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SpatialAquaCrop, an R Package for Raster-Based Implementation of the AquaCrop Model

Modeling crop water use and soil moisture availability is becoming increasingly critical, particularly in light of recent drought events. Our study focuses on the spatial application of the AquaCrop model, using a raster-based approach in an R-based environment. The formulated methodology was initia...

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Detalles Bibliográficos
Autores principales: Barros, Vinicius Deganutti De, Waltner, István, Minoarimanana, Rakotoarivony A., Halupka, Gábor, Sándor, Renáta, Kaldybayeva, Dana, Gelybó, Györgyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9654151/
https://www.ncbi.nlm.nih.gov/pubmed/36365360
http://dx.doi.org/10.3390/plants11212907
Descripción
Sumario:Modeling crop water use and soil moisture availability is becoming increasingly critical, particularly in light of recent drought events. Our study focuses on the spatial application of the AquaCrop model, using a raster-based approach in an R-based environment. The formulated methodology was initially applied and tested on two point-based examples in the Central region of Hungary, followed by the spatial application of the model at the Rákos Stream catchment in the same region. For evaluation purposes, we also utilized satellite-based NDVI data. The results showed that there is a strong correlation between NDVI values and the model-based biomass estimation. We also found that the model simulated the soil moisture content fairly well, with a correlation coefficient of 0.82. While our results support the validity of the applied methodology, it is also clear that input data availability and quality are still critical issues in spatial application of the AquaCrop model.