Représentation et simulation des pratiques culturales des agriculteurs à l'échelle régionale pour estimer la demande en eau d'irrigation : application à un basin versant maïsicole du sud-ouest de la France…

Les pratiques culturales sont un élément déterminant des prélèvements d'eau pour l'irrigation. Or ces pratiques sont elles-mêmes conditionnées par le contexte pédoclimatique et le contexte d'exploitation. Il est donc important pour la simulation de scénarios décrivant l'évolution du climat et des exploitations irrigantes de bien représenter ces pratiques au sein de modèles visant à estimer la demande régionale en eau d'irrigation à moyen terme. Tel est l'objectif de la thèse. La démarche suivie durant la thèse est le résultat d'une double contrainte résultant de l'étendue considérée: (a) la représentation de la diversité des pratiques culturales et (b) la simplification de cette diversité. Elle a consisté à (i) identifier la diversité des pratiques culturales par confrontation de différents types de données (expertise, entretiens, calendriers culturaux obtenus par enquêtes postales, pratiques recommandées), (ii) formaliser les pratiques sous forme de stratégies par analyses multivariées et classification ascendante hiérarchique et (iii) rechercher des indicateurs de leur distribution spatiale à travers différents types de déterminants facilement accessibles à l'échelle régionale. Il a été choisi de simplifier les processus représentés en se concentrant sur la culture ayant le plus d'influence sur la demande en eau (le maïs grain) et en étudiant deux interventions techniques (le semis, l'irrigation) et un choix technique (le choix de la précocité des variétés) au sein de l'itinéraire technique. Le terrain d'application est un bassin versant irrigué des coteaux de Gascogne au sein du système Neste. Les données sur les pratiques culturales à l'origine du modèle ont été acquises entre 2000 et 2004. A partir des résultats d'analyse des pratiques culturales, un modèle permettant d'estimer les dates de semis, les précocités semées, les densités de semis et les surfaces semées pour le maïs une année au sein de la zone a été développé. L'estimation est stochastique et se fait en fonction de variables décrivant les systèmes de production et les conditions météorologiques de l'année. Couplé à un modèle bio-décisionnel pré-existant simulant la pratique de l'irrigation et le développement des plantes à l'échelle parcellaire, il permet l'estimation de la demande régionale en eau par agrégation des résultats obtenus pour chaque parcelle. Ce modèle a été évalué grâce aux données observées obtenues par une enquête postale réalisée en 2005. Les résultats de comparaison des données observées et simulées montrent que l'estimation de la demande en eau est correcte. Par rapport aux modèles développés jusque là, ce modèle permet l'estimation de la variabilité de la demande en eau et ouvre des perspectives pour l'évaluation de scénarios prospectifs dans le cadre du changement de politique agricole commune et de l'évolution du climat. La représentation et la simulation des pratiques culturales à l'échelle régionale réalisée pendant la thèse sont une contribution aux travaux de spatialisation des systèmes de culture. ABSTRACT : Agricultural practices are a key-element to determine the irrigation water requirements. These practices depend both on soil and climate and on the general context of the farm enterprise. If one wants to simulate the evolution of the irrigation water demand at a regional scale due to some modifications of climate or farm enterprise, it is then important to provide a correct representation of the agricultural practices within the simulation model. This is the main goal of the thesis. Our approach is the result of two different questions linked to the spatial scale of the study: (a) how to represent the diversity of the agricultural practices, (b) how to simplify this diversity. Three steps have been followed: i) identification of the diversity of the agricultural practices using different sources of data (expertise, interviews, agricultural practices calendar from mail surveys, advisors proposition); ii) analyses of these data with multivariate analyses and hierarchical classifications in order to express strategies; iii) identification of keydeterminants part of regional databases that may be used to provide a spatial representation of these strategies. Some simplifications have been made: to focus only on irrigated corn (main irrigated crop in surface and in volume in the study area), to analyse only sowing and irrigation practices as the two main practices within the crop management systems that build the irrigation water demand. The choice of corn precocity is also integrated in the analysis. The study area is a watershed in the Gascogne region part of the Neste system. Agricultural practices were gathered between 2000 and 2004. From the results of the three previous steps, a model (SIMITKO) has been built that allows to estimate the sowing date, the choice of corn precocity, the sowing density and the area sown a given year. The model is stochastic and uses as input data some variables describing the production system and the climatic data of the given year. SIMITKO is linked to an existing biodecisional model (MODERATO) aimed at simulating corn irrigation strategies. This linkage provides an estimation of the regional water demand for irrigation through the aggregation of simulated demands at a plot scale. The model is evaluated on independent data obtained by a mail survey in 2005. Simulated and observed data are closed. Contrarily of pre-existing models, our model allows to estimate the variability of the irrigation water demand at a regional scale and may be used to test CAP or climate modifications. This work is part of a more general question on how to give a spatial representation of cropping system

