Stocker du carbone dans les sols francais, quel potentiel au regard de l’objectif 4 pour 1000 et a quel cout ?. Synthese du rapport d'etude

L’initiative « ‰ sur les sols pour la securite alimentaire et le climat », lancee par la France a l’occasion de la Conference de Paris sur le climat (COP-21), propose d’augmenter chaque annee d’un quatre millieme le stock de carbone present dans tous les sols du monde afin de compenser les emissions anthropiques de CO2. Cet objectif, tres ambitieux, necessite des evolutions profondes des pratiques agricoles et des modes de gestion sylvicoles, certaines pouvant s’accompagner de modifications de systemes de production et, eventuellement, des modes d’usage des sols. C'est dans ce contexte que le Ministere de l’Agriculture et de l’Alimentation (MAA) et l’Agence De l'Environnement et de la Maitrise de l'Energie (ADEME) ont demande a l'INRA de conduire la presente etude 4 pour mille France. Les objectifs etaient : i) d’identifier des pratiques agricoles et sylvicoles plus que les pratiques actuellement mises en œuvre ; ii) de chiffrer le potentiel de stockage additionnel associe, de le cartographier, de quantifier les autres effets induits lies a l’adoption de ces pratiques stockantes (pertes ou gains de rendement, emissions de N2O, lixiviation de nitrate, utilisation de produits phytosanitaires...) ; iii) de chiffrer leur cout de mise en œuvre et de proposer une strategie cout-efficace de stockage. Le present document constitue le rapport scientifique de cette etude. Ce travail a fait l'objet de documents de synthese et d'un colloque public de restitution, qui s'est tenu a Paris le 13 juin 2019.

The recent controversy about the 4 per 1000 initiative has emphasized the need for a quantitative assessment of the C storage potential of agricultural soils. Moreover a clear distinction is required between the biophysically and the economically achievable potentials. Here we used a modelling approach at a fine spatial-scale resolution (< 8 km2) to quantify the additional C storage in agricultural soils of mainland France following the implementation, when feasible, of a range of soil C storing practices (i.e. cover crops, reduced tillage, new C inputs, grazing instead of mowing,…). The additional cost for farmers was also calculated, thus yielding the cost per Mg of additional C stored in soils. Results showed that the average additional C storage calculated over 30 years ranged between +0.028 and + 0.466 Mg C ha-1 yr-1 (i.e. between +0.5 and +7.2‰) for the different tested practices, with a very high spatial variability over France for each practice related to initial C stocks and pedo-climatic conditions. The storing practices where then ranked according to the cost of the additional C stored in soils (expressed in euro per Mg of C) and an optimal cost-efficient strategy was proposed at the national level.

Les ecosystemes agricoles sont l'un des six volets de l'Evaluation francaise des ecosystemes et des services ecosystemiques (EFESE), programme lance en 2012 par le Ministere en charge de l'Environnement pour apporter des connaissances sur l'etat actuel et l'utilisation durable des ecosystemes (voir encadre 2). En 2014, le Ministere de l'Environnement a sollicite l'Inra pour prendre en charge le volet relatif aux ecosystemes agricoles. Le programme federateur de recherche EcoSerV (Services rendus par les ecosystemes), lance par l'Inra en 2013, a egalement soutenu cette etude qu'il va ensuite completer et etendre. L'ecosysteme agricole, vu comme l'ensemble des parcelles dediees a la production de biomasse agricole, est configure et gere par l'agriculteur qui combine, dans ses pratiques de production, processus ecologiques et apports d'intrants exogenes. L'un des enjeux forts associes a l'analyse des services ecosystemiques est la conception de systemes de production reposant sur la valorisation de ces services, donc peu consommateurs en intrants exogenes et repondant aux enjeux de societe tels que la conservation de la biodiversite ou la limitation des impacts environnementaux.

Modelling soil erosion sensitivity at continental scale provides a way to compare different countries and to identify those areas that are most seriously threatened. In this research, the MESALES model was applied to 3 large areas in Europe and Morocco, using soil data from ESDB and DSMW as well as from the newly developed e-SOTER database. Land use data were derived from the Global Land Cover 2000 database, and slope angle from the HYDRO1K DEM. The aim was to evaluate whether the e-SOTER database resulted in better assessment of soil erosion sensitivity than existing data. To judge this, expert opinion was used. The comparison of results obtained with existing data and with e-SOTER data showed considerable differences. However, it proved impossible to say which results were better. The main reasons for that were that MESALES predicts soil erosion sensitivity, which cannot be measured in the field, and that expert judgement of model results proved inconclusive. Another reason can have been that the e-SOTER database is as yet incomplete. The fact that the application of different soil databases resulted in quite different results does, however, indicate the importance of using the best available data for evaluation of soil threats. However, a current lack of options to validate soil erosion sensitivity estimates was also identified.

