[en] Purpose: Identification of hotspots of accelerated erosion of soil and organic carbon (OC) is critical to the targeting of soil conservation and sediment management measures. The erosion risk map (ERM) developed by Lilly and Baggaley (Soil erosion risk map of Scotland, 2018) for Scotland estimates erosion risk for the specific soil conditions in the region. However, the ERM provides no soil erosion rates. Erosion rates can be estimated by empirical models such as the Revised Universal Soil Loss Equation (RUSLE). Yet, RUSLE was not developed specifically for the soil conditions in Scotland. Therefore, we evaluated the performance of these two erosion models to determine whether RUSLE erosion rate estimates could be used to quantify the amount of soil eroded from high-risk areas identified in the ERM. Methods: The study was conducted in the catchment of Loch Davan, Aberdeenshire, Scotland. Organic carbon loss models were constructed to compare land use specific OC yields based on RUSLE and ERM using OC fingerprinting as a benchmark. The estimated soil erosion rates in this study were also compared with recently published estimates in Scotland (Rickson et al. in Developing a method to estimate the costs of soil erosion in high-risk Scottish catchments, 2019). Results: The region-specific ERM most closely approximated the relative land use OC yields in streambed sediment however, the results of RUSLE were very similar, suggesting that, in this catchment, RUSLE erosion rate estimates could be used to quantify the amount of soil eroded from the high-risk areas identified by ERM. The RUSLE estimates of soil erosion for this catchment were comparable to the soil erosion rates per land use estimated by Rickson et al. (Developing a method to estimate the costs of soil erosion in high-risk Scottish catchments, 2019) in Scottish soils except in the case of pasture/grassland likely due to the pastures in this catchment being grass ley where periods of surface vegetation cover/root network absence are likely to have generated higher rates of erosion. Conclusion: Selection of suitable erosion risk models can be improved by the combined use of two sediment origin techniques—erosion risk modelling and OC sediment fingerprinting. These methods could, ultimately, support the development of targeted sediment management strategies to maintain healthy soils within the EU and beyond.
This work was supported by the Natural Environment Research Council and the Biotechnology and Biological Sciences Research Council (Grant number NE/ M009106/1) through a studentship award to CW by STARS (Soils Training And Research Studentships) Centre for Doctoral Training and Research Programme. The authors thank the CASE funder for this work Scottish Environment Protection Agency (SEPA). We thank Nikki Baggaley from The James Hutton Institute, Aberdeen, UK for providing access to the soil erosion risk maps. We also thank the reviewers whose comments helped focus and strengthen the manuscript.
S. Addy S. Ghimire S. Cooksley Assessment of the multiple benefits of river restoration: the Logie Burn meander reconnection project BHS Eleventh National Symposium, Hydrology for a Changing World, Dundee 2012 2012 01 05 10.7558/bhs.2012.ns01
C. Alewell A. Birkholz K. Meusburger et al. Quantitative sediment source attribution with compound-specific isotope analysis in a C3 plant-dominated catchment (central Switzerland) Biogeosci 2016 13 1587 1596 1:CAS:528:DC%2BC1cXnvVCqsb0%3D 10.5194/bg-13-1587-2016
C. Alewell P. Borrelli K. Meusburger P. Panagos Using the USLE: Chances, challenges and limitations of soil erosion modelling Int Soil Water Conserv Res 2019 7 203 225 10.1016/j.iswcr.2019.05.004
