1. Predicting the spatio-temporal dynamic of soil surface characteristics after tillage
- Author
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Xavier Louchart, Marc Voltz, Patrick Andrieux, Anne Biarnès, N. Pare, Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH), Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
- Subjects
surface du sol ,010504 meteorology & atmospheric sciences ,Runoff ,agricultural management ,Drainage basin ,Logistic regression ,Soil Science ,Soil science ,runoff ,vineyard ,[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study ,Vineyard ,hydrologie ,infiltration ,Catchment ,01 natural sciences ,Soil crusting ,Soil management ,crust development ,eau de pluie ,soil crusting ,catchment ,mediterranean vineyard ,0105 earth and related environmental sciences ,Earth-Surface Processes ,hydraulic properties ,2. Zero hunger ,geography ,geography.geographical_feature_category ,variability ,logistic regression ,Infiltration ,04 agricultural and veterinary sciences ,15. Life on land ,erosion ,southern france ,Tillage ,Infiltration (hydrology) ,Soil water ,040103 agronomy & agriculture ,runoff generation ,northern france ,0401 agriculture, forestry, and fisheries ,Environmental science ,Surface runoff ,Agronomy and Crop Science - Abstract
Contact: pare@supagro.inra.fr; International audience; Soil surface characteristics (SSC) influence strongly hydrological processes and are known to vary largely in space and time according to soil characteristics and soil management. Because tillage is a main source of variation, the goal of this study was to present and evaluate a prediction model of the temporal variation of the SSC after tillage at the catchment level. The study focused on bare soils prevailing in spring and summer. A logistic regression approach was used to predict the evolution along three stages, starting from the fresh tillage stage to the crusted soil stage. This method provides the probabilities of occurrence of each stage. The predictor candidates tested were a rainfall characteristic, namely cumulative rainfall depth or cumulative kinetic energy, basic soil properties and tillage features. The results showed that a model based on cumulative kinetic energy since tillage and soil stoniness accurately predicts the dynamics of SSC: the rate of well classified SSC was 91%. However, no significant difference in the prediction performance was found using as predictor either cumulative kinetic energy or cumulative rainfall amount since tillage. In the prediction model, the rainfall characteristic was the most significant predictor for the SSC evolution and the only one during the first stages of crust development since tillage. Stoniness was also shown to influence SSC evolution but only during the last stages of crust development: high stone cover speeds up soil surface evolution. The same approach using logistic regression can be applied elsewhere but will require a re-examination of the most relevant predicting variables. Finally, to be able to predict the soil surface characteristic evolution on an annual scale, weed growth characteristics must be considered in the list of predictor candidates.
- Published
- 2011
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