O. Cerdan

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.

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.

Comparative sensitivity analysis of four distributed erosion models

[1]xa0Using a previously defined framework, we performed a comparative sensitivity analysis of four very different distributed erosion models (MHYDAS, STREAM, PESERA, and MESALES). We investigated their sensitivities to input fluxes, hydrological submodels, and specific erosion parameters gathered into equivalent slope and equivalent erodibility for each model, thus allowing explicit comparisons between models. Tests involved multiple combinations of rain intensities and runoff conditions for selected screenings of the equivalent parameter space, resorting to one-at-a-time displacements and Latin hypercube samples. Sensitivity to spatial distributions of erosion parameters was calculated as a normalized index of numerical spread of soil loss results, obtained at the outlet of a nine-cell virtual catchment endowed with a fixed flow pattern. Spatially homogeneous or distributed parameterizations yielded responses of comparable magnitudes. Equivalent erodibility was often the key parameter, while sensitivity trends depended on input fluxes and the propensity of soils for runoff, affecting continuous and discrete models in clearly dissimilar ways.