G. Angst S. John C.W. Mueller et al. Tracing the sources and spatial distribution of organic carbon in subsoils using a multi-biomarker approach Sci Rep 2016 6 1 12 1:CAS:528:DC%2BC28XhtFGmu7vE 10.1038/srep29478
N. Baggaley A. Lilly K. Blackstock et al. Soil risk maps – Interpreting soils data for policy makers, agencies and industry Soil Use Manag 2020 36 19 26 10.1111/sum.12541
P.V.G. Batista J. Davies M.L.N. Silva J.N. Quinton On the evaluation of soil erosion models: Are we doing enough? Earth Sci Rev 2019 197 10.1016/j.earscirev.2019.102898
M.Z. Bieroza R. Bol M. Glendell What is the deal with the Green Deal: Will the new strategy help to improve European freshwater quality beyond the Water Framework Directive? Sci Total Environ 2021 10.1016/j.scitotenv.2021.148080
W.H. Blake K.J. Ficken P. Taylor et al. Tracing crop-specific sediment sources in agricultural catchments Geomorphol 2012 139–140 322 329 10.1016/j.geomorph.2011.10.036
P. Borrelli M. Märker P. Panagos B. Schütt Modeling soil erosion and river sediment yield for an intermountain drainage basin of the Central Apennines, Italy CATENA 2014 114 45 58 10.1016/j.catena.2013.10.007
P. Borrelli K. Van Oost K. Meusburger et al. A step towards a holistic assessment of soil degradation in Europe: Coupling on-site erosion with sediment transfer and carbon fluxes Environ Res 2018 161 291 298 1:CAS:528:DC%2BC2sXhvVKhtb7I 10.1016/j.envres.2017.11.009
L. Borselli P. Cassi D. Torri Prolegomena to sediment and flow connectivity in the landscape: A GIS and field numerical assessment CATENA 2008 75 268 277 10.1016/j.catena.2008.07.006
Brenning A, Becker M, Bangs D (2018) RSAGA: SAGA Geoprocessing and Terrain Analysis. R package. https://cran.r-project.org/package=RSAGA
M. Cavalli S. Trevisani F. Comiti L. Marchi Geomorphometric assessment of spatial sediment connectivity in small Alpine catchments Geomorphol 2013 188 31 41 10.1016/j.geomorph.2012.05.007
F.X. Chen N.F. Fang Y.X. Wang et al. Biomarkers in sedimentary sequences: Indicators to track sediment sources over decadal timescales Geomorphol 2017 278 1 11 10.1016/j.geomorph.2016.10.027
Cloy JM, Lilly A, Hargreaves PR et al (2021) A state of knowledge overview of identified pathways of diffuse pollutants to the water environment. CRW2018_18. https://www.crew.ac.uk/publications
Cole B, King S, Ogutu B et al (2015) Corine land cover 2012 for the UK, Jersey and Guernsey. In: NERC Environmental Information Data Centre. https://doi.org/10.5285/32533dd6-7c1b-43e1-b892-e80d61a5ea1d. Accessed 18 Jan 2021
A.L. Collins M. Blackwell P. Boeckx et al. Sediment source fingerprinting: benchmarking recent outputs, remaining challenges and emerging themes J Soils Sediments 2020 20 1460 1493 10.1007/s11368-020-02755-4
R.J. Cooper N. Pedentchouk K.M. Hiscock et al. Apportioning sources of organic matter in streambed sediments: An integrated molecular and compound-specific stable isotope approach Sci Total Environ 2015 520 187 197 1:CAS:528:DC%2BC2MXkvVymtb8%3D 10.1016/j.scitotenv.2015.03.058
F. De Mastro C. Cocozza G. Brunetti A. Traversa Chemical and spectroscopic investigation of different soil fractions as affected by soil management Appl Sci 2020 10.3390/app10072571
P.J.J. Desmet G. Govers A GIS procedure for automatically calculating the USLE LS factor on topographically complex landscape units J Soil Water Conserv 1996 51 427 433
European Commission (2021) EU Soil Strategy for 2030: Reaping the benefits of healthy soils for people, food, nature and climate. 1–26. https://ec.europa.eu/environment/publications/eu-soil-strategy-2030_en
European Commission (2022a) A European Green Deal: Striving to be the first climate-neutral continent. https://ec.europa.eu/info/strategy/priorities-2019-2024/european-green-deal_en. Accessed 13 Mar 2022
European Commission (2022b) EU Soil Observatory (EUSO). https://joint-research-centre.ec.europa.eu/eu-soil-observatory-euso_en. Accessed 13 Mar 2022
