Algorithms for quantitative pedology: A toolkit for soil scientists

Beaudette, Dylan; Roudier, Pierre; O’Geen, A. T.

doi:10.1016/j.cageo.2012.10.020

Cited by 157 publications

(112 citation statements)

References 21 publications

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“…Mean values across the two standardized soil depth intervals (0-20 and 20-50) were calculated for each property, thus allowing for comparisons between soil profiles with differing soil genetic horizon thicknesses. The segmenting algorithm was implemented using the 'GSIF' and 'aqp' packages for R (Beaudette et al, 2013). .…”

Section: Soil Sampling and Analysismentioning

confidence: 99%

Scale-dependency of LiDAR derived terrain attributes in quantitative soil-landscape modeling: Effects of grid resolution vs. neighborhood extent

Maynard

Johnson

2014

Geoderma

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Quantifying the spatial distribution of soil properties is essential for ecological and environmental modeling at the landscape scale. Terrain attributes are among the primary covariates in soil-landscape models due to their control on energy and mass fluxes, which in turn control the spatial distribution of soil properties and processes. While numerous studies have demonstrated the importance of terrain attributes for predicting landscape-scale soil variability, considerable uncertainty exists as to the scale-dependency of light detection and ranging (LiDAR) derived terrain attributes on the accuracy of soil-landscape model predictions. Thirty five pedons were sampled by genetic horizon in a 2300 ha forested watershed and three soil properties (clay, sum of bases, and total carbon), representing dominant pedogenic processes within the watershed were analyzed. Soil properties were used as dependent variables and terrain attributes, calculated from LiDAR derived DEMs of various grid resolutions (ranging from 5 to 50 m) and neighborhood extents (ranging from 15 to 350 m), were used as predictor variables in ordinary least-squares (OLS) regression models. Results from this study show that model predictions exhibit a strong scale-dependency, with percent clay, sum of bases, and total carbon having the highest R 2 -adj and lowest root mean square error (RMSE) at coarse neighborhood extents (i.e., 150 to 300 m) both between soil variables and across soil depths. Furthermore, in certain instances grid resolution was also shown to affect soil-terrain correlations, although to a lesser degree than neighborhood extent. In many cases fine to moderate scale grid resolutions (i.e.,b 30 m) more accurately represented terrain features, resulting in higher correlations to soil properties at fixed neighborhood extents relative to course grid resolutions. Additionally, these results show that fine scale topographic information (i.e., 1 to 5 m) does not necessarily provide a stronger predictor of soil spatial variability relative to moderate scale information. This study provides a robust framework for investigating pedogeomorphological processes on a landscape scale through examination of the scale dependency of modeled terrain attributes in quantitative soil-landscape modeling.Published by Elsevier B.V.

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Section: Soil Sampling and Analysismentioning

confidence: 99%

Scale-dependency of LiDAR derived terrain attributes in quantitative soil-landscape modeling: Effects of grid resolution vs. neighborhood extent

Maynard

Johnson

2014

Geoderma

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“…Horizon-scale soil property data were aggregated to the profile scale using horizon thickness-weighted averages, and 2. Soil property data were aligned to a regular sequence of 10 cm-thick depth "slabs" using thickness-weighted averages when slabs included more than one genetic horizon (Beaudette et al, 2013b).…”

Section: Discussionmentioning

confidence: 99%

“…Various parametric (Myers et al, 2011) and spline functions (Bishop et al, 1999;McBratney et al, 2000;Malone et al, 2009) have been used to accommodate vertical anisotropy and variable horizon thickness. An alternative approach based on the evaluation of percentiles along 1-cm depth slices, or larger "slabs" (e.g., 10-cm sections), was suggested by Beaudette et al (2013b). Explicitly accounting for these complexities has the potential to create a more robust model that incorporates three-dimensional soil property data.…”

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confidence: 99%

Topographic and Geologic Controls on Soil Variability in California's Sierra Nevada Foothill Region

