Old landscapes, pre-weathered materials, and pedogenesis in tropical Africa: How can the time factor of soil formation be assessed in these regions?

Costa, Pauline Yawoa D. Da; Nguetnkam, Jean Pierre; Mvoubou, Castane M.; Togbe, Kodjo Adika; Ettien, Jean-Baptiste D.; Yao-Kouamé, Albert

doi:10.1016/j.quaint.2014.04.062

Cited by 11 publications

(6 citation statements)

References 18 publications

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“…3) var(log 10λ i ) decreased with decreasing spatial resolution; the absolute scaling parameter variability of the Africa region is largest. This can be explained by the fact that the Sahel is prone to strong seasonal dry-wet cycles, which induces large variability in soil development (Da Costa et al, 2015). On the other hand, the relative decrease of variance with coarser resolution for this region is comparable to the other ones (Fig.…”

Section: Analysing Scaling Variability For Different Spatial Resolutionsmentioning

confidence: 78%

A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves

Montzka¹,

Herbst²,

Weihermüller³

et al. 2017

Earth Syst. Sci. Data

123

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Abstract. Agroecosystem models, regional and global climate models, and numerical weather prediction models require adequate parameterization of soil hydraulic properties. These properties are fundamental for describing and predicting water and energy exchange processes at the transition zone between solid earth and atmosphere, and regulate evapotranspiration, infiltration and runoff generation. Hydraulic parameters describing the soil water retention (WRC) and hydraulic conductivity (HCC) curves are typically derived from soil texture via pedotransfer functions (PTFs). Resampling of those parameters for specific model grids is typically performed by different aggregation approaches such a spatial averaging and the use of dominant textural properties or soil classes. These aggregation approaches introduce uncertainty, bias and parameter inconsistencies throughout spatial scales due to nonlinear relationships between hydraulic parameters and soil texture. Therefore, we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the mentioned problems. The approach is based on Miller–Miller scaling in the relaxed form by Warrick, that fits the parameters of the WRC through all sub-grid WRCs to provide an effective parameterization for the grid cell at model resolution; at the same time it preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters. Based on the Mualem–van Genuchten approach we also derive the unsaturated hydraulic conductivity from the water retention functions, thereby assuming that the local parameters are also valid for this function. In addition, via the Warrick scaling parameter λ, information on global sub-grid scaling variance is given that enables modellers to improve dynamical downscaling of (regional) climate models or to perturb hydraulic parameters for model ensemble output generation. The present analysis is based on the ROSETTA PTF of Schaap et al. (2001) applied to the SoilGrids1km data set of Hengl et al. (2014). The example data set is provided at a global resolution of 0.25° at https://doi.org/10.1594/PANGAEA.870605.

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Section: Analysing Scaling Variability For Different Spatial Resolutionsmentioning

confidence: 78%

A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves

Montzka¹,

Herbst²,

Weihermüller³

et al. 2017

Earth Syst. Sci. Data

123

View full text Add to dashboard Cite

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“…As there is little deposition and accumulation of organic litter in arid and semiarid zones, the organic matter content of the soils was low. When these soils are cultivated, the limited organic matter content is quickly decomposed (Da Costa et al, 2015). For all profiles in the study area, the organic matter content was highest (1.0 to 1.6 %) in the surface horizon and lowest in the subsurface horizons (0.4 to 1.4 %), with an abrupt decrease in the subsurface horizon.…”

Section: Physical and Chemical Characteristicsmentioning

confidence: 90%

Chemical weathering indices applied to soils developed on old lake sediments in a semi-arid region of Turkey

Tunçay

Dengi̇z

Bayramin

et al. 2019

Eurasian Journal of Soil Science (Ejss)