Benefits of adapting to sea level rise : the importance of ecosystem services in the French Mediterranean sandy coastline

This article proposes an innovative approach to assess the benefits of adapting to sea level rise (SLR) in a coastal area on a regional scale. The valuation framework integrates coastal ecosystem services, together with urban and agricultural assets. We simulate the impacts of a progressive 1 m rise in sea level in the twenty-first century and an extreme flooding event in 2100 for four contrasted adaptation scenarios (Denial, “Laissez-faire”, Protection and Retreat). The assessment involves coupling the results of hazard-modelling approaches with different economic valuation methods, including direct damage functions and methods used in environmental economics. The framework is applied to the French Mediterranean sandy coastline. SLR will result in major land-use changes at the 2100 time horizon: relocation or densification of urban areas, loss of agricultural land, increase in lagoon areas and modification of wetlands (losses, migration or extension of ecosystems). Total benefits of public adaptation options planned in advance could reach €31.2 billion for the period 2010–2100, i.e. €69,000 per inhabitant (in the study area) in 2010 or €135 million/km of coastline. Our results highlight the importance of (i) raising awareness to ensure that public services and coastal managers can anticipate the consequences of SLR and (ii) incorporating coastal ecosystems into the assessment of the adaptation options. Our findings could provide a basis for participatory foresight approaches to build coastline adaptation pathways.PostprintPeer reviewe

Evolution of coastal zone vulnerability to marine inundation in a global change context. Application to Languedoc Roussillon (France)

The coastal system is likely to suffer increasing costal risk in a global change context. Its management implies to consider those risks in a holistic approach of the different vulnerability components of the coastal zone, by improving knowledge of hazard and exposure as well as analyzing and quantifying present day and future territory vulnerability. The ANR/VMC2007/MISEEVA project (2008-2011) has applied this approach on Languedoc Roussillon region in France. MISEEVA approach relies on several scenarios for 2030 and 2100, in terms of meteorology (driver of coastal hazard), sea level rise, and also considering further trends in demography and economy, and possible adaption strategies Hazard has been modeled (SWAN, MARS and SURFWB), on the base of the presentday situation, sea level rise hypotheses, and existing or modeled data, of extreme meteorological driving f. It allowed to assess the possible surges ranges and map coastal zone exposure to: - a permanent inundation (considering sea level rise in 2030 and 2100, - a recurrent inundation (considering sea level rise and extreme tidal range) - an exceptional inundation (adding extreme storm surge to sea level rise and tidal range). In 2030, exposure will be comparable to present day exposure. In 2100, extreme condition will affect a larger zone. Present days social and economic components of the coastal zone have been analyzed in terms of vulnerability and potential damaging. Adaptation capacity was approached by public inquiries and interviews of stakeholders and policy makers, based on existing planning documents The knowledge of the present day system is then compared to the possible management strategies that could be chosen in the future, so to imagine what would be the evolution of vulnerability to marine inundation, in regards to these possible strategies

Représentation et simulation des pratiques culturales des agriculteurs à l'échelle régionale pour estimer la demande en eau d'irrigation (application à un basin versant maïsicole du sud-ouest de la France )

