Vincent Wawrzyniak

Prediction of water temperature heterogeneity of braided rivers using very high resolution thermal infrared TIR images

Braided rivers exhibit high spatial thermal heterogeneity that is difficult to understand using only in situ measurements. In this summer study, we used a drone and a powered paraglider to acquire very high spatial resolution (14–27 cm) thermal infrared (TIR) images of nine braided reaches located in the French Alps. We applied atmospheric corrections to TIR images and calibrated them based on in situ data. To characterize spatial and temporal thermal patterns, three temporal approaches were applied. A single survey of each site was performed to comparatively explore the nine braided reaches. Three reaches were imaged twice, in 2010 and 2011, to explore inter-annual variability. Finally, two reaches were selected for an intra-day survey for which four and three flights, respectively, were realized within one day. We reported two types of thermal patterns in braided reaches, the first showing very low thermal variability throughout the day. This low variability was linked to the low diversity found in the aquatic habitat, notably due to proglacial regimes with high summer flows which homogenize water temperatures. The second type exhibited a higher thermal variability with changes during the day. The temperature of flowing channels changed during the daytime according to air temperature. In contrast, the temperature of channels downstream connected to the main network exhibited smaller changes, which created thermal variability over space and time associated with hyporheic or phreatic flows. Non-proglacial and proglacial reaches behaved differently according to air temperature. Proglacial reaches were colder and less sensitive to air temperature in comparison with non-proglacial reaches. These findings allow for a prediction of habitat diversity from temperature heterogeneity based on time and the proportion of ponds, alluvial, and groundwater channels.

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.