Drivers of soil drying in the Czech Republic between 1961 and 2012. (13th October 2014) - Trnka, M.; Brázdil, R.; Balek, J.; Semerádová, D.; Hlavinka, P.; Možný, M.; Štěpánek, P.; Dobrovolný, P.; Zahradníček, P.; Dubrovský, M.; Eitzinger, J.; Fuchs, B.; et al.
ABSTRACT Soil moisture dynamics and their temporal trends in the Czech Republic are forced by various drivers. The methodology of applying remotely sensed data with both high temporal and spatial resolutions provides detailed insight and objective quantification of the causes of changes in soil moisture patterns. Our analysis of temporal trends indicates that shifts in drought severity between 1961 and 2012 (especially in the April, May, and June period, which displayed a 50% increase in drought probability between 1961–1980 and 2001–2012) are alarming. We found that increased global radiation and air temperature together with decreased relative humidity (all statistically significant at the 0.05 level) led to increases in the reference evapotranspiration in all months of the growing season; this trend was particularly evident in April, May, and August, when more than 80% of the territory displayed an increased demand for soil water. This finding was shown to be consistent with the measured pan evaporation (1968–2012) that was characterized by increasing trends, particularly during the April–June period. These changes, in combination with the earlier end of snow cover and the earlier start of growing season (up to 20 days in some regions), led to an increased actual evapotranspiration at the start of growing season that tends to deplete the soil moisture earlier, leaving the soil more exposed to the impacts of rainfall variability. These results support concerns related to the potentially increased severity of drought events in Central Europe. The reported trend patterns are of particular importance with respect to the expected climate change, given the robustness and consistency of the trends shown and the fact that they can be aligned with the existing climate model projections.