In a context of increased land and natural resources scarcity, the possibilities for local authorities and stakeholders of anticipating evolutions or testing the impact of envisaged developments through scenario simulation are new challenges. PRECOS's approach integrates data pertaining to the fields of water and soil resources, agronomy, urbanization, land use and infrastructure etc. It is complemented by a socio-economic and regulatory analysis of the territory illustrating its constraints and stakes. A modular architecture articulates modeling software and spatial and temporal representations tools. It produces indicators in three core domains: soil degradation, water and soil resources and agricultural production. As a territory representative of numerous situations of the Mediterranean Basin (urban pressures, overconsumption of spaces, degradation of the milieus), a demonstration in the Crau's area (Southeast of France) has allowed to validate a prototype of the approach and to test its feasibility in a real life situation. Results on the Crau area have shown that, since the beginning of the 16th century, irrigated grasslands are the cornerstones of the anthropic-system, illustrating how successfully men's multi-secular efforts have maintained a balance between environment and local development. But today the ecosystem services are jeopardized firstly by urban sprawl and secondly by climate change. Pre-diagnosis in regions of Emilia-Romagna (Italy) and Valencia (Spain) show that local end-users and policy-makers are interested by this approach. The modularity of indicator calculations and the availability of geo-databases indicate that PRECOS may be up scaled in other socio-economic contexts.
By combining a crop model (STICS) and a geochemical model (PHREEQC), a new approach to assess the sustainability of agrosystems is proposed. It is based upon aqueous geochemistry and the stepwise modifications of soil solution during its transfer from the surface till aquifer. Meadows of Crau (SE France), irrigated since the 16th century, were field monitored (2012-2015) and modelled. Except for N, the mineral requirements of hay are largely covered by dissolved elements brought by irrigation water with only slight deficits in K and P, which are compensated by P-K fertilizers and the winter pasture by sheep. N cycle results in a very small nitrate leakage. The main determinants of the chemical composition changes of water are: concentration by evaporation, equilibration with soil pCO, mineral nutrition of plants, input of fertilizers, sheep grazing, mineral-solution interactions in superficial formations till the aquifer, including ion exchange. Inverse modelling with PHREEQC allows for quantifying these processes. For groundwater, measured composition fit statistically very well with those computed, validating thus this approach. This long-term established agrosystem protects both soil and water resources: soil nutritional status remains constant with even some P and (minor) K fixation in soils; long-term decarbonatation occurs but it is greatly slowed by saturation of irrigation water by carbonate; P fixation in soil protects groundwater from eutrophication.
This study is a survey on state-of-the-art methods based on artificial intelligence and image processing for precision agriculture on Crop Management, Pest and Disease Management, Soil and Irrigation Management, Livestock Farming and the challenges it presents. Precision agriculture (PA) described as applying current technologies into conventional farming methods. These methods have proved to be highly efficient, sustainable and profitable to the farmer hence boosting the economy. This study is a survey on the current state of the art methods applied to precision agriculture. The application of precision agriculture is expected to yield an increase in productivity which ultimately ends in profit to the farmer, to the society increase sustainability and also improve the economy.
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