**1. Introduction**

A serious issue is soil erosion, which averages 30–40 t/ha per year in South America, Africa, and Asia, and in the South Asia region is thought to be severe [1]. The agroecological efficacy in semiarid and arid regions is facing a significant impact from climate change, primarily due to an increased rate of land degradation [2, 3]. Due to the undulating to steep terrain and heavy rainfall, particularly in the first few years after establishment, soil erosion is typically higher in plantation farms. In order to maintain the productivity and fertility of the estates, appropriate soil conservation measures must be taken in order to reduce this soil erosion to a higher level. These measures included reducing soil erosion, strengthening the soil's structure to make it more resilient to detachment and transportation and more permeable to surface water, shielding the surface from the effects of rainfall, reducing runoff, and

providing secure disposal options for excess runoff. Some of the features that have been seen include drainage systems, embankments, fences, cover crops, and stone terracing [4]. Despite the fact that soil is regarded as a mass containing nutrients, topsoil with nutrients has been drained in those fields over time, owing primarily to soil erosion. As a result, reliable and timely soil erosion monitoring in agricultural and plantation regions is crucial for developing soil preservation strategies and improving agricultural practices [5]. Numerous nations in the twentieth century experienced increased land loss as a result to raise human-induced soil erosion [6]. The most fertile topsoil can be lost due to erosion, which lowers soil productivity. Investigating soil loss mechanisms and determining the risk of soil erosion are crucial for planning future management of soils, preservation, and land-use activities [7–9].

Soil erosion can be evaluated using traditional field-based techniques and soil erosion modeling [10]. Agricultural computerization has increased along with the accessibility of finer-scale global-level data, which has improved the potency of modeling techniques associated with agriculture and the environment [11]. Fieldbased approaches to measuring soil erosion are labor-intensive, time-consuming, limited in flexibility, and incomparable, whereas soil erosion modeling has numerous benefits over these approaches [12, 13]. Several methods for modeling soil erosion have been established in recent years with varying needs for input and complexity [5]. Applications, specifications, intended uses, and the type of data each model provides vary significantly [14]. Soil erosion modeling, which is employed in place of traditional methodologies, is the most practical and trustworthy instrument for evaluating soil erosion and enabling the appropriate selection of soil erosion management strategies [12]. One of the primary reasons for the widespread use of soil erosion modeling around the world is unquestionably its high degree of adaptability and data accessibility, as well as its sparse parameterization, broad research, and comparability of results, which allow the model to be applied to almost any situation or geographical area [13]. The Universal Soil Loss Equation (USLE) and its associated models, which are widely employed to address soil erosion, are among the most extensively used designs. These soil erosion algorithms have been applied in a variety of contexts worldwide, making them well-known [15]. In this chapter of the book, soil erosion, risk modeling, and management using the model are discussed.
