Abstract. Soil erosion is a major problem around the world because of its effects on
soil productivity, nutrient loss, siltation in water bodies, and degradation
of water quality. By understanding the driving forces behind soil erosion, we
can more easily identify erosion-prone areas within a landscape to address
the problem strategically. Soil erosion models have been used to assist in
this task. One of the most commonly used soil erosion models is the Universal
Soil Loss Equation (USLE) and its family of models: the Revised Universal
Soil Loss Equation (RUSLE), the Revised Universal Soil Loss Equation
version 2 (RUSLE2), and the Modified Universal Soil Loss Equation (MUSLE).
This paper reviews the different sub-factors of USLE and RUSLE, and analyses
how different studies around the world have adapted the equations to local
conditions. We compiled these studies and equations to serve as a reference
for other researchers working with (R)USLE and related approaches. Within each sub-factor section, the
strengths and limitations of the different equations are discussed, and
guidance is given as to which equations may be most appropriate for
particular climate types, spatial resolution, and temporal scale. We
investigate some of the limitations of existing (R)USLE formulations, such as
uncertainty issues given the simple empirical nature of the model and many of
its sub-components; uncertainty issues around data availability; and its
inability to account for soil loss from gully erosion, mass wasting events,
or predicting potential sediment yields to streams. Recommendations on how to
overcome some of the uncertainties associated with the model are given.
Several key future directions to refine it are outlined: e.g. incorporating
soil loss from other types of soil erosion, estimating soil loss at
sub-annual temporal scales, and compiling consistent units for the future
literature to reduce confusion and errors caused by mismatching units. The
potential of combining (R)USLE with the Compound Topographic Index (CTI) and
sediment delivery ratio (SDR) to account for gully erosion and sediment yield
to streams respectively is discussed. Overall, the aim of this paper is to
review the (R)USLE and its sub-factors, and to elucidate the caveats,
limitations, and recommendations for future applications of these soil
erosion models. We hope these recommendations will help researchers more
robustly apply (R)USLE in a range of geoclimatic regions with varying data
availability, and modelling different land cover scenarios at finer spatial
and temporal scales (e.g. at the field scale with different cropping
options).
Assessing spatial distribution of soil erosion in a karst region in southwestern China: A case study in Jinfo Mountains