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Climate is a major influence on weathering processes affecting soil parent materials. Important contributors to soil formation in arid and semi-arid climatic zones are the diurnal cycles of solar heating and cooling that cause mechanical or physical disintegration of rock or parent materials, and wind-blown sands that score and abrade exposed rock surfaces. By using the Soil Taxonomy classification system, the initial aim of this study was to carry out a pedological evaluation for four soil profiles, classified as Xeric Haplocalcid and Xeric Haplocambid, formed on different parent materials (limestone, marl and old alluvial deposits) under the same conditions, including topography and vegetation, in a semiarid region. The second stage was the exploration of the similarities and differences in the classifications resulting from either the pedogenic processes, or from other factors, by determining the degree of soil weathering using geochemical data. To achieve this, soil samples were collected from the horizons to investigate their mineralogical, geochemical and physiochemical properties. The study also considered other features, such as the pedogenic evolution of soils, through the use of weathering indices, namely the Chemical Index of Alteration (CIA), Chemical Index of Weathering (CIW), Base/R2O3 Ratio, Weathering Index of Parker (WIP) and Plagioclase Index of Alteration (PIA). The results clearly showed that soil development at the Altınova State Farm at Konya in the Central Anatolia region of Turkey is due to slow pr ogressive weathering. For this case, the main indicators are secondary calcium carbonate illuviation and weak structural development with a weathering ratio of silicon to aluminium greater than two in all profiles.

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“…For all three case sites (North America, Africa, and China, see also Fig 3) var(log 10̂) decreased with decreasing spatial resolution; the absolute scaling parameter variability of the Africa region is largest. This can be explained by the fact that the Sahel is prone to strong seasonal dry-wet cycles, which induces large variability in soil development (Da Costa et al, 2015). On the other hand, the relative decrease of variance with coarser resolution for this region is compared to the other ones (Figure 11 right panel).…”

Section: Analysing Scaling Variability For Different Spatial Resolutionsmentioning

confidence: 93%

A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves

Montzka¹,

Herbst²,

Weihermüller³

et al. 2017

Preprint

View full text Add to dashboard Cite

Abstract. Agroecosytem models, regional and global climate models, as well as numerical weather prediction models require adequate parameterization of soil hydraulic properties. These properties are fundamental for describing and predicting water and energy exchange processes at the transition zone between solid Earth and Atmosphere, and regulate evapotranspiration, infiltration, and runoff generation. Hydraulic parameters describing the soil water retention (WRC) and hydraulic conductivity (HCC) curves are typically derived from soil texture via pedotransfer functions (PTFs). Resampling of those parameters for specific model grids is typically performed by different aggregation approaches such a spatial averaging and the use of dominant textural properties or soil classes. These aggregation approaches introduce uncertainty, bias and parameter inconsistencies throughout spatial scales due to nonlinear relationships between hydraulic parameters and soil texture. Therefore, we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the mentioned problems. The approach is based on Miller-Miller scaling that fits the parameters of the WRC through all sub-grid WRCs to provide an effective parameterization for the grid cell at model resolution; at the same time it preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters. Based on the Mualem van Genuchten approach we also derive the unsaturated hydraulic conductivity from the water retention functions, thereby assuming that the local parameters are also valid for this function. In addition, via the Miller-Miller scaling parameter lambda, information on global sub-grid scaling variance is given that enables modellers to improve dynamical downscaling of (regional) climate models or to perturb hydraulic parameters for model ensemble output generation. The present analysis is based on the ROSETTA PTF of Schaap et al. (2001) applied to the SoilGrids1km data set of Hengl et al. (2014). The example data set is provided at a global resolution of 0.25° at DOI:10.1594/PANGAEA.870605 (DOI registration in progress, so far the data can be accessed under https://doi.pangaea.de/10.1594/PANGAEA.870605).

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Old landscapes, pre-weathered materials, and pedogenesis in tropical Africa: How can the time factor of soil formation be assessed in these regions?

Cited by 11 publications

References 18 publications

A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves

A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves

Chemical weathering indices applied to soils developed on old lake sediments in a semi-arid region of Turkey

A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves

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