Toward process-based modeling of geochemical soil formation across diverse landforms: A new mathematical framework

Yoo, Kyungsoo; Mudd, Simon M.

doi:10.1016/j.geoderma.2008.05.029

Cited by 72 publications

(72 citation statements)

References 86 publications

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“…This is a very commonly used assumption for aerial representation of a landscape using a grid mesh. Some soil profile models [e.g., Yoo and Mudd, 2008b] use dynamic profile layer size. Our algorithmic solution of constant layer size is largely dictated by computational efficiency which led us to our use of transition matrices to describe the 3-D soil-landscape (see Cohen et al [2009Cohen et al [ , 2010] for more details).…”

Section: 1002/2014jf003186mentioning

confidence: 99%

The effects of sediment transport, weathering, and aeolian mechanisms on soil evolution

et al. 2015

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Aeolian-derived soils are found throughout the world. Soil evolution processes in aeolian-dominated landscapes differ from processes in bedrock-weathering landscapes by a number of key aspects including the lack of (1) soil production depth dependency, (2) surface armoring, and (3) grain size self-organization in the soil profile. We use here a soil evolution model (mARM5D) to study the differences between aeolian and bedrock-weathering-dominated landscapes by analyzing soil evolution on a hillslope under various aeolian and bedrock-soil supply settings subject to fluvial and diffusive sediment transport. The model simulates spatial and temporal variation in soil particle size distribution (PSD) and profile depth for each grid cell on the landscape, as a function of physical weathering, aeolian deposition, and diffusive and fluvial sediment transport. Our results indicate that surface armoring plays a major role in soil evolution. Under bedrock-weathering-dominated conditions, armoring reduces soil erosion and in conjunction with depth-dependent soil production, leads to steady state soil grading and depth and a relatively uniform soil distribution. In contrast, aeolian-dominated landscapes tend to have considerable spatial variability in soil depth and PSD. Our results also indicate that in contrast with diffusive transport, which is assumed to be PSD independent, fluvial sediment transport is strongly influenced by the soil production mechanism (aeolian or bedrock weathering). Based on the results presented here, we propose that aeolian-dominated landscapes are more responsive to environmental changes (e.g., climatic and anthropogenic) compared with bedrock-weathering landscapes. We further propose that this sensitivity may help explain the patchy soil distribution that is often observed in aeolian-dominated regions.

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Section: 1002/2014jf003186mentioning

confidence: 99%

The effects of sediment transport, weathering, and aeolian mechanisms on soil evolution

et al. 2015

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“…In a more extended way, changes in soil material mass can be expressed by: Yoo et al 2007;Yoo and Mudd 2008).…”

Section: Soil Production and Formationmentioning

confidence: 99%

An attempt to estimate tolerable soil erosion rates by matching soil formation with denudation in Alpine grasslands

2014

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Purpose Natural rates of soil production or a target soil thickness that allows unrestricted land use can serve as a basis for defining tolerable soil erosion rates. Guidelines for tolerable soil erosion rates in alpine grasslands do not yet exist, partly due to the lack of information of soil formation and production rates. We (i) defined soil formation/production rates for alpine grasslands on siliceous lithology and compared them to measured and modelled soil erosion rates and resulting soil thickness with a special focus on the Urseren Valley (Central Swiss Alps) and (ii) discussed possible trends for alpine soils under global change. Materials and methods Ranges of soil formation, production and erosion rates were determined using published and our own data for Alpine grasslands soils. Two definitions of tolerable erosion rate were used: when (i) current soil depth remains constant over time; and (ii) at least a minimum soil depth is maintained (minimum thicknesses for individual land uses still need to be defined). Results and discussion Soil production and related tolerable erosion rates (i.e. 50-90 % of the soil production rate) are a strong function of time. Average soil production rate in alpine areas for relatively old soils (>10-18 kyr) is between 54 (±14) and 113 (±30)t km . Measured recent soil erosion rates in alpine areas at intensively used slopes range from 600 to 3000 t km −2 year −1 . Average catchment values for the Urseren Valley using the model USLE plus soil loss due to landslides resulted in an overall loss of 180 t km −2 year −1

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“…Soil production is related to climatic variation (Amundson et al, 2015), with this variation partly captured by EEMT and TPE, leading to the slightly stronger predictive power of the model. However, soil production is also highly influenced by redistributive hillslope process, chemical and physical weathering, and tectonic uplift (Heimsath et al, 1997;Riebe et al, 2004;Yoo and Mudd, 2008b) and can be a highly nonlinear process (Pelletier and Rasmussen, 2009a). These factors were not directly accounted for in this study in that topography was not a quantified factor, which likely represents a large proportion of the remaining unexplained variance in solum thickness.…”

Section: Model Results For Chronosequencesmentioning

confidence: 93%

A probabilistic approach to quantifying soil physical properties via time-integrated energy and mass input

Shepard

Schaap

Pelletier

et al. 2017

SOIL

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Abstract. Soils form as the result of a complex suite of biogeochemical and physical processes; however, effective modeling of soil property change and variability is still limited and does not yield widely applicable results. We suggest that predicting a distribution of probable values based upon the soil-forming state factors is more effective and applicable than predicting discrete values. Here we present a probabilistic approach for quantifying soil property variability through integrating energy and mass inputs over time. We analyzed changes in the distributions of soil texture and solum thickness as a function of increasing time and pedogenic energy (effective energy and mass transfer, EEMT) using soil chronosequence data compiled from the literature. Bivariate normal probability distributions of soil properties were parameterized using the chronosequence data; from the bivariate distributions, conditional univariate distributions based on the age and flux of matter and energy into the soil were calculated and probable ranges of each soil property determined. We tested the ability of this approach to predict the soil properties of the original soil chronosequence database and soil properties in complex terrain at several Critical Zone Observatories in the US. The presented probabilistic framework has the potential to greatly inform our understanding of soil evolution over geologic timescales. Considering soils probabilistically captures soil variability across multiple scales and explicitly quantifies uncertainty in soil property change with time.

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Toward process-based modeling of geochemical soil formation across diverse landforms: A new mathematical framework

Cited by 72 publications

References 86 publications

The effects of sediment transport, weathering, and aeolian mechanisms on soil evolution

The effects of sediment transport, weathering, and aeolian mechanisms on soil evolution

An attempt to estimate tolerable soil erosion rates by matching soil formation with denudation in Alpine grasslands

A probabilistic approach to quantifying soil physical properties via time-integrated energy and mass input

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