Improving Rainfall Interception Models with Physically-Based Mechanisms of Canopy Storage
Canopy interception accounts for ~20% of the water budget at the annual scale, yet modeling for individual storm events, a time step which is required for many large-scale water and energy models, is challenging. Our research has demonstrated that canopy interception model inaccuracies likely derive from the lack of explicit representation of physical processes responsible for routing rain water through the canopy and the literature suggests these inaccuracies are masked at coarse temporal resolutions due to compensating errors between too much evaporation and too little canopy storage. Sensitivity and uncertainty analysis of canopy interception models has highlighted the importance of bark water storage in determining net interception and stable water isotopes (δD and δ18O) are proving to be valuable in understanding residence time of storm water on canopy surfaces. Storm climatology (duration, intensity, intra-cloud rainout dynamics) strongly influences the isotopic signature of rainfall, which is further transformed in throughfall and stemflow via bark structural characteristics (thickness and roughness).
Collaborators: Anna Linhoss (MSU), Richard Keim (LSU), Katy Limpert (MS 2016), Mercedes Siegle-Gaither (MS 2018)