Pierre Curmi

Improving soil hydromorphy prediction according to DEM resolution and available pedological data.

Abstract This study analyses the sensitivity of soil hydromorphy prediction methods with regard to the resolution of topographical information and additional soil data. Seven Digital Elevation Models (DEM) were computed and compared to topographic measurements, with different resolutions (10, 20, 30 and 50 m) and construction mode (inputting actual stream location in addition to contour lines). Prediction models of soil hydromorphy using linear regression and co-kriging were established from detailed descriptions of soil catenas and topographical investigations on a 2 ha site. These models were compared on a validation set. The DEMs with fine resolutions from 10 to 30 m estimated in a unbiased way the elevation ( E ), the elevation above the stream bank (ES), the downslope gradient (DG), and the upslope contributing area (Amu), whereas prediction errors increased for the lower resolution 50-m DEMs. Apparently, the location of the channel network had no systematic effect on the estimation errors. There was a strong relationship between soil hydromorphy index (HI) and ES ( r 2 =0.80) and the Compound Topographic Index (CTI)=ln(Amu/DG) ( r 2 =0.62). For DEM resolutions of less than 30 m, soil hydromorphy prediction models bound on a regression model with topographic attributes appeared efficient and even better than ordinary kriging (OR) with 10 or 60 point observations. Coarser DEM resolutions (30 and 50 m) highly deteriorated prediction quality. For these resolutions, quality of soil hydromorphy prediction was highly improved by co-kriging of 10 and especially 60 pedological data points with a topographical regression model.

Soil carbon storage prediction in temperate hydromorphic soils using A morphologic index and digital elevation model

Because soils are both a source and a sink for atmospheric CO2, there is an increasing need to characterize the spatial distribution of soil C pools. Large amounts of organic carbon (OC) accumulate in hydric bottom-lands soils. In the Armorican Massif (Western France) where these soils represent 20% of the total surface area, the spatial characterization of OC pools is difficult to assess due to methodological problems such as high spatial variability. Soil color indexes, which combine various characteristics of soil horizons or profiles, are an alternative approach for quantifying the differences in OC storage. In addition, terrain attributes derived from Digital Elevation Models (DEM) may be useful in characterizing the distribution of soil color indexes over large areas. Thus, the overall goal of this work was the development and application of a model for use in predicting the organic carbon (OC) content of soil areas. To accomplish this, extensive examination of soil morphology combined with selected terrain attributes measured in the field and calculated from a digital elevation model (DEM) were used. Soil samples were collected in Western France from a 2-ha agricultural parcel that forms the major part of a hillslope. The results indicate that OC stocks of the entire profile were correlated highly to a soil hydromorphic index (HI) (r2 = 0.80). HI is a function of the percent of the total soil profile depth constituted by horizons with some degree of hydromorphic feature development and the moist color of the surface A horizon. Using a stepwise regression technique, we constructed a prediction model of HI distribution by using the relations between HI and (i) the elevation above the stream bank (ES) (r2 = 0.80); (ii) the downslope gradient (DG) (r2 = 0.55); and (iii) the upslope contributing area (AMU) (r2 = 0.60). Validation of this model on a second site showed that topographical attributes explained up to 75% of the profile OC stock variability. These results confirmed that the integration of a soil index and topographical information is a useful tool for prediction of OC distribution. In addition, the use of soil morphologic indexes could significantly improved the construction and the validation of soil-landscape models because it would minimize laboratory measurements of OC reservoirs.

