During past decades a marked manifestation of widespread erosion phenomena was studied worldwide. Global conservation community has launched campaigns at local, regional and continental level in developing countries for preservation of soil resources in order not only to stop or mitigate human impact on nature but also to improve life in rural areas introducing new approaches for soil cultivation. After the adoption of Sustainable Development Goals of UNs and launching several world initiatives such as the Land Degradation Neutrality (LDN) the world came to realize the very importance of the soil resources on which the biosphere relies for its existence. The main goal of the chapter is to review different types and structures erosion models as well as their applications. Several methods using spatial analysis capabilities of geographic information systems (GIS) are in operation for soil erosion risk assessment, such as Universal Soil Loss Equation (USLE), Revised Universal Soil Loss Equation (RUSLE) in operation worldwide and in the USA and MESALES model. These and more models are being discussed in the present work alongside more experimental models and methods for assessing soil erosion risk such as Artificial Intelligence (AI), Machine and Deep Learning, etc. At the end of this work, a prospectus for the future development of soil erosion risk assessment is drawn.

过去几十年来，普遍的侵蚀现象引起了广泛的研究关注。在发展中国家，全球保护社区在地方、区域和大陆层面上发起了运动，以保护土壤资源，不仅要阻止或减轻人类对自然的影响，还要引入新的土壤栽培方法，改善农村地区的生活。本章的主要目标是综述不同类型和结构的侵蚀模型及其应用，同时讨论全球范围内和美国实施的一些利用地理信息系统的空间分析能力进行土壤侵蚀风险评估的方法，如通用土壤流失方程（USLE）、修订版通用土壤流失方程（RUSLE）和MESALES模型。此外，还介绍了更多实验模型和评估土壤侵蚀风险的方法，如人工智能、机器学习和深度学习等。最后，对未来土壤侵蚀风险评估的发展进行了展望。

运用地理信息科学与遥感评估土壤侵蚀风险--评述