ESDAC (2014) Soil Erodibility (K- Factor) High Resolution dataset for Europe. In: Joint Research Centre of the European Commission. https://esdac.jrc.ec.europa.eu/content/soil-erodibility-k-factor-high-resolution-dataset-europe. Accessed 7 Jun 2019
ESDAC (2015a) Estimating the soil erosion cover-management factor at European scale. In: Joint Research Centre of the European Commission. https://esdac.jrc.ec.europa.eu/content/cover-management-factor-c-factor-eu. Accessed 19 Mar 2012
ESDAC (2015b) Rainfall Erosivity in the EU and Switzerland (R-factor). In: European Commission, Joint Research Centre. https://esdac.jrc.ec.europa.eu/content/rainfall-erosivity-european-union-and-switzerland. Accessed 7 Jun 2019
ESRI (2017) ArcGIS Desktop. https://www.esri.com/
N. Estrada-Carmona E.B. Harper F. DeClerck A.K. Fremier Quantifying model uncertainty to improve watershed-level ecosystem service quantification: a global sensitivity analysis of the RUSLE Int J Biodivers Sci Ecosyst Serv Manag 2017 13 40 50 10.1080/21513732.2016.1237383
N. Fenton M. Neil Risk Assessment and Decision Analysis with Bayesian Networks 2018 Boca Raton, Florida USA CRC Press Taylor & Francis 10.1201/b21982
C.E. Galoski A.E. Jiménez Martínez G.B. Schultz et al. Use of n-alkanes to trace erosion and main sources of sediments in a watershed in southern Brazil Sci Total Environm 2019 682 447 456 1:CAS:528:DC%2BC1MXhtVejurfM 10.1016/j.scitotenv.2019.05.209
M. Glendell R. Jones J.A.J. Dungait et al. Tracing of particulate organic C sources across the terrestrial-aquatic continuum, a case study at the catchment scale (Carminowe Creek, southwest England) Sci Total Environ 2018 616 1077 1088 1:CAS:528:DC%2BC2sXhslaltLnP 10.1016/j.scitotenv.2017.10.211
M. Griepentrog S. Bodé P. Boeckx G.L.B. Wiesenberg The fate of plant wax lipids in a model forest ecosystem under elevated CO2 concentration and increased nitrogen deposition Org Geochem 2016 98 131 140 1:CAS:528:DC%2BC28XpsVGmtLo%3D 10.1016/j.orggeochem.2016.05.005
G.J. Hancock A.T. Revill Erosion source discrimination in a rural Australian catchment using compound-specific isotope analysis (CSIA) Hydrol Process 2013 27 923 932 1:CAS:528:DC%2BC3sXjsFKisbc%3D 10.1002/hyp.9466
Hijmans RJ (2020) Raster: Geographic Data Analysis and Modeling. R package. https://cran.r-project.org/package=raster.
P. Hirave M. Glendell A. Birkholz C. Alewell Compound-specific isotope analysis with nested sampling approach detects spatial and temporal variability in the sources of suspended sediments in a Scottish mesoscale catchment Sci Total Environ 2020 10.1016/j.scitotenv.2020.142916
J. Hooke J. Souza M. Marchamalo Evaluation of connectivity indices applied to a Mediterranean agricultural catchment CATENA 2021 207 10.1016/j.catena.2021.105713
Y. Jiang J. Gao L. Yang et al. The interactive effects of elevation, precipitation and lithology on karst rainfall and runoff erosivity CATENA 2021 207 10.1016/j.catena.2021.105588
H. Karambiri O. Ribolzi J.P. Delhoume et al. Importance of soil surface characteristics on water erosion in a small grazed Sahelian catchment Hydrol Process 2003 17 1495 1507 10.1002/hyp.1195
S.A. Kelsey A.G. Grottoli J.E. Bauer et al. Effects of agricultural and tillage practices on isotopic signatures and fluxes of organic and inorganic carbon in headwater streams Aquat Sci 2020 82 1 13 1:CAS:528:DC%2BB3cXltFygurY%3D 10.1007/s00027-019-0691-7
Lilly A, Baggaley N (2014) Developing simple indicators to assess the role of soils in determining risks to water quality, CREW project number CD2012_42. https://www.crew.ac.uk/publications
Lilly A, Baggaley NJ (2018) Soil erosion risk map of Scotland. https://soils.environment.gov.scot/maps/risk-maps/map-of-soil-erosion-risk-partial-cover/
