Abstract

Summary Although soil erosion is one of the main threats to agriculture sustainability in many areas of the world, its processes are difficult to measure and still need a better characterization. The use of iron oxides as sediment tracers, combined with erosion and mixing models opens up a pathway for improving the knowledge of the erosion and redistribution of soil, determining sediment sources and sinks. In this study, magnetite and a multivariate mixing model were used in rainfall simulations at the micro-plot scale to determine the source of the sediment at different stages of a furrow–ridge system both with (+T) and without (–T) wheel tracks. At a plot scale, magnetite, hematite and goethite combined with two soil erosion models based on the kinematic wave approach were used in a sprinkler irrigation test to study trends in sediment transport and tracer dynamics along furrow lengths under a wide range of scenarios. In the absence of any stubble cover, sediment contribution from the ridges was larger than the furrow bed one, almost 90%, while an opposite trend was observed with stubble, with a smaller contribution from the ridge (32%) than that of the bed, at the micro-plot trials. Furthermore, at a plot scale, the tracer concentration analysis showed an exponentially decreasing trend with the downstream distance both for sediment detachment along furrows and soil source contribution from tagged segments. The parameters of the distributed model KINEROS2 have been estimated using the PEST Model to obtain a more accurate evaluation. Afterwards, this model was used to simulate a broad range of common scenarios of topography and rainfall from commercial farms in southern Spain. Higher slopes had a significant influence on sediment yields while long furrow distances allowed a more efficient water use. For the control of runoff, and therefore soil loss, an equilibrium between irrigation design (intensity, duration, water pattern) and hydric needs of the crops should be defined in order to establish a sustainable management strategy.

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