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.
LGLTPE, CNRS-UMR 5276, Université de Lyon, Université Lyon 1, ENS de Lyon, 2 rue Raphaël Dubois, F69622 Villeurbanne Cedex, France.
Sci Total Environ. 2017 Aug 15;592:616-626. doi: 10.1016/j.scitotenv.2017.03.019. Epub 2017 Mar 17.
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.
在全球变暖的背景下，了解控制河流温度的驱动因素对于减轻温度升高至关重要。建模方法可用于量化不同驱动因素的相对重要性，特别是地下水输入和河岸遮荫，这对于降低夏季温度可能至关重要。在本研究中，我们使用一维确定性模型来预测法国下莱茵河（Lower Ain River）21 公里河段夏季每小时的水温。这条蜿蜒的砾石河床河流夏季水温升高，可能对鲑鱼种群产生影响。该模型考虑了水-气界面的热通量、河岸森林对太阳辐射的衰减、地下水输入以及河流的水力特性。建模在 2010 年和 2011 年夏季的两个为期五天的时间段内进行。河道特性是根据横断面轮廓和水位测量结果通过水力建模获得的。我们使用 LiDAR 数据对河道表面的植被阴影进行建模。地下水输入是使用航空热红外（TIR）图像和水文数据确定的。结果表明，植被和地下水输入可以缓解夏季高温。两个时期的河岸遮荫效应相当相似（-0.26±0.12°C 和-0.31±0.18°C）。地下水输入冷却在两个研究期间变化：当地下水流量占河流流量的 16%时，它会使河流冷却 0.68±0.13°C，而当地下水流量仅占 2%时，冷却效果非常低（0.11±0.01°C）。遮荫的影响随时间而变化：清晨较低，下午和傍晚较高，而地下水输入引起的影响则全天较为稳定。总体而言，河岸植被和地下水输入的影响在 2010 年占水温日振幅的 10%左右，在 2011 年占 24%左右。