This paper investigates how the spatial correlations between topographic attributes and a soil thickness can be improved by focusing on the relationships between them at specific spatial scales. In addition, this paper examines the effects of the topographic attribute data sources that are used as explanatory variables for modeling the response variable, and considers the possibility of model extrapolation for mapping beyond the area where the model was established. Here, factorial kriging analysis (FKA) and partial least square regression (PLSR) analysis are used to separate nuggets and small- and large-scale structures in data including four topographic attributes and soil thickness (ST). These analyses were conducted at different scales to analyze the relationships between ST and the selected topographic attributes in the southwest region of the Parisian Basin. The structural correlation coefficients from the FKA show strong correlations between the variables. These correlations, which change as a function of spatial scale, are not revealed by the linear correlation coefficients. The Eigen vectors from the principal component analysis that was performed on the small-scale and large-scale structures of the linear co-regionalization model are used to obtain ST and the topographic attributes at both spatial scales over the study area. The ST models are built as a function of topographic attributes using PLSR. Results have shown that the models built using variables that were assessed at a specific scale are better at predicting the target variable than models that were built using raw data. Regarding the models that were built using raw data, the structural correlations that occur at different spatial scales are merged together and the variance–covariance matrix of the nugget that represents data noise is not filtered out. Measures of model performance that are based on a validation data set have shown that the model based on small-scale structure (Model-S) is better for predicting soil thickness than the model based on large-scale structure (Model-L). The effects of topographic attribute data sources as explanatory variables for modeling ST are less significant than the effects of the two models for mapping. Moreover, extrapolation of the model-S beyond the area where it was generated is appropriate. The decomposition process is associated with a modeling approach, such as the PLSR, which accounts for the collinearity between predictor variables and leads to an efficient prediction model. These results are important for modeling soil properties based on topographic attributes and for spatially generalizing models that have been established over small to large areas. Thus, in the presence of nested variogram models, the correlations between variables of interest and auxiliary information should be improved by filtering out some of the spatial structures by factorial kriging. The information filtered is associated with an appropriate approach for modeling when collinearity occurs between the predictor variables and provides a suitable model for predicting and spatially generalizing a locally established model.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. A Python script to produce datasets to support GlobalSoilMap mapping of soil properties Joël Daroussin, John Gallant

Soil erosion rates in cultivated areas have intensified during the last decades leading to both on and off-site problems for farmers and rural communities. Furthermore, soil redistribution processes play an important role in sediment and carbon storage within, and exports from, cultivated catchments. This study focuses on the impact of land consolidation and changes in landscape structure on medium term soil erosion and landscape morphology within a 3.7-ha field in France. The area was consolidated in 1967 and we used the 137Cs-technique to quantify soil erosion for the period (1954–2009). We measured the 137Cs inventories of 68 soil cores sampled along transects covering the entire area and especially specific linear landforms located along both present and past field borders (i.e., lynchets and undulations landforms, respectively). These results were then confronted with the outputs of a spatially-distributed 137Cs conversion model that simulates and discriminates soil redistribution induced by water and tillage erosion processes. Our results showed that tillage processes dominated the soil redistribution in our study area for the last 55years and generated about 95% (i.e., 4.50Mg·ha−1·yr−1) of the total gross erosion in the field. Furthermore, we demonstrated that soil redistribution was largely affected by the presence of current and also former field borders, where hotspots areas of erosion and deposition (>20Mg·ha−1·yr−1) were concentrated. Land consolidation contributed to the acceleration of soil erosion through the conversion of depositional areas into sediment generating areas. Although the conversion model was able to reproduce the general tendencies observed in the patterns of 137Cs inventories, the model performance was relatively poor with a r2 of 0.20. Discrepancies were identified and associated with sampling points located along the current field borders. Our data suggests that tillage erosion processes near field boundaries cannot be described as a typical diffusive process. These processes near field boundaries should be characterised and taken into account in a future version of the model to accurately simulate rates and patterns of past soil redistribution in fragmented cultivated hillslopes. We also showed that the use of an accurate DEM resulting from LIDAR data, based on present-day topography, leads to the underestimation of soil redistribution rates by the model, especially in this landscape submitted to recent and important morphological changes. Our results have important implications for the simulation of tillage erosion processes and our understanding of soil redistribution processes in complex cultivated areas. This is of particular interest to improve our knowledge and prediction of patterns of soil physical parameters, such as carbon storage or water content, particularly sensitive to surface erosion and landscape structuration.

