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PLoS One ; 16(4): e0250979, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33930081

RESUMO

While only 20% of harvested lands are actually irrigated, 40% of global agricultural production originates from irrigated areas. Therefore, assessing irrigation requirements is essential for the development of effective water-related policies for an efficient management of water resources. Moreover, global-scale analyses are becoming increasingly relevant, motivated by globalized production and international trade of food as well as by the need of common strategies to address climate change. In this study, a comprehensive model to estimate crop growth and irrigation requirements of 26 main crops at global scale is presented. The model computes a soil water balance using daily precipitation and reference evapotranspiration based on a high-resolution ERA5 reanalysis dataset from the European Copernicus Program. The irrigation requirement, defined as the minimum water volume to avoid water stress, is computed for year 2000 at the resolution of 5 arc-min (or 0.0833°) and aggregated at different spatial and temporal scales for relevant analyses. The estimated global irrigation requirements for 962 km3 is described in detail, also in relation to the spatial variability and to the monthly variation of the requirements. A focus on different areas of the world (California, Northern Italy and India) highlights the wealth of information provided by the model in different climatic conditions. National data of irrigation withdrawals have been used for an extensive comparison with model results. A crop-specific validation has also been made for the State of California, comparing model results with local data of irrigation volume and independent estimates of crop water use. In both cases, we found a good agreement between model results and real data.


Assuntos
Irrigação Agrícola/métodos , Agricultura/métodos , Mudança Climática/estatística & dados numéricos , Produtos Agrícolas/crescimento & desenvolvimento , Irrigação Agrícola/estatística & dados numéricos , Agricultura/estatística & dados numéricos , Simulação por Computador , Bases de Dados Factuais , Internacionalidade , Modelos Teóricos , Solo , Recursos Hídricos
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