"MIRSED" towards a MIR approach to modelling hillslope soil erosion at the national scale

R. E. Brazier, J. S. Rowan, S. G. Anthony, P. F. Quinn

    Research output: Contribution to journalArticle

    29 Citations (Scopus)

    Abstract

    This paper reports a new methodology for assessing regional and national patterns of hillslope scale soil erosion rates in the UK using a MIR (minimum information requirement) version of WEPP (Water Erosion Prediction Project) known as MIRSED. WEPP is parameterised using a national coverage, environmental database containing topographic, soil, land management and climate variables for all hillslopes within each grid cell to be modelled. The MIRSED matrix summarises the behaviour of WEPP in a multi-dimensional parameter space, allowing results to be queried using a subset of key, spatially variable parameters to produce an averaged hillslope soil erosion response from each 1 km² grid cell. The approach is demonstrated for the Great Ouse catchment, Cambridgeshire, UK and highlights highest hillslope erosion rates of 2.2 t ha?¹ year?¹ associated with steepest slopes, erodible soils and management practices that leave the soil exposed for critical times of the year. A mean soil erosion rate of 0.4 t ha?¹ year?¹ is predicted from hillslopes across the catchment which compares well with observed data collated at different scales, using contrasting measurement techniques.
    Original languageEnglish
    Pages (from-to)59-79
    Number of pages21
    JournalCATENA
    Volume42
    Issue number1
    DOIs
    Publication statusPublished - Jan 2001

    Fingerprint

    hillslope
    soil erosion
    water erosion
    erosion rate
    modeling
    prediction
    catchment
    soil
    land management
    management practice
    matrix
    methodology
    climate
    project
    parameter

    Keywords

    • Soil erosion
    • Hillslope erosion
    • Erosion modelling
    • GIS
    • WEPP
    • UK

    Cite this

    Brazier, R. E. ; Rowan, J. S. ; Anthony, S. G. ; Quinn, P. F. / "MIRSED" towards a MIR approach to modelling hillslope soil erosion at the national scale. In: CATENA. 2001 ; Vol. 42, No. 1. pp. 59-79.
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    abstract = "This paper reports a new methodology for assessing regional and national patterns of hillslope scale soil erosion rates in the UK using a MIR (minimum information requirement) version of WEPP (Water Erosion Prediction Project) known as MIRSED. WEPP is parameterised using a national coverage, environmental database containing topographic, soil, land management and climate variables for all hillslopes within each grid cell to be modelled. The MIRSED matrix summarises the behaviour of WEPP in a multi-dimensional parameter space, allowing results to be queried using a subset of key, spatially variable parameters to produce an averaged hillslope soil erosion response from each 1 km² grid cell. The approach is demonstrated for the Great Ouse catchment, Cambridgeshire, UK and highlights highest hillslope erosion rates of 2.2 t ha?¹ year?¹ associated with steepest slopes, erodible soils and management practices that leave the soil exposed for critical times of the year. A mean soil erosion rate of 0.4 t ha?¹ year?¹ is predicted from hillslopes across the catchment which compares well with observed data collated at different scales, using contrasting measurement techniques.",
    keywords = "Soil erosion, Hillslope erosion, Erosion modelling, GIS, WEPP, UK",
    author = "Brazier, {R. E.} and Rowan, {J. S.} and Anthony, {S. G.} and Quinn, {P. F.}",
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    "MIRSED" towards a MIR approach to modelling hillslope soil erosion at the national scale. / Brazier, R. E.; Rowan, J. S.; Anthony, S. G.; Quinn, P. F.

    In: CATENA, Vol. 42, No. 1, 01.2001, p. 59-79.

    Research output: Contribution to journalArticle

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    AU - Rowan, J. S.

    AU - Anthony, S. G.

    AU - Quinn, P. F.

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    N2 - This paper reports a new methodology for assessing regional and national patterns of hillslope scale soil erosion rates in the UK using a MIR (minimum information requirement) version of WEPP (Water Erosion Prediction Project) known as MIRSED. WEPP is parameterised using a national coverage, environmental database containing topographic, soil, land management and climate variables for all hillslopes within each grid cell to be modelled. The MIRSED matrix summarises the behaviour of WEPP in a multi-dimensional parameter space, allowing results to be queried using a subset of key, spatially variable parameters to produce an averaged hillslope soil erosion response from each 1 km² grid cell. The approach is demonstrated for the Great Ouse catchment, Cambridgeshire, UK and highlights highest hillslope erosion rates of 2.2 t ha?¹ year?¹ associated with steepest slopes, erodible soils and management practices that leave the soil exposed for critical times of the year. A mean soil erosion rate of 0.4 t ha?¹ year?¹ is predicted from hillslopes across the catchment which compares well with observed data collated at different scales, using contrasting measurement techniques.

    AB - This paper reports a new methodology for assessing regional and national patterns of hillslope scale soil erosion rates in the UK using a MIR (minimum information requirement) version of WEPP (Water Erosion Prediction Project) known as MIRSED. WEPP is parameterised using a national coverage, environmental database containing topographic, soil, land management and climate variables for all hillslopes within each grid cell to be modelled. The MIRSED matrix summarises the behaviour of WEPP in a multi-dimensional parameter space, allowing results to be queried using a subset of key, spatially variable parameters to produce an averaged hillslope soil erosion response from each 1 km² grid cell. The approach is demonstrated for the Great Ouse catchment, Cambridgeshire, UK and highlights highest hillslope erosion rates of 2.2 t ha?¹ year?¹ associated with steepest slopes, erodible soils and management practices that leave the soil exposed for critical times of the year. A mean soil erosion rate of 0.4 t ha?¹ year?¹ is predicted from hillslopes across the catchment which compares well with observed data collated at different scales, using contrasting measurement techniques.

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