Using remote sensing to parameterise a leaky barrier hydraulic unit

A canopy-resistance based debris factor, CA (Follett et al., 2020), can be used to model the head-loss from flows passing through and over a leaky barrier. The advantage over a Mannings coefficient typically used in hydraulic modelling is the debris factor is a direct construct from physical factors characterising the bulk properties of the woody debris, including frontal area and bulk density. The debris factor has been established to be a robust predictor of head-loss across a range of flows. The aim here has been to quantify CA from remotely sensed data based on photogrammetric techniques estimating the required physical characteristics. To do this we have worked with a leading specialist UK surveyor, Storm Geomatics, who surveyed two small watercourses (Nethercote and Paddle brook) near Shipston-on-Stour, England.    

A HEC-RAS 2D-only hydraulic model driven by design rainfall has been setup with 37 features in Nethercote Brook. The debris factor was first estimated based on photographic lookup and then refined to be based on analysis of photogrammetric data. For each unit a rating equation is generated given the estimate of CA which governs the head losses. The intention is that this process will become automated, such that a hydraulic unit for the leaky barrier can be generated automatically.  

An equivalent reach-scale Mannings roughness (see Follett and Hankin, 2022) is also considered with a view to using in other catchments more easily based on the type of modelling typically undertaken. In a further UK case study, in the intensively monitored Eddleston Water catchment, the reach-scale roughness approach was also tested for leaky barriers in Middle Burn, applying a Mannings uplift based off photographs taken of the leaky barrier construction. Here CA is estimated and the equations to convert to a reach-scale equivalent Mannings is used.  

As 3d point-cloud data from photogrammetry becomes more widely available, the intention is to make it easier to quantify CA and use the canopy resistance-based equations to generate a hydraulic unit for use in e.g. HEC-RAS 2D directly. This will help quantify the effectiveness of a range of nature-based solutions from large wood to woody debris barriers to slow the flow.  

Follett, E., Schalko, I., & Nepf, H. 2020. Momentum and energy predict the backwater rise generated by a large wood jam. Geophysical Research Letters, 47, e2020GL089346. https://doi.org/ 10.1029/2020GL089346 

Follett, E., Hankin, B., 2022. Investigation of effect of logjam series for varying channel and barrier physical properties using a sparse input data 1D network model. Environmental Modelling & Software, Volume 158, 2022, 105543, ISSN 1364-8152, https://doi.org/10.1016/j.envsoft.2022.105543 

Hankin, B., Hewitt, I., Sander, G., Danieli, F., Formetta, G., Kamilova, A., Kretzschmar, A., Kiradjiev, K., Wong, C., Pegler, S., and Lamb, R. 2020: A risk-based, network analysis of distributed in-stream leaky barriers for flood risk management. Nat. Hazards Earth Syst. Sci., 20, 2567–2584, 2020 https://doi.org/10.5194/nhess-20-2567-2020 .