Modeling Phenological Phases of Winter Wheat Based on Temperature and the Start of the Growing Season

0564647 - ÚVGZ 2023 RIV CH eng J - Journal Article
Dížková, Petra - Bartošová, Lenka - Bláhová, Monika - Balek, Jan - Hájková, L. - Semerádová, Daniela - Bohuslav, Jakub - Pohanková, Eva - Žalud, Zdeněk - Trnka, Miroslav
Modeling Phenological Phases of Winter Wheat Based on Temperature and the Start of the Growing Season.
Atmosphere. Roč. 13, č. 11 (2022), č. článku 1854. E-ISSN 2073-4433
R&D Projects: GA MŠMT(CZ) EF16_019/0000797
Research Infrastructure: CzeCOS III - 90123
Institutional support: RVO:86652079
Keywords : phenology * field crop * PhenoClim model * modis * remote sensing
OECD category: Ecology
Impact factor: 2.9, year: 2022
Method of publishing: Open access
https://www.mdpi.com/2073-4433/13/11/1854

The phenological phases of field crops have shifted to earlier times in the Czech Republic in recent decades, additionally, they have shown correlations with temperatures from previous spring months. Using a thermal time model called PhenoClim, the correlations between temperatures and phenophases allow us to evaluate the strongest predictors (i.e., maximum temperature) and indicators of base temperatures and growing degree days for the selected phenophases of winter wheat (Triticum aestivum L.). With the help of this model, it is possible to explain 0.6-0.82% of the phase variability and to estimate the onset of phenophases for the selected time period and stations (with the RMSE values of 9.4 days for jointing, 4.3 days for heading, and 5.3 days for full ripeness). To further refine the modeled onsets of phenophases, we used satellite data, specifically the normalized difference vegetation index and the enhanced vegetation index 2 from MODIS, based on these vegetation indices, the start of the growing season (SOS) was determined. After including SOS to model PhenoClim, we modeled the onsets of phenophases, with average accuracies ranging from 6.2 to 15.2. By combining the thermal time model and remote sensing data, specifically the data concerning the determination of SOS, we can refine the modeling of the onset of full ripeness in some locations.
Permanent Link: https://hdl.handle.net/11104/0336304