Agricultural practices are a key-element to determine the irrigation water requirements. These practices depend both on soil and climate and on the general context of the farm enterprise. If one wants to simulate the evolution of the irrigation water demand at a regional scale due to some modifications of climate or farm enterprise, it is then important to provide a correct representation of the agricultural practices within the simulation model. This is the main goal of the thesis. Our approach is the result of two different questions linked to the spatial scale of the study: (a) how to represent the diversity of the agricultural practices, (b) how to simplify this diversity. Three steps have been followed: i) identification of the diversity of the agricultural practices using different sources of data (expertise, interviews, agricultural practices calendar from mail surveys, advisors proposition); ii) analyses of these data with multivariate analyses and hierarchical classifications in order to express strategies; iii) identification of keydeterminants part of regional databases that may be used to provide a spatial representation of these strategies. Some simplifications have been made: to focus only on irrigated corn (main irrigated crop in surface and in volume in the study area), to analyse only sowing and irrigation practices as the two main practices within the crop management systems that build the irrigation water demand. The choice of corn precocity is also integrated in the analysis. The study area is a watershed in the Gascogne region part of the Neste system. Agricultural practices were gathered between 2000 and 2004. From the results of the three previous steps, a model (SIMITKO) has been built that allows to estimate the sowing date, the choice of corn precocity, the sowing density and the area sown a given year. The model is stochastic and uses as input data some variables describing the production system and the climatic data of the given year. SIMITKO is linked to an existing biodecisional model (MODERATO) aimed at simulating corn irrigation strategies. This linkage provides an estimation of the regional water demand for irrigation through the aggregation of simulated demands at a plot scale. The model is evaluated on independent data obtained by a mail survey in 2005. Simulated and observed data are closed. Contrarily of pre-existing models, our model allows to estimate the variability of the irrigation water demand at a regional scale and may be used to test CAP or climate modifications. This work is part of a more general question on how to give a spatial representation of cropping systems.Les pratiques culturales sont un élément déterminant des prélèvements d'eau pour l'irrigation. Or ces pratiques sont elles-mêmes conditionnées par le contexte pédoclimatique et le contexte d'exploitation. Il est donc important pour la simulation de scénarios décrivant l'évolution du climat et des exploitations irrigantes de bien représenter ces pratiques au sein de modèles visant à estimer la demande régionale en eau d'irrigation à moyen terme. Tel est l'objectif de la thèse. La démarche suivie durant la thèse est le résultat d'une double contrainte résultant de l'étendue considérée: (a) la représentation de la diversité des pratiques culturales et (b) la simplification de cette diversité. Elle a consisté à (i) identifier la diversité des pratiques culturales par confrontation de différents types de données (expertise, entretiens, calendriers culturaux obtenus par enquêtes postales, pratiques recommandées), (ii) formaliser les pratiques sous forme de stratégies par analyses multivariées et classification ascendante hiérarchique et (iii) rechercher des indicateurs de leur distribution spatiale à travers différents types de déterminants facilement accessibles à l'échelle régionale. Il a été choisi de simplifier les processus représentés en se concentrant sur la culture ayant le plus d'influence sur la demande en eau (le maïs grain) et en étudiant deux interventions techniques (le semis, l'irrigation) et un choix technique (le choix de la précocité des variétés) au sein de l'itinéraire technique. Le terrain d'application est un bassin versant irrigué des coteaux de Gascogne au sein du système Neste. Les données sur les pratiques culturales à l'origine du modèle ont été acquises entre 2000 et 2004. A partir des résultats d'analyse des pratiques culturales, un modèle permettant d'estimer les dates de semis, les précocités semées, les densités de semis et les surfaces semées pour le maïs une année au sein de la zone a été développé. L'estimation est stochastique et se fait en fonction de variables décrivant les systèmes de production et les conditions météorologiques de l'année. Couplé à un modèle bio-décisionnel pré-existant simulant la pratique de l'irrigation et le développement des plantes à l'échelle parcellaire, il permet l'estimation de la demande régionale en eau par agrégation des résultats obtenus pour chaque parcelle. Ce modèle a été évalué grâce aux données observées obtenues par une enquête postale réalisée en 2005. Les résultats de comparaison des données observées et simulées montrent que l'estimation de la demande en eau est correcte. Par rapport aux modèles développés jusque là, ce modèle permet l'estimation de la variabilité de la demande en eau et ouvre des perspectives pour l'évaluation de scénarios prospectifs dans le cadre du changement de politique agricole commune et de l'évolution du climat. La représentation et la simulation des pratiques culturales à l'échelle régionale réalisée pendant la thèse sont une contribution aux travaux de spatialisation des systèmes de culture.TOULOUSE-ENSAT-Documentation (315552324) / SudocSudocFranceF

