Dominique King

Mapping erosion risk for cultivated soil in France

Abstract Surface runoff and soil erosion are major threats to sustainable agriculture and mapping regional erosion risk is increasingly needed by national and international environment agencies. Because erosion results from the interaction of several parameters which vary in space and time, no simple model can take into account all relevant factors, particularly in cultivated areas where human influences are predominant. The aim of this work is to develop a methodology based on present knowledge and available data for the evaluation of erosion risk at national scale. The various erosion factors have been graded for different geographical situations and erosion mechanisms have been expressed with the help of expert decision. The various erosion types observed in France had been previously classified. Soil crustability is considered as a key factor in runoff and erosion risk on cultivated soils. A geographical database has been created for French territory, and a model of erosion risk has been developed within a Geographical Information System (GIS). The model uses expert rules to combine data on land use (CORINE Land Cover database), soil crustability and soil erodibility (determined by pedotransfer rules from the French soil database), relief (Digital Elevation Model from the National Geographic Institute) and meteorological data from Meteo-France at the scale of 250×250 m pixels. Results are spatially aggregated using various administrative or environmental units. The main areas affected by erosion risk are the north, west and east of the Paris basin with intensive agriculture on crusting soils, the Rhone valley and southwest of France where vineyard or spring crops cover large areas. Other areas like Britany, the south of the Massif Central or the Mediterranean area are moderately affected. Areas with a permanent cover of woodland or grassland show a low erosion risk.

Crusting, runoff and sheet erosion on silty loamy soils at various scales and upscaling from m2 to small catchments

Water erosion is one of the most active processes in soil genesis and dynamics. It is also at the origin of significant environmental problems. Soil surface state is one of the most important factors for erosion risk assessment. However, it is not easy to determine the effect of this factor at a large scale. A field experiment was held in Pays de Caux (Normandy, France) in order to study and quantify crusting, runoff and sheet erosion at the cultivated field and catchment scales. We measured crust formation, runoff and erosion during two seasons on 1-m2, 20-m2 and 500-m2 experimental plots and on a small catchment. Results allow a ranking of the most important factors influencing crusting and erosion at the different scales. They also enable the development of relationships for upscaling from small plot results to the cultivated field and catchment for specific conditions. However, upscaling from plots to catchments is generally difficult and needs to take catchment spatial structures into account. We distinguish between runoff and erosion scale transfer, the latter being at the origin of specific problems that need further research to be solved.

Effects of tillage on runoff directions: consequences on runoff contributing area within agricultural catchments

Abstract In areas of intensive agriculture, e.g. ‘Pays de Caux’ in France, which was the study area, field observations have shown that runoff directions were modified by agricultural activities. In order to account for factors responsible for modifications of the runoff direction (roughness, tillage direction and agricultural patterns, e.g. dead furrow or dirt tracks), we constructed a discriminant function based on field observations. This function enables us to decide whether flow direction for slopes of up to 15% was imposed by slope direction or tillage direction. It can be applied to any location, provided there are known roughness, known slope intensity, known aspect and known tillage azimuth. In order to examine the effects of these agricultural activities at the catchment scale, we compared two models by analysing the same hydrological variables: the area contributing to runoff and the flow network. The first model (Topo) was built according to the runoff direction derived from a Digital Elevation Model (DEM). The second model (Tillage) was constructed by combining information from the DEM, and information from rules based on field observations or resulting from statistical analysis. For 23 basic catchments, the result of the comparison between the two models (Topo and Tillage) showed that a major part of the catchments and the drainage network was affected by modifications related to the introduction of man-made agricultural factors. For example, for 20 of 23 catchments, the runoff flows over more than 50% of the surface of such areas were produced along the direction imposed by tillage. The introduction of tillage effect brings about modifications of both the shape and size of catchments.

