Erosion Model Validation Research Articles

Performance evaluation of a water erosion tracer using plot-scale experiments and process-based modeling

Socioeconomic and environmental losses caused by water erosion have highlighted the importance of quantifying and understanding the dynamics of soil redistribution in the landscape to develop effective soil management practices. Several methods are applied to estimate erosion/deposition rates and identify sources of sediments, among them, the one that uses rare earth elements (REE) as a tracer stands out. However, an alternative not yet explored that can benefit the accuracy of the estimates provided by the method is using a tracer containing a chemical signature composed of more than one REE. The present study aimed to evaluate the performance of a new water erosion tracer based on montmorillonite labeled with rare earth elements (La40-MMT). The innovative aspects of this La40-MMT tracer include its highly stable multi-chemical signature (Nd3+, La3+, and Pr3+), which enhances tracer detection in the environment, and its low production cost due to the use of an industrial residue in the synthesis process. The tracer was evaluated for a typical soil of the Cerrado biome, using a natural rainfall field-scale plot - NRFP (5 m × 20 m) and a physical predictive erosion model (WEPP). The results showed that the La40-MMT tracer could be used to estimate erosion/deposition rates, with agreement between the values observed with the tracer and the WEPP model. Thus, this study confirmed the great potential of La40-MMT as a tool to identify patterns of soil redistribution at the field scale and aid in the validation of erosion models.

Mapping rill soil erosion in agricultural fields with UAV‐borne remote sensing data

AbstractSoil erosion by water is a main form of land degradation worldwide. The problem has been addressed, among others, in the United Nations Sustainability Goals. However, for mitigation of erosion consequences and adequate management of affected areas, reliable information on the magnitude and spatial patterns of erosion is needed. Although such need is often addressed by erosion modelling, precise erosion monitoring is necessary for the calibration and validation of erosion models and to study erosion patterns in landscapes. Conventional methods for quantification of rill erosion are based on labour‐intensive field measurements. In contrast, remote sensing techniques promise fast, non‐invasive, systematic and larger‐scale surveying. Thus, the main objective of this study was to develop and evaluate automated and transferable methodologies for mapping the spatial extent of erosion rills from a single acquisition of remote sensing data. Data collected by an uncrewed aerial vehicle was used to deliver a highly detailed digital elevation model (DEM) of the analysed area. Rills were classified by two methods with different settings. One approach was based on a series of decision rules applied on DEM‐derived geomorphological terrain attributes. The second approach utilized the random forest machine learning algorithm. The methods were tested on three agricultural fields representing different erosion patterns and vegetation covers. Our study showed that the proposed methods can ensure recognition of rills with accuracies between 80 and 90% depending on rill characteristics. In some cases, however, the methods were sensitive to very small rill incisions and to similar geometry of rills to other features. Additionally, their performance was influenced by the vegetation structure and cover. Besides these challenges, the introduced approach was capable of mapping rills fully automatically at the field scale and can, therefore, support a fast and flexible assessment of erosion magnitudes.

Sediment Production From Forest Roads in Western Montana1

Abstract: Unpaved roads are a primary sediment source in forested watersheds. Validation of erosion models and improvements to road management require information on road erosion rates and the factors controlling erosion. This study measured sediment yields from twenty ∼0.05 ha unsurfaced (native) road plots in Belt Supergroup and glacial till parent materials of western Montana, and investigated the factors controlling erosion. Annual sediment yields for individual plots ranged from 0 to 96.9 Mg/ha/yr over 3 years (2002‐2004). Annual mean sediment yield ranged from 2.1 Mg/ha in 2003 to 9.9 Mg/ha in 2004 with an overall mean of 5.4 Mg/ha/yr. The mean of log‐transformed sediment yields for sites in glacial till parent materials was higher than Belt Supergroup parent materials (p = 0.063). A regression model with road slope, time since last grading, roadbed gravel content, and precipitation as predictive variables explained 68% of the variability in sediment yield (F = 28.2; p < 0.0001). Road erosion in western Montana is limited by low erodibility of the dominant parent materials and low rainfall. Management procedures such as reducing the frequency of grading can significantly reduce sediment yields from forest roads.