*3.5.4 Magnetic tracer method*

The application of magnetic tracers has two aspects: (i) to trace sediment sources using magnetic minerals in the environment, (ii) to indicate environmental change in basins. Hence Li *et al.* [34] synthesized that the magnetic tracer method can reflect the history of land use pattern, vegetation succession, and soil erosion in a watershed. It can also identify the soil distribution and the erosion rate for certain period. Therefore, this method can be used to provide a theoretical basis for soil erosion prediction and monitoring, and a history of the development of small watersheds. The advantages of this method are the transportability of the equipment, the methods simplicity; meeting the need of large samples and nondestructive nature. The method is however constrained by inability to trace magnetic properties and depth of soil erosion or deposition. Presently, magnetic tracers have been used to study soil formation, classification of soils, and the quantitative description of evolution, occurrence, and development of erosion.

## **3.6 Soil erosion models**

Soil erosion models are quantitative approaches in study of soil erosion. Based on literature searches, the application of models in Southeastern Nigeria is still minimal. Models can be classified into three groups viz. Empirical, Physically-based and Conceptual (partly empirical/mixed) [41].

#### *3.6.1 Empirical statistical model*

Empirical models are based primarily on observation and inductive logic from the environment. Empirical models such as the Universal Soil Loss Equation (USLE), Revised Universal Soil Loss Equation (RUSLE), the Unit Stream Power Based Erosion/Deposition model (USPED), Erosion Productivity Impact Calculator (EPIC). Empirical models are mainly based on the USLE and remain widely used till date even in regions with limited data. Li *et al.* [34] documented the advantage and disadvantage of these models to include: (1) the formula is concise and the meaning of each factor is clear. (2) The calculation method of the factor has been basically mature and the parameters are easy to obtain for the continuous improvement and perfection of the model. (3) After several years of verification and testing, the accuracy of the model meets the needs of the application. In the tropics, the incompetence of the USLE in its rainfall erosivity component has been overcome by the incorporation of rainfall erosivity values in the RUSLE [27]. Applying the equation in the Anambra area, they observed that about 1804.39 km<sup>2</sup> (39.49%) of the area had slight erosion rate of 0–10 t/ha/yr., while rates of erosion in 746.60 km2 (16.34%), 1025.38 km2 (6.28%) and 45.59 km<sup>2</sup> (1.02%) of the area are 10.6–85.3, 85.4–235.2, 235.3–608, 608.1–2200 and > 2200.1 t/ha/yr. respectively. They noted that high rainfall erosivity, moderate to high slope and decreasing vegetal cover were the major factors driving soil loss in the area. In an earlier study, Igwe *et al.* [24] compared the USLE and the Soil Loss Estimation Model for South Africa (SLESMA) in producing soil erosion working maps in Anambra and Enugu States, South-East Nigeria. They found out that the USLE model reflected better the actual field situations except for its high values, absolute values compared to the global scale. The values were categorized into very slight (<50 Mg/ha/yr); slight (50–150 Mg/ha/yr); moderate (151–500 Mg/ha/yr); severe (501–1500 Mg/ ha/yr) and very severe (>1500 Mg/ha/yr). A similar high value of above 200 t/ ha/yr. was reported in Uyo metropolis, Nigeria by Fashae *et al.* [42] who observed that the values corresponded with areas with active gullies and altered vegetation cover. Obinna *et al.* [43] applied RUSLE model on the entire Southeastern Nigeria and observed that the results corresponded with known areas of gully menace in the region. Most of the erosion hotspots were located around the north-eastern part of the region covering most parts of Ebonyi State, some parts of Enugu State (Northwest axis), Anambra State (South East and Central axis), and most parts of Abia State. It could, therefore, be concluded that the high number of active gully occurrence may translate into the likelihood of other forms of erosion in the tropics.

#### *3.6.2 Physical process model*

The physical process model is based on the study of the processes and mechanisms of soil erosion e.g. stream flow or sediment transport. Examples of physical models include Water Erosion Prediction Project (WEPP), European Soil Erosion Model (EUROSEM). The WEPP model can simulate soil erosion, non-regular steep slope, and soil, tillage, and management measures by calculating the temporal and

#### *Erosion Quantification and Management: Southeastern Nigeria Case Study DOI: http://dx.doi.org/10.5772/intechopen.99551*

spatial distribution of soil erosion and predicting the movement of sediment in the slope and basin [34]. The WEPP model reflects the applicability and ductility of the temporal and spatial distribution of erosion and sediment; thus, numerous scholars still use this method. Although the physical model greatly compensates for the defects of the empirical model, this approach also has some shortcomings. (1) The physical mechanism of soil erosion is relatively complex and unclear. Some parameters in the physical process model are still dependent on the empirical model. (2) The large range of the study area is the major obstacle that hinders the use of the model because of the exacting demand of the model parameters. (3) The structure of the physical process model is complex and may change because the form has not been unified.
