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Fingerprinting sediment sources in a large agricultural catchment under no-tillage in Southern Brazil (Conceicao River)

机译:巴西南部(康西岛河)下耕地下的大型农业集水区的指纹沉积物来源

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Brazil is a leader in the adoption of conservation agriculture practices and technologies. However, the impact of these practices on sediment sources at the catchment scale has not been quantified yet, particularly in grain growing regions, where a conservationist no-tillage system is implemented to protect soils. To address this knowledge gap, a sediment fingerprinting study based on elemental geochemistry was carried out in a large agricultural catchment (804 km(2)) of Southern Brazil where no-tillage practices dominate. A total of 156 soil samples were taken to characterize the three main potential sediment sources: cropland (n = 79), unpaved roads (n = 41), and channel banks (n = 36). Sediment sampling was performed using a time-integrated sampler (n = 33) and by collecting fine-bed material (n = 34) at five locations across the catchment. Sediment was also sampled during flood events at the catchment outlet (n = 20). Sediment source contributions were calculated using an optimal suite of geochemical properties and a mixing model. Results showed that although the catchment is not particularly sensitive to soil erosion (i.e., deep clayey soils with gentle slopes), the amount of sediment supplied by cropland to the river network remains very high (up to 1.63 Mg.ha(-1).year(-1)). Sediment fingerprinting results showed that even when no-tillage is implemented, cropland remains an important source of sediment, supplying up to 70% of the material transiting the ConceicAo River. Accordingly, the current conservation farming system in this catchment needs to be improved to further reduce soil erosion and sediment yield.
机译:巴西是通过保护农业实践和技术的领导者。然而,这些实践对集水区沉积物来源的影响尚未量化,特别是在谷物生长区域中,保护家庭无耕作系统以保护土壤。为了解决这一知识差距,基于元素地球化学的沉积物指纹研究是在大型农业集水区(804公里(2))的南部巴西,其中没有耕作实践占主导地位。共有156种土壤样品来表征三个主要潜在沉积物来源:农田(n = 79),未铺砌的道路(n = 41)和渠道银行(n = 36)。使用时间集成采样器(n = 33)进行沉积物采样,并通过在整个集水器上的五个位置收集细床材料(n = 34)。在集水区出口(n = 20)的洪水事件中也被取样了沉积物。使用最佳地球化学性质和混合模型来计算沉积物源贡献。结果表明,虽然该集水区对土壤侵蚀(即,深层粘土泥土的深层粘土污水),但农田向河网提供的沉积物量仍然非常高(高达1.63 mg.ha(-1)。年(-1))。沉积物指纹识别结果表明,即使在耕作实施时,农田仍然是沉积物的重要来源,供应高达70%的物质过滤康西岛河。因此,需要改进该集水区的当前保守养殖系统,以进一步降低土壤侵蚀和沉积物产量。

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