Geo-referenced indicators of maize sowing and cultivar choice for better water management

Agriculture is a major consumer of water, with up to 88% of the total water consumption in summer in irrigated regions, either in France or, for instance, in Australia. Good water management therefore requires an accurate estimation of regional water demand by agriculture, which depends on both soil and weather conditions and on farmers’ practices. We studied the farmers’ practices that influence maize irrigation : sowing and the choice of cultivar in regard to its earliness. Specifically, we aimed to identify geo-referenced indicators that could be used to estimate the spatial and temporal distribution of the various combinations of sowing date, sowing density, sown area and maize earliness. The study was conducted in a 500-km2 irrigated area in south-western France. We first conducted a quantitative analysis of postal survey data to identify environmental factors and farm descriptors that could determine sowing practices and the choice of earliness of cultivar. We then interviewed a group of farmers to find out the main constraints relevant to the sowing date and earliness of cultivar. We identified variables that can be used as indicators of the spatial variability of the studied practices. Our results show that the spatial distribution of sowing date and cultivar earliness over a region can be estimated from climatic descriptors of the area and structural farm characteristics. The first factor allows estimation of tactical variables, the sowing starting date and the cultivar earliness groups, while the second allows estimation of sowing and earliness choice strategies. This is one of the first studies identifying on a regional scale geo-referenced indicators of a crop management system, and the first that provides a conjunctive estimation of sowing and earliness choice practices on a regional scale. This study suggests that for estimating any crop management system, it is helpful to treat strategic and tactical variables separately

Soil-water adaptive management process: the case of On-site Wastewater TreatmentSystems in peri-urban areas in France

International audienc

Assessing the irrigation strategies over a wide geographical area from structural data about farming systems.

International audienceAccurate estimation of regional water demand by agriculture, mainly consumed by farmers for irrigation, is a key requirement for water management. It depends on the farmers’ irrigation practices which itself depend on the farmers’ irrigation strategies. Describing irrigation strategies over a region is rather difficult due to the large number and the diversity of farmers. We seek whether it is possible to characterise irrigation strategies from easily accessible farm characteristics data at the regional scale. For that purpose, we investigated the relationships between maize irrigation strategies and three farming sub-systems: the production system, the water resource system and the irrigation equipment system. Based on a 56-farmers survey of maize irrigation strategies carried out in two different areas in south-western France, we firstly created typologies from the three farming sub-systems and from irrigation strategies and, in a second step, analysed the links between the different typologies. Multivariate analyses, cluster analyses, linear regressions and regression trees were used for that purpose. Only two types of irrigation strategies were found that could not be fully explained by the three sub-systems typologies. However, the theoretical irrigation capacity explains a part of the irrigation strategies. Such data can be obtained at a wide geographical scale from administrative data bases. Strategic management of irrigation is similar amongst farmers in a given area while more operational actions differ from farmer to farmer. Standardisation of strategies due to county-based advice is then discussed

Modelling the days which are agronomically suitable for sowing maize

International audienceClimate change influences crop production. Crop management will have to adapt the crop to this new climate. Models can be used to guide this new crop management. Using expert knowledge and surveys we developed a model that aims to simulate the number of days suitable for sowing maize. Our model is based on three modules: a module dealing with the sowing constraint due to frost; a module for constraints due to temperature to grow crop and a module for constraints due to soil moisture. The model was calibrated using recorded sowing dates in 2000 and 2003 and evaluated using an independent set of recorded dates in 2005 in southwestern France. Results are good, as only four farmers over 39 sowed on an apparently unsuitable date. Inaccuracy of input data such as rainfall is discussed and some modifications to the present algorithm are proposed