that could affect juvenile Atlantic salmon. Uncertainty was incorporated into the assessment using the generalized likelihood uncertainty estimation approach. Results showed that by decreasing both the warming (daylight hours) and the cooling (night-time hours) rates, forest cover leads to a reduction of the temperature range (with a delay of the time to peak by up to 2 hr) and can therefore be effectively used to moderate projected climate change effects. The modelling presented here facilitated the quantification of potential mitigating effects of alternative riparian management strategies and provided a valuable tool that has potential to be utilized as an evidence base for catchment management guidance.

Original languageEnglish
Pages (from-to)776-791
Number of pages16
JournalHydrological Processes
Issue number6
Early online date26 Feb 2018
Publication statusPublished - 15 Mar 2018


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