水文学(农业)
土壤水分
水土保持
土壤科学
侵蚀控制
耕作
含水量
作者
Okan Aygün,Christophe Kinnard,Stéphane Campeau
出处
期刊:Catena
[Elsevier]
日期:2021-06-01
卷期号:201: 105184-
被引量:1
标识
DOI:10.1016/j.catena.2021.105184
摘要
Abstract This study explores the potential impacts of climate change on soil erosion in an agricultural catchment in eastern Canada. The Modified Universal Soil Loss Equation (MUSLE) was used to calculate the sediment yields from the Acadie River Catchment for the historical 1996–2019 period. The runoff variables of the MUSLE were obtained from a physically based hydrological model previously built and validated for the catchment. Then, the hydrological model was perturbed using climate change projections and used to assess the climate sensitivity of the sediment yield. Two runoff types representing possible modes of soil erosion were considered. While type A represents a baseline case in which soil erosion occurs due to surface runoff only, type B is more realistic since it assumed that tile drains also contribute to sediment export, but with a varying efficiency throughout the year. The calibration and validation of the tile efficiency factors against measurements in 2009–2015 for type B suggest that tile drains export the sediments with an efficiency of 20% and 50% in freezing and non-freezing conditions, respectively. Results indicate that tile drains account for 39% of the total annual sediment yield in the present climate. The timing of highest soil erosion shifts from spring to winter in response to warming and wetting, which can be explained by increasing winter runoff caused by shifting snowmelt timing towards winter, a greater number of mid-winter melt events as well as increasing rainfall fractions. The large uncertainties in precipitation projections cascade down to the erosion uncertainties in the more realistic type B, with annual sediment yield increasing or decreasing according to the precipitation uncertainty in a given climate change scenario. This study demonstrates the benefit of conservation and no-till pratices, which could reduce the annual sediment yields by 20% and 60%, respectively, under any given climate change scenario.
科研通智能强力驱动
Strongly Powered by AbleSci AI