当前位置: X-MOL 学术J. Great Lakes Res. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Using remote sensing to assess how intensive agriculture impacts the turbidity of a fluvial lake floodplain
Journal of Great Lakes Research ( IF 2.2 ) Pub Date : 2023-10-21 , DOI: 10.1016/j.jglr.2023.102240
Maxime Clermont , Christophe Kinnard , Daphney Dubé-Richard , Stéphane Campeau , Pierre-André Bordeleau , Arthur de Grandpré , Jawad Ziyad , Alexandre Roy

Lake St-Pierre is set in the largest floodplain in the province of Quebec, Canada, and is a rich ecosystem of great ecological importance. However, Lake St-Pierre has seen its ecological integrity deteriorate in recent decades, largely due to the development of agriculture in and around its floodplain. This study uses a simple turbidity retrieval model (NIR and RED reflectances from Sentinel-2) to quantify the impact of land use on water turbidity within the lake floodplain during the 2019 and 2020 spring flood. Using a linear mixed effect model, we assessed how land use (wet meadows, cultivated grasslands, soybean, corn fields) impacts turbidity retrieved from Sentinel-2. Water turbidity was found to increase with the level of agricultural perturbations. During the severe and long 2019 flood, the turbidity was 5% higher over cultivated grassland fields, 35% higher over soybean fields and 70% higher over corn fields, compared to wet meadows. For 2020, a comparatively drier year, the corresponding impacts were 9% for cultivated grassland fields, 65% for soybean fields and 93% for corn fields. However, land use only explained 4% (2019) and 5% (2020) of the water turbidity spatiotemporal variance, which was instead mostly driven by the sediment load coming from upstream watersheds. Our results indicate that, despite complex processes driving water mass movements in the floodplain, intensive farming practices lead to higher water turbidity compared to natural lands. This study provides evidence that intensive agriculture impacts the water quality in a critical moment for the long-term health of the Lake St-Pierre.



中文翻译:

利用遥感评估集约化农业对河流湖泊漫滩浊度的影响

圣皮埃尔湖位于加拿大魁北克省最大的洪泛区,是一个具有重要生态意义的丰富的生态系统。然而,近几十年来,圣皮埃尔湖的生态完整性不断恶化,这主要是由于其洪泛区及其周围农业的发展。本研究使用简单的浊度反演模型(来自 Sentinel-2 的 NIR 和 RED 反射率)来量化 2019 年和 2020 年春季洪水期间土地利用对湖泊漫滩内水体浊度的影响。使用线性混合效应模型,我们评估了土地利用(湿草地、耕地、大豆、玉米田)如何影响从 Sentinel-2 检索到的浊度。发现水的浊度随着农业扰动的程度而增加。在2019年严重而漫长的洪水期间,与湿草地相比,耕地的浊度高出5%,大豆田的浊度高出35%,玉米田的浊度高出70%。2020年是相对干旱的一年,耕地的相应影响为9%,大豆田的影响为65%,玉米田的影响为93%。然而,土地利用仅解释了水浊度时空变化的 4%(2019 年)和 5%(2020 年),而这主要是由上游流域的沉积物负荷驱动的。我们的结果表明,尽管驱动洪泛区水团运动的过程很复杂,但与自然土地相比,集约化农业实践导致水体浊度更高。这项研究提供了证据,表明集约化农业在圣皮埃尔湖长期健康的关键时刻影响着水质。

更新日期:2023-10-21
down
wechat
bug