Soils and landscapes evolve simultaneously. Soil evolution is controlled by redistribution and transformation processes influenced by topographic and climatic parameters, with also a major contribution of management strategies. The perennial landscape features have a strong influence on soil spatial distribution (geometry) and soil genesis. Building landscapes which enhance soil resilience to degradation processes and increase soil services appears as a promising way to adapt to forthcoming climatic and land use evolutions. The presentation aims to synthetize major results from a research program nicknamed Landsoil which focused on the evolution of agricultural soils over medium time scales (decades to centuries) in relation to changing conditions of land use and climate. Precise study of the soil 3D organization in three contrasted landscapes (Brittany, Touraine, Languedoc-Roussillon) enabled to link soil redistribution in space to landscape components (field geometry, hedges or ditches network) and their past evolution. A dynamic and high resolution spatial modeling approach was developed coupling erosion processes and soil organic matter evolution and was calibrated over past evolution using dating techniques (Cs137, C14, OSL). The resulting Landsoil model was afterwards applied in a prospective manner under different scenarios of land use and climate change over the 21th century. Indicators of soil vulnerability and soil resilience were defined and tested by the comparison of several prospective scenarios applied on a same landscape and by comparison of the contrasted landscapes

Les reseaux de bordures de parcelles structurent les paysages cultives et exercent un role important sur la variabilite spatiale des processus d’erosion-depot de sols. Les bordures vegetalisees (haies, bandes enherbees…) affectent les connectivites hydrologiques et sedimentologiques a travers les versants, et l’ensemble des bordures de parcelles fait obstacle aux transferts de sols induits par le labour. Ces phenomenes locaux d’erosion-depot entrainent le developpement de figures morphologiques lineaires et decametriques (par exemple des banquettes agricoles ou cretes de labour) qui continuent d’evoluer apres la disparition des bordures associees. Ceci se verifie particulierement en Europe de l’Ouest ou la mecanisation et les politiques agricoles ont mene a la disparition massive de bordures de parcelles via de nombreuses campagnes de remembrements (annees 1960-1990). Dans un contexte de changement climatique et d’evolution des pratiques agricoles, la comprehension de l’effet des structures paysageres et de leur evolution sur la redistribution des sols parait essentielle pour l’avenir. Des informations sont en effet necessaires afin d’envisager quelles configurations paysageres optimiseraient la conservation des sols. Le but de cette etude est donc d’evaluer l’effet des bordures de parcelles et de leur disparition sur la redistribution des sols au sein d’un versant cultive.

Soils are a non-renewable resource and evolve through time in response to changes in land-use and environmental conditions. To predict this soil evolution requires the development of mechanistic modelling. Only a few attempts of this kind exist in the literature, and these often use an extremely simplified representation of soil structure, with the soil being frequently considered as a succession of homogeneous “boxes”. In this paper we have quantified the evolution of the soil structure during pedogenesis using image analysis. This analysis was performed along a sequence of morphological degradation in an Albeluvisol perpendicular to a drain. These soils, which are commonplace in Europe, are characterised by horizons consisting in a juxtaposition of soil volumes differing in texture (silty to clayey) and colour (ochre, pale-brown, white-grey and black). The image analysis approach was based on these differences in colour and combined i) a supervised training method using ERDAS IMAGINE® to assign the different pixels to the different types of soil volumes and ii) ARCInfo™ for characterisation of the morphology of the different soil volumes. The organisation of the different volumes in space suggests that ochre volume is transformed to pale-brown one and then to grey-white one, whilst black volume is formed within the residual ochre one, due to precipitation of Mn. As the process progresses along the drainage sequence, progressive indentation and final disintegration of the ochre volume are responsible for the release of the black volume into the pale-brown matrix. Ochre volume alteration takes place mainly at the border of the volume which is indicated by the geometry of the pale-brown and ochre volumes. Finally, the formation of the white-grey volume from the pale-brown one occurs in the core of the latter, mainly by eluviation, and is centripetal. We conclude that soil structure needs to be considered when modelling pedogenetic soil evolution.

The modeling of soil erosion by water supposes an accurate and thorough understanding of the hydrology. Thus, it is critical to have a good delineation of the surface flow path. The flow network data are critical for important uses such as flood forecasting and watershed management. Geographic Information System (GIS) functions are able to compute a flow network directly from the digital elevation models. Because the flow directions are only based on the topography, the other factors controlling the flow directions are overlooked. In the agricultural areas, work such as tillage can have a large impact on the flow direction. We propose a 5-step procedure to account for such man-made features. The use of this procedure clearly improves the quality of the computed flow network. This procedure has been successfully implemented in a GIS and improves the prediction of surface flow and therefore improves water erosion modeling at the watershed scale.

