Assessing the applicability of the Revised Universal Soil Loss Equation (RUSLE) to Irish Catchments

Abstract

Elevated suspended sediment concentrations in fluvial environments have important implications for system ecology and even small concentrations may have serious consequences for sensitive ecosystems or organisms, such as freshwater pearl mussels (Margaritifera margaritifera). Informed decision making is therefore required for land managers to understand and control soil erosion and sediment delivery to the river network. However, given that monitoring of sediment fluxes requires financial and human resources which are often limited at a national scale, sediment mobilisation and delivery models are commonly used for sediment yield estimation and management. The Revised Universal Soil Loss Equation (RUSLE) is the most widely used model for overland flow erosion and can, when combined with a sediment delivery ratio (SDR), provide reasonable sediment load estimations for a catchment. This paper presents RUSLE factors established from extant GIS and rainfall datasets that are incorporated into a flexible catchment modelling approach. We believe that this is the first time that results from a RUSLE application at a national scale are tested against measured sediment yield values available from Ireland. An initial assessment of RUSLE applied to Irish conditions indicates an overestimation of modelled sediment yield values for most of the selected catchments. Improved methods for model and SDR factors estimation are needed to account for Irish conditions and catchment characteristics. Nonetheless, validation and testing of the model in this study using observed values is an important step towards more effective sediment yield modelling tools for nationwide applications.

Comparing different multiple flow algorithms to calculate RUSLE factors of slope length (L) and slope steepness (S) in Switzerland

“…On the other hand, a very high-resolution DEM can lead to very high LS-factor values and therefore to an overestimation of soil erosion risk by RUSLE. Many studies show an overestimation of the risk of erosion based on the RUSLE approach compared to measured soil erosion (Abu Hammad et al 2004, Rymszewicz et al 2015. Some researchers have tried to understand the resolution effect of the digital elevation models (DEM) on the RUSLE topographic LS-factor, but most of them use a DEM resolution of 10 m or coarser: e.g.…”

Untitled

“…For example, sediment sources and slope erosion rates have been estimated as a first approximation using simple empirical tools such as the RUSLE (Revised Universal Soil Loss Equation) (Rymszewicz et al, 2014). River bank erosion upstream can also be a key source of fine sediment entering river systems (e.g.…”

Water Resource Risk Assessment Based on Non-Point Source Pollution

“…This equation is widely used mainly because it can be multiplied using a series of simplified variables to determine soil loss in a given area [43]; however, the usefulness of the USLE is affected by survey data, which cannot be effectively combined with soil loss data, and its applications are limited to a certain extent [44]. Conversely, the modified universal soil loss equation improves the process of expanding field data and combining soil erosion data to allow a wider range of applications [45,46].…”