Hybridizing local and generic information to model cropping system spatial distribution in an agricultural landscape

Autor: Olivier Therond, Delphine Leenhardt, Clément Murgue
Přispěvatelé: Compagnie d'Aménagement des Côteaux de Gascogne (CACG), AGroécologie, Innovations, teRritoires (AGIR), Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées
Jazyk: angličtina
Rok vydání: 2016
Předmět:
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences
mixed methods
Computer science
Geography
Planning and Development
010501 environmental sciences
Management
Monitoring
Policy and Law
Spatial distribution
01 natural sciences
irrigation
Identification system
perception-based regional mapping
Operations management
landscape agronomy
Cropping system
0105 earth and related environmental sciences
Nature and Landscape Conservation
2. Zero hunger
business.industry
Environmental resource management
Forestry
04 agricultural and veterinary sciences
15. Life on land
Water resources
13. Climate action
Agriculture
040103 agronomy & agriculture
0401 agriculture
forestry
and fisheries
farming system
[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]
Scale (map)
business
Cropping
Common Agricultural Policy
Zdroj: Land Use Policy
Land Use Policy, Elsevier, 2016, 54, pp.339-354. ⟨10.1016/j.landusepol.2016.02.020⟩
ISSN: 0264-8377
Popis: International audience; For quantitative water management, fine analysis of spatial and temporal interactions between cropping systems and water resources helps identify time and site-specific withdrawal situations. However, it is a methodological challenge to provide fine-resolution analyses at the scale of large watersheds used for crises management. In this study, we present a methodology based on multiple methods and mixed sources of information to finely model an agricultural landscape (AL) that represents the spatial distribu- tion of cropping systems. Our approach is based on progressively hybridizing databases and local actors’ and experts’ knowledge to produce a spatially explicit and dynamic model. The Land Parcel Identifica- tion System database, which resulted from the European Common Agricultural Policy, is crucial for our method since it provides the spatial and temporal basis of our model (i.e., geographic delineation of islets and information about crop sequences). Local knowledge is used to identify factors determining spatial distribution of cropping systems and to build a generic model that simulates farmers’ crop-management strategies. The model was qualitatively and quantitatively evaluated using a multi-agent simulation plat- form (MAELIA). We asked local experts on quantitative water management to evaluate the ability of the platform to reproduce intra- and inter-annual dynamics at different levels when using our model of the AL as input. The experts were satisfied with the results; they validated the predicted dynamics of the vari- ables, and some discussed the objectivity of the values. We discuss the method’s contribution to current challenges in modeling large agricultural areas and the associated tradeoffs. The approach is promising for policy makers who wish to develop integrated, locally adapted land-management strategies.
Databáze: OpenAIRE
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