Des estimations de l'alea d'erosion ont ete realisees a l'echelle europeenne notamment par le programme PESERA (Kirkby et al., 2003), ainsi qu'a l'echelle nationale grâce a un modele cartographique nomme MESALES (Le Bissonnais et al., 1998 ; Le Bissonnais et al., 2002). Ce modele integre les parametres de l'erosion (occupation du sol, battance, pente, erodibilite et climat) selon un arbre logique qui hierarchise et pondere les classes de ces parametres. Le travail mene porte sur l'evaluation de l'alea erosif en Bretagne (Colmar, 2006). Son objectif est de valider, a l'echelle regionale et par avis d'experts, la carte d'evaluation de l'alea erosif issue de l'application a l'echelle nationale du modele MESALES (Le Bissonnais et al., 2002). Des entretiens avec des experts pedologues et des conseillers agricoles de la region ont permis de delimiter les zones sur- ou sous-estimees par le modele et de proposer des ameliorations des donnees d'entree. D'apres les avis d'expert, l'alea erosif predit par le modele est sous-estime dans la partie est de la region et differe de leur expertise dans d'autres secteurs. Dans un second temps, les resolutions spatiales des donnees d'entree du modele ont ete ameliorees, induisant une modification significative des aleas predits. Une nouvelle carte d'evaluation de l'alea erosif de la region est proposee, correspondant mieux aux avis d'expert.

Soils are characterised by a spatial variability in the three dimensions (3D) of space. However, 3D studies remain scarce due to the qualitative nature of many soil horizon characteristics, notably the horizon designation. Indeed, existing 3D tools are mainly developed for quantitative data. To solve this difficulty, we propose a new approach based on the interpolation of the horizon thickness to derive digital elevation models for both the upper and the lower limits of each horizon. This approach was applied to Planosols previously extensively studied with 2D approaches. The. pseudo 3D obtained representation evidences soil processes that were missed in 2D approaches. As an example, we evidence the impact of differential weathering, resulting from the mineralogical heterogeneity of the parent material, on the subsequent pedogenesis. To cite this article: E Delarue et al., C R. Geoscience 341 (2009). (C) 2009 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.

This paper compares two approaches for upscaling the Aisne (a 7,536 kin 2 French department) soil database from the initial 1:25,000 nominal scale to the 1:250,000 target scale. Soil features are represented at the nominal scale, whereas pedolandscapes, which are a combination of soil-forming factors and soil variables, are required at the target scale. Because the initial soil database does not contain soil forming factor information, data on pedogenesis have to be added to the initial database. Based on the assumption that most of lithographic layers are horizontal in the area, only landform attributes are chosen to represent the soil-forming factors.Two different approaches are used to map the final pedolandscapes. The first one. called the bottom-up approach consists of classifying the soil and the landforill attributes together for defining taxonomic units, which then undergo generalisation of their contours to result in pedolandscape mapping units.The second approach, called a top-down approach, consists of classifying and then mapping the landform units in order to delineate the pedolandscapes. In this paper, we focus only on the pedolandscape delineation for the target scale. The results of the two methodologies are compared to contours manually drafted by soil surveyors. The final discussion analyses the impact of taking the very detailed soil database in the Digital Soil Mapping process into account, and to give advice for digital soil mapping with limited input data.

Summary The principles and theoretical background are presented for a new process‐based model (PESERA) that is designed to estimate long‐term average erosion rates at 1 km resolution and has, to date, been applied to most of Europe. The model is built around a partition of precipitation into components for overland flow (infiltration excess, saturation excess and snowmelt), evapo‐transpiration and changes in soil moisture storage. Transpiration is used to drive a generic plant growth model for biomass, constrained as necessary by land use decisions, primarily on a monthly time step. Leaf fall, with corrections for cropping, grazing, etc., also drives a simple model for soil organic matter. The runoff threshold for infiltration excess overland flow depends dynamically on vegetation cover, organic matter and soil properties, varying over the year. The distribution of daily rainfall totals has been fitted to a Gamma distribution for each month, and drives overland flow and sediment transport (proportional to the sum of overland flow squared) by summing over this distribution. Total erosion is driven by erodibility, derived from soil properties, squared overland flow discharge and gradient; it is assessed at the slope base to estimate total loss from the land, and delivered to stream channels.