C. Liu B.X. Hu Z. Li et al. Linking soils and streams: Chemical composition and sources of eroded organic matter during rainfall events in a Loess hilly-gully region of China J Hydrol 2021 600 1:CAS:528:DC%2BB3MXhtlaju77J 10.1016/j.jhydrol.2021.126518
C. Liu Z. Wu B.X. Hu Z. Li Linking recent changes in sediment yields and aggregate-associated organic matter sources from a typical catchment of the Loess Plateau China Agric Ecosyst Environ 2021 321 1:CAS:528:DC%2BB38XhvFCjsbc%3D 10.1016/j.agee.2021.107606
L. Mabit M. Gibbs M. Mbaye et al. Novel application of Compound Specific Stable Isotope (CSSI) techniques to investigate on-site sediment origins across arable fields Geoderma 2018 316 19 26 1:CAS:528:DC%2BC2sXitVaqurjM 10.1016/j.geoderma.2017.12.008
V.S. Marques M.B. Ceddia M.A.H. Antunes et al. USLE K-factor method selection for a tropical catchment Sustainability 2019 11 1 17 10.3390/su11071840
M.P. Martin M. Wattenbach P. Smith et al. Spatial distribution of soil organic carbon stocks in France Biogeosci 2011 8 1053 1065 1:CAS:528:DC%2BC3MXhtVKltLrF 10.5194/bg-8-1053-2011
S. Mayer A. Kühnel J. Burmeister et al. Controlling factors of organic carbon stocks in agricultural topsoils and subsoils of Bavaria Soil Tillage Res 2019 192 22 32 10.1016/j.still.2019.04.021
J. Meersmans F. De Ridder F. Canters et al. A multiple regression approach to assess the spatial distribution of Soil Organic Carbon (SOC) at the regional scale (Flanders, Belgium) Geoderma 2008 143 1 13 1:CAS:528:DC%2BD2sXhsVentrbL 10.1016/j.geoderma.2007.08.025
J. Meersmans M.P. Martin F. De Ridder et al. A novel soil organic C model using climate, soil type and management data at the national scale in France Agron Sustain Dev 2012 32 873 888 10.1007/s13593-012-0085-x
Met Office (2021) UK Climate Average. https://www.metoffice.gov.uk/research/climate/maps-and-data/uk-climate-averages/gfjuxqwcs. Accessed 18 Jan 2021
R. Mukundan D.E. Walling A.C. Gellis et al. Sediment source fingerprinting: transforming from a research tool to a management tool J Am Water Resour Assoc 2012 48 1241 1257 10.1111/j.1752-1688.2012.00685.x
Odhiambo BK, Rihl G, Hood-Recant S (2021) Historic land use and sedimentation in two urban reservoirs, Occoquan Reservoir and Lake Manassas, Virginia, USA. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-021-16461-2
Ordnance Survey (2021) OS Terrain 5 [ASC geospatial data], Scale 1:10000, Tiles: nj30ne,nj30nw,nj30se,nj30sw,nj31se,nj31sw,nj40ne,nj40nw,nj40se,nj40sw,nj41se,nj41sw,nj50ne,nj50nw,nj50se,nj50sw,nj51se,nj51sw,no39ne,no39nw,no49ne,no49nw,no59ne,no59nw,. In: EDINA Digimap Ordnance Survey Service. https://digimap.edina.ac.uk. Accessed 14 Dec 2018
P. Panagos K. Meusburger C. Ballabio et al. Soil erodibility in Europe: A high-resolution dataset based on LUCAS Sci Total Environ 2014 479–480 189 200 1:CAS:528:DC%2BC2cXjs1OjtLo%3D 10.1016/j.scitotenv.2014.02.010
P. Panagos C. Ballabio P. Borrelli et al. Rainfall erosivity in Europe Sci Total Environ 2015 511 801 814 1:CAS:528:DC%2BC2MXotVCisw%3D%3D 10.1016/j.scitotenv.2015.01.008
P. Panagos P. Borrelli K. Meusburger et al. Estimating the soil erosion cover-management factor at the European scale Land Use Policy 2015 48 38 50 10.1016/j.landusepol.2015.05.021
E.J. Pebesma Multivariable geostatistics in S: the gstat package Comput Geosci 2004 30 683 691 10.1016/j.cageo.2004.03.012
Pebesma EJ, Bivand RS (2005) Classes and methods for spatial data in R: The sp package. R News 5 (2). https://rdrr.io/cran/sp/f/inst/doc/intro_sp.pdf
K. Quenea S. Derenne C. Largeau et al. Variation in lipid relative abundance and composition among different particle size fractions of a forest soil Org Geochem 2004 35 1355 1370 1:CAS:528:DC%2BD2cXptV2ntLs%3D 10.1016/j.orggeochem.2004.03.010