Distribution and dynamics of gibbsite and kaolinite in an oxisol of Serra do Mar, southeastern Brazil

Abstract In the Serra do Mar region, in southeastern Brazil, the soil mantle is mainly characterised by (i) a gibbsitic saprolite, (ii) various kaolinitic horizons within the gibbsitic material, (iii) kaolinito-gibbsitic topsoil horizons. This organisation does not match with the thermodynamic stability of gibbsite and kaolinite accompanying the solution percolation through soil profiles. A study of the micromorphological, mineralogical and chemical properties of the soil mantle reveals that this organisation arises from the in situ development of the soil from the crystalline bedrock. The bauxitic weathering of the bedrock, even if it is rich in quartz, can be explained by a fast renewal of the solutions and/or a high solubility of the kaolinite. Recycling of Si and Al by the forest can maintain a dynamic equilibrium of kaolinite in the topsoil horizons, as observed in Amazonia. The kaolinitic compact horizons evolve upslope at the expense of the gibbsitic material. At the contact between kaolinitic and gibbsitic material, dissolution patterns of quartz and gibbsite are observed, indicating that this evolution is in process. These observations and the organisation of the soil mantle set the problem of the apparent stability of gibbsite and kaolinite in this environment. Various assumptions that could explain this organisation of the soil mantle are discussed. Changes in the activity of water due to the pore size diminution and displacement of the gibbsite–kaolinite equilibrium appear insufficient to explain the stability of kaolinite. However, it could be allotted to the slow down of water flows in the soil mantel. Lastly, the eventual role of the complexing organic matter is presented. More investigations on the biogeochemical cycle of Si and Al and on the physico-chemical processes at the soil solution–mineral interface are necessary to explain the stability and dynamics of gibbsite and kaolinite in this environment.

Mapping field-scale hydromorphic horizons using Radio-MT electrical resistivity

Pedological soil surveys usually based on auger sampling encounter methodological and economic difficulties. Electrical resistivity (ER) techniques could be used as a simple and practical method to determine their spatial variability. However, attempts to map soils using ER techniques have very often limited success, especially in bottomland areas, due to large variations inherent in ground data. The aim of this study is to seek the interest of a geophysical method, the radio magnetotelluric-resistivity (Radio-MT), to map field-scale hydromorphic horizons for loamy pedological systems in bottomlands characterized by large variations of soil water content and depth to upper boundary of saprolite. The sampling survey was carried in the Armorican massif (western France). The electrical measurements were taken along transects on an agricultural field (80×150 m). The soil sampling was performed on a regular grid with a mesh of 10 m. On each point, some soil properties were measured (type and thickness of the loamy horizons, depth to the upper boundary of saprolite, soil water content at 10, 20, 40 and 60 cm depths). A direct relationship between apparent resistivity and horizon type distribution was not established. The best correlations were between the electrical conductivity and depth to the upper boundary of saprolite and topsoil water content. The correlation coefficients, r, are 0.51 and 0.34, respectively. To identify the soil types, we modeled the influence of these two soil properties by multiple regression technique. Deviations from the regression model were then interpreted by taking into account the succession of soil horizons. These results seem to indicate that the electrical method used in this study could not be directly used to evaluate spatial prediction of the hydromorphic soil distribution, but indirectly by taking into account soil properties such as the soil water content and the upper boundary of saprolite.

The use of auxiliary geophysical data to improve a soil-landscape model

Soil-landscape models have prediction errors that can be reduced by using auxiliary soil data. However, standard soil surveys using auger hole and laboratory analysis encounter both methodological and economical constraints because of, for example, the short-range variability of soils and the expens

Soil spatial distribution in the Armorican Massif, western France: Effect of soil-forming factors

Soil spatial distribution, i.e. the spatial distribution of soils within landscapes, is difficult to predict because numerous processes operate simultaneously, but variably, over time. Quantifications of large areas with an acceptable degree of precision and low in cost require the development of specific methods making the best possible use of existing soil data and auxiliary information such as soil-forming factors. The quantification of the influence of soil-forming factors on soil spatial distribution is seldom performed over large areas such as regions. This study aimed to quantify the relationship between soil spatial distribution and the soil-forming factors of geology, topography, climate, and tectonic regime in order to predict soil spatial distribution over a wide region (30,000 km2). The Armorican Massif (western France), a complex basement of Proterozoic and Paleozoic rocks affected by recent tectonic activity and characterized by variations in topography and climate, was chosen as the study site. Detailed soil maps (1:25,000) were used to describe soil spatial distribution along transects. An ANOVA performed on 314 transects showed a high correlation between the occurrence of soils with particular features (namely redoximorphic, leached, glossic, and albic) and geological substrate, uplift ratio, mean slope gradient, and net rainfall. No such correlation was found with fluvic soils. These soil-forming factors seem to act through saprolite quality and erosion processes, which in turn control the development of soil features. A quantification of the relationship between soil features and soil-forming factors was performed by regression analysis in order to allow further prediction of the soil spatial distribution over the entire Armorican Massif. These results revealed and quantified the hitherto unrecognized role of tectonism on soil distribution and its relative importance in respect to other soil-forming factors. Finally, such an analysis, which is based on existing maps, can help to describe, quantify, and predict detailed soil spatial distribution at smaller scales.

