Skip to main content

Research Repository

Advanced Search

Improving representation of riparian vegetation shading in a regional stream temperature model using LiDAR data

Loicq, Pierre; Moatar, Florentina; Jullian, Yann; Dugdale, Stephen J.; Hannah, David M.

Authors

Pierre Loicq

Florentina Moatar

Yann Jullian

David M. Hannah



Abstract

Modelling river temperature at the catchment scale is needed to understand how aquatic communities may adapt to current and projected climate change. In small and medium rivers, riparian vegetation can greatly reduce maximum water temperature by providing shade. It is thus important that river temperature models are able to correctly characterise the impact of this riparian shading. In this study, we describe the use of a spatially-explicit method using LiDAR-derived data for computing the riparian shading on direct and diffuse solar radiation. The resulting data are used in the T-NET one-dimensional stream temperature model to simulate water temperature from August 2007 to July 2014 for 270 km of the Loir River, an indirect tributary of the Loire River (France). Validation is achieved with 4 temperature monitoring stations spread along the Loir River. The vegetation characterised with the LiDAR approach provides a cooling effect on maximum daily temperature (Tmax) ranging from 3.0 °C (upstream) to 1.3 °C (downstream) in late August 2009. Compared to two other riparian shading routines that are less computationally-intensive, the use of our LiDAR-based methodology improves the bias of Tmax simulated by the T-NET model by 0.62 °C on average between April and September. However, difference between the shading routines reaches up to 2 °C (monthly average) at the upstream-most station. Standard deviation of errors on Tmax is not improved. Computing the impact of riparian vegetation at the hourly timescale using reach-averaged parameters provides results close to the LiDAR-based approach, as long as it is supplied with accurate vegetation cover data. Improving the quality of riparian vegetation data should therefore be a priority to increase the accuracy of stream temperature modelling at the regional scale.

Citation

Loicq, P., Moatar, F., Jullian, Y., Dugdale, S. J., & Hannah, D. M. (2018). Improving representation of riparian vegetation shading in a regional stream temperature model using LiDAR data. Science of the Total Environment, 624, 480-490. https://doi.org/10.1016/j.scitotenv.2017.12.129

Journal Article Type Article
Acceptance Date Dec 12, 2017
Online Publication Date Dec 27, 2017
Publication Date May 15, 2018
Deposit Date Nov 23, 2018
Journal Science of the Total Environment
Print ISSN 0048-9697
Electronic ISSN 1879-1026
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 624
Pages 480-490
DOI https://doi.org/10.1016/j.scitotenv.2017.12.129
Public URL https://nottingham-repository.worktribe.com/output/1302667
Publisher URL https://www.sciencedirect.com/science/article/pii/S0048969717335556
Additional Information This article is maintained by: Elsevier; Article Title: Improving representation of riparian vegetation shading in a regional stream temperature model using LiDAR data; Journal Title: Science of The Total Environment; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.scitotenv.2017.12.129; Content Type: article; Copyright: © 2017 Elsevier B.V. All rights reserved.