Coupling LiDAR and thermal imagery to model the effects of riparian vegetation shade and groundwater inputs on summer river temperature.
In the context of global warming, it is important to understand the drivers controlling river temperature in order to mitigate temperature increases. A modeling approach can be useful for quantifying the respective importance of the different drivers, notably groundwater inputs and riparian shading which are potentially critical for reducing summer temperature. In this study, we use a one-dimensional deterministic model to predict summer water temperature at an hourly time step over a 21km reach of the lower Ain River (France). This sinuous gravel-bed river undergoes summer temperature increase with potential impacts on salmonid populations. The model considers heat fluxes at the water-air interface, attenuation of solar radiation by riparian forest, groundwater inputs and hydraulic characteristics of the river. Modeling is performed over two periods of five days during the summers 2010 and 2011. River properties are obtained from hydraulic modeling based on cross-section profiles and water level surveys. We model shadows of the vegetation on the river surface using LiDAR data. Groundwater inputs are determined using airborne thermal infrared (TIR) images and hydrological data. Results indicate that vegetation and groundwater inputs can mitigate high water temperatures during summer. Riparian shading effect is fairly similar between the two periods (-0.26±0.12°C and -0.31±0.18°C). Groundwater input cooling is variable between the two studied periods: when groundwater discharge represents 16% of the river discharge, it cools the river down by 0.68±0.13°C while the effect is very low (0.11±0.01°C) when the groundwater discharge contributes only 2% to the discharge. The effect of shading varies through the day: low in the morning and high during the afternoon and the evening whereas those induced by groundwater inputs is more constant through the day. Overall, the effect of riparian vegetation and groundwater inputs represents about 10% in 2010 and 24% in 2011 of water temperature diurnal amplitudes.
EVS, CNRS-UMR 5600, Université de Lyon, ENS de Lyon, Plateforme ISIG. 15, Parvis René Descartes, BP 7000, F69342 Lyon Cedex 07, France; ThéMA, CNRS-UMR 6049, Université Bourgogne - Franche-Comté, 32 rue Mégevand, F25030 Besançon Cedex, France. Electronic address: vincent.wawrzyniak@univ-fcomte.fr.
Vincent
V
Wawrzyniak
LGLTPE, CNRS-UMR 5276, Université de Lyon, Université Lyon 1, ENS de Lyon, 2 rue Raphaël Dubois, F69622 Villeurbanne Cedex, France.
Pascal
P
Allemand
EVS, CNRS-UMR 5600, Université de Lyon. Université Lyon 2, Campus Porte des Alpes, 5 avenue Pierre Mendès France, F69500 Bron, France.
Sarah
S
Bailly
EVS, CNRS-UMR 5600, Université de Lyon. Université Lyon 2, Campus Porte des Alpes, 5 avenue Pierre Mendès France, F69500 Bron, France.
Jérôme
J
Lejot
EVS, CNRS-UMR 5600, Université de Lyon, ENS de Lyon, Plateforme ISIG. 15, Parvis René Descartes, BP 7000, F69342 Lyon Cedex 07, France.
Hervé
H
Piégay
1-D deterministic model; Ain River (France); LiDAR data; Thermal infrared (TIR) remote sensing