TESTING QUANTITATIVE SOIL-LANDSCAPE MODELS FOR PREDICTING THE SOIL HYDROMORPHIC INDEX AT A REGIONAL SCALE

Quantitative soil-landscape models, based on topographic attributes, make possible the characterization of large areas because of the widespread availability of digital elevation models (DEMs). However, these soil-landscapes models, which are usually generated and validated on the same detailed, single research site, such as a hillslope or an elementary catchment, may show high prediction errors when applied to other areas of a region. The effect of the regional variations of topography, climate, parent material, land-use, and/or soil has seldom been analyzed. The objective of this study was to test multiple-regression relationships between the soil hydromorphic index (HI) and topographic attributes on different catchments of the Armorican Massif (30,000 km2) in western France. Regression models were validated using 565 data points collected from four sites along hillslopes. These four sites, located throughout this region, were included in three catchments with surface areas of 78, 82, and 120 ha, respectively, and differing in topography (mean elevation from 39 to 202 m and slope gradient from 3.4 to 7.9%), parent material (granite and schist), and precipitation (700 to 900 mm y−1). The existing models were multiple regression equations between the HI and the elevation above the stream bank, the compound topographic index (regression 1, r2 = 0.84), or the upslope drained area (regression 2, r2 = 0.86). At each validation point, systematic soil observation for HI estimation was compared with estimations from terrain attributes derived from DEMs at a 30-m resolution. Results showed small prediction errors for all study sites, with mean absolute errors between 5 and 15% of the HI range. Errors were not spatially correlated. Minimum prediction errors were encountered in the catchment for which the models were generated and also in one other that differed only in the parent material. In the other validation site, the models systematically overestimated HI. At the site of model generation, both regressions were accurate. However on the other sites, prediction errors using regression 2 were systematically higher than for regression 1, which uses a topographic index with a physical basis. These results revealed that soil-landscape models may be useful for predicting soil hydromorphy over a region but only when validated under several environmental conditions.

Arguments cartographiques en faveur du rôle de la tectonique récente sur la distribution régionale des sols du Massif armoricain

Abstract The study of pedological maps from the Armorican Massif evidenced the effect of recent tectonics (500 000–700 000 years BP) on the regional hydromorphic soil distribution. Blocs in relative uplift were characterized by a low proportion of hydromorphic soils, whereas a higher proportion marked blocs in relative downlift. Such clear differences can be related to the denudation regime which affects topography and saprolite properties, two soil formation factors. Improvements in soil modelling may be achieved by taking into account the regional trends of soil waterlogging and hydromorphy.

Analyse de cartes pédologiques pour identifier le rôle du régime tectonique sur la répartition régionale de la perméabilité des altérites

Abstract Soil maps analysis to identify the role of the tectonic regime on saprolite permeability regional distribution. For applied geology, e.g., geotechnics or hydrogeology, it is of prime interest to know the spatial distribution of the saprolite permeability. This study focuses on the role of the tectonic regime on saprolite permeability regional distribution. Comparison of data concerning the uplift regime and soil organisation data from several pedological maps of the Armorican Massif (France) showed that blocks in relative uplift were characterized by a low proportion of hydromorphic soils, whereas a higher proportion marked blocks in relative downlift. Such differences can be related to the denudation regime, which affects the saprolite permeability.