Development of a soil geographic database from the Soil Map of the European Communities

Abstract Questions on land use and soil conservation require increasingly accurate information on soil properties and their geographical location. Soil maps have helped to answer them thus helping in decision making. Information presented on soil maps are now managed by computer. This is the case for the Soil Map of European Communities (EC) at a scale of 1 : 1 000 000. Computerization of soil maps is often limited to soil boundaries and to the few descriptive items on the paper themselves. Much of the original survey is lost either during mapping or because it is published separately in explanatory notes or legends. This was also the case for the EC Soil Map. Many scientific publications and draft documents were used to make the original paper map, but were greatly condensed and simplified. The first version of the EC soil database is an exact copy of the paper map, thus having the same deficiencies. Using Geographical Information System technology, an efficient data structure has to be developed to take into account efficiently the internal organization of the soil cover. Such a structure should match conceptually the soil scientist review of spatial soil organization at a given scale within a computerized model. As a first step towards such a “Soil Spatial Organization Model” the material available for the compilation of the EC Soil Map is analysed. A logical data structure to receive a posteriori these informations is proposed and the databases improvement in terms of quantity as well as quality is demonstrated.

Comparison of kriging with external drift and simple linear regression for predicting soil horizon thickness with different sample densities

Abstract This study examines two mapping methods sensitivity to the sampling density of the variable of interest, which is the thickness of a silty-clay–loam (TSCL) horizon. The two methods are simple linear regression (SLR) and universal kriging with external drift (UKEXD). As slope gradient ( β ) derived from a DEM, is available for the whole study area and linearly related to TSCL horizon, was used for TSCL prediction by SLR and by UKEXD. The accuracy performance of TSCL prediction using these methods was assessed by comparison with another group of 69 sample points (validation sample) where the TSCL is actually measured. In the validation procedure for the two methods, two indices were calculated from the validation sample (measured values) and predicted values. These two indices are the mean error (ME) and the root mean square error (RMSE). The results showed that UKEXD was more accurate than the SLR. The improvement of the accuracy of the prediction from SLR to UKEXD was about 38%. To examine the effect of sampling density of TSCL (variable of interest) on the performance of both mapping methods, five subsets of 40, 50, 75, 100 and 125 observation sites of TSCL were randomly selected from the 150 sites of the prediction sample. For each subset, a prediction of TSCL was performed over the study area by: (i) SLR; (ii) UKEXD. The validation sample was used to compare the performance of the two methods according to the sample size of the variable of interest. The results show that whatever the sample size may be, UKEXD performs on average more accurate predictions than SLR. Moreover, the results indicate that UKEXD performed better when the sample size of the variable of interest increases. On the contrary, the performances with the linear regression remain stable whatever the sample size may be.

Relationship of the presence of a non-calcareous clay–loam horizon to DEM attributes in a gently sloping area

Abstract The initial objective of this study was to identify relationships between terrain attributes and soil cover over a Loessic flat area covering a limestone plateau. The second objective was to determine those energy factors (flow path, solar radiation, wind intensity) which could improve the understanding of morphology and soil genesis. We describe 341 field observations taken over 1600 ha of an experimental area used for monitoring the water and nitrate supply in the Petite Beauce Region (100 km to the Southwest of Paris). For each observation, several soil variables were encoded. One was the presence of a non-calcareous clay–loam (NCCL) horizon. Relief is very smooth in this region (mean slope around 0.5%). The main terrain attributes were derived from a Digital Elevation Model (DEM) at 20×20 m and assigned to the pedological observations. A multiple logistic regression was used to analyse the relationship between the NCCL horizon and terrain attributes. Special statistics were used for aspect, because of the circular nature of this variable. The results show a strong relationship between the presence of NCCL horizon and slope gradient and slope aspect, while hydrological parameters are not correlated with this horizon. The mean angle of the aspect frequency of the NCCL horizon was calculated and compared to the mean angles of wind direction and solar radiation balance. There is a small difference between wind direction and aspect frequency of the NCCL horizon. This result confirms the role of wind in the spatial pattern of soils. Further data are required to better understand the combination of several factors (role of vegetation) and the age of the reshaping.

Using multiple external drifts to estimate a soil variable

Abstract Kriging with topographic variable (β) and electrical resistivity (ρ) measurements used as external drifts was compared with universal kriging and kriging either with a topographic variable or with electrical resistivity measurements taken as external drift, to predict the depth of a limestone bedrock upper boundary (LUB) in the “Petite Beauce” region, southwest of the Paris Basin. Two sets of limestone depth apparition (LUB) were recorded. A first set of 67 measurements was used for the prediction and another set of 50 measurements was kept for the validation. The slope gradient (β) and the resistivity (ρ), which are linearly related to the limestone upper boundary depth (LUB) and exhaustively sampled over the whole study area, were used as external drift variables for kriging. Two indices, (i) the mean error (ME) and (ii) the root mean square error (RMSE), as well as residuals analysis, were computed from the validation sample (observed data) and predicted values. On the 50 test data, the results showed that kriging using two external drifts proved to be less unbiased and more precise compared to kriging using only one external drift variable in predicting the target variable.