Beaudette¹,

O’Geen

2016

Soil Science Society of America Journal

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We evaluated the feasibility of quantitative soil mapping in two catenas established on different lithologies (metavolcanic and granitic) in the Sierra Foothill Region of California. Indices of landform and microclimate were extracted from a 1-m elevation model. Variation in soil "character" (clay content, pH, color, cation-exchange capacity [CEC], and Fe o /Fe d ) was partitioned across variables associated with terrain shape and microclimate, lithologic variability, and sampling depth. The potential for using digital elevation models (DEM)-derived indices of terrain shape to predict spatial patterns in soil properties varied greatly between our two experimental catenas. Terrain shape accounted for 4% (metavolcanic site) to 30% (granitic site) of variance in soil properties, while lithology accounted for 14% (metavolcanic site) to 22% (granitic site) of variance in soil properties. Sample depth accounted for 3% (metavolcanic site) to 12% (granitic site) of variance in soil properties. At the metavolcanic site, variability in lithology contributed more to soil variation than terrain shape, which makes digital soil modeling efforts a challenge in these regions. Up to 66% of the variance in soil properties was explained at the granitic site when considering terrain, lithology, sample depth, and associated interactions of these variables. Variance proportions can provide insight into the relative importance of soil-forming factors and is a useful tool when evaluating the efficacy of digital soil mapping projects.Abbreviations: CEC, cation-exchange capacity; CS, conditional simulation; CTI, compound topographic index; DEM, digital elevation models; OK, ordinary kriging; pRDA, partial redundancy analysis; PCA, principal components analysis; QSM, quantitative soil mapping; RDA, redundancy analysis; RCS, restricted cubic splines; RST, regularized splines in tension; RTK, real-time kinematice; SFR, Sierra Nevada Foothill Region; SFREC, Sierra Foothill Research and Extension Center; SJER, San Joaquin Experimental Station; TCI, terrain characterization index; XRF, x-ray fluorescence.T he development and application of the soil-landscape paradigm has played a significant role in how soil scientists conduct research, interpret and communicate their findings, and apply the resulting knowledge to solve real-world problems (Hudson, 1992). Within this framework, repeating patterns in soil properties or classes are correlated with factors that drive redistribution of sediment (slope angle), effective precipitation (surface curvature), and microclimate (slope aspect); and are stratified according to differences in parent material, biota, and time. Traditionally, this approach has been implemented through qualitative evaluation (i.e., mental models) of Hans Jenny's ( Jenny, 1941) state-factor model of soil genesis. Modern extensions to this framework for mapping soils commonly termed digital soil mapping are based on a numerical integration of soil property or class data with quantitative proxies of soil-forming factors (Moore et ...

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“…Mean values at each 1-cm depth increment were calculated across all sampling dates and sampling locations within each hydrologic zone. The segmenting algorithm was implemented using the 'GSIF' and 'aqp' packages for R (Beaudette et al, 2013).…”

Section: Water Collection and Analysismentioning

confidence: 99%

Fate of nitrate in seepage from a restored wetland receiving agricultural tailwater

Brauer

Maynard

Dahlgren

et al. 2015

Ecological Engineering

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A B S T R A C TConstructed and restored wetlands are a common practice to filter agricultural runoff, which often contains high levels of pollutants, including nitrate. Seepage waters from wetlands have potential to contaminate groundwater. This study used soil and water monitoring and hydrologic and nitrogen mass balances to document the fate and transport of nitrate in seepage and surface waters from a restored flow-through wetland adjacent to the San Joaquin River, California. A 39% reduction in NO 3 -N concentration was observed between wetland surface water inflows (12.87 AE 6.43 mg L À1 ; mean AE SD) and outflows (7.87 AE 4.69 mg L À1 ). Redox potentials were consistently below the nitrate reduction threshold ($250 mV) at most sites throughout the irrigation season. In the upper 10 cm of the main flowpath, denitrification potential (DNP) for soil incubations significantly increased from 151 to 2437 mg NO 3 -N m À2 d À1 when nitrate was added, but showed no response to carbon additions indicating that denitrification was primarily limited by nitrate. Approximately 72% of the water entering the wetland became deep seepage, water that percolated beyond 1-m depth. The wetland was highly effective at removing nitrate (3866 kg NO 3 -N) with an estimated 75% NO 3 -N removal efficiency calculated from a combined water and nitrate mass balance. The mass balance results were consistent with estimates of NO 3 -N removed (5085 kg NO 3 -N) via denitrification potential. Results indicate that allowing seepage from wetlands does not necessarily pose an appreciable risk for groundwater nitrate contamination and seepage can facilitate greater nitrate removal via denitrification in soil compared to surface water transport alone.

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Algorithms for quantitative pedology: A toolkit for soil scientists

Cited by 157 publications

References 21 publications

Scale-dependency of LiDAR derived terrain attributes in quantitative soil-landscape modeling: Effects of grid resolution vs. neighborhood extent

Scale-dependency of LiDAR derived terrain attributes in quantitative soil-landscape modeling: Effects of grid resolution vs. neighborhood extent

Topographic and Geologic Controls on Soil Variability in California's Sierra Nevada Foothill Region

Fate of nitrate in seepage from a restored wetland receiving agricultural tailwater

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