SpatialAquaCrop, an R Package for Raster-Based Implementation of the AquaCrop Model
Vinicius Deganutti De Barros,
István Waltner,
Rakotoarivony A. Minoarimanana,
Gábor Halupka,
Renáta Sándor,
Dana Kaldybayeva,
Györgyi Gelybó
Affiliations
Vinicius Deganutti De Barros
Doctoral School of Environmental Sciences, Hungarian University of Agriculture and Life Sciences, 2100 Gödöllő, Hungary
István Waltner
Department of Water Management and Climate Adaption, Institute of Environmental Sciences, Hungarian University of Agriculture and Life Sciences, 2100 Gödöllő, Hungary
Rakotoarivony A. Minoarimanana
Department of Geography, Oklahoma State University, Stillwater, OK 74078, USA
Gábor Halupka
Department of Water Management and Climate Adaption, Institute of Environmental Sciences, Hungarian University of Agriculture and Life Sciences, 2100 Gödöllő, Hungary
Renáta Sándor
Agricultural Institute, Centre for Agriculural Research, Eötvös Loránd Research Network, Martonvásár, Brunszvik u. 2., 2462 Martonvásár, Hungary
Dana Kaldybayeva
Department of Water Management and Climate Adaption, Institute of Environmental Sciences, Hungarian University of Agriculture and Life Sciences, 2100 Gödöllő, Hungary
Györgyi Gelybó
Department of Water Management and Climate Adaption, Institute of Environmental Sciences, Hungarian University of Agriculture and Life Sciences, 2100 Gödöllő, Hungary
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.