Scale of spatial dependence between chemical properties of topsoil and subsoil over a geologically contrasted area (Massif central, France)

This study investigates scale spatial specific dependence of some major and trace element contents in topsoil horizons and in alterite type horizons (subsoil horizons) over a weakly contaminated area. The study seeks also to compare the spatial distributions of chemical elements at both depths to the spatial variability of the alterite type in order to examine the effect of the parent material. The probability of occurrence of alterite type was estimated using indicator kriging (IK). Factorial kriging analysis (FKA) was used to analyze spatial variability in some soil chemical properties (Ca, Mg, K, Fe, Cr and Co) measured at two depths over a geologically contrasted area of 10 ha in central of France. The coefficients of the coregionalization matrix at different spatial scales reveal the dominant long-range autocorrelation and cross-correlation in all chemical elements in both depths except for trace elements (Co and Cr) where the short-range structure dominates the cross-correlation. The resulting structural correlation coefficients showed strong correlations between variables changing as a function of spatial scale. These relationships between chemical properties at different spatial scales were not revealed by the linear correlation coefficients. A principal component analysis was performed on the coregionalization matrices at each depth to summarize the relationships among the variables at the different spatial scales. Cokriging allowed mapping each spatial component for both depths. These maps were then compared with the probability map of alterite type estimated using indicator kriging. This comparison revealed that the spatial pattern of chemical elements in the subsoil horizons is almost certainly due to the alterite type effect, whereas the alterite type effect on the spatial pattern of chemical properties in the topsoil horizons was partly hidden by human activities and erosion.

Effect of Agricultural Practices on Trace‐Element Distribution in Soil

Abstract The impact of agricultural practices on the spatial distribution of trace elements (TEs) in the surface horizon of Albeluvisols was studied by comparing three types of situation with an increasing anthropogenic gradient: a forest soil, considered as a reference, and cultivated soils with and without spreading of sewage sludge. Total cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) were determined in soil surface horizons. The quantity of particles finer than 2 µm, organic carbon (OC), iron (Fe), manganese (Mn), and calcium (Ca) contents were also measured and used as tracers of soil components that may have contained TEs. Governing factors of the spatial variability of TEs were searched for through comparison of the descriptive statistics (mean and coefficient of variation) and the determination of the best multivariate model predicting TE contents. Nickel and Cr distributions seem to be mainly linked to variability of the parent material composition, whereas that of Co is related to redox pedological processes. In addition, agricultural practices play a role in TE distribution, through the input of TEs, mostly Cd, Cu, and Zn, via sewage sludge spreading and liming amendments, and lateral (homogenization) and vertical (mixing of horizons) redistribution through tilling the soil.

Predicting soil classes with parameters derived from relief and geologic materials in a sandstone region of the Vosges mountains (Northeastern France)

Abstract The present study involves the possibility of using geology and relief to map soil classes. We initially focused on two small catchments considered as representative of a 6000-ha forested area overlying a sandstone bed. The catchments differed in the stratigraphic sequence of sandstones, i.e., rich or poor in weatherable minerals. In one, the depleted bedrock was downstream and the rich was upstream, and the converse obtained for the second. Relationships between soil classes and environmental factors were modeled using two discriminant functions corresponding to the two types of stratigraphic sequences found in the catchments. More than 70% of the soil class distribution in small catchments can be explained by the nature of the substratum and attributes derived from a digital elevation model (DEM). These relationships were then applied to a larger region. An automatic catchment delineation was first carried out with the DEM and was then combined with geologic maps. The choice between the two discriminant functions was based on the stratigraphic sequences in each catchment. Predicted soil classes were compared to soil classes conventionally mapped in 1978 at the scale of 1:100,000. The results show that the model reproduced the soil map over 55% of the area studied. Disagreements were due primarily to the existence of superficial deposits not mentioned on the geologic maps and to an altitude effect that is not sufficiently considered in the study of small catchments.