Soil Loss Assessment Using the Revised Universal Soil Loss Equation (RUSLE) Model

Abstract

Many catchment areas have suffered from exhaustive changes because of various land use activities over the recent past. These land use changes are associated with intensified environmental degradation witnessed in catchment areas. Such environmental problems include extreme soil erosion. Soil erosion is one of the most critical problems responsible for the degradation of land worldwide. This phenomenon occurs as a result of the complex interactions that exist between natural and human-induced factors. Most factors experience spatiotemporal variations, hence complicating the soil erosion phenomenon. This complexity in the erosion process makes it difficult to quantify soil loss. Without proper information on soil loss, it becomes quite hard for decision-makers and managers to manage catchment areas. However, the availability of soil erosion models has made it easy to estimate soil loss. Many models have been developed to consider these complexities in soil erosion studies. Empirical models such as RUSLE provide a simple and broad methodology through which soil erosion is assessed. The RUSLE model integrates well geographic information system (GIS) and above all remote sensing. This paper presents an overview of the developmental milestones in estimating soil loss using the RUSLE model. The parameterization of the RUSLE model has been adequately reviewed with much emphasis on challenges and successes in derivation of each individual factor. From the review, it was established that different equations have been developed by researchers for modeling the five factors for the RUSLE model. The development of such equations was found to take into account the different variations that depict the soil erosion process.

Review of Soil Loss Estimation in Ethiopia: Evaluating the Use of the RUSLE Model integrated with GIS and Remote Techniques

“…Examples of physically based models include the SWAT (Soil and Water Assessment Tool), KINEROS (Kinematic Runoff and Erosion Model), WEEP (Watershed Erosion Prediction Project) (Luvai et al, 2022;Regasa et al, 2021).…”

“…Despite being primarily developed using the spatial data collected in the United States, this model, along with its revised and modi ed versions, has gained widespread global application. Numerous subsequent models have been developed based on the foundation provided by the USLE model (Luvai et al, 2022;Regasa et al, 2021).…”

GEE based soil loss estimation in Eastern Tigray Zones, Ethiopia

“…(Moges and Bhat 2017). The selection on a suitable model is highly dependent on the aim of the study, catchment properties, data availability, model accuracy and simplicity (Luvai, Obiero, and Omuto 2022).For instance, RUSLE, is a commonly applied empirical soil erosion model designed for areas with hilly topography. Empirical models such as RUSLE are easy to use models, which can even be applied in case of limited input data (P. U.…”

Geoinformatics of soil loss using GEE in Tigray regional state of Ethiopia.

“…all with a common goal of sediment or soil loss estimation but mostly differ on the input parameters, whether an empirical, conceptual or physical based models are used for simulating the model, process and complexity of the model etc (Moges and Bhat 2017). The selection on a suitable model is highly dependent on the aim of the study, catchment properties, data availability, model accuracy and simplicity (Luvai, Obiero, and Omuto 2022).For instance, RUSLE, is a commonly applied empirical soil erosion model designed for areas with hilly topography.Empriclal models such as RUSLE are an easy to use models which can even be applied in case of limited input data(P. U. et al 2017).…”

“…Some of the papers that combined GIS and one of the RUSLE erosion models (Ahmed Harb Rabia 2012; Bagegnehu et al 2019;Borrelli et al 2021;K. et al 2020;Luvai et al 2022;Moges and Bhat 2017).…”