K. Quénéa C. Largeau S. Derenne et al. Molecular and isotopic study of lipids in particle size fractions of a sandy cultivated soil (Cestas cultivation sequence, southwest France): Sources, degradation, and comparison with Cestas forest soil Org Geochem 2006 37 20 44 1:CAS:528:DC%2BD2MXhtlertLfK 10.1016/j.orggeochem.2005.08.021
R Core Team (2020) R: A language and environment for statistical computing. https://www.r-project.org/
Renard KG, Foster GR, Weesies GA et al (1997) Predicting soil erosion by water: A guide to conservation planning with the revised universal soil loss equation (RUSLE)., Agricultur. U.S. Dept. of Agriculture, Agricultural Research Service, Washington, D.C
Rickson RJ, Baggaley N, Deeks LK et al (2019) Developing a method to estimate the costs of soil erosion in high-risk Scottish catchments. Report to the Scottish Government. Available online from https://www.gov.scot/ISBN/978-1-83960-754-7
S. Schmidt C. Alewell K. Meusburger Mapping spatio-temporal dynamics of the cover and management factor (C-factor) for grasslands in Switzerland Remote Sens Environ 2018 211 89 104 10.1016/j.rse.2018.04.008
E. Sirjani M. Mahmoodabadi A. Cerdà Sediment transport mechanisms and selective removal of soil particles under unsteady-state conditions in a sheet erosion system Inter J Sediment Res 2022 37 151 161 10.1016/j.ijsrc.2021.09.006
Scottish Government (2009) The Scottish Soil Framework. http://www.gov.scot/Resource/Doc/273170/0081576.pdf
Stock BC, Semmens BX (2016) MixSIAR GUI User Manual. Version 3.1. https://github.com/brianstock/MixSIAR
Stock BC, Jackson AL, Ward EJ et al (2018) MixSIAR model description. 2018. https://peerj.com/articles/5096
The James Hutton Institute (2018) 1:25,000 Soil Map (partial cover). https://www.hutton.ac.uk/soil-maps/
B. Thornton Z. Zhang R.W. Mayes et al. Can gas chromatography combustion isotope ratio mass spectrometry be used to quantify organic compound abundance? Rapid Commun Mass Spectrom 2011 25 2433 2438 1:CAS:528:DC%2BC3MXhtFGgsbvL 10.1002/rcm.5148
D.E. Walling P.N. Owens G.J.L. Leeks Fingerprinting suspended sediment sources in the catchment of the River Ouse, Yorkshire, UK Hydrol Process 1999 13 955 975 10.1002/(SICI)1099-1085(199905)13:7<955::AID-HYP784>3.0.CO;2-G
M. Wiesmeier J. Prietzel F. Barthold et al. Storage and drivers of organic carbon in forest soils of southeast Germany (Bavaria) - Implications for carbon sequestration For Ecol Manage 2013 295 162 172 10.1016/j.foreco.2013.01.025
M. Wiesmeier L. Urbanski E. Hobley et al. Soil organic carbon storage as a key function of soils - A review of drivers and indicators at various scales Geoderma 2019 333 149 162 1:CAS:528:DC%2BC1cXhtlOit7rN 10.1016/j.geoderma.2018.07.026
C. Wiltshire M. Glendell T.W. Waine et al. Assessing the source and delivery processes of organic carbon within a mixed land use catchment using a combined n-alkane and carbon loss modelling approach J Soils Sediments 2022 22 1629 1642 1:CAS:528:DC%2BB38XhsVaqur3N 10.1007/s11368-022-03197-w
C. Wiltshire T.W. Waine R.C. Grabowski et al. Assessing n -alkane and neutral lipid biomarkers as tracers for land-use specific sediment sources Geoderma 2023 10.1016/j.geoderma.2023.116445
Wischmeier W, Smith D (1978) Predicting rainfall erosion losses: a guide to conservation planning. Agricultural Handbook No. 537.
M. Yu T.I. Eglinton N. Haghipour et al. Molecular isotopic insights into hydrodynamic controls on fluvial suspended particulate organic matter transport Geochim Cosmochim Acta 2019 262 78 91 1:CAS:528:DC%2BC1MXhsFSrtb3M 10.1016/j.gca.2019.07.040
Y. Zhang A.L. Collins S. McMillan et al. Fingerprinting source contributions to bed sediment-associated organic matter in the headwater subcatchments of the River Itchen SAC, Hampshire, UK River Res Appl 2017 33 1515 1526 10.1002/rra.3172
