Abstract The coupled relationship between soil erosion and soil organic matter (OM) dynamics has sparked considerable interest in scientific communities in recent decades. However, the question of whether soil erosion acts as a net source or sink for atmospheric carbon dioxide is still a pending issue, possibly due to the uncertainties regarding the fluxes and fates of laterally transported OM in eroding landscapes. Quantifying the OM sources of redistributed sediments on the earth’s surface provides new insight for understanding this issue. In this review, we offer a comprehensive cross-disciplinary review of three approaches to modeling (i.e., end-member mixing models, Bayesian isotope mixing models, and parallel factor analysis (PARAFAC) models) that are widely used to accurately quantify the sources of redistributed OM in its bulk and soluble phases. Furthermore, we present the current knowledge of the benefits and shortcomings of each model and identify key challenges for determining their feasibility. We find that Bayesian isotope mixing models, especially the stable isotope analysis in the R model, better incorporate the uncertainty and variation of tracers compared with end-member mixing models, demonstrating a greater capability for quantifying various bulk OM sources. Excitation-emission matrix spectroscopy (EEMs) - PARAFAC models can identify changes in the fluorescence of dissolved OM to enable tracing of individual fluorescent fractions, thereby usefully supplementing and enhancing bulk OM source apportionment. Finally, future perspectives are proposed to further our understanding of model performance for quantifying the fluxes and fates of redistributed OM across a range of conditions.

中文翻译：

---

侵蚀景观中沉积物通量的有机物质来源建模：回顾、关键挑战和新视角

摘要 近几十年来，土壤侵蚀与土壤有机质 (OM) 动态之间的耦合关系引起了科学界的极大兴趣。然而，土壤侵蚀是大气二氧化碳的净源还是净汇的问题仍然是一个悬而未决的问题，这可能是由于侵蚀景观中横向迁移 OM 的通量和命运的不确定性。量化地球表面重新分布沉积物的 OM 来源为理解这个问题提供了新的见解。在这篇综述中，我们对三种建模方法（即端元混合模型、贝叶斯同位素混合模型、和平行因子分析 (PARAFAC) 模型），这些模型被广泛用于准确量化其本体和可溶相中重新分布的 OM 的来源。此外，我们介绍了每个模型的优点和缺点的当前知识，并确定了确定其可行性的关键挑战。我们发现，与端元混合模型相比，贝叶斯同位素混合模型，尤其是 R 模型中的稳定同位素分析，更好地结合了示踪剂的不确定性和变化，证明了量化各种大容量 OM 源的能力更强。激发发射矩阵光谱 (EEM) - PARAFAC 模型可以识别溶解的 OM 的荧光变化，从而能够追踪单个荧光部分，从而有效地补充和增强大量 OM 源分配。最后，