## 4 Discussion  
### Verification of Drought Maps  
The method used for verification of the drought maps was based on the assumption that severe drought should have an impact on yield reduction of the main crops. Therefore, yield data covering the 2001-2018 period were collected from the Central Statistical Office (CSO) for all NUTS 2 regions (i.e., vovodeships) in Poland. Next, years with maximum yields were determined for each vovodeship in order to calculate at the next stage yield reductions. Figure 19 demonstrates various levels of maximum yield depending on the region, highlighting three years when maximum yields appeared, namely 2014 (primarily), 2017, and 2016.  
When analyzing time series of yield over the period 2001-2018, it was found that a significant increasing trend appears for each region (i.e., vovodeship); therefore, the de-trending procedure was applied. The increasing trend resulted from the gradually improved agricultural practices and from better crop varieties applied by the farmers. An example of yield values before and after application of the de-trending procedure is presented in Figure 20.  
Figure 19: Maximum yields for particular vovodeships in Poland.  
At the next stage, the percentage reduction of yield in relation to the maximum yield was calculated for each year and for each NUTS 2 region. The information on the yield reduction for cereal in graphical form is presented for the selected NUTS 2 regions in Figure 21.  
Figure 21: Cereal yield reduction for the selected NUTS 2 regions.  
Figure 20: Cereal yield before and after de-trending procedure—NUTS 2 PL51.  
Finally, statistical analysis (ANOVA) described in the Method section has been applied to find the relationship between the level of yield reduction and percentage of drought occurrence; it revealed the correlation of these two parameters, especially for a group with high yield reductions.  
The maps of the drought index based on satellite data can be used for detailed spatial analysis of the variability of the drought conditions within the vegetation period, as presented in Figures 24-28. However, they can also be effectively applied for distinguishing areas (regions) with the highest intensity of drought from a multiyear perspective. Such an analysis was carried out by applying information on the percentage of drought occurrence within particular NUTS 2 regions (i.e., voivodeships) in the 2001-2019 timeframe. This information was derived from the maps of the DISS drought index, calculating the average percentage of drought area in the whole vegetation period. The results of the analysis are presented in Figure 22.  
The study confirmed that in the years 2002, 2003, 2006, 2007, 2011, 2012, 2015, 2016, 2018, and 2019, the extent of the drought for the majority of NUTS 2 regions was the highest, for most voivodeships reaching over 20% of the agricultural area. In particular, it revealed extremely high drought in 2018, which reached over 40% of the agricultural area for almost all voivodeships. Simultaneously, a comparative analysis of the occurrence of drought within particular regions, performed for the whole 2001-2019 period, pointed out those voivodeships that are especially prone to drought conditions. The results of this analysis in graphical form are presented in Figure 23.  
The regions most heavily affected by drought were PL71 (Lodzkie), PL41 (Wielkopolskie), PL43 (Lubuskie), PL92 (Mazowieckie), PL61 (Kujawsko-Pomorskie), and PL51 (Dolnoslaskie), all located in central and western Poland. In these regions, drought hazards are also most frequently described by meteorological parameters, which correlate well with the satellite-based drought index.  
Figure 22: Percentage of drought area occurrence in Poland (2001–2019).