A. Couturier

Incorporating soil surface crusting processes in an expert-based runoff model: Sealing and Transfer by Runoff and Erosion related to Agricultural Management

Abstract In European loess belt soils, infiltration and erosion processes are strongly influenced by surface crusting. Modelling infiltration into these crusts has led to the development of equations of varying complexity, ranging from simple empirical equations to numerical solution of the Richards equation. However, a number of issues important for modelling effective erosion at the catchment scale remain unsolved. The objective of this study was to contribute to the elaboration of an expert-based runoff prediction model able to simulate the influence of soil conservation practices in the context of loess soils susceptible to crusting. Experiments have been implemented both in the laboratory and in the field at various scales ranging from small plots up to catchments. The experimental results provided a set of reference infiltration and runoff data under a variety of different situations in terms of weather conditions, surface state, land use and agricultural practices. Infiltrability ranged from 2 mm h −1 for crusted surfaces up to more than 30 mm h −1 for undegraded surfaces. These references were used to develop decision rules in the forms of matching tables to characterise agricultural fields with an infiltration capacity for a given rainfall event. For the area of the Pays-de-Caux (Normandie, France), we defined five potential infiltrability classes of 2, 5, 10, 20 and 50 mm h −1 . A runoff circulation network calculated from a Digital Elevation Model (DEM) combined with information on field operations allows the calculation of total runoff volume for a rainfall event at any point of the catchment. Calculated and measured runoff for a first series of events were in satisfactory accordance.

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.

Rill erosion on cultivated hillslopes during two extreme rainfall events in Normandy, France

In the Normandy region of France, two extreme runoff events took place during winter of 1999 and spring of 2000 that caused flooding and considerable on-site as well as off-site damages. After each event, erosion damage was mapped on an experimental cultivated catchment (94 ha). The location and extent of rill, ephemeral gullies and deposits were measured. For each field, information on land use and soil surface characteristics were also collected. Since 1991, when experimental work and survey campaigns were initiated on this catchment, interrill erosion dominated over rill or ephemeral gully erosion. Our objective was to link information on topography, soil surface characteristics, and land use with intensity and type of erosion that developed. Erosion features that were most related to topographic attributes and hence less affected by seasonal variations were ephemeral gullies and some predefined deposit types. Topographic attributes alone were not sufficient to determine development of rill erosion, due to seasonal differences in vegetative cover. At the catchment scale, total erosion varied from 10 t/ha in December with 93% of the catchment area with vegetation cover ≤20%; to 1.5 t/ha in May, with 73% of the catchment area with vegetation cover >60%. The relative importance of ephemeral gully erosion out of total linear erosion varied from ca. 24% for the rainfall events of December to more than ca. 83% for the rainfall events of May. These results also highlight the fact that average annual sediment delivery as well as the relative importance of different erosion forms at the catchment scale cannot be generalised. Erosion prediction and erosion assessment risks are strongly dependent on catchment land use, morphology and storm characteristics.

Modelling ephemeral gully erosion in small cultivated catchments

Abstract This paper describes a new erosion model to predict the location and volume of ephemeral gullies within the main runoff collector network of agricultural catchments. This model, using an expert-based approach, combines field experiment results and knowledge about erosion processes and agricultural practices. It takes into account slope gradient, parameters reducing runoff flow velocity or increasing soil resistance (land use, plant cover percentage, roughness and soil surface crusting stage), the hydrological structure of catchments and the runoff volume. The model is used to calculate the soil sensitivity to ephemeral gully erosion at any point in four small cultivated catchments. Results show that it is possible to predict gully erosion from simple information that can easily be recorded by farmers. However, our model tends to overestimate the erosion level in some cases. Furthermore, the quality of the results varies strongly according to the catchment and to the rainfall event used. To increase the quality of the results, it will be necessary to improve our knowledge database from experimental results and to use a calibration procedure.

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.

Exploring the Spatial Relationships Between Some Soil Properties and Wheat Yields in Two Soil Types

A field study was conducted to quantify spatial soil variability and to analyze correlations among soil properties at different spatial scales. Soil samples from 0 to 30 cm depth were collected from two adjacent fields in the southwestern Beauce Plain (France) which consisted of Haplic Calcisols and Rendzic Leptosols. Factorial kriging analysis (FKA) was used to describe the co-regionalization of nine soil properties. A linear model of co-regionalization including a nugget effect, and two spherical models were fitted to the experimental data direct and cross-variograms of the topsoil layer properties which were previously estimated. Co-kriged regionalized factors, related to short and long-range variation, were then mapped to characterize soil variation across the two fields. The potential value of ancillary sampled variables, such as yield data, to provide information on soil properties was tested. The relation between yield and measured soil properties appeared to be weak in general. However, the structures of the variation in yield appeared to be relatively stable for two years and showed similar patterns as the co-kriged soil factors. This suggests that information on the scale of variation of soil properties can be derived from yield maps, which can also be used as a guide to suitable sampling interval for soil properties and as a basis for managing fields in a precise way.