Abstract:

The study of Source-to-Sink systems is an important field of research focused on understanding the entire process of material transport from source areas like mountain ranges or other landforms to sink areas like river basins, lakes, and oceans. This process entails weathering of the parent rock, erosion of materials, transportation via various agents (such as wind, water, or ice), and eventual deposition at sink locations. Analyzing this system reveals dynamic surface changes, material cycling mechanisms, and how these processes adapt to environmental shifts over time. Understanding these complex processes is crucial for a variety of scientific fields, including geomorphology, environmental science, and natural resource management; however, the traditional methods such as field observations and laboratory analyses, Have their own set of challenges. Data availability, low spatiotemporal resolution, and ambiguity in interpretation make it difficult to capture the rapid and dynamic changes occurring in natural systems. Furthermore, these methods are not ideally suited for analyzing long-term evolutionary processes or large-scale systems. Consequently, numerical modeling has emerged as an essential tool studying source-to-sink systems, addressing these traditional limitations by simulating complex processes over varying spatial and temporal scales. They offer more quantitative insights into the dynamics of erosion, transport, and deposition under different environmental conditions.This paper reviews five key numerical tools commonly used in source-to-sink research: Dionisos, SEDSIM, Landlab, goSPL, and Delft3D. Each tool has specific advantages that render it suitable for various research purposes. Dionisos, for instance, excels at modeling large-scale, long-term basin-filling processes though it is less effective for simulating small-scale, dynamic changes. SEDSIM, based on hydrodynamic equations, produces highly accurate results for clastic sedimentary processes, but tends to be slower and more focused on specific types of sediment. LandLab is highly customizable and capable of multi-process simulations; although, it requires advanced programming skills. goSPL handles global-scale high-resolution simulations effectively, despite struggling with localized phenomena and requiring significant computational resources. Delft3D is ideal for small-scale, fine-detail simulations, particularly in coastal, riverine, and lacustrine environments, although it faces challenges in large-scale applications. With ongoing advances in computational power and algorithms, future advancements in source-to-sink modeling are expected. The integration of big data and AI will likely enhance the accuracy of predictions, facilitate multidisciplinary integration, and drive the intelligent evolution of the field.

Key words: Sediment Source-to-Sink system, Numerical simulation, Numerical model

摘要：

沉积源—汇系统研究通过分析物质从源到汇的全过程，旨在揭示地表动态变化、物质循环机制及其对环境变化的响应，有助于我们全面了解沉积物从母岩风化、剥蚀、搬运至最终沉积的复杂过程。传统的源—汇研究多依赖于野外地质观测和实验室分析，这些方法受限于数据的可获取性较差、时空分辨率低和多解性，难以捕捉过程的动态变化和长期、大尺度的系统演化。随着计算机软硬件的飞速发展，数值模拟已成为源—汇研究的重要工具。数值模拟能够弥补传统方法的不足，定量分析沉积物在不同环境条件下的侵蚀、搬运和沉积过程，从而提供更全面、更动态的沉积源—汇系统演化视图。重点介绍5种主流的沉积源—汇系统数值模拟工具：Dionisos、SEDSIM、Landlab、goSPL和Delft3D。这些工具各具特点，适用于不同的研究场景。Dionisos擅长模拟大尺度、长时间跨度的沉积盆地充填过程，但结果趋于平均化，不擅长小尺度的动态变化模拟；SEDSIM基于水动力方程精准模拟沉积过程，结果更符合实际情况，但模拟速度较慢，更多集中于碎屑岩沉积模拟；Landlab提供高度自定义和多过程耦合的模拟能力，适合多种研究需求，但需要用户有较强的编程能力；goSPL能够进行全球尺度的高分辨率源—汇过程模拟，但处理局部地质现象时存在局限，同时对计算资源要求较高；而Delft3D在小尺度精细模拟方面表现优越，广泛应用于海岸、河流和湖泊环境模拟，但对于大尺度模拟存在一定的局限性。未来，随着算力的进一步增强和算法模型的优化，预计将出现更多高精度、多过程耦合的模拟工具。同时，大数据和人工智能技术在源—汇研究中的应用将成为重要趋势，也将更好地助力源—汇模拟，推动该领域的多学科融合和智能化发展。

关键词: 沉积源—汇系统, 数值模拟, 数值模型