Abstract. Climate change, accompanied by intensified extreme weather events, results in changes in intensity, frequency and magnitude of soil erosion. These unclear future developments make adaption and improvement of soil erosion modelling approaches all the more important. Hypothesizing that models cannot keep up with the data, this review gives an overview of 44 process based soil erosion models, their strengths and weaknesses and discusses their potential for further development with respect to new and improved soil and soil erosion assessment techniques. We found valuable tools in areas, as remote sensing, tracing or machine learning, to gain temporal and spatial distributed high resolution parameterization and process descriptions which could lead to a more holistic modelling approach. Most process based models are so far not capable to implement cross-scale erosional processes or profit from the available resolution on a temporal and spatial scale. We conclude that models need further development regarding their process understanding, adaptability in respect to scale as well as their parameterization and calibration. The challenge is the development of models which are able to simulate soil erosion processes as close to reality as possible, as user-friendly as possible and as complex as it needs to be.

中文翻译：

---

模型能跟上数据吗？在基于过程的土壤侵蚀模型背景下土壤和土壤表面评估技术的可能性——综述

摘要。气候变化伴随着加剧的极端天气事件，导致土壤侵蚀的强度、频率和幅度发生变化。这些不明确的未来发展使得土壤侵蚀建模方法的适应和改进变得更加重要。假设模型跟不上数据，这篇综述概述了 44 个基于过程的土壤侵蚀模型及其优缺点，并讨论了它们在新的和改进的土壤和土壤侵蚀评估技术方面进一步发展的潜力。我们在遥感、追踪或机器学习等领域找到了有价值的工具，以获得时空分布式高分辨率参数化和过程描述，这可能会导致更全面的建模方法。迄今为止，大多数基于过程的模型无法实现跨尺度侵蚀过程或从时间和空间尺度上的可用分辨率中获益。我们得出的结论是，模型需要在过程理解、规模适应性以及参数化和校准方面进一步发展。挑战在于开发能够模拟土壤侵蚀过程的模型，尽可能接近现实，尽可能方便用户，并尽可能复杂。