Hydrological thresholds of soil surface properties identified using conditional inference tree analysis

Matthew Tighe, Carlos Muñoz-Robles, Nick Reid, Brian Wilson, Sue Briggs

    Research output: Contribution to journalArticle

    5 Citations (Scopus)

    Abstract

    There has been limited success in determining critical thresholds of ground cover or soil characteristics that relate to significant changes in runoff or sediment production at the microscale (<1?m2), particularly in semi-arid systems where management of ground cover is critical. Despite this lack of quantified thresholds, there is an increasing research focus on the two-phase mosaic of vegetation patches and inter-patches in semi-arid systems. In order to quantify ground cover and soil related thresholds for runoff and sediment production, we used a data mining technique known as conditional inference tree analysis to determine statistically significant values of a range of measured variables that predicted average runoff, peak runoff, sediment concentration and sediment production at the microscale. On Chromic Luvisols across a range of vegetation states in semi-arid south-eastern Australia, large changes in runoff and sediment production were related to a hierarchy of different variables and thresholds, but the percentage of bare soil played a primary role in predicting runoff and sediment production in most instances. The identified thresholds match well with previous thresholds found in semi-arid and temperate regions (including the approximate values of 30%, 50% and 70% total ground cover). The analysis presented here identified the critical role of soil surface roughness, particularly where total ground cover is sparse. The analysis also provided evidence that a two-phase mosaic of patches and inter-patches identified via rapid visual assessment could be further delineated into distinct groups of hydrological response, or a multi-phase rather than a two-phase system. The approach used here may aid in assessing scale-dependent responses and address data non-linearity in studies of semi-arid hydrology
    Original languageEnglish
    Pages (from-to)620-632
    Number of pages13
    JournalEarth Surface Processes and Landforms
    Volume37
    Issue number6
    DOIs
    Publication statusPublished - 2012

    Fingerprint

    ground cover
    soil surface
    runoff
    sediment
    hydrological response
    Luvisol
    data mining
    vegetation
    bare soil
    surface roughness
    nonlinearity
    analysis
    hydrology
    soil
    mosaic

    Cite this

    Tighe, Matthew ; Muñoz-Robles, Carlos ; Reid, Nick ; Wilson, Brian ; Briggs, Sue. / Hydrological thresholds of soil surface properties identified using conditional inference tree analysis. In: Earth Surface Processes and Landforms. 2012 ; Vol. 37, No. 6. pp. 620-632.
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    Hydrological thresholds of soil surface properties identified using conditional inference tree analysis. / Tighe, Matthew; Muñoz-Robles, Carlos; Reid, Nick; Wilson, Brian; Briggs, Sue.

    In: Earth Surface Processes and Landforms, Vol. 37, No. 6, 2012, p. 620-632.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Hydrological thresholds of soil surface properties identified using conditional inference tree analysis

    AU - Tighe, Matthew

    AU - Muñoz-Robles, Carlos

    AU - Reid, Nick

    AU - Wilson, Brian

    AU - Briggs, Sue

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    N2 - There has been limited success in determining critical thresholds of ground cover or soil characteristics that relate to significant changes in runoff or sediment production at the microscale (<1?m2), particularly in semi-arid systems where management of ground cover is critical. Despite this lack of quantified thresholds, there is an increasing research focus on the two-phase mosaic of vegetation patches and inter-patches in semi-arid systems. In order to quantify ground cover and soil related thresholds for runoff and sediment production, we used a data mining technique known as conditional inference tree analysis to determine statistically significant values of a range of measured variables that predicted average runoff, peak runoff, sediment concentration and sediment production at the microscale. On Chromic Luvisols across a range of vegetation states in semi-arid south-eastern Australia, large changes in runoff and sediment production were related to a hierarchy of different variables and thresholds, but the percentage of bare soil played a primary role in predicting runoff and sediment production in most instances. The identified thresholds match well with previous thresholds found in semi-arid and temperate regions (including the approximate values of 30%, 50% and 70% total ground cover). The analysis presented here identified the critical role of soil surface roughness, particularly where total ground cover is sparse. The analysis also provided evidence that a two-phase mosaic of patches and inter-patches identified via rapid visual assessment could be further delineated into distinct groups of hydrological response, or a multi-phase rather than a two-phase system. The approach used here may aid in assessing scale-dependent responses and address data non-linearity in studies of semi-arid hydrology

    AB - There has been limited success in determining critical thresholds of ground cover or soil characteristics that relate to significant changes in runoff or sediment production at the microscale (<1?m2), particularly in semi-arid systems where management of ground cover is critical. Despite this lack of quantified thresholds, there is an increasing research focus on the two-phase mosaic of vegetation patches and inter-patches in semi-arid systems. In order to quantify ground cover and soil related thresholds for runoff and sediment production, we used a data mining technique known as conditional inference tree analysis to determine statistically significant values of a range of measured variables that predicted average runoff, peak runoff, sediment concentration and sediment production at the microscale. On Chromic Luvisols across a range of vegetation states in semi-arid south-eastern Australia, large changes in runoff and sediment production were related to a hierarchy of different variables and thresholds, but the percentage of bare soil played a primary role in predicting runoff and sediment production in most instances. The identified thresholds match well with previous thresholds found in semi-arid and temperate regions (including the approximate values of 30%, 50% and 70% total ground cover). The analysis presented here identified the critical role of soil surface roughness, particularly where total ground cover is sparse. The analysis also provided evidence that a two-phase mosaic of patches and inter-patches identified via rapid visual assessment could be further delineated into distinct groups of hydrological response, or a multi-phase rather than a two-phase system. The approach used here may aid in assessing scale-dependent responses and address data non-linearity in studies of semi-arid hydrology

    KW - erosion

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