English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

. Soil erosion is a major problem around the world because of its effects onsoil productivity, nutrient loss, siltation in water bodies, and degradationof water quality. By understanding the driving forces behind soil erosion, wecan more easily identify erosion-prone areas within a landscape to addressthe problem strategically. Soil erosion models have been used to assist inthis task. One of the most commonly used soil erosion models is the UniversalSoil Loss Equation (USLE) and its family of models: the Revised UniversalSoil Loss Equation (RUSLE), the Revised Universal Soil Loss Equationversion 2 (RUSLE2), and the Modified Universal Soil Loss Equation (MUSLE).This paper reviews the different sub-factors of USLE and RUSLE, and analyseshow different studies around the world have adapted the equations to localconditions. We compiled these studies and equations to serve as a referencefor other researchers working with (R)USLE and related approaches. Within each sub-factor section, thestrengths and limitations of the different equations are discussed, andguidance is given as to which equations may be most appropriate forparticular climate types, spatial resolution, and temporal scale. Weinvestigate some of the limitations of existing (R)USLE formulations, such asuncertainty issues given the simple empirical nature of the model and many ofits sub-components; uncertainty issues around data availability; and itsinability to account for soil loss from gully erosion, mass wasting events,or predicting potential sediment yields to streams. Recommendations on how toovercome some of the uncertainties associated with the model are given.Several key future directions to refine it are outlined: e.g. incorporatingsoil loss from other types of soil erosion, estimating soil loss atsub-annual temporal scales, and compiling consistent units for the futureliterature to reduce confusion and errors caused by mismatching units. Thepotential of combining (R)USLE with the Compound Topographic Index (CTI) andsediment delivery ratio (SDR) to account for gully erosion and sediment yieldto streams respectively is discussed. Overall, the aim of this paper is toreview the (R)USLE and its sub-factors, and to elucidate the caveats,limitations, and recommendations for future applications of these soilerosion models. We hope these recommendations will help researchers morerobustly apply (R)USLE in a range of geoclimatic regions with varying dataavailability, and modelling different land cover scenarios at finer spatialand temporal scales (e.g. at the field scale with different croppingoptions).

A review of the (Revised) Universal Soil Loss Equation ((R)USLE): with a view to increasing its global applicability